The geological record provides insight into how climate and carbon cycle processes operate and evolve under different than modern boundary conditions and forcings. Understanding past climate evolution is paramount to progressing on understanding fundamental questions of Earth System feedbacks and sensitivity to perturbations, such as the behaviour of the climate system and carbon cycle under elevated atmospheric CO2 concentration—relative to the Quaternary—, or the existence of environmental tipping points and thresholds. In recent years, geochemical techniques and Earth System Models complexity have been greatly improved and several international projects on past climates (e.g., DeepMIP, MioMIP, PlioMIP) have been initiated within the wider PMIP, helping to bridge the gap between palaeoclimate modelling and data communities. This session invites work on past climates and carbon cycling across the Phanerozoic using model simulations and/or proxy-based reconstructions. We especially encourage submissions featuring reconstructions of palaeoenvironments or processes, palaeoclimate-ocean and carbon cycle modelling, and the integration of CO2 and (hydro)climate proxies with models of any complexity.

Dissolved oxygen in seawater is vital for marine life, diversity, and global biogeochemical cycles. Understanding how oxygen has changed through the geological record offers key insights to understand potential future scenarios. In the past, both the absolute abundance and distribution of ocean oxygenation was at times, different from today. Such changes are driven by different processes, including oxygen solubility, ocean circulation, and/or biological processes. In this session, we invite contributions investigating past seawater dissolved oxygen reconstructions on regional to global scales across the Phanerozoic. This includes studies of drivers and mechanisms of change, feedback, and impacts on ecosystems and the Earth system. Studies focussing on proxy applications or development, modelling, and proxy-model comparisons are welcome.

Accurate reconstructions of sea surface, bottom water, and continental surface temperatures during the Cenozoic era are essential for understanding climate dynamics in the geological past, particularly under warmer-than-present conditions. However, producing robust and precise paleotemperature estimates remains inherently challenging. Temperature proxies are subject to a range of geochemical, biological, environmental, and analytical uncertainties, which lead to discrepancies in both absolute and relative temperature estimates across different methods. These limitations hinder efforts to synthesize globally representative paleotemperature records and to constrain the rates and magnitudes of global temperature changes in response to both abrupt and long-term changes in atmospheric CO2.

Addressing these challenges requires new approaches, including improved proxy calibrations, and more comprehensive inter-proxy and proxy-model comparisons, to obtain a better understanding of the uncertainties associated with paleotemperature reconstructions. In this session, we welcome contributions that push the boundaries of Cenozoic paleotemperature research, including new multi-proxy and multi-site temperature reconstructions, new advances in proxy ground-truthing, applications, and calibrations, and novel modelling perspectives on paleotemperature changes. By bringing together the diverse community using proxy and modelling techniques, we seek to increase the robustness of Cenozoic ocean and terrestrial temperature reconstructions. Ultimately, this will improve our understanding of Earth’s climate system and its behaviour during warmer-than-present states.

Earth's climate has undergone pronounced changes across geological time, from greenhouse states to icehouse conditions and back, to name just a few of the changes. While orbital forcing and carbon-cycle feedbacks are well established as pacemakers of Quaternary glacial cycles, the slower geodynamic processes that set the baseline climate state and modulate it on million-year timescales remain actively debated. Plate tectonics governs the carbon cycle at its source through volcanic degassing, and at its sink, through the uplift of terrains that accelerate chemical weathering. Seafloor spreading rates and the lengths of mid-ocean ridges, continental configuration and position, and the opening and closing of ocean gateways reshape global ocean circulation and heat transport. Large igneous province eruptions have been implicated in mass extinctions and hyperthermal events, while orogenesis and continental rifting alter atmospheric circulation patterns and the long-term drawdown of CO2.

This session invites contributions that explore the connections between solid-Earth dynamics and climate across all timescales - from the multi-hundred-million-year supercontinent cycle to million-year and sub-million-year variability. We welcome observational, modeling, and data-driven studies, including plate kinematic reconstructions, mantle convection simulations, paleoclimate proxy analyses, geochemical models, and statistical or spectral approaches that quantify the co-evolution of tectonic and climatic records. We particularly encourage contributions that bridge disciplinary boundaries linking geodynamic forcing functions to their surface expression in the sedimentary, geochemical, and paleobiological records.

Micropaleontological data provide unique insights into the dynamics and tipping points of past environments and climates through changes in the fossil record, including assemblage composition, morphology, and evolutionary patterns. Micropaleontology lies at the heart of biostratigraphy and provides a fundamental tool for reconstructing and stratigraphically constraining past changes in the Earth system. Our session aims to bring together a broad spectrum of micropaleontologists to showcase recent advances in the application of micropaleontological data to paleoenvironmental, paleoclimatological, and stratigraphic research in both marine and terrestrial settings.
We invite contributions from the field of micropaleontology that focus on the development and application of microfossils (including, but not limited to, coccolithophores, diatoms, dinoflagellates, foraminifera, ostracods, radiolarians, conodonts, and pollen) as proxies for paleoenvironmental and paleoclimatological reconstructions and tools for stratigraphic correlation. We particularly encourage submissions of multi-proxy approaches that merge micropaleontological, geochemical, and paleobiological information. The application of microfossils as stratigraphic markers and the advancement of multivariate statistical techniques with a focus on microfossil assemblages are encouraged.

This session aims to bring together multidisciplinary perspectives on the interplay between microbial activity, sedimentary processes, and geochemical signatures in lacustrine and marine environments, both modern and ancient. We seek contributions that explore how microbial metabolisms influence mineral formation (e.g., carbonates, clays, sulphates) how isotopic and molecular biosignatures record biogeochemical processes, and how sedimentary archives can be interpreted to reconstruct past environmental and climatic conditions.

We particularly encourage submissions that combine natural systems with experimental analogues, including laboratory simulations of mineral precipitation, microbe–mineral interactions, and environmental gradients. Studies integrating field observations, experimental data, and cutting-edge analytical or computational approaches (e.g., spectroscopy, synchrotron techniques, geochemistry, stable isotopes, machine learning) are especially welcome.

Topics of interest include, but are not limited to:
• Microbially mediated mineral precipitation in lacustrine and marine systems
• Early diagenesis and biosignature formation: field, lab, and model approaches
• Stable isotope systems as proxies for microbial and environmental processes
• Experimental analogues simulating early Earth, Mars-like, or extreme environments
• Sedimentary and geochemical archives for paleoclimate and paleoenvironmental reconstructions
• Integration of microbial ecology, mineralogy, and geochemistry to assess biogeochemical feedbacks
• Applications to the search for early life and biosignatures in the geological record and planetary contexts

This session aims to place recently observed climate change in a long-term perspective by highlighting the importance of paleoclimate research spanning the past 2000 years. We invite presentations that provide insights into past climate variability, over decadal to millennial timescales, from different paleoclimate archives (ice cores, marine sediments, terrestrial records, historical archives and more). In particular, we are focussing on quantitative temperature and hydroclimate reconstructions, and reconstructions of large-scale modes of climate variability from local to global scales. This session also encourages presentations on the attribution of past climate variability to external drivers or internal climate processes, data syntheses, model-data comparison exercises, proxy system modelling, and novel approaches to producing multi-proxy climate field reconstructions such as data assimilation or machine learning.

Tree rings are one of nature’s most versatile archives, providing insight into past environmental conditions at annual and intra-annual resolution and from local to global scales. Besides being valued proxies for historical climate, tree rings are also important indicators of plant physiological responses to changing environments and of long-term ecological processes. In this broad context we welcome contributions using one or more of the following approaches to either study the impact of environmental change on the growth and physiology of trees and forest ecosystems, or to assess and reconstruct past environmental change: (i) dendrochronological methods including studies based on tree-ring width, MXD or Blue Intensity, (ii) stable isotopes in tree rings and related plant compounds, (iii) dendrochemistry, (iv) quantitative wood anatomy, (v) ecophysiological data analyses, and (vi) mechanistic modeling, all across temporal and spatial scales.

Speleothems are key terrestrial archives of regional to global palaeoclimatic and palaeoenvironmental changes on sub-seasonal to orbital timescales. They provide high temporally resolved records which can be accurately and precisely dated using U–Th or U–Pb techniques in combination with a variety of proxies such as stable O and C isotopes and trace element ratios. Recent efforts have seen the rise in more non-traditional proxies, such as fluid inclusion water isotopes, organic biomarkers, pollen, dead carbon fraction etc. This advancement towards quantitative reconstructions of past precipitation, temperature, or other environmental variables and climate patterns are key for data-model comparisons and further evaluations. Beyond this, caves and karst areas additionally host an enormous suite of valuable proxy archives such as cave ice, cryogenic carbonates, clastic sediments, tufa, or travertine sequences, which complement the terrestrial palaeorecord, and are often associated with important fossils, historical or archaeological findings.

This session aims to integrate recent developments in the field and invites abstract submissions from a broad range of cave- and karst-related studies from orbital to sub-seasonal timescales.
In particular, we welcome contributions from:
(1) (quantitative) reconstructions of past climatic and environmental variables to explore precipitation, vegetation, fire frequency, and temperature changes across different climate zones;
(2) field- and lab-based developments of process-based methods to improve the application of cave and karst-related proxy variables;
(3) developments in chronological methods and their applications;
(4) process and proxy-system model studies as well as integrated research on developing and using databases such as SISAL (Speleothem Isotope Synthesis and AnaLysis).

We further welcome advancements in related and/or interdisciplinary areas, which pave the way towards robust (quantitative) interpretations of proxy time series, improve the understanding of proxy-relevant processes, or enable regional-to-global and seasonal-to-orbital scale analyses of the relationships between proxies and environmental parameters. In addition, research contributing to current international co-ordinated activities, such as the PAGES working group on Speleothem Isotopes Synthesis and AnaLysis (SISAL) and others are welcome.

This session invites contributions that advance a comprehensive understanding and quantification of climate shifts across multiple timescales, from local to global scales. Submissions may highlight new (multi-)proxy reconstructions from diverse archives, chronological improvements, emerging statistical approaches, and/or climate simulations that help identify, quantify, and interpret transient vs. abrupt climate changes across Quaternary glacial-interglacial cycles.

The session welcomes participants beyond the INTIMATE network who contribute to its central aims: progress on relative or absolute chronological methods, the reduction of reconstruction uncertainties, multi-site integration towards common timescales (e.g., to the Greenland event stratigraphy), a dedicated use of model-data or multi-proxy comparisons to disentangle climate or ecosystem signals, and exploring teleconnections, i.e., linking impacts to different climate system components across time and space.

We particularly invite studies that improve our understanding of atmosphere–ocean linkages of extreme climate events (e.g., AMOC weakening), those that seek to separate signals of changing seasonality and/or temperature vs. hydroclimate and their implications on past societies, as well as ecosystems. Where applicable, we encourage contributions that reflect on the potential implications of past climate shifts for: (1) understanding future climate change; (2) assessing impacts on terrestrial ecosystems and societies; and (3) identifying links between extreme climate states on land and changes in ocean circulation, external forcing, internal climate variability, or volcanic activity.

Past climate variability and extreme events cannot be understood from any single source of information. Climate-model simulations provide physically consistent representations of past climate states and the processes governing variability and extremes, but they cannot reproduce the unique sequence of events that actually occurred. Geological and biological proxies, historical documents, archaeological records and other event-based archives instead preserve evidence of the realised past, but with heterogeneous temporal resolution, spatial coverage, sensitivity, preservation and uncertainty. This session invites contributions that combine, compare or jointly interpret multiple sources of information to investigate past climate change, variability and extremes.

We particularly welcome studies integrating climate-model simulations with geological, palaeoenvironmental, documentary, historical or archaeological evidence; approaches addressing rare or high-impact events such as storms, floods, droughts and heat extremes; statistical or probabilistic methods designed to account explicitly for dating uncertainty, proxy sensitivity, observational thresholds, preservation biases and model uncertainty.

Of particular interest are approaches that move beyond simple model–data comparison towards a process-based understanding of what different sources can reveal about past climate states and events. Contributions exploring data assimilation, probabilistic inference, multi-proxy synthesis, event attribution, high-resolution palaeoclimate modelling, machine learning, or methods for identifying convergence and disagreement among heterogeneous evidence are encouraged.

The session aims to foster dialogue across traditionally separate communities and to explore how complementary information from models and archives can be combined to produce more physically grounded and uncertainty-aware reconstructions of past climate variability and extremes.

The Atlantic Meridional Overturning Circulation (AMOC), Earth's most critical climate heat distributor, may slow down sooner than previously expected. Although similar scenarios have occurred in the past, their expressions remain understudied.
The transition from the Last Glacial period into the Holocene was punctuated by a series of abrupt cooling events, linked to AMOC slowdown, such as the Younger Dryas, Heinrich-1, and the 8.2 ka event. These provide ground-truth evidence on the regional impacts on ecosystems and regional weather patterns. Understanding the mechanics, regional extent, and temporal progression of such events can inform us about how future AMOC-slowdown scenarios may play out.
We encourage contributions combining multi-proxy records (ice cores, lacustrine and marine sediments, and speleothems), regional syntheses, numerical modeling, and proxy–model comparisons, in particular, on the Younger Dryas period. We aim to integrate discussions of the interconnected mechanisms linking (hydro)climatic changes to disruptions in atmospheric and ocean circulation. Responses to the impacts of large-scale processes on regional (hydro)climatic and environmental expressions across regions, building a broader picture and highlighting spatio-temporal disparities. Thereby, exploring new avenues that go beyond the ‘classical’ AMOC weakening/strengthening conversation.

The Quaternary (2.56 Ma to present) is characterized by recurring glacial–interglacial cycles and major reorganizations of the climate system. Two particularly prominent transitions stand out: the Mid-Pleistocene Transition (MPT, ~ 1.2–0.65 Ma), marked by a shift in dominant glacial cyclicity from ~ 41 kyr to ~ 100 kyr, and the Mid-Brunhes Transition (MBT, ~430 ka), associated with a shift toward generally stronger interglacials and changes in atmospheric CO₂, ice volume and ocean–atmosphere interactions.

Both transitions involved profound changes in the climate system, including reorganizations of atmospheric and oceanic circulation, ocean heat redistribution and carbon storage, as well as adjustments in global thermal and hydrological gradients. These were accompanied by significant changes in the cryosphere, including ice sheet extent and dynamics, and in both marine and terrestrial biospheres. However, despite decades of research, the relative roles of orbital forcing, internal feedbacks and changing climate system sensitivity remain debated.

This session aims to bring together new insights from marine and lacustrine sediment cores, ice cores, speleothems and numerical simulations in order to better characterize the paleoenvironmental conditions associated with these key transitions and to constrain the interactions among the different components of the climate system.

We welcome contributions based on geochemical, mineralogical, micropalaeontological, and modelling approaches, covering a broad range of timescales and regions. We particularly encourage contributions addressing orbital and millennial-scale variability as well as regional vs global climate signals. Those integrating multiple archives, proxies or modelling approaches are especially welcome.

The global ocean and climate variability is controlled by manifold and complex interactions between low and high latitudes, mediated via atmospheric and oceanic circulation. For instance, waxing and waning of Northern Hemisphere ice sheets modulate global monsoon systems and the ITCZ through their influence on the global overturning circulation. In turn, the low latitude oceans and atmospheric circulation are central to the global hydrological cycle and climate as they provide the heat and moisture distributed across latitudes and longitudes. Western boundary currents connect low and high latitudes as they control heat and salt export from the tropics towards the poles. The Southern Ocean is central to the global carbon cycle and thought to control glacial-interglacial changes in atmospheric CO2.

While the interplay between low and high latitudes is essential for major global climate changes on various time scales, documenting the teleconnections and transmission pathways involving “atmospheric bridges” and “ocean tunnels” remains a major challenge. Numerous issues remain unresolved: For instance, do the low latitudes lead or lag the high-latitude changes during terminations and millennial events? Do Northern or Southern Hemisphere high latitudes exert a more dominant influence on the tropics?

In this session, we welcome contributions on all aspects of climate linkages between low and high latitudes from around the globe spanning centennial to orbital time scales during the Quaternary. This includes proxy reconstructions from various archives (marine sediments, corals, speleothems, lake sediments and ice cores), as well as numerical models (including PMIP, freshwater housing experiments, transient simulations). By bringing together communities working across different latitudes, this session aims to reconcile proxy and model perspectives of inter- and intra-hemispheric coupling to foster an improved understanding of large-scale ocean and climate dynamics.

The dispersal and evolution of hominins from North Africa to Eurasia coincided with large-scale climatic and environmental changes. Glacial-interglacial cycles, abrupt climate events, and long-term environmental variability across the Mediterranean and Western Asia shaped migration pathways, ecosystem dynamics, and human adaptation. This session aims to bring together researchers investigating the climate history of this interconnected region using paleoclimate and archaeological archives, such as cave sediments, open-air sites, and rock shelters. We welcome contributions spanning a wide range of timescales and reconstruction methods. Topics include, but are not limited to, high-resolution reconstructions of temperature, hydroclimate, vegetation, atmospheric circulation, and archaeological evidence using any archive, including dispersion- and climate models. We encourage studies that combine paleoenvironmental records with archaeological evidence to investigate the environmental context of hominin evolution, migration, and technological change in corridors of Eurasian expansion. By fostering dialogue between paleoclimatologists/modelers, and archaeologists, this session seeks to advance an integrated understanding of how climate variability influenced the Eurasian landscapes through which hominins dispersed and adapted.

Skeletal remains, like shells, ossicles, corals, bones, or fish otoliths, are valuable archives of physical, chemical, or paleogenetic information, helping us understand ecological and environmental changes over periods ranging from decades to millennia, whether on land or in the ocean. This session invites researchers who employ these archives to reconstruct changes in species and ecosystems in relation to climate variability and/or human impacts across both the deep time and the recent past. We encourage contributions that focus on biotic interactions, species and community dynamics, sclerochronology, isotope geochemistry, trait-based analyses, morphometric approaches, and ancient DNA/sedimentary DNA, in particular conservation-oriented case studies that combine data from modern biota and fossil remains. Complementary paleoecological archives—such as biogeochemical and isotopic signatures from sedimentary succession or archaeological middens—are also welcome, primarily when they document histories of environmental disturbance and its ecological consequences. We also welcome paleobiogeographic reconstructions that explore range shifts, corridor/barrier dynamics, and distributional disequilibria to inform how species’ spatial patterns have responded to past environmental change. In conclusion, by examining long-term records, we can gain insights into the potential consequences of present-day environmental stressors and climate change, reconstruct past dynamics of species and ecosystem changes, including extinction, recovery, and biogeographic shifts, and thus obtain valuable insights that can help us sketch the near-future trajectories of contemporary ecosystems.

Long-term instrumental weather records are limited even in data-rich regions such as Europe and North America, and are much scarcer elsewhere. Understanding climate change requires a truly global picture built from observations worldwide. The existing gaps limit our ability to study multi-decadal climate change across much of the globe. Closing them requires a coordinated international effort to create a comprehensive inventory of records that already exist in paper format, scan them, and rescue their data. These observations provide a key starting point for understanding past climates, a reference for validating climate models, and essential input for climate reanalyses.
This session invites abstracts on the identification and rescue of historical weather observations from previously unexplored locations and periods, including former European territories and administrative regions, as well as newly independent countries in Asia and Africa. Contributions focusing on the creation of inventories of historical weather records are also particularly welcome. Submissions may address new data sources, innovative methods of data extraction, or applications of rescued data. We particularly welcome work using automated AI/ML workflows, citizen-science approaches, and best practices, as well as studies applying historical data to understand climate extremes, floods, and other risks. By incorporating evidence from historical extreme climate events, this session will further support research and action on climate adaptation.

Urban areas fundamentally alter micro- to regional-scale atmospheric and hydrological processes via modification of energy and water balances. With urbanization continuing globally, understanding and mitigating these impacts on society and infrastructure is critical. This session solicits submissions from research and practice communities bridging natural and social sciences to address urban climate and water challenges. Relevant approaches span micro- to regional-scale modeling, high-resolution satellite remote sensing, and dense low-cost or crowdsourced networks that capture fine-scale to city-wide heterogeneity of the urban canopy layer.
We welcome studies on urban atmospheric and hydrological dynamics, their biometeorological implications, and the efficacy of urban planning and design strategies in mitigating the impacts of urban heat, floods, droughts, and other hazards.
We specifically invite research:
- resolving these processes across different spatial and temporal scales
- linking physical dynamics with human health and well-being under extreme events
- highlighting cascading and compound hazards such as concurrent heatwaves, drought and pluvial flooding, and their disproportionate impacts on communities with unequal adaptive capacity
- focusing on actionable science demonstrating how cities use novel data products and climate services to guide planning and policy
- applying emerging innovations and approaches that foster climate-resilient and adaptive cities and citizens, such as digital twins, AI-based forecasting, early-warning systems, and citizen science, as well as other innovations for climate resilience.

The radiation budget of the Earth is a key determinant for the genesis and evolution of climate on our planet and provides the primary energy source for life. Anthropogenic interference with climate occurs first of all through a perturbation of the Earth radiation balance. We invite observational, modelling and data-driven papers on all aspects of radiation and energy flows in the climate system. A specific aim of this session is to bring together newly available information on the spatial and temporal variation of radiative and energy fluxes at the surface, within the atmosphere and at the top of atmosphere (including EEI). This information may be obtained from direct measurements, satellite-derived products, climate modelling as well as AI-based and process studies. Scales considered may range from local radiation and energy balance studies to continental and global scales. In addition, related studies on the spatial and temporal variation of cloud properties, albedo, water vapour and aerosols, which are essential for our understanding of radiative forcings, feedbacks, and related climate change, are encouraged. Studies focusing on the impact of radiative forcings on the various components of the climate system, such as on the hydrological cycle, on the cryosphere or on the biosphere and related carbon cycle, are also much appreciated.

Subsurface temperature, particularly groundwater temperature, is an emerging indicator of environmental change. Climate change and urban heat are altering subsurface temperature regimes, including their long-term trends, spatial patterns, and seasonality. Yet subsurface temperatures remain largely “out of sight, out of mind”: observations are fragmented, monitoring approaches vary widely, and we still lack a comprehensive understanding of how subsurface temperatures are changing and what these changes mean.
This session brings together research on subsurface temperature monitoring, from soil and borehole measurements to groundwater temperature observations, as well as approaches for estimation, modelling, and prediction in both urban and rural environments. We also welcome studies investigating changes in subsurface temperature and seasonality and their consequences. Contributions may span spatial and temporal scales, from individual monitoring sites and urban environments to regional and global assessments. We particularly encourage work exploring both the challenges and opportunities associated with changing subsurface temperature regimes.

High-quality observational data are crucial to establish reliable datasets for studying historical changes, the current state, and the future evolution of Earth's climate. This session provides a forum to discuss best practices for quality control, harmonization, and homogenization of observational data for climate services and applications. Key topics include data assimilation into reanalyses (e.g., ECMWF's forthcoming ERA-6), as well as integration into physical retrieval algorithms and AI/ML techniques (e.g., within ESA's Climate Change Initiative or EUMETSAT Satellite Application Facilities). We also invite contributions analyzing the impact of these data on long-term Essential Climate Variable (ECV) datasets.

Integrating observational data into climate services demands strict quality and consistency standards, including calibration, spatial/temporal coverage, and homogeneity. Reanalyses perform best with well-calibrated data that preserve each sensor's unique characteristics (harmonized data), whereas long-term ECV datasets across atmospheric, terrestrial, and oceanic domains rely on data adjusted to a common reference (homogenized data).

We invite contributions on climate datasets from in-situ observation networks, satellite remote sensing, and reanalyses. The aim is to bring together data developers and users to demonstrate the downstream impact of these observational data on climate applications. Specifically, the session seeks presentations on:
- Data rescue and recovery of historical climate datasets.
- Harmonization, homogenization, and validation of observational climate datasets.
- Novel prospects (AI/ML) to exploit observations and their emerging requirements.
- Impact evaluation of observational datasets on climate services, trend analysis, and attribution studies of weather and climate extremes.

The Intergovernmental Panel on Climate Change (IPCC) describes adaptation as the process of adjustment to actual or expected climate and its effects, in order to moderate harm or exploit beneficial opportunities. With over 1 degree Celsius of global warming already experienced, adapting to current and future climate changes is now of far greater focus for all levels of policymaking than ever before. Yet, the IPCC and the UNEP-WASP Adaptation Gap Reports (2023) both conclude that despite progress, adaptation gaps exist and will continue to grow at current rates of implementation.

More recently, the UNFCCC had agreed a set of 59 Global Goal on Adaptation (GGA) Indicators, of which, monitoring, evaluation and learning is one of the four core targets. The text states that by 2030, all Parties have designed, established and operationalized a system for monitoring, evaluation and learning for their national adaptation efforts and have built the required institutional capacity to fully implement the system.
Satellite Earth Observation (EO) revolutionized systemic observations and has played a pivotal role in understanding climate changes to date, yet its potential to support adaptation is only beginning to be explored. EO has great potential for supporting climate action across all stages of the adaptation process, greater than what is already being achieved today.

This session will highlight ongoing research projects that use EO to plan, monitor and/or evaluate climate change adaptation across a multitude of scales and sectors.
References
IPCC, 2022: Climate Change 2022: Impacts, Adaptation, and Vulnerability. Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press. Cambridge University Press, Cambridge, UK and New York, NY, USA, 3056 pp., doi:10.1017/9781009325844.
Connors, S., Schneider, R., Nalau, J. et al. Earth observations for climate adaptation: tracking progress towards the Global Goal on Adaptation through satellite-derived indicators. npj Clim Atmos Sci 8, 359 (2025). https://doi.org/10.1038/s41612-025-01251-1
United Nations Environment Programme (2023). Adaptation Gap Report 2023: Underfinanced. Underprepared. Inadequate investment and planning on climate adaptation leaves world exposed. Nairobi. https://doi.org/10.59117/20.500.11822/43796
The UNFCCC Global Goal on Adaptation Indicators: https://unfccc.int/topics/adaptation-and-resilience/workstreams/gga

Atmospheric reanalyses combine historical observations with a consistent numerical weather prediction model and data assimilation system to provide spatially and temporally complete reconstructions of the atmosphere. They are indispensable tools for studying climate variability, atmospheric dynamics and high-impact weather. However, their utility in diagnosing the mechanisms behind extreme events can be limited by inherent structural uncertainties and data artefacts. While modern reanalyses generally agree on large-scale climatological means, discrepancies can emerge when evaluating transient sub-synoptic gradients, localised diabatic feedbacks, and circulation features during extreme events. These differences can be particularly pronounced in regions and periods with sparse observational coverage, where reanalyses are more weakly constrained by observations and therefore more susceptible to biases in the underlying model and data-assimilation system. Furthermore, changes in the assimilated observations can introduce non-climatic jumps, representation errors, and artificial trends.

This session provides a forum for diagnosing uncertainties, limitations and artefacts in global and regional reanalyses when studying tropospheric circulation and weather extremes. We invite contributions addressing:

1. Structural uncertainties from large-scale teleconnections to atmospheric blocking, jet stream waviness, Rossby wave breaking, and storm tracks across reanalysis products (e.g., ERA5, MERRA-2, JRA-3Q).
2. Artefacts, discontinuities, and spurious trends introduced by changes in the observing system over time, alongside robust variability and trends shared across reanalysis.
3. Representation errors in land-atmosphere and air-sea coupling, including how biases in sensible/latent heat fluxes, diabatic heating and water budgets alter synoptic- and mesoscale extremes (e.g., convective environments, atmospheric rivers, explosive cyclogenesis).
4. Physical consistency, uncertainties, and artefacts in emerging machine-learning-based or AI-assisted reanalyses, particularly during extreme weather.

We welcome both studies evaluating the suitability and robustness of reanalyses for diagnosing tropospheric circulation and weather extremes, and science-driven studies using multiple reanalyses to assess the robustness of specific atmospheric or climate questions.

Attribution research in the context of climate change investigates the extent to which human influence, via different factors, contributes to changes and events in the climate system and their impacts on natural, managed, and human systems. Disentangling external forcing and climate variability as well as isolating climate change impacts from other drivers is a challenging task engaging various approaches.

The field of Detection and Attribution (D&A) identifies historical changes over long timescales, typically multi-decadal, of weather and climate as well as their impacts. D&A specifically quantifies the contributions of various external forcings as their signal emerges from internal climate variability. Moreover, event attribution (EA) assesses how human-induced climate change is modifying the frequency and/or intensity of extreme weather events (e.g. a heatwave), their impacts (e.g., economic loss or loss of life associated with flooding), or events from an impact perspective (e.g., a crop failure). These and other analyses focusing on attributing impacts combine observations with model-based evidence or process understanding. The attribution of climate change impacts is particularly complex due to the influence of additional non-climatic human influences.

This session highlights recent studies from the broad spectrum of attribution research that address some or all steps of the climate-impact chain from emissions to climate variables, to impacts in natural, managed, and human systems and aims to explore the diversity of methods employed across disciplines and schools of thought. It also covers a broad range of applications, case studies, current challenges of the field, and avenues for expanding the attribution research community. It specifically also includes studies that focus on the influence of specific externally forced changes as well as separating, quantifying, and understanding internal variability as both constitute a key uncertainty in climate attribution.

Presentations will cover common and new methodologies (improved statistical methods, statistical causality, Artificial Intelligence) using single climate realisations, large ensembles, or other methods to derive counterfactuals, on single climate variable or compound/cascading events, on impacts on natural, managed, or human systems.

Climate model development is currently undergoing profound expansion with the application of cutting-edge technologies such as machine learning, the development of process resolving models on ever finer scales and the improved representation of climate variability and trends. However, deficiencies in model simulations remain and work to address these continues as we strive to understand our rapidly changing climate. Observations are a vital for improving models: guiding development foci and for evaluation of model performance. At the same time the observational ecosystem is constantly changing not least due to shifting funding priorities for both space and earth-based observation networks. Nevertheless, recent years have seen increased engagement between observation providers and the modelling community and, importantly, the start of significant improvements in communicating observation quality and uncertainty. The interface between observations and models is complex and identifying the correct observational dataset for a specific application is not always straightforward, particularly for satellite-derived CDRs, where retrieval assumption and algorithm choices can generate uncertainties comparable to the model differences. Developments in this space recognise that better communication between observational and modelling communities is required and a number of initiatives provide platforms which allow access to datasets in standardised formats or peer reviewed and traceable methods to produce model validation diagnostics.

The WCRP core project CLIVAR and the WCRP ESMO working group WGORC are jointly organising this session with the aim to build stronger links between observational and modelling communities and explore recent advances in the use of observations for evaluating climate models.

We invite submissions on innovative approaches comparing models and observations including, but not limited to, the detailed consideration of uncertainties, use of ensembles and the use of novel observational datasets. We also welcome studies which use observations to assess processes across the coupled climate system and presentations showcasing recent developments in tools and platforms and data driven methods for model/observation comparisons.

Climate change is reshaping European ecosystems through increasing drought, heat stress and disturbances frequency and intensity as well as increased plant mortality, thereby altering the structure and composition of these ecosystems. Plants regeneration therefore appears as a key process for the persistence and redistribution of plant populations under these changing conditions. Regeneration is not a single demographic rate, but rather a trajectory consisting of a sequence of stages and transitions, from flowering and seed production through dispersal, germination, establishment, and recruitment. This breadth, together with the scarcity of long-term and large-scale monitoring, result in regeneration being poorly understood compared to other processes, despite its central role in determining the future dynamics of populations and communities.
Because successful recruitment depends on plant survival throughout the regeneration trajectory, climate-driven changes occurring at any stage of this trajectory can constrain the success of subsequent stages and ultimately determine regeneration success. Conversely, other stages may potentially buffer the negative effects of climate change. The future and importance of each regeneration stage in the upcoming years therefore depend on its sensitivity to environmental drivers. Although important drivers are likely to be stage- and species-specific and to be variable among regions and environmental conditions, this variation could also reveal broader and potentially generalisable patterns.
Many questions remain as to which stages of regeneration are most sensitive to ongoing climate change, where and under which conditions regeneration is most at risk, and which species, populations, traits, or environmental contexts support resilience. This session aims to bring together research on managed and unmanaged ecosystems (excluding purely agricultural settings) across the regeneration trajectory. We welcome contributions using long-term observational data, experiments, spatial gradients, demographic analyses, and modelling to investigate how biotic and environmental drivers shape European’s tree and long-lived plant regeneration. By gathering observations from numerous species, regeneration stages and locations evidence, this session seeks to advance understanding of where and why regeneration is succeeding or failing, and what these changes imply for the composition and resilience of European ecosystems.

Phenological changes induced by ongoing climate change are affecting species, ecosystems, and even the global climate by altering species performance, species interactions (potential mismatches and new opportunities in the food web), and water and carbon cycles. Observations of plant and animal phenology as well as remote sensing and modeling studies document complex interactions and raise many open questions about the future sustainability of species and ecosystems. In this session we invite all contributions that address seasonality changes based on plant and animal phenological observations, pollen monitoring, historical documentary sources, or seasonality measurements using climate data, remote sensing, flux measurements, modeling studies or experiments. We also welcome contributions addressing cross-disciplinary perspectives and international collaborations and program-building initiatives including citizen science networks and data analyses from these networks.
This session is organized by a consortium representing the International Society of Biometeorology (Phenology Commission), the Pan-European Phenology Network - PEP725, the Swiss Academy of Science SCNAT, the TEMPO French Phenology Network and the USA National Phenology Network.

Climate change-induced drought and extreme events are exerting increasing pressure on forest persistence and resilience. This pressure manifests across biological, spatial and temporal scales, from trees adjusting physiological processes and resource allocation under limiting water conditions to changes in interactions among individuals, species and their environment. These responses can translate into altered growth and functioning, increased mortality, and shifts in population dynamics and community structure.
A major challenge is to understand how processes and responses observed at one organizational scale relate to those emerging at others. This requires integrating complementary perspectives.
This session welcomes research connecting two or more scales of tree-to-forest responses, from biochemical and ecophysiological processes to, populations, communities and landscapes. We invite contributions using stable isotopes, tree rings, ecophysiological measurements, experiments, long-term forest observations, remote sensing, demographic approaches aimed at understanding the processes of forest resilience in a rapidly changing climate.

The statistical characterization and modelling of precipitation are crucial in a variety of applications, such as flood forecasting, water resource assessments, evaluation of climate change impacts, infrastructure design, and hydrological modelling. This session aims to gather contributions on research, advanced applications, and future needs in the understanding and modelling of precipitation, including its variability at different scales and its sources of uncertainty.

Contributions focusing on one or more of the following issues are particularly welcome:
- Process conceptualization and approaches to modelling precipitation at different spatial and temporal scales, including model parameter identification, calibration and regionalisation, and sensitivity analyses to parameterization and scales of process representation.
- Novel studies aimed at the assessment and representation of different sources of uncertainty of precipitation, including natural climate variability and changes caused by global warming.
- Uncertainty and variability in spatially and temporally heterogeneous multi-source ground-based, remotely sensed, and model-derived precipitation products.
- Estimation of precipitation variability and uncertainty at ungauged sites.
- Modelling, forecasting and nowcasting approaches based on ensemble simulations for synthetic representation of precipitation variability and uncertainty.
- Machine-learning approaches for precipitation modelling, forecasting, and downscaling: Machine-learning and hybrid (physics-informed) methods for precipitation simulation, uncertainty quantification, bias correction, and spatio-temporal downscaling, including baseline comparisons, cross-climate transfer tests, and evaluations of explainability and robustness.
- Scaling and scale invariance properties of precipitation fields in space and/or in time.
- Dynamical and statistical downscaling approaches to generate precipitation at fine spatial and temporal scales from coarse-scale information from meteorological and climate models.

Recent changes across the Antarctic atmosphere–ocean–cryosphere system have been profound, and projections suggest that many of these changes will continue or even accelerate. These changes arise from interactions spanning scales from turbulent boundary-layer exchange and individual weather systems to basin-scale ocean circulation and large-scale atmospheric variability. These components are often studied separately, despite forming connected physical pathways. Large-scale circulation and storm tracks modulate cyclones, katabatic winds and air-mass intrusions; atmospheric heat, moisture and momentum fluxes affect sea-ice formation, drift, export and polynya activity; sea-ice changes modify air–sea exchange, ocean stratification, mixing and continental-shelf circulation; and ocean heat and freshwater exchanges influence ice-shelf basal melting, cavity circulation and downstream climate feedbacks. Resolving these multiscale pathways is essential for understanding recent Antarctic change and improving future projections.
We invite contributions based on in situ observations, field campaigns, satellite remote sensing, reanalyses, theory, process studies, regional coupled models and Earth system models. Topics include multiscale atmospheric forcing of sea ice, polynyas and ice shelves; interactions among katabatic winds, cyclones, large-scale circulation and surface fluxes; feedbacks from leads and open water to the atmospheric boundary layer; sea-ice–wave–ice-shelf interactions; upper-ocean buoyancy forcing, stratification and convection; continental-shelf circulation, dense-water formation and export; ice-shelf meltwater and coupled feedbacks; and emergent behaviour under future climate change. We particularly encourage studies that connect two or more components through testable physical mechanisms, quantify interactions across weather-to-climate scales, assess observational or modelling uncertainties, or identify priorities for future observing systems and coupled-model development.

Weather and climate extremes, such as intense precipitation, tropical and extratropical storms, drought, heatwaves, and compound events, pose substantial risks to society, infrastructure, and ecosystems across the globe. Yet directly and explicitly modelling such extremes and their future behaviour remains challenging, owing to the high computational cost of resolving relevant processes, incomplete understanding of many driving mechanisms, and the chaotic nature of atmospheric dynamics, which further limits predictability at longer lead times. Consequently, model-based projections often carry large uncertainties, especially in how complex and non-linear interactions among atmospheric variables shape these extremes in a future warmer world.

Observational constraints and statistical approaches offer a complementary pathway. Observations from ground-based networks, radars, and satellites, together with reanalysis simulations, can provide information on the characteristics and physical drivers that can be used to evaluate and constrain models. Statistical and data-driven models, when constrained by associated temperature, moisture, storm characteristics, and regional and global circulation teleconnections, can provide viable alternatives for problems that remain too computationally expensive, while incorporation of constraints in explicit physical simulations can help narrow uncertainties and reduce model biases.

This session aims to bring together research on the use of observational constraints, physical theory, and statistical approaches for improved understanding, prediction and projection of past and future extremes. We welcome contributions including, but not limited to, assessing the drivers of extremes, scaling relationships based on physical theory, storyline approaches, and statistical and hybrid approaches, as well as studies critically evaluating the physical basis and robustness of the proposed constraints. Contributions spanning various types of extremes, spatial and temporal scales, and observational and modelling frameworks are encouraged.

Rossby wave dynamics stands at the intersection of several open research questions, ranging from our basic understanding of mid-latitude variability, to the short- and medium-range predictability of high-impact weather events, and to the circulation changes expected from anthropogenic global warming. Rossby waves exist and propagate along vorticity gradients such as the one related to the tropopause-level jet stream, whose complex meandering often "breaks" creating nonlinear circulation features, such as atmospheric blocking.

Recent extreme weather and climate episodes, like heavy rainfall events leading to flash floods, recurrent and concurrent summer heatwaves or unforeseen winter cold spells, highlight the need to improve our understanding of jet streams and of the associated linear and non-linear, planetary and synoptic-scale Rossby wave dynamics in the atmosphere to better constrain the impacts of Rossby waves and of atmospheric blocking on extreme weather and climate events.

Abstracts are invited on a wide range of topics, with a focus on, but not limited to, the following areas:

(1) Theoretical developments in the dry and moist dynamics of Rossby waves, wave breaking, atmospheric blocking, and of jet streams acting as atmospheric Rossby waveguides. This includes the role of local and remote drivers (e.g., the tropics, Arctic, or stratosphere) in affecting Rossby wave evolution.
(2) Linkages between extreme weather/climate events and the jet stream, as well as the associated linear and non-linear Rossby wave evolution during such events, including Rossby wave breaking, cut-off formation and re-absorption, and atmospheric blocking.
(3) Application of cutting-edge methods to study the multi-scale interaction of Rossby waves from the convective scale to the large-scale dynamics, and its representation in existing weather and climate models (e.g. hierarchical and/or high-resolution modelling, machine learning/AI-based approaches).
(4) Exploring the effect of Rossby wave packets on predictability at lead times from medium range (~2 weeks) to seasonal time-scales. This includes the potential role of blocking and of teleconnections involving Rossby wave propagation.
(5) Projected future changes in planetary or synoptic-scale Rossby waves, and in their connection to extreme weather and events in a changing climate.

Mountains cover approximately one quarter of the earth’s land surface, and a significant fraction of the world’s population lives within them, in their vicinity, and downstream of them. Orography critically affects weather and climate processes across all scales and, in connection with factors such as land-cover heterogeneity, is responsible for high spatial variability in mountain weather and climate. This session showcases research that contributes to improving our understanding of weather and climate processes in mountain and high-elevation areas around the globe, as well as their modification induced by global environmental change, including studies connected to the TEAMx research programme.

We invite theoretical, modeling and observational contributions that address the influence of mountains on the atmosphere from meteorological to climate time scales, including terrain-induced flows, orographic gravity waves, orographic precipitation, land-atmosphere exchange over mountains, forecasting and predictability of mountain weather, and the interaction of mountain weather and climate with the terrestrial cryosphere.

Furthermore, we invite studies that investigate climate processes and climate change in mountain areas based on monitoring and modeling activities, including in particular contributions that address the interdisciplinary objectives of the Elevation-Dependent Climate Change (EDCC) working group of the Mountain Research Initiative, as well as the application and development of high-resolution (kilometer-scale) climate models over complex mountainous terrain, such as advances in model design, challenges, and observational gaps needed for robust model evaluation and improvement.

Traditionally, hydrologists focus on the partitioning of precipitation water on the land surface into evaporation and runoff, while ignoring factors that influence precipitation. However, more than half of the evaporation globally returns as precipitation on land. Given this important feedback of the water cycle, changes in land-use and water-use, as well as climate variability and change, impact not only the partitioning of precipitation water but also the atmospheric input of water as precipitation, at both remote and local scales.

This session aims to:
i. investigate the remote and local atmospheric feedbacks from human interventions such as greenhouse gasses, irrigation, deforestation, and reservoirs on the water cycle, precipitation and climate, based on observations and coupled modelling approaches,
ii. investigate the use of hydroclimatic frameworks such as the Budyko framework to understand the human and climate effects on both atmospheric water input and partitioning,
iii. explore the implications of atmospheric feedbacks on the hydrological cycle for land and water management.

Applied studies in this session may adopt fundamental characteristics of the atmospheric branch of the hydrological cycle on different scales. These fundamentals include, but are not limited to, atmospheric circulation, humidity, hydroclimate frameworks, residence times, recycling ratios, sources and sinks of atmospheric moisture, energy balance and climatic extremes. Studies may also evaluate different data sources for atmospheric hydrology and implications for inter-comparison and meta-analysis. Examples of data sources and methodological approaches include observation networks, isotopic studies, conceptual models, Budyko-based hydroclimatological assessments, back-trajectories, reanalysis and fully coupled Earth system model simulations.

Climate is inherently geographical. Climatic processes vary across space and time and interact with topography, land cover, water bodies, ecosystems, urban environments and human societies. Geographical climatology provides an integrative framework for understanding these interactions and for bridging atmospheric processes with their spatial expression and environmental and societal consequences.
This session invites contributions addressing the geographical dimensions of climate variability and change across a broad range of spatial and temporal scales.
We particularly welcome studies dealing with:
• synoptic, regional and local climatology;
• spatial and temporal variability of temperature, precipitation and other climatic variables;
• heat waves, droughts, floods, storms, cold spells and other climatic extremes;
• urban climatology, urban heat islands and thermal environments;
• topoclimatology and microclimatology;
• land–atmosphere and ocean–atmosphere interactions;
• climate variability and long-term climatic trends;
• geographical patterns and regional manifestations of climate change;
• climate hazards, vulnerability and risk;
• interactions between climate, landscapes, ecosystems and human societies;
• climate-related impacts on health, agriculture, water resources and urban environments;
• adaptation to climate change at local and regional scales;
• remote sensing and GIS applications in climatology;
• spatial climatological databases, reanalysis products and observational networks;
• statistical, geospatial and modelling approaches to geographical climatology.
The session particularly encourages research that crosses traditional disciplinary boundaries and demonstrates how geographical approaches can contribute to understanding climate processes and their environmental and societal impacts.
Contributions integrating observations, remote sensing, reanalysis data, climate modelling and spatial analysis are welcome, as are comparative studies from different climatic regions of the world.
The session aims to strengthen interaction between climatology and the broader geographical and geoscientific communities and to highlight the continuing importance of geographical perspectives for understanding climate variability, extremes and climate change.

Large-scale atmospheric dynamics and synoptic systems are key drivers of near-surface variables (e.g., air temperature, precipitation), their variability and their extremes such as heatwaves, floods, and droughts. To be prepared for potential future extreme weather events, we need to further study the link between regional extremes and features of the large-scale atmospheric circulation (e.g., circulation patterns, weather regimes, blocking patterns, extra-tropical cyclones, teleconnection indices) and if and how these dynamics are changing. Various linear and non-linear approaches of synoptic climatology (e.g., multiple regression, canonical correlation, neural networks) can be applied to relate the circulation dynamics to diverse climatic and environmental elements and extremes. This session focuses on understanding regional extremes, their link to atmospheric dynamics, and their future evolution under climate change while welcoming contributions from various methodological approaches.
We welcome contributions that explore:
- The links between large-scale atmospheric circulation features (e.g., circulation patterns, weather regimes, blocking patterns, extra-tropical cyclones, teleconnection indices, NAO) and various types of regional extreme weather events (such as heat waves, heavy precipitation, floods, droughts)
- Past, recent and future trends in frequency, intensity, and variability of regional extremes or surface environmental variables and their associated atmospheric features under climate change
- The influence of internal climate variability on the occurrence of regional extreme events associated with large-scale atmospheric circulation features
- The use of innovative methods, including large ensembles, and AI for circulation type classification
This session invites contributions that explore the connections between different types of regional extremes and the atmospheric circulation, as well as studies from general synoptic climatology that focus on the relationship between atmospheric circulation dynamics and near surface environmental variables, their variability, and changes. The aim is to enhance our understanding of the dynamic drivers behind regional extremes in the context of climate change.

Kilometer-scale models provide new opportunities to understand how weather systems respond to climate change by explicitly representing convection, mesoscale organization, complex terrain, and coupled processes. Regional convection-permitting simulations and emerging global storm-resolving models offer complementary approaches, ranging from targeted event studies to multi-decadal climate simulations.

This session focuses on how kilometer-scale modelling can advance our understanding of weather in a changing climate. We particularly welcome studies using event attribution, storylines, pseudo-global-warming experiments, extreme-event boosting, and other process-oriented approaches to investigate the mechanisms driving changes in individual events or classes of weather systems.

We invite contributions that:
1. use regional or global kilometer-scale simulations to investigate climate change effects on weather and extremes;
2. use attribution, storylines, pseudo-global-warming, extreme-event boosting, or targeted experiments to investigate the effects of climate change on weather systems and the mechanisms involved;
3. examine the physical mechanisms and cross-scale interactions that control changes in the intensity, frequency, duration, or organization of extremes;
4. compare regional and global kilometer-scale modelling approaches, including their respective strengths, limitations, and complementarity;
5. evaluate the added value, biases, uncertainties, and computational challenges of kilometer-scale modelling.

Studies of heavy precipitation, severe convection, tropical cyclones, heatwaves, windstorms, compound extremes, and other high-impact weather are encouraged. Contributions from regional and global modelling communities, including those involved in CORDEX, DYAMOND, nextGEMS, Destination Earth, and EERIE, are particularly welcome.

The accelerating growth of atmospheric CO2, CH4, and N2O poses major threats to the Earth system and climate, having moved the world closer to breaching international climate targets, such as the Paris Agreement and the Global Methane Pledge. In recent years, evidence is accumulating that warming is driving increased greenhouse gas emissions from natural systems. This emission-driven warming will likely continue and intensify due to climate feedback mechanisms. These biogeochemical feedbacks involve not only well-known processes in the atmosphere, ocean, and cryosphere, but also land-based systems such as permafrost, boreal–tropical forests, dynamic vegetation, wetlands, fire, and inland waters, many of which are tightly linked to one another. However, large uncertainties remain in the quantification of these processes for both warming-induced emissions and the associated temperature implications. Understanding these underlying mechanisms will help us address our remaining questions, such as: 1) Which feedback processes are most relevant for mitigation strategy planning (e.g., via the Transient Climate Response to cumulative Emissions of carbon dioxide (TCRE) or non-CO2 contributions to carbon budgets)? 2) What drives nonlinearity in the future climate trajectories? 3) Is the future climate (ir)reversible? 4) When will the climate be irreversible? 5) How will the climate respond to “overshoot, peak, and decline” scenarios? 6) What are the associated uncertainties across regional to global scales?

This session aims to gather and integrate work that tackles the impacts of warming-induced emissions on the Earth system and the mechanisms underlying them, thereby providing clearer guidance for sustaining human society within the remaining carbon budget. All community efforts (e.g., WIEMIP) toward these goals are strongly encouraged. We welcome all contributions spanning laboratory-based experiments, satellite and field observations, machine-learning emulators, and modeling approaches, including fully-coupled Earth system models and stand-alone models.

Running Earth system models, downscaling outputs and driving process-based impact models are computationally expensive tasks that hinder the exploration of climate change impacts. New generations of statistical, physical, and hybrid climate change emulators reduce these bottlenecks by mimicking global, regional and extreme-event responses to generate projections of climate change and its associated impacts more efficiently. This capability transforms the assessment of climate change impacts and risks by enabling rapid policy-relevant analyses for sectors such as natural systems, agriculture, water resources, economics, energy systems and human health.

This session invites contributions on the developments and applications in climate change emulation, highlighting opportunities and challenges for robust and computationally efficient climate risk assessments. This includes simple climate models, probabilistic emulation techniques and machine learning approaches, including traditional pattern scaling, as well as benchmarking efforts that aid in interpretability and consistency between emulation methods. To foster interdisciplinary exchange, we also encourage submissions regarding approaches for climate impact projections.

Cold cloud thinning covers proposed climate interventions that looks to seed ice clouds with efficient ice nucleating particles, so they trap less outgoing longwave radiation. With cirrus cloud thinning, seeding aims to shift ice formation away from homogenous to heterogenous freezing nucleation, producing fewer but larger ice crystals that fall out faster, giving thinner, shorter-lived clouds. More recently, mixed-phase cloud thinning has sought to target supercooled clouds over the polar oceans in the winter, where cloud glaciation could reduce longwave radiation from reaching the surface and so help slow sea ice loss. Model estimates of the resulting cooling varies from net negative to net positive when clouds are overseeded, and much of this spread comes from processes that are difficult to constrain, such as the competition between nucleation modes, pre-existing ice, small-scale updrafts, and gravity waves.

This session focusses on work that helps improve our understanding of the ice cloud processes that decide whether cold cloud thinning could work, and what its side effects might be. We welcome laboratory studies of ice nucleation and possible seeding particles, field experiments including targeted glaciogenic seeding, in situ and satellite observations of cirrus and mixed-phase clouds (including early results from EarthCARE), and modelling from process- to global-scale climate models. Natural analogues are of interest, since mineral dust, volcanic eruptions and aviation all perturb ice clouds in ways that let us test seeding hypotheses in the atmosphere. Contributions on detectability, attribution, risks, and wider impacts are also welcome, and we encourage early career researchers to submit.

In recent decades, dry-hot compound extremes, characterized by concurrent droughts and heatwaves, have significantly changed in their intensity, spatial modes, and temporal evolution. These emerging changes may reflect that the climatic boundary conditions causing dry-hot compound extremes could cross critical thresholds, with potential cascading effects that are fundamentally shifting the pattern of dry-hot compound extremes toward a new regime. This poses novel and often unanticipated extreme disasters, severely challenging the adaptability of local ecosystems and human health.
This session aims to advance our understanding of dry-hot compound extremes by integrating observational analyses, climate modeling, and artificial intelligence frameworks. Key focuses include:
1) Novel theories and methodologies for terrestrial heatwave understanding—elucidating mechanisms from the perspective of land-atmosphere-ocean coupling;
2) Drivers and mechanisms—elucidating dynamic (e.g., shifts of atmospheric circulation, and transitions of ocean circulation state) and thermodynamic (e.g., direct warming effect of greenhouse gases) processes changing compound events;
3) Long-term changes—quantifying historical trends, current intensification, future trajectories and abrupt changes under emission scenarios;
4) Climate effects—assessing cascading impacts on vegetation, ecosystem carbon cycling, and its modulation on aerosol formation.

Solar Radiation Management (SRM) refers to climate intervention technologies which propose to temporarily modify Earth’s radiative budget to offset climate risks associated with climate change. These include stratospheric aerosol injection (SAI), marine cloud brightening (MCB), and cirrus cloud thinning (CCT), among others. In all cases, the tightly coupled complex interplay between chemistry, radiation and dynamics especially with respect to aerosol-cloud interactions, make the regional and global impacts of these proposals highly uncertain. These uncertainties cascade into assessment of human and ecosystem relevant impacts, including but not limited to our understanding of the agricultural, ecological, or socio-political ramifications of large-scale adoption.

This session focuses on advances in the natural science of SRM and seeks to identify or reduce sources of uncertainty. This may include climate modeling studies, idealized process investigations, experimental results, or observations of natural analogues. We welcome submissions from across the natural sciences as well as the social sciences, including impacts assessment or governance related to SRM strategies. We are particularly interested in work which focuses on understanding and constraining uncertainty related to regions or communities that are especially vulnerable to climate change, and we encourage early career or new members of the research community to consider applying.

The oceans are changing rapidly in response to the changing climate, as evidenced by record-breaking sea surface temperatures in several different regions around the world, altered ocean currents, and shifts in the marine carbon ecosystem. Additional transformations are expected in a warmer future climate. Identifying the mechanisms of oceanic climate change and variability are crucial to developing realistic ocean projections. Projections simulated using the recent Climate Model Intercomparison Project (CMIP) phase 6, provide meaningful insights on the ocean circulation responses under various climate change scenarios. These models are essential to quantify the impacts of oceanic warming and to develop successful adaptation strategies. This session will bring together researchers focused on shaping our understanding of future ocean circulation. First insights from CMIP7 simulations are very much encouraged!
We encourage submissions from studies covering global, basin wide, regional, and coastal oceanic changes. Topics covering altering ocean circulation and transports, variability and trends, tipping points and extremes, as well as temperature, salinity and biogeochemistry are welcomed. This session is not limited to CMIP analysis and submissions using other modelling datasets and statistical projections are very much encouraged.

The Arctic region has undergone rapid and often abrupt changes over the past decades. Sea ice has become thinner, more mobile, and more prone to sudden breakup. Extreme temperature events have also become routine, with 2023 recording the warmest Arctic summer so far. The Arctic is warming nearly four times faster than the global average, driving ice sheet melt, sea ice retreat in the Kara and Laptev Seas, permafrost thaw, glacier loss, and wildfire activity. Consequently, the exposed ocean is increasingly prone to eddies, extreme events, and low-frequency climate oscillations and more susceptible to abrupt transitions in water mass structure and atmospheric circulation. Together with rising freshwater volumes, increased coastal runoff from Siberia and Greenland, and stronger exchange with the Atlantic and Pacific, these shifts are drastically reshaping the region's already fragile ecosystems.
Projections point to a seasonally ice-free Arctic Ocean by mid-century. This raises pressing questions: What might the future Arctic Ocean look like? How do Arctic changes interact with, and respond to, conditions at lower latitudes? What mechanisms drive the ongoing loss of sea ice, and how might they evolve in an increasingly ice-free system? Where should observational, remote sensing, and modeling efforts focus next?
This session invites contributions spanning the recent past, present, and future of the Arctic and subarctic oceans. We welcome studies of ocean-atmosphere-sea ice interactions; ocean eddies, extremes, and climate oscillations; the processes and feedbacks driving trends, transitions, and abrupt shifts in the Arctic system; small-scale dynamics, internal waves, and mixing; the sources and downstream impacts of freshwater change, including subarctic deep convection; and the broader coupling between the Arctic and global ocean circulation. Cross-disciplinary submissions are especially encouraged, particularly those connecting physical, cryospheric, biogeochemical, and ecological processes, as well as their links to terrestrial systems.
We welcome discussions on the future of Arctic Ocean observation, remote sensing, and modeling strategies (including the upcoming CMIP7 cycle) and on ways to validate and improve models against observations. Submissions drawing on recent field programs such as MOSAiC, the Nansen Legacy Project, and the Synoptic Arctic Survey are welcome, as are contributions from those planning the upcoming International Polar Year 2032-33.

Our understanding of the Indian Ocean’s physical, biogeochemical, and ecological characteristics and their variability across a range of spatiotemporal scales has advanced in recent years. However, there remain significant gaps in our knowledge in observing, modeling, and predicting the Indian Ocean’s changing environmental conditions and its role in regional and global climate.
This session invites Indian Ocean contributions based on observations, modelling, theory, and palaeo proxy evidence across a range of timescales from synoptic, interannual, decadal to centennial and beyond. Topics of interest include past, current, and projected changes in Indian Ocean physical and biogeochemical properties and their impacts on ecological processes, diversity in Indian Ocean modes of variability, interactions and exchanges between the Indian Ocean and other ocean basins via both oceanic and atmospheric pathways, as well as impacts on regional hydroclimate and the adjacent Asia-Australia-Africa monsoon systems.
Submissions are sought on assessing and predicting weather and climate extremes of societal relevance in the Indian Ocean and surrounding regions. We especially welcome submissions addressing compound extreme events that span across the ocean, atmosphere, land, and/or biogeochemical and ecological realms. Furthermore, studies evaluating climate risks, vulnerability, resilience, adaptation and mitigation strategies in coastal and watershed regions affected, for example, by a warming climate, tropical cyclones, and extremes in sea level are encouraged.
We also welcome contributions that address research on the Indian Ocean, using advanced techniques such as artificial intelligence/machine learning, and new technological advances in observing systems.

Regional monsoons have profound impacts on water, energy, and food security. Monsoons cause severe floods and droughts as well as undergoing variability on subseasonal, interannual and decadal-to-multi-decadal time scales. In addition to their profound local effects, monsoon variability also causes global-scale impacts via teleconnections, and the monsoons are linked together as part of the global monsoon via the divergent circulation, with aspects of coherent variability and interactions with planetary scale transports of heat and moisture.

Monsoons are complex phenomena involving coupled atmosphere-ocean-land interactions and remain notoriously difficult to forecast at NWP, subseasonal and seasonal scales, casting doubt also on our future climate projections. A better understanding of monsoon physics and dynamics, with more accurate simulation, prediction and projection of monsoon systems is therefore of great importance.

This session invites presentations on any aspects of monsoon research in present-day, future and palaeoclimate periods, involving observations, modelling, attribution, prediction and climate projection. Topics ranging from theoretical works based on idealized planets and ITCZ frameworks to the latest field campaign results are equally welcomed, as is work on impacts, extremes, NWP modelling, S2S and decadal forecasting, and the latest CMIP or PMIP findings to help inform the IPCC AR7.

The subtropics are global hotspots of climate change, yet climate model simulations and projections for these regions remain highly uncertain. These regions are home to a large share of the world's population, including many communities with the least historical GHG emissions that are disproportionately exposed to extreme events and climate change. As a zone of interaction between tropical and extratropical circulation regimes, the subtropics are characterised by a unique hydroclimate, with strong spatial gradients, distinct seasonal cycles, and high sensitivity to climate variability and change. Despite their importance for both society and the climate system, subtropical weather and climate processes remain comparatively understudied. This session invites contributions that advance process understanding and prediction of weather and climate with a particular focus on the subtropics. We welcome studies based on observations, theory, numerical models, and machine learning. Topics of interest include, but are not limited to:
- Atmospheric processes, such as tropical–extratropical interactions, subtropical jet fluctuations, Rossby wave dynamics, transient eddies, monsoon circulations, and convergence zones, shaping surface weather, clouds, and transport of dust and air pollution.
- Weather, climate, and compound extremes – droughts, heatwaves, wildfires, heavy precipitation, floods, dust storms, and windstorms – spanning their drivers, future changes, and impacts on society and ecosystems.
- The water cycle – rainfall, evapotranspiration, and moisture transport – modulated by weather systems such as cyclones, cut-off lows, cold air outbreaks, mesoscale convective systems, easterly waves, atmospheric rivers, and cloud bands.
- Coupled interactions between Earth system components, including land-atmosphere and ocean-atmosphere feedbacks, and the role of sea surface temperature patterns in shaping subtropical climate.
- Climate variability and remote linkages with ENSO, the Madden-Julian Oscillation (MJO), and the Hadley circulation.
- Observations and climate model simulations addressing past and future changes in regional circulation patterns and surface weather, and novel approaches for identifying model biases and for reducing uncertainties in projections.

Weather and climate extremes, such as recent events unprecedented in the observational record, have extensive impact globally. Some of these events would have been nearly impossible without human-made climate change, exhibiting conditions well beyond previous records due to complex, and at times unprecedented configurations of their underlying physical drivers. Furthermore, compounding hazards and cascading risks resulting from these high-impact extremes are becoming evident. Continued warming does not only increase the frequency and intensity of such extremes, it also potentially increases the risk of unseen non-linear behaviours or unprecedented impacts. To increase preparedness for high-impact climate events, developing novel methods, models and process-understanding that capture these hazards and their associated impacts is paramount.
This session aims to bring together the latest research quantifying and understanding high-impact climate events in past, present and future climates. We welcome studies across all spatial and temporal scales, and covering compound, cascading, and connected extremes as well as worst-case scenarios, with the ultimate goal to provide actionable climate information to increase societal preparedness to such extreme high-impact events.
We invite work addressing high-impact extreme events via, but not limited to, model experiments and intercomparisons, diverse storyline approaches such as event-based or dynamical storylines, climate projections including large ensembles and unseen events, insights from paleo archives, and attribution studies. We also especially welcome contributions focusing on physical understanding of high-impact events, on their ecological and socioeconomic impacts, as well as on approaches to potentially limit societal impacts.
The session is closely linked to the World Climate Research Programme lighthouse activities on Understanding High-Risk Events and Explaining and Predicting Earth System Change.

Climate services challenge the traditional interface between users and providers of climate information as it requires the establishment of a dialogue between subjects, who often have limited knowledge of each-other’s activities and practices. Increasing the understanding and usability of climate information for societal use has become a major challenge where economic growth, and social development crucially depends on adaptation to climate variability and change.

To this regard, climate services do not only create user-relevant climate information, but also stimulate the need to quantify vulnerabilities and come up with appropriate adaptation solutions that can be applied in practice. This session invites contributions from all fields in which climate information is used in decision-making processes, including agriculture, renewable energy, banking, water management, tourism and any other societal sector dependent on climate information.

The operational generation, management and delivery of climate services poses a number of new challenges to the traditional way of accessing and distributing climate data. With a private sector growing and playing an increasingly important role as a service provider, it is important to understand the roles and responsibilities of publicly funded climate data, information and services, as well as the standardisation process for climate services.

This session aims to gather best practices and lessons learnt, for how climate services can successfully facilitate adaptation to climate variability and change by providing climate information that is tailored to the real user need.
Contributions are encouraged from public and private climate services providers, as well as from international efforts (GFCS, CSP, …); European Initiatives (HEU, ERA4CS, C3S, ClimatEurope, ECRA, JPI-Climate…) as well as national, regional and local experiences.

Achieving the climate goals of the Paris Agreement requires deep greenhouse gas emissions reductions towards a net-zero world and beyond. Advancements in mitigation-relevant science continuously inform the strategies and measures that society could pursue to achieve this goal. This session aims to further our understanding of the science surrounding the pursuit of the Paris Agreement’s temperature goal, including carbon budgets, zero emissions commitment, carbon dioxide removal strategies, and their policy implications. We will explore global to regional climate dynamics under net-zero, and peak and decline CO2 pathways, and mechanisms of committed or irreversible changes, including the risk of non-linear Earth system change.

We welcome both theoretical, empirical and modelling studies exploring all aspects of climate change in response to ambitious mitigation scenarios, including overshoot pathways through scenarios that pursue net negative emissions and a reversal of global warming. In addition to studies exploring the remaining carbon budget and the transient climate response to cumulative emissions of CO2 (TCRE), we welcome contributions on the zero emissions commitment (ZEC), effects of different forcings and feedbacks (e.g. permafrost carbon feedback), non-CO2 contributions to stringent climate change mitigation (e.g. non-CO2 greenhouse gases, and aerosols), and climate and carbon-cycle effects of carbon removal strategies, including their implications for policy. We also invite analysis focusing on consequences in a wide range of Earth System components and sectors, from ocean dynamics to the cryosphere, biodiversity and biosphere changes to human systems and economic consequences of overshoot, as well as the implications of overshoots for climate change adaptation planning.

We invite contributions that use a variety of tools, including fully coupled Earth System Models (ESMs), sectoral impact models, Integrated Assessment Models (IAMs), or Simple Climate Models (SCMs) and climate emulators. Interdisciplinary contributions from the fields of climate policy and economics focused on applications of carbon budgets, net-zero pathways, and their wider implications are also encouraged.

Tipping points refer to critical thresholds in the Earth system that, once crossed, can lead to rapid and potentially irreversible changes in environmental conditions in systems such as the Atlantic Meridional Overturning Circulation, the Greenland and Antarctic ice sheets, tropical and boreal forests, permafrost, and monsoon systems. They remain a major source of uncertainty in climate projections, particularly at the regional level, with potentially profound impacts on the climate, ecological, and societal systems, and are therefore highly relevant to the national and international climate assessment reports and climate adaptation plans, including the IPCC's Seventh Assessment Report (AR7).

This session invites contributions that advance our understanding of tipping dynamics through climate and Earth system modelling approaches. We particularly welcome multi-model analyses building on a number of recent multimodel experiment protocols, including TIPMIP-ESM (Jones et al. 2026), TIPMIP-Ocean (Swingedouw et al. 2026), TIPMIP-Ice as well as the CMIP7 AFT and other MIPs, investigating climate responses and tipping behaviours across the atmosphere, ocean, cryosphere, and biosphere. We also encourage cross-component syntheses that compare the mechanisms, thresholds, timescales, and reversibility of different tipping elements. The session also invites studies using other modelling frameworks and approaches — including single-model analyses — with a focus on tipping dynamics in any Earth system component. We aim to bring together the climate modelling community working across this broad theme, to foster comparisons across models and methodologies (thus distinguishing robust from model-dependent findings), and ultimately to inform the assessment of tipping risks for AR7.

Earth resilience is the capacity of the intertwined human-Earth system to resist, recover, and regenerate back to a Holocene-like and habitable functioning in response to human pressures. A deeper understanding of Earth system resilience is key to charting safe operating spaces for prosperous and equitable future human development. Recent assessments of Earth system integrity highlight the deteriorating resilience of our planet, with planetary-scale human pressures (such as greenhouse gas emissions and land-use change) pushing the Earth system into the uncharted territory of the Anthropocene. Of particular concern are risks of triggering nonlinear changes in large-scale components of the Earth that can undergo abrupt, often irreversible state shifts once critical thresholds are crossed. Examples include the Greenland ice sheets, the Atlantic Meridional Overturning Circulation, and major ecosystems such as the Amazon rainforest. Their interactions may trigger tipping cascades, where the destabilization of one element increases the risk of others tipping, thereby amplifying Earth system change and undermining long-term Earth resilience.

The Earth system’s future trajectory is now co-shaped by human–Earth system feedbacks, where human activities both drive and respond to biophysical change. Fossil fuel use, deforestation, and land-use intensification contribute to destabilizing Earth system dynamics, while societal responses - such as mitigation policies, technological innovation, or behavioral shifts - can either reinforce unsustainable trajectories or create stabilizing feedbacks. In this context, research is uncovering the potential for social tipping dynamics, which could accelerate decarbonization and foster transformative pathways towards global sustainability to revitalize and regenerate Earth resilience.

We invite contributions on all topics relating to Earth resilience, planetary boundaries, safe operating spaces, tipping points in the Earth system, positive (social) tipping, as well as their interactions and potential domino effects. We welcome studies that use Earth system modelling, integrated human-Earth system models, from conceptual approaches to data-driven analysis to investigate nonlinear dynamics, abrupt shifts, and tipping points, as well as contributions exploring social transformation processes and their role in shaping a more sustainable future for people and the planet.

Explosive volcanic eruptions inject large volumes of ash and gas into the atmosphere, with significant environmental and climatic consequences. As human populations increasingly occupy volcanic regions, and as global trade, transport, and food systems become more interconnected, the impacts of eruptions are no longer confined to the host country. Even geologically ‘modest’ events (e.g., Eyjafjallajökull 2010 CE) can trigger cascading, global-scale disruptions with serious economic, societal, and environmental repercussions. Studying large explosive eruptions, and their impacts on both climate and society can help to prepare for volcanic-induced disruptions in the future. Namely, because it provides critical opportunity to: (1) assess their short- (<1 year) and long-term (>1000 years) impacts on the Earth system, (2) improve calibration of climate model simulations, (3) understand their impacts on civilisational development, and (5) evaluate how modern human activities may be pushing Earth system responses to eruption events into new states. However, despite substantial recent advances, challenges remain in quantifying eruption impacts across different magnitudes, styles, and regions.
This session invites contributions that seek to address these challenges by improving reconstructions of past eruptions, elucidating climate system responses, and assessing implications for human infrastructure and society. This encompasses a variety of research themes including (but not limited to) volcanology, paleoclimatology, history, archaeology and tephrochronology, as well as ash/aerosol and climate modelling. We encourage submissions from disciplines related to policy development and volcanic risk management, particularly in regions vulnerable to disruptions of food, energy, and water resources. Hence, this session is well suited to scientific research looking to advance interdisciplinary understanding of links between volcanism, climate, and society, and enhance global preparedness for future volcanic crises.

Earth observation provides repeated and consistent measurements across most of the planet, including regions where field observations and monitoring infrastructure are limited. AI makes it possible to process these data systematically and to develop global workflows that study different regions through a consistent analytical framework and at comparable levels of detail. This combination can widen access to evidence on climate change and reduce some of the geographical, economic and technical barriers that still shape climate research.

Global coverage, however, does not automatically guarantee global knowledge. Models developed in data-rich regions may perform differently under other environmental or socioeconomic conditions. Their evaluation is often constrained by sparse reference data, uneven monitoring capacity and limited local validation. Geographical bias, uncertainty and transferability therefore need to be assessed explicitly rather than assumed.

This session focuses on the use of AI and Earth observation to make climate change research more accessible, systematic and geographically inclusive. It welcomes studies of climate impacts, risks, vulnerability and adaptation, including their links with natural hazards, public health, ecosystems, population, infrastructure, early warning and disaster response.

Relevant contributions may address scalable and reproducible workflows, validation in data-scarce settings, uncertainty assessment and generalisation across regions. Studies combining satellite observations with field measurements or local knowledge are particularly relevant, as are open data, accessible tools and methods that can be adapted to different contexts. The aim is to understand how global Earth observations can make robust and actionable climate knowledge available across different communities and contexts, including those where conventional monitoring and research capacity remain limited.

Storylines, defined as “physically self-consistent unfoldings of past events, or of plausible future events or pathways,” can be used to describe risks and impacts of climate-driven trends or extreme events while making uncertainty, assumptions and decision relevance explicit. They provide a powerful framework to investigate short- to long-term climate risk pathways driven by the interplay of hazard, exposure, vulnerability and response capacity, including compound and cascading risks, stress testing of systems, and intervention options in uncertain futures. As boundary objects across climate science, disaster risk reduction, adaptation, social sciences and operational decision-making, they can support dialogue across disciplines, but also reveal that communities do not always share the same definitions, evidence standards or expectations of use. 
This session brings together researchers and practitioners working across climate science, impacts and risk assessment, disaster risk reduction, social sciences and decision practice to advance the physical understanding, methodological development and application of climate risk storylines. We welcome contributions that span the full chain from physical climate modelling and event attribution to impact analysis, participatory co-production, and the translation of scenarios into real-world decision contexts.
We invite abstracts that address, among others:
a) Physical and impact-based climate storylines, including past events, attribution studies, downward counterfactuals and plausible future extremes
b) Methods for integrating quantitative and qualitative knowledge, and linking climate and non-climate risk drivers across scales
c) Conceptual models and frameworks for combining hazards, exposure, vulnerability, response capacity and cascading impacts
d) Applications of storylines and scenarios for stress testing, impact and risk assessment, early warning systems, adaptation planning and policy support
e) Participatory and co-production approaches that enhance relevance, transparency, robustness and uptake for decision-making
f) Reflections on terminology, quality criteria and responsible translation of storylines across scientific, policy and practice communities
By bridging physical modelling, socioeconomic pathways and stakeholder-driven approaches, this session aims to strengthen the role of storylines as shared, transparent and actionable tools for managing climate risks in a rapidly changing world.

This session invites contributions advancing the understanding, modelling, and prediction of extreme events in weather, climate, and other geophysical systems. It brings together researchers from the geophysical sciences and those applying mathematical, statistical, and dynamical-systems approaches.

Topics of interest include, but are not limited to:
* Variability and projected changes in extremes under climate change
* Representation of extreme events in weather and climate models
* Attribution of extreme events
* Emergent constraints on extreme-event behaviour
* Predictability of extremes across meteorological and climate timescales
* Connections between extremes in dynamical systems and observed geophysical extremes
* Theoretical and applied studies of extremes in nonlinear and chaotic systems
* Downscaling methods for extreme events
* Links between the physical dynamics of extremes and their impacts on society and ecosystems

We particularly welcome interdisciplinary contributions, novel methodologies, and studies connecting theory with observed geophysical extremes. Submissions from early-career researchers are especially encouraged.

Climate change is reshaping infectious-disease risks. Hydroclimatic extremes such as floods, droughts, and heatwaves can alter vector habitats, pathogen survival, water quality, sanitation, human mobility and patterns of human contact. Adaptation measures (including vector control, water management, healthcare preparedness, vaccination and behavioural responses) can reduce these risks or unintentionally create new pathways of transmission.

The session welcomes contributions on vector-borne, waterborne, foodborne, respiratory and zoonotic diseases, including research on compound hazards, unequal impacts and adaptation responses. We particularly invite diverse methodological approaches, including:

Dynamical systems approaches to modelling and understanding infectious diseases
Large-scale statistical, epidemiological and climate–health analyses;
Process-based and data-driven models;
Local, urban and neighbourhood-scale modelling;
Qualitative, participatory and mixed-methods approaches;
Surveys, behavioural studies and assessments of public perceptions;
Surveillance, early-warning and climate-informed forecasting systems;
Evaluations of adaptation, preparedness, resilience and risk-management strategies.
Veterinary medicine

The session aims to bring together researchers working across geosciences, climate science, epidemiology, microbiology, ecology, public health and disaster-risk reduction. By connecting these perspectives, we hope to improve understanding of when and where natural hazards become infectious-disease threats, and how these risks can be anticipated and managed.

Assessing the impact of climate variability and changes on hydrological systems and water resources is crucial for society to better adapt to future changes in water resources, as well as extreme conditions (floods and droughts). However, important sources of uncertainty have often been neglected in projecting climate impacts on hydrological systems, especially uncertainties associated with internal/natural climate variability. From one model to another, or one model realisation to another, the impact of diverging trends and sequences of interannual and decadal variability of various internal/natural climate modes (e.g., ENSO, NAO, AMO) could substantially alter the impact of human-induced climate change on hydrological variability and extremes. Therefore, we need to improve both our understanding of how internal/natural climate patterns affect hydrological variability and extremes, and how we communicate these impacts. We also need to understand better how internal/natural variations interact with various catchment properties (e.g., vegetation cover, groundwater support) and land-use changes. Developing storylines of plausible worst cases, or multiple physically plausible cases, arising from internal climate variability can complement information from probabilistic impact scenarios.

We welcome abstracts capturing recent insights for understanding past, present, and future impacts of internal/natural climate variability on hydrological systems and extremes, as well as newly developed probabilistic and storyline impact scenarios. Results from model intercomparisons using large ensembles are encouraged.

Human-induced climate change has increased the frequency and intensity of many weather and climate hazards, including heatwaves and humid heat, droughts, floods and heavy precipitation, windstorms, tropical cyclones, and wildfires, often with severe societal impacts. Yet the confidence with which observed changes can be attributed to anthropogenic influence still varies between hazard types, as does climate models’ ability to reproduce observed extreme events. Both limit our ability to project future risks at different warming levels.

Understanding and projecting changes in these emerging hazards, including unprecedented, compound, consecutive, flash-change, and seasonally-shifting extremes, as well as their interaction with exposure, vulnerability, and adaptation, is a challenge that spans the physical sciences, statistics and machine learning, climate risk modelling, geography, and the socioeconomic sciences. The sheer number of recent extreme events underlines the urgency of improved understanding and modelling capacities for better adaptation, policymaking, and early warning systems.

This session highlights recent progress on understanding, modelling, and projecting weather and climate hazards across these disciplines and aims to identify open research questions and form new collaborations. Which hazards receive too little attention compared to, e.g., heat and drought, and which regions remain under-studied? Which sectors should work more closely with weather and climate scientists to make progress?

We invite contributions on changing weather and climate hazards and their impacts from all regions of the world. Studies on floods, storms, humid heat, and other hazards less represented in the literature are particularly welcome, as are contributions including, but not limited to:
- Understanding physical processes associated with weather extremes, including unprecedented, compound, consecutive, flash-change, and seasonality-related extremes
- Teleconnections and natural modes of variability as well as their links to hazards and impacts
- Advances in hazard and impact modelling, including bias-adjustments and data-driven approaches
- Detection and attribution of weather and climate hazards and their impacts
- Storyline and other approaches to low-likelihood, high-impact events
- Trends and projections of hazards on decadal to centennial timescales
- Changing exposure and vulnerability; interactions between hazards, local socioeconomics, & adaptation

Climate change and urbanisation increase climate risks and the negative consequences of extreme events. For instance, floods cost billions of euros of losses and result in thousands of fatalities every year. Accelerated adaptation by societies, including governments, insurance companies, households and others is urgently required. However, there are limits to the adaptability of societies. For instance, social vulnerability factors (e.g. income, education, etc.) may reduce households’ adaptation efforts. When societies stop implementing additional adaptation, risk may become ‘intolerable’, and adaptation limits may be reached. At such point, people may have to migrate to safer locations. However, very little is known about the extent to which societies can adapt, which factors drive these limits, and where and when limits to adaptation will be reached.
This session welcomes abstracts considering how to conceptualise, assess, project and avoid adaptation limits. The session aims to facilitate discussions and cooperation about interdisciplinary research on adaptation and its limits by bringing together experts in climate, natural hazards and the social sciences.
Relevant topics include, but are not limited to:
• Where were soft or hard limits of adaptation reached already?
• Which social and physical vulnerability constraints can lead to adaptation limits?
• How to conceptualise and measure intolerable risk
• Motivation for and hindrances of adaptation efforts
• Simulation of adaptation and migration decisions
• Quantification of adaptation effects

Agricultural systems are increasingly exposed to droughts, heatwaves, floods, and compound extremes, with impacts that can cascade across water resources, crops production, and rural livelihoods. Addressing such challenges requires better hazard monitoring or sensing technologies. A stronger link between observation, prediction, and the practical adaptation decisions is also needed that allow agricultural systems to anticipate, cope with, and recover from natural hazards.
This session brings together research that connects these different steps, from monitoring and prediction to adaptation and decision-making in agriculture under hydro-climatic extremes. Although hazard monitoring and precision agriculture technologies have advanced rapidly, turning these developments into tangible improvements in resilience remains challenging. This requires closer integration of hydrology, agriculture, remote sensing, climate science, and decision-support approaches.
We welcome contributions covering the full chain from observation to action, including Earth Observation and in situ monitoring of agricultural exposure and impacts; AI, machine learning, and hybrid modelling for impact prediction and early warning; agro-hydrological and land surface modelling under changing and compound climate conditions; and the use of monitoring and prediction to support adaptation, such as smart irrigation, precision water management, nature-based solutions, and climate-resilient cropping systems.
We particularly encourage studies that show how advances in observation and modelling can be translated into practical decision-support and adaptation. Contributions addressing compound and cascading hazards, especially those linking monitoring and modelling with agricultural impacts and management responses, are also welcome.

Climate change is increasingly interacting with rapid urbanization, socioeconomic transformation, environmental degradation, and uneven development across Asia. Floods, droughts, tropical cyclones, sea-level rise, salinity intrusion, landslides, etc., and compound extremes are affecting communities, ecosystems, infrastructure, livelihoods, and economic development. These challenges are particularly significant in emerging and developing regions, where high exposure often coincides with limited resources, institutional constraints, and social inequalities.
At the same time, communities, governments, researchers, and other actors across Asia are developing diverse ways to anticipate, absorb, adapt to, and transform in response to climate risks. Understanding which approaches are effective, under what conditions, and how they can support long-term climate-resilient development remains a major scientific and policy challenge.
This session brings together interdisciplinary research on the assessment, mechanisms, practices, and pathways of climate resilience in emerging and developing Asia. We welcome contributions that connect climate hazards and environmental change with social, institutional, technological, and policy responses, including:
 Measurement and assessment of climate resilience and climate-resilient development
 Innovative technologies, modelling approaches, and nature-based solutions for climate adaptation
 Empirical case studies, best practices, and lessons from successful and unsuccessful resilience initiatives
 Governance, institutional capacity, and policy mechanisms for climate resilience
 Community resilience, socio-cultural dimensions, equity, justice, and local knowledge
 Methodological advances in climate resilience research, including GIS, remote sensing, participatory methods, and data-driven approaches
 Adaptation pathways, transformative resilience, and opportunities for scaling up effective solutions
 Theoretical, conceptual, comparative, and review studies on climate resilience in emerging and developing Asia.

Climate change has long shaped the distribution, adaptation, and extinction of terrestrial life. Past climate variability has driven large-scale migrations, evolutionary innovations, and ecosystem restructuring, while modern human activities have added unprecedented pressures to biodiversity and habitats. Understanding the complex interactions between climate and life is essential for assessing the ongoing biodiversity crisis and developing effective strategies for future conservation.

This session explores how climate influences terrestrial life and ecosystems across timescales – from deep-time events to present, and future challenges. We welcome multidisciplinary studies integrating climate science, ecology, paleoecology, evolutionary biology, and conservation.

Topics of interest include, 


- Extinctions: drivers, mechanisms, and ecological consequences

- Biodiversity: changes in species distribution and emerging trends
- Vegetation and biome dynamics

- Climate- and human-induced habitat fragmentation and ecological connectivity.

- Adaptation and resilience: species and ecosystem response to environmental changes
- Climate-human-faunal interactions and influence on ecosystems

- Insights from advanced observations, ecological datasets and climate-ecosystem models 


By connecting past, present, and future perspectives, this session aims to forge collaborations and cross-disciplinary dialogue on climate–life interactions and implications for terrestrial ecosystems.

Climate change is altering the characteristics of extreme events globally, affecting their frequency, intensity, duration, timing, spatial extent, and persistence. Extreme precipitation, heatwaves, droughts and flash droughts, floods, tropical cyclones, and compound events can generate cascading impacts on water resources, agriculture, ecosystems, human health, and infrastructure. Understanding where and how extremes are changing, the physical mechanisms driving these changes, and their links to anthropogenic climate change is essential for assessing evolving climate risks.
This session invites research on the evolution of climate extremes across past, present, and future climates using observations, palaeo-climate records, reanalyses, climate models, and statistical approaches. We particularly welcome studies examining the physical drivers of extremes, including atmospheric circulation, moisture transport, land-atmosphere interactions, ocean-atmosphere coupling, and large-scale climate variability. Studies of compound, concurrent, sequential, and rapidly transitioning extremes, including hydroclimatic whiplash, are especially encouraged.
Contributions addressing future changes in extreme-event intensity, frequency, seasonality, spatial distribution, and dependence between hazards are welcome, alongside studies of model uncertainty, internal variability, scenario uncertainty, and detection and attribution. We particularly encourage emerging AI/ML and data-driven approaches for extreme event detection, prediction, attribution, downscaling, and process understanding, including hybrid physics-ML frameworks and explainable methods. Critical assessments of their uncertainty, physical interpretability, and transferability are also encouraged.
By connecting observed changes, physical processes, and future projections, this session aims to advance understanding of evolving climate extremes and the uncertainties and emerging risks associated with them.

The Coupled Model Intercomparison Project (CMIP) identified four fundamental topics on which coupled modelling offers opportunities for rapid progress across the seventh phase of the project, CMIP7: 1) Patterns of sea surface warming, 2) Changing extremes, 3) The Water-Carbon-Climate nexus, and 4) Points of no return/ratcheting. CMIP7 includes Diagnostic, Evaluation, and Characterization of Klima (DECK) and Assessment Fast Track experiments to address these guiding science priorities as well as the community’s requirements for prediction and projection, attribution, characterisation, and process understanding towards assessment of state-of-the-art Earth system models.

We invite contributions across research using coupled Earth system modelling including representation of historical and future change, comparison with previous CMIP phases, idealised analyses, single- or multi-model frameworks, and others across different timescales. We are especially interested in studies examining responses using the CMIP7 Assessment Fast Track. Submissions that explore interactions across multiple components of the Earth system—ocean, atmosphere, cryosphere, land surface and subsurface, and biosphere—and highlight novel insight into the coupled Earth system are highly encouraged.

The Mediterranean regions of the world are climate risk hotspots with concurrent climate extremes and complex compound events representing threats for their societies, economic and financial sectors, and ecosystems. Characterising past changes, current trends, emerging patterns, and future possible evolution is essential as well as understanding the processes associated with and their dynamics.
This session aims at promoting a multi-disciplinary approach to climate risks to deal with these increasingly complex challenges, design and develop effective solutions and practices, and build the path towards resilience. Studies on observed and reconstructed past changes as well as on future climate projections focused on physical, biogeochemical, and socio-economic aspects are all welcome. Analyses looking at emerging patterns and at extremes such as drought, floods, wildfire, heatwaves also inspired by recent events are highly encouraged. Similarly, socio-economic contributions on the Mediterranean regions in relation to the other areas of the world are invited to this interdisciplinary session.

We invite contributions which discuss possible connections between the astronomical forcing and transitions in the dynamics of the Earth system, including global: extinctions, anoxia, global glaciations, regime changes, and more regional events. We aim at bringing together contributions which are either based on observations, on theoretical arguments, or both. We welcome submissions which explore the climate system response to orbital forcing, and that analyse the stability of these relationships under different climate regimes or across evolving climate states. This includes the Cenozoic (e.g. mid Pleistocene transition, Pliocene-Pleistocene transition, Miocene vs Pliocene), and the other periods of the Phaneorozoic and before. We also particularly welcome submissions which explore the effects of astronomical forcing on expression and amplification of millennial variability.

The over half-century since the first deep ice core drilling at Camp Century, Greenland, has seen increased spatial coverage of polar ice cores, as well as extensive development in methods of ice sample extraction, analysis and interpretation. Growth and innovation continue as we address pressing scientific questions surrounding past climate dynamics, environmental variability and glaciological phenomena. New challenges include the retrieval of old, highly thinned ice, interpretation of altered chemical signals, and the integration of chemical proxies into earth system models. We invite contributions reporting the state-of-the-art in ice coring science, including drilling and processing, dating, analytical techniques, results and interpretations of ice core records from polar ice sheets and mid- and low-latitude glaciers, remote and autonomous methods of surveying ice stratigraphy, proxy system modelling and related earth system modelling. We encourage submissions from early career researchers from across the broad international ice core science community. Contributions from on-going projects focusing on old and/or deep ice including, Green2Ice, COLDEX and Beyond EPICA Oldest Ice are very welcome.

Modelling past climate states, and the transient evolution of Earth’s climate, remains challenging. Time periods such as the Eocene, Miocene, Pliocene, the Last Interglacial, the Last Glacial Maximum or the Holocene span across a vast range of climate conditions. At times, these lie far outside the bounds of the historical period that most models are designed and tuned to reproduce, providing valuable additional constraints on model sensitivities. Yet our ability to predict future climate conditions and potential pathways to them is dependent on our models' abilities to simulate a realistic range of climate variability as it occurred in Earth’s history. Thus, our geologic past is ideally suited to test and evaluate models against data, so they may be better able to simulate the present and make more reliable future climate projections.
    We invite contributions on palaeoclimate-specific model development, tuning, simulations, and model-data comparison studies. Simulations may be targeted to address specific questions or follow specified protocols (as in the Paleoclimate Modelling Intercomparison Project – PMIP or the Deep Time Model Intercomparison Project – DeepMIP). They may include or juxtapose time-slice equilibrium experiments and long transient climate simulations (such as over the last millennium). Comparisons may include different time periods (e.g., deep time, Quaternary, historical as well as future simulations), and focus on comparison of mean states, spatial gradients, circulation or modes of variability using different models, or contrast model results with reconstructions of temperature, precipitation, vegetation or circulation tracers (e.g. δ18O, δD or Pa/Th).
    Presentation and discussion of results using CMIP7 models and experiments that form part of PMIP7 are encouraged. We are hoping to see descriptions and analyses of abrupt-127k experiments from the CMIP Assessment Fast Track. However, we also solicit comparisons across time periods, between models and data, and analyses of underlying mechanisms of change as well as contributions introducing novel model or experimental designs that allow to improve future projections.

The climate system varies in complex ways across a wide range of timescales. Teleconnections—recurring patterns in the atmosphere and ocean that link remote regions—play a central role in shaping regional climate variability, predictability, and long-term change. Understanding and representing these links is therefore essential not only for advancing process understanding, but also for delivering robust and actionable regional climate information. However, given the large internal variability and strong external forcings involved, understanding the role of teleconnections in climate variability and change remains challenging. Both dynamical and modelling approaches, as well as statistical and other data-driven methods, have provided the foundation for many insights to date.

This session aims to bring together researchers using any combination of these approaches to study teleconnections across timescales, from synoptic to multi-decadal changes. In particular, we invite contributions that address one or more of the following topics: studies of the dynamics, variability, and predictability of teleconnections and their response to anthropogenic forcing; studies investigating and addressing model-observation discrepancies across the model hierarchy, from conventional to high-resolution and km-scale models and AI-based weather and climate models, as well as studies on regional impacts of teleconnections to assess physically consistent climate storylines and constrain projections.

We particularly encourage studies that bridge physical understanding and data-driven analysis, with an emphasis on physical interpretability and explainability. This includes theoretical advances and novel diagnostics for teleconnections, analysis of model experiments, as well as statistical and machine learning methods, including causal inference, Bayesian methods, and explainable or physics-informed deep learning.

The African continent hosts a wide variety of climates, ranging from tropical rainforests to arid deserts, shaped by the interplay between monsoon systems, large-scale atmospheric circulation, and regional geographic features. This climatic diversity supports a wide variety of ecosystems and biodiversity, while also contributing to the continent’s exceptional diversity of environments and human societies. Moreover, Africa preserves some of the oldest and richest early hominin fossil records, alongside a detailed archaeological record, providing a vital resource for understanding human origins and how human populations have adapted to changing environmental conditions. Today, climate variability and extremes profoundly affect water availability, agriculture, ecosystems, and livelihoods across the continent. As the climate changes, improving our understanding of past and present climate variability, and of the processes driving it, is essential for understanding its impacts and building resilience to future changes.

The extent to which climate models may under- or overestimate Africa’s hydroclimate and temperature changes is currently poorly known. Instrumental records and paleoclimate reconstructions are limited to only some African regions. This hampers our understanding of climate variability across time and space. Consequently, climate models continue to exhibit significant biases in their representation of monsoon systems. The past evolution of the African climate and projections of its future evolution remain uncertain. Therefore, improving our understanding of the mechanisms driving monsoon circulations, land–atmosphere interactions, and convection processes is therefore essential to better simulate monsoon systems and climate across Africa.

We welcome contributions on all aspects of African climate: from paleoclimate reconstructions to future projections, including S2S to decadal prediction, centennial to orbital scale changes, and work emphasising physical processes and numerical modelling. We also invite studies on climate-related applications using Natural Language Processing and other ML/AI techniques, as well as presentations on operational applications and observational networks. We also welcome studies connecting African climate change and variability to human health and adaptation, food and water security, and socio-economic development.

Solar forcing influences the Earth’s atmosphere through variations in solar irradiance and energetic particle precipitation, with the latter heavily modulated by the strength and configuration of the Earth’s magnetic field. Together, these processes affect atmospheric composition, Earth’s radiative balance, and atmospheric dynamics across different timescales. Numerical modelling is an essential tool for investigating these interactions and understanding how solar forcing and the geomagnetic field affect the atmosphere and climate.
This multidisciplinary session welcomes contributions using chemistry-climate models, Earth system models, and related modelling frameworks to investigate interactions among solar forcing, atmospheric composition, atmospheric dynamics, and climate under present-day, past, and future boundary conditions. Key topics include, but are not limited to, the production of odd nitrogen (NOx) and odd hydrogen (HOx), ozone changes, radiative and dynamical responses, atmosphere-ocean coupling, and Earth system feedback.
We encourage studies exploring the role of changes in the geomagnetic field, including variations in field strength as well as geomagnetic excursions and reversals, in modulating energetic particle precipitation and its atmospheric effects. Contributions spanning individual solar proton events and geomagnetic storms, solar cycle variability, grand solar minima, and geomagnetic excursions are particularly welcome. Studies addressing model development, parameterisations of solar and particle forcing, validation against observations and cosmogenic radionuclide records, model intercomparisons, and uncertainty assessment are also encouraged.
By bringing together experts in atmospheric chemistry, climate dynamics, solar-terrestrial physics, geomagnetism, and Earth system modelling, this session aims to support interdisciplinary discussion and improve our understanding of how solar and geomagnetic forcings influence Earth’s atmosphere and climate, from individual events to long-term Earth history.
This session is dedicated to the memory of Dr Eugene Rozanov (1955-2026), whose pioneering contributions to chemistry-climate modelling and solar-terrestrial interactions continue to inspire research across these disciplines.

Hybrid statistical–dynamical approaches have emerged as a promising avenue to improve our understanding of the climate system and to better simulate and predict its variability on multiple timescales. They combine the strengths of dynamical and statistical models, preserving the physical consistency of numerical models, while benefiting from statistical and data-driven methodologies to address key model deficiencies (e.g., low signal-to-noise ratio, biases in spatio-temporal variability, unresolved sub-grid processes, and limited resolution) and mitigate computational costs.

This session aims to bring together the latest advances in the hybrid approaches to (i) improve our understanding and ability to simulate the climate system and its variability, (ii) enhance climate predictions on multiple timescales, and (iii) translate these advances into more reliable climate services for diverse users (e.g., health, energy, agriculture, water).

With these objectives in mind, we welcome contributions on, but not limited to: subsampling and filtering strategies to enhance predictions of climate variability and extremes on different timescales (including process-constrained projections); advanced machine learning (ML) and causal discovery techniques for validation, bias-correction and downscaling of dynamical model outputs; hybrid multimodel ensemble approaches to improve climate model simulations; transfer learning to leverage climate model outputs and expand ML training datasets; physics-informed ML parametrization of sub-grid processes; hybrid surrogate models that emulate or correct specific components of dynamical models; and impact/service oriented studies that deploy hybrid pipelines to support decision-making, such as hybrid seasonal forecasts and early warning systems based on ML or causal discovery techniques.

The stability of the Southern Ocean and Antarctic ice sheet plays a critical role in global ocean circulation, climate dynamics, the marine carbon cycle and global sea level. While reconstructions of southern, high-latitude paleoclimate are still sparse, recent years have seen much progress, including a multitude of land- and sea-based coring efforts, major IODP expeditions and work on legacy sediment cores. This session aims to bring together researchers working on understanding key climate processes across all sectors of the Southern Ocean and/or Antarctic ice sheet dynamics, their interaction with each other and associated impacts on global climate. We invite contributions from a broad range of numerical modeling studies and proxy reconstructions, including surface ocean changes, deep water circulation, upper-ocean stratification, sea ice, nutrient distribution and utilization, lithogenic inputs and oceanic frontal migration as well as ice sheet retreat/advance and meltwater supply. Studies may address a wide range of timescales from tectonic and orbital to millennial. We also welcome submissions that compare recent observations with paleoclimate records or that advance methods and approaches for reconstructing polar paleoclimate.

Atmospheric teleconnections link and influence weather and climate across geographically distant regions and can have far-reaching societal impacts. Understanding how specific teleconnections can modulate regional extremes and affect societal outcomes (for example water scarcity, agricultural impacts, disease spread or increased morbidity and mortality) is critical for anticipating their consequences.

This session invites a broad range of contributions investigating atmospheric teleconnections, their influence on regional climate variability and extremes, and their societal impacts. We welcome submissions focusing on different types of atmospheric teleconnections, their influence on regional extremes and those describing their sectorial impacts including agriculture, disease propagation, human health, water and food security and socio-economic impacts. Contributions may address subseasonal, seasonal, interannual or decadal timescales and focus on past climates, historical periods or future projections.

We particularly encourage studies that connect atmospheric teleconnection changes to real-world outcomes, using a broad range of tools, from observations, reanalyses, regional and Earth System models. These may include the links with climate-sensitive diseases (dengue, chikungunya, Zika, malaria etc.) or the assessment of crop yields and other agricultural or economic impacts Finally, as teleconnections underpin much of the skill of subseasonal-to-decadal forecasts, we also welcome contributions on how this knowledge is used in prediction, early warning systems and climate services.

The importance of tropical Indo-Pacific modes on global climate is evident in the ongoing strong El Nino event and the Indian Ocean leading surface ocean warming. But with a short observational record that misses many different climate states, to understand how the complex tropical circulation and the resulting hydroclimate variability that is essential to billions of people will change in the future, longer records from different mean climates are required. Recent advances in Paleoceanographic and Paleoclimate studies have greatly contributed to our understanding of the link between the Indian Ocean and the Pacific Ocean and raised new questions related to hydroclimate in the region. This session invites presentations of research designed to investigate the paleoclimate changes across different time scales from the common era, Quaternary and deeper times, using a variety of physical, geochemical and biological proxies. Contributions that discuss or even model the specific local processes and regional factors in the Indo-Pacific along with their links to the global climate system are particularly welcome. Studies on the interaction between the low and high latitudes and the roles of low latitude processes, the manifestation and mechanisms of rapid climatic events and transitions, the relationship between the monsoon and ITCZ movement, and their controlling factors are encouraged.

In response to anthropogenic greenhouse gas emissions and land-use change, we are transitioning towards a climate state that may feature rapid changes. This will have severe impacts on the occurrence of extreme weather events and increasing risk of crossing large-scale tipping points. Neither these transitions nor long-term climate states have been observed by instrumental measurements, making information on past climatic states increasingly important to anticipate future Earth System change. The availability of paleoenvironmental records have enormously expanded over the past decades, providing extremely rich information about physical, cryospheric, biological, and ecological processes on many spatial and temporal scales. Yet, it has been challenging so far to directly transform knowledge on past processes into a more confident evaluation of future projections for the Earth system.
Being able to reconstruct past climate evolution is a necessary step for enhancing our capacity to look into the future. Incorporating palaeodata-based information on past climate requires substantial improvements to state-of-the-art Earth System Models (ESMs). So far, ESMs are mainly calibrated and validated with respect to the instrumental records of the last ~170 years of relatively stable climate, while the Earth’s longer-term history is characterised by an interplay of gradual climate change, variability, and critical transitions between competing states, with profound impacts on climate subsystems, ecosystems, and civilisations.
Understanding the leading dynamical processes and feedbacks and in particular improving our ability to model and anticipate critical transitions in the climate and ecosystems is key to project future climate change on spatio-temporal scales relevant for societies, ecosystems, and the planet.

We invite contributions that
- advance process understanding of past climate changes and enhance ESM development through high resolution reconstructions of five key climate system parameters: atmospheric CO2-concentration, ice sheet (sea level) and sea ice extent, ocean temperatures, and terrestrial vegetation;
- explore modern approaches to incorporate palaeoclimate information into the development of ESMs of varying complexity, including rigorous model-data comparison techniques;
- make use of information from paleoenvironmental proxy data, past civilisations, ESMs, and rigorous theoretical approaches - individually or in combination.

Tropical reef ecosystems are facing a potential turning-point as they are experiencing the most extreme conditions on record. While the 4th global coral bleaching event (2023–25) exposed ~84% of the world's reefs to bleaching-level heat stress, the next extreme El Niño has started. Yet the observational baseline against which these events are assessed spans only a few decades, whereas the processes that determine whether certain reefs will persist can span centuries to millennia. To assess whether corals can adapt or have adapted to these extremes and which reefs will survive, we require baseline data that go far beyond current timespans alongside improved projections of the coming decades to centuries. Such information also provides an important foundation for restoration and conservation planning–a growing need. This session aims to bring together coral palaeoclimatology, reef (palaeo)ecology and (palaeo)biology, observations, and modelling relevant to restoration and conservation planning, policy-making, and understanding tropical climate dynamics.

We invite contributions from tropical and subtropical settings, including marginal, turbid and naturally extreme reefs, across timescales from deep time to future projections. Topics include, but are not limited to:

• high-resolution coral reconstructions and observations of ocean and climate variability (ENSO, IOD); oceanographic/ecological monitoring, remote sensing; skeletal growth/calcification, other marine biogenic archives (molluscs, sclerosponges, coralline algae)

• proxy development, process understanding; novel geochemical proxies (nitrogen, boron, clumped isotopes), biomineralisation

• coral reef ecology, biology, physiology under stress; thermal tolerance, trophic ecology, microbial symbiont dynamics, connectivity, community change, adaptation, reef refugia

• databases, synthesis, FAIR workflows; PAGES CoralHydro2k and CoralHydro2k-Seawater, CoralCache, GBR Coral Skeletal Records; proxy system modelling, isotope-enabled simulations, data assimilation, proxy-model comparison

• future projections of tropical climate and reef environments constrained by palaeorecords and observations; translation into baselines, thresholds, conservation planning

Contributions from coordinated programmes, such as PAGES working groups (e.g., 2k Network), DFG Priority Programme "Tropical Climate Variability & Coral Reefs", IODP research (e.g., IODP Exp. 389 Hawaiian Drowned Reefs), among others, are welcome.

Northeast Greenland occupies an important position within the Arctic, linking the Greenland Ice Sheet and ice-free terrestrial landscapes with the Arctic Ocean and Greenland Sea. Geologically and environmentally, the region has undergone major change associated with the opening and deepening of Fram Strait, the onset and intensification of Arctic–Atlantic water exchange, the early formation of ephemeral glaciers, the later build-up of the Greenland Ice Sheet, and its repeated expansion and retreat throughout the Quaternary. Ice-core records from EGRIP provide insights into past climate and ice-sheet dynamics, while observations of the Northeast Greenland Ice Stream and its outlet glaciers reveal ongoing changes in one of the ice sheet's major drainage systems. Under ongoing anthropogenically forced warming, Northeast Greenland is particularly sensitive to Arctic amplification, resulting in rapid changes across its terrestrial, cryospheric, marine and atmospheric systems. Understanding these changes, their interactions and their future trajectories requires integration across disciplines and timescales.
We invite contributions from marine, cryospheric, terrestrial and atmospheric research focused on Northeast Greenland, extending from eastern North Greenland to northern East Greenland. Studies that improve our understanding of the region across geological timescales through the present and into the future, using geological and palaeoenvironmental archives, ice-core records, contemporary observations, process studies, remote sensing and numerical modelling, are all invited. We particularly encourage studies that explore connections among systems, including the dynamics and evolution of the Northeast Greenland Ice Stream, ice-sheet–ocean interactions, atmospheric and oceanic forcing, freshwater and sediment fluxes, ocean circulation and sea ice, long-term landscape evolution and its interactions with glaciation, permafrost dynamics, and terrestrial and marine ecosystem change.

This session covers climate predictions from seasonal to multi-decadal timescales and their applications. Continuing to improve such predictions is of major importance to society. The session embraces advances in our understanding of the origins of seasonal to decadal predictability and of the limitations of such predictions. This includes advances in improving forecast skill and reliability and making the most of this information by developing and evaluating new applications and climate services, including windows of opportunity.
The session welcomes contributions from dynamical modeling, machine-learning or other statistical methods and hybrid approaches. It will investigate predictions of various climate phenomena, including extremes, from global to regional scales, and from seasonal to multi-decadal timescales (including seamless predictions). Physical processes and sources relevant to seasonal to (multi-)decadal predictability (e.g. ocean, cryosphere, or land) as well as predicting large-scale atmospheric circulation anomalies associated with teleconnections will be discussed. Analysis of predictions in a multi-model framework, and ensemble forecast initialization and generation will be another focus of the session. We are also interested in approaches addressing initialization shocks and drifts. The session welcomes work on innovative methods of quality assessment and verification of climate predictions. We also invite contributions on the use of seasonal-to-decadal predictions for risk assessment, adaptation and further applications.

The Arctic plays a vital role in the Earth's climate system through complex interactions among the atmosphere, ocean, cryosphere, and biosphere. Its sea ice cover reflects most of the incoming solar radiation and regulates the surface energy balance. Freshwater and heat fluxes associated with river runoff, the melting of the Greenland Ice Sheet as well as the formation and melting of sea ice can influence deep-water formation in the North Atlantic and hence the Atlantic Meridional Overturning Circulation. Additionally, the meridional temperature gradient between low and high latitudes drives large-scale atmospheric circulation. In the meantime, Arctic permafrost and peatlands store vast amounts of carbon, and the region is home to unique and vulnerable ecosystems.
However, anthropogenic climate change is warming the Arctic nearly four times faster than the global average in recent decades. Numerous feedbacks amplify this Arctic warming, known as Arctic amplification, and modulate the response of climate. The resulting changes are affecting Arctic ecosystems and potentially also influence remote regions through atmospheric and oceanic teleconnections.
Past warm climates act as natural laboratories and provide valuable information for the understanding of key processes and feedbacks involved in Arctic changes, establishing a basis for constraining future Arctic projections. Climate models on the other hand, project that the Arctic Ocean could become nearly ice-free during summers within the next few decades. Nevertheless, substantial uncertainties remain regarding the future Arctic evolution, potential variation of its influence on the global climate system and its ecosystem responses under continued warming. The ERC synergy grant i2B (Into the Blue) aims to address these research gaps by an integrative approach, combining paleoclimate evidence, modern observations, and numerical modelling.
Building on this interdisciplinary perspective, this session brings together studies that explore Arctic processes and their wider implications across different climate states. Therefore, we welcome contributions from all career stages investigating the Arctic mechanisms, impacts and interconnections across past, present, and future warm climate states from observational, proxy, or modelling perspectives.

To address societal concerns over rising sea levels, associated extreme events, and their impacts on coastal communities, ecosystems, and the global economy, it is essential to understand the drivers and contributions to these changes. This session responds to this need by inviting research from the international sea level community that advances knowledge of past, present, and future changes in global and regional sea levels, extreme events, and coastal impacts.
The session focuses on studies that explore the physical mechanisms of sea level rise and variability, as well as the underlying drivers, across timescales ranging from paleo records to high-frequency phenomena to long-term projections, using observations and/or model simulations. Research on linkages between sea level variability, heat and freshwater content, ocean dynamics, ice-sheet and glacier mass loss, land subsidence, and terrestrial water storage is welcome. We encourage studies addressing future sea level changes, including high-end projections from rapid ice-sheet mass loss, and those assessing short-, medium-, and long-term coastal impacts and their broader implications.

Land–atmosphere interactions often play a decisive role in shaping climate extremes. As climate change continues to exacerbate the occurrence of extreme events, a key challenge is to unravel how land states regulate the occurrence of droughts, heatwaves, intense precipitation and other extreme events. This session focuses on how natural and managed land surface conditions (e.g., soil moisture, soil temperature, vegetation state, surface albedo, snow or frozen soil) interact with other components of the climate system – via water, heat and carbon exchanges – and how these interactions affect the state and evolution of the atmospheric boundary layer. Moreover, emphasis is placed on the role of these interactions in alleviating or aggravating the occurrence and impacts of extreme events. We welcome studies using field measurements, remote sensing observations, theory and modelling to analyse this interplay under past, present and/or future climates and at scales ranging from local to global but with emphasis on larger scales.

The climate system is changing rapidly, with some regions experiencing increases in extreme events beyond what is expected from climate model simulations. To improve the accuracy of climate predictions and projections, it is necessary to (1) identify and explain what factors and processes drive observed and predicted climate changes, (2) critically assess how key processes are represented in climate models, (3) understand and explain the predicted signals, which often result from the interaction of multiple drivers, and (4) use this knowledge to calibrate and further develop predictions to provide more reliable and thus useful information to society. In combination, these research activities contribute to building the capability for an integrated attribution and prediction of climate change - a key goal of the WCRP Lighthouse Activity on Explaining and Predicting Earth System Change (EPESC) and the Horizon-Europe project EXPECT.

Progress in integrated attribution and prediction will benefit from combining diverse data sources, such as Earth Observations, and various climate model experiments, including those at very high resolutions. This session invites contributions on advancing integrated attribution and prediction, with a particular focus on annual to decadal timescales, which involves explaining, predicting and constraining climate changes from regional to global scales. Relevant topics include, for example, studies attributing the drivers of specific climate phenomena and extremes such as the atmospheric circulation during the boreal summer and related surface extremes, evaluating climate responses to different forcings and internal variability, correcting biased climate responses e.g. using process-based constraints, providing calibrated prediction and projections of future climate based on these constraints, and methods that exploit a variety of data in combination with novel analysis techniques including Artificial Intelligence.

A longstanding pursuit in climate science is to better understand Earth’s climate sensitivity, which quantifies how global mean surface temperature responds to changes in radiative forcing. Uncertainty in climate sensitivity arises due to forcing and radiative feedbacks, which are influenced by processes ranging from cloud microphysics and local meteorology to large-scale atmospheric circulation and the spatial pattern of surface temperature changes. This session solicits work across theory, observations, and modeling focusing on climate sensitivity, radiative feedbacks, and the pattern effect. It aims to serve as an exchange platform for atmospheric and oceanic science communities, showcasing the full spectrum of modeling approaches from conceptual frameworks and CMIP ensembles to km-scale simulations and novel machine learning methods.

We welcome contributions related to, but not limited to:
- Process studies of feedbacks from clouds, convection, and moist processes
- The modulation of radiative feedbacks by surface warming patterns (the "pattern effect'')
- Theoretical and conceptual models of climate sensitivity (ECS, TCR)
- Relationships between idealized climate sensitivity measures and climate change projections
- Insights into CMIP6 "hot models'' as well as novel CMIP7 simulations
- Ocean heat uptake, air-sea interactions, and ocean dynamics shaping surface temperature patterns, radiative feedbacks, and transient climate sensitivity
- Carbon-climate feedbacks, carbon-cycle interactions, and Earth system/emission response metrics (TCRE, ZEC, ESS)

Throughout Earth’s history, large explosive volcanic eruptions and asteroid impacts have episodically perturbed the Earth system, driving major climate disruptions with profound consequences for the biosphere. These events can modify atmospheric composition, perturb Earth’s radiative balance, trigger abrupt surface cooling, weaken the hydrological cycle, alter ocean circulation and biogeochemistry, suppress terrestrial and marine productivity, and generate cascading effects across ecosystems and food webs. Such environmental changes may further shape the evolutionary trajectories of species, including humans.

One notable example is the Chicxulub impact about 66 million years ago, which generated a global impact winter and almost certainly triggered the Cretaceous–Paleogene mass extinction. Another example is the Toba supereruption about 74,000 years ago, which likely caused substantial climatic effects and may have affected human populations. However, the magnitudes, timescales, spatial patterns, and underlying mechanisms of climate and biosphere responses to major perturbations remain incompletely understood and actively debated.

This session invites contributions that investigate how major perturbations—including volcanic eruptions, asteroid impacts, and other abrupt climatic events of varying magnitudes—affect the climate system, terrestrial and marine ecosystems, and the evolution of mammals and humans across a wide range of timescales and regions. We welcome theoretical, observational, proxy-based, and modeling studies from multidisciplinary perspectives spanning volcanology, planetary science, climate science, paleoclimatology, ecology, archaeology, and paleoanthropology.

Global coupled models that resolve ocean mesoscale eddies, and increasingly atmospheric storms, can now be run over multidecadal to centennial timescales. This allows us to ask whether small-scale processes change the large-scale climate: its mean state, its modes of variability and its response to forcing. This session focuses on the rectified effect of resolved small scales in the ocean, the atmosphere and at the air-sea interface on the climate system.

We welcome contributions from global km-scale models as well as from eddy-rich coupled configurations with coarser atmospheres, regional high-resolution setups and model hierarchies. Topics include the role of ocean mesoscale and submesoscale dynamics, boundary currents and fronts in climate; mesoscale air-sea coupling and its influence on storm tracks, jets, and precipitation; interannual to decadal to centennial variability including the AMOC, the Southern Ocean and tropical modes; whether resolution alters forced responses, climate sensitivity and SST trend patterns; sea ice, and ice-sheet-ocean interactions at high resolution; biogeochemistry, impacts on marine ecosystems, and km-scale mechanisms underlying the exchange of carbon at the air-sea interface and its subsequent transport in the ocean.
We also welcome studies exploring how resolved oceanic and atmospheric small-scale processes influence extremes, including heatwaves, marine heatwaves, ocean carbon uptake and acidification, heavy precipitation and compound events, particularly where these provide insight into climate variability and climate change.

We also invite studies using pacemaker or filtered-forcing experiments and resolved-versus-parameterised comparisons to isolate mechanisms or transfer insight to coarser models, as well as storyline approaches, pseudo-global-warming experiments, uniform warming experiments (e.g. +4 K frameworks), and related targeted methodologies used to understand the role of resolved small-scale processes in climate variability, extremes, and climate change, as well as work on challenges specific to long coupled simulations such as spin-up, drift, tuning, and initialisation.

Contributions from EERIE, DestinE, nextGEMS, WarmWorld, DYAMOND, DYAMOND3, MESACLIP, HighResMIP and related efforts are encouraged.

The large-scale atmospheric circulation is an essential component of the climate system. Understanding the drivers, variability and the dynamical processes of this circulation is important for improving global and regional climate projections under anthropogenic climate change, and for predicting the associated impacts on extreme weather and climate events. This session encourages theoretical, modelling and observational research on the large-scale atmospheric circulation, including (but not limited to) the following topics:
-Response of the large-scale atmospheric circulation to climate change, including shifts and changes in intensity of the jet stream, Hadley and Walker cells, intertropical convergence zone, and monsoons;
-Changes in storm track intensity and structure in response to climate change and/or internal variability;
-Representation of the large-scale atmospheric circulation in climate models: inter-model variability, model biases, and methodologies for reducing uncertainty in model projections;
-Novel metrics and analysis methods for studying the large-scale atmospheric circulation;
-Interactions between the different components of the large-scale circulation, including tropical-extratropical interactions and teleconnection patterns;
-Role of moisture in the large-scale atmospheric circulation;
-Energy transport by the large-scale atmospheric circulation;
-Stratospheric-tropospheric interactions affecting the large-scale circulation.

Earth's climate is undergoing rapid change, with anthropogenically forced trends emerging across the atmosphere, ocean, and cryosphere. At the same time, internally generated multidecadal variability continues to modulate regional and global climate evolution, complicating attribution and prediction. Therefore, understanding the interplay between externally forced change and natural variability is essential for improving confidence in climate projections, decadal predictions, and climate risk assessments.

Recognizing the importance of addressing these issues, the WCRP CLIVAR has initiated a research focus on “Confronting Earth System Model Trends and Multidecadal Variability with Observations (CEMT-MV)”. This session contributes to CEMT-MV, offering a venue to summarize recent work and to stimulate new research. We invite contributions on the detection and attribution of observed climate trends, separation of externally forced signals and internal climate variability, and multidecadal variability in the atmosphere, ocean, cryosphere, and coupled climate system. We are particularly interested in the evaluation of existing and new ESM simulations (e.g., CMIP7 and PMIP7) and reanalysis datasets, on the mechanisms underlying simulated and observed multidecadal variability, and on implications for decadal climate prediction. We welcome studies utilizing paleo-climate reconstructions and data-model comparisons for the last millenium and ones that introduce new methods, including AI and machine learning, for identifying trends and multidecadal variability. Implications for future climate projections, regional climate change, and climate services.

The Arctic is undergoing rapid climate and environmental change, but understanding the processes driving this transformation requires a longer-term perspective. Marine sediment archives preserve evidence of past changes in ocean circulation, sea-ice conditions, ice-sheet dynamics, freshwater discharge, sediment transport, productivity, biogeochemical cycling and ecosystem changes across a wide range of timescales.
Shallow coring methods are suitable for obtaining detailed information on late Quaternary ice-ocean-climate variability, while ocean drilling records extends the perspective into older Cenozoic time windows when climate backgrounds were, substantially different from the present. Together, these archives provide complementary perspectives on rapid and long-term Arctic climate variability, helping to better understand global processes and constrain model predictions.
This session invites contributions based on the study of marine sediment cores and ocean drilling records and corresponding site surveys from the Arctic Ocean and surrounding continental margins. We particularly welcome studies integrating sedimentological, stratigraphic, micropaleontological, palaeogenomic, geochemical, paleomagnetic, physical-properties, and geophysical datasets to develop robust age models and paleoenvironmental reconstructions.
Topics of interest include, but are not limited to:
- Arctic Ocean circulation and variability across the Arctic gateways;
- sea-ice evolution and ocean–ice–atmosphere interactions;
- ice-sheet growth, retreat, and instability;
- sediment provenance and depositional processes;
- palaeoceanographic and palaeoclimatic reconstructions across the Cenozoic;
- past marine ecosystem and biodiversity changes, including sedimentary ancient DNA
- abrupt climate events and glacial–interglacial transitions;
- seismic stratigraphy and geophysical constraints on sedimentary archives;
- development and correlation of age models using multidisciplinary and novel approaches;
We particularly encourage contributions that bridge different spatial and temporal scales and combine multiple archives and methodologies. The session aims to provide a forum for connecting high-resolution shallow-core studies with the longer-term perspective offered by ocean drilling, thereby improving our understanding of the evolution and sensitivity of the Arctic climate system.

Why do past climatic changes produce different societal outcomes across regions and through time? This session focuses on the pathways and feedbacks linking climate change, water availability, ecosystem productivity, resource landscapes, human agency, and societal changes during the Holocene and beyond. We invite empirical, theoretical, and modelling studies that identify these processes across past and present human-environment systems. Of particular interest are studies that integrate palaeoclimate and environmental records with archaeological, historical, or societal evidence; examine thresholds, feedbacks, and nonlinear responses; or use process-based, agent-based, network, complex-systems, and data-driven approaches to connect environmental forcing with human decision-making and societal change. By bridging together climate, environmental, and social perspectives, this session aims to advance a process-based understanding of why climatic changes produce diverse societal trajectories under different environmental and social context.

Land-atmosphere coupling modulates the exchange of water, heat and carbon between the land surface and the atmosphere. Therefore, it can dampen or exacerbate climate extremes (e.g., heat waves and droughts) and affect ecosystem processes (e.g., the land carbon sink). However, there are several key aspects related to uncertainties that hinder the accurate quantification of land-atmosphere coupling. Firstly, different metrics/indices can be used to describe (aspects of) land-atmosphere coupling, introducing uncertainties between the respective estimates. Secondly, an increasing amount of data describing land-atmosphere coupling is available, together with increasingly powerful methods for analysing them. In response to this, a more thorough consideration of uncertainty stemming from data and methods is critical in interpreting the robustness of emerging patterns. Lastly, physical processes underlying land-atmosphere coupling occur on different spatiotemporal scales ranging from in-situ to the regional scale and from seconds to months, which may or may not be reflected in the data we use to study them, in turn further inducing uncertainties.
Only by considering these aspects it is possible to determine accurately where available information is (not) sufficient to draw robust conclusions. Addressing the uncertainty challenge aims at a more precise identification of e.g. accurate observational constraints for process-based modelling or a more accurate determination of the role of land-atmosphere interactions for changes in (surface) weather and climate.
We invite abstracts that quantify uncertainties of various origins relevant for studying land-atmosphere interactions, including but not limited to inter- and intracomparisons of observations and model output, evaluations across spatiotemporal scales, and assessments of variables capturing surface carbon or water fluxes and indices/metrics.
We are especially interested in abstracts that move beyond solely quantifying the uncertainties, but motivate us to address and reconcile them and abstracts focusing on the implications of uncertainties related to land-atmosphere interactions on the evolution and location of extremes, carbon processes or the location of land-atmosphere coupling hot spots, among others.

The Atlantic Meridional Overturning Circulation (AMOC) plays a crucial role in shaping the dynamics of the Earth’s climate by distributing heat and nutrients across the Atlantic. It is important to understand the past, present and future changes in the dynamics of the AMOC, either gradual or abrupt, since such changes, and the possibility of its tipping, can have profound climatic and societal impacts. In this regard, big data and AI play an increasingly important role in studying AMOC dynamics based on diverse types of data. These range from geological proxies over contemporary in-situ and remote sensing observations to simulations of state-of-the-art ocean or coupled Earth system models and provide an ever increasing amount of more and more complex data on the AMOC. Advanced numerical methods and AI can help us to uncover critical aspects of the AMOC dynamics by extracting new patterns and highlighting the role of complex physical mechanisms and feedbacks, including early warnings of future regime shifts of the AMOC or some of its subcomponents like the Nordic Seas deep convection or the Northern hemisphere subpolar gyre.
In this session we welcome contributions exploring new ways of using big data and AI to elucidate AMOC dynamics. We aim to cover a broad variety of computational methods, making use of the wealth of AMOC-related observational and/or model data. These can range from statistical methods exploiting big datasets to machine learning and deep learning approaches, including neural-network emulators of the AMOC. The session is open to work on a wide range of timescales, from paleoclimate reconstruction, through current observations to future projections. Contributions may address the analysis of short-term AMOC dynamics, as well as longer-term behaviour, including tipping of the circulation and associated forecast and impact studies.

Climate modeling is pushing the frontier towards increasingly complex, high-resolution earth system models (ESMs). At the same time, nonlinearities and emergent phenomena in the climate system are often studied by means of conceptual models, which offer qualitative understanding and permit theoretical approaches. Recent advancements in statistical and physical emulators – ranging from reduced-complexity climate models to machine learning-based techniques – are enabling rapid and computationally efficient assessments of climate trajectories, impacts, and risks.

Between these approaches, a persistent “gap between simulation and understanding” (Held 2005) challenges our ability to transfer insights from conceptual models to reality, and to distill the physical mechanisms underlying the behavior of complex (climate) models. This calls for a concerted effort to learn from the entire model hierarchy, understanding the differences and similarities across its various levels of complexity, to increase confidence in climate projections.

In this session, we invite contributions from all subfields of climate science that showcase how different modeling approaches advance our understanding of the Earth system and its components, and/or highlight inconsistencies in the model hierarchy. We also welcome studies exploring a single modeling approach, as we aim to encourage exchange between researchers working on different rungs of the model complexity ladder. Contributions may employ dynamical systems models, physics-based low-order models, explainable machine learning, Earth System Models of Intermediate Complexity (EMICs), simplified or idealized setups of ESMs (radiative-convective equilibrium, single-column models, aquaplanets, slab-ocean models, idealized geography, etc.), full ESMs or standalone models of components of the Earth system, and km-scale models.

Processes and phenomena of interest include, but are not limited to:
* Earth system response to climate forcing
* Tipping behavior and critical transitions
* (Coupled) modes of climate variability
* Extremes and predictability

The Quaternary Period (the last 2.6 million years) is characterized by frequent and abrupt climate swings and rapid environmental change. Studying these changes requires accurate, precise dating methods that can be applied effectively to environmental archives. Different methods or a combination of various dating techniques can be used depending on the archive, time range, and research question. Varve counting and dendrochronology allow for the construction of high-resolution chronologies. In contrast, radiometric methods (radiocarbon, cosmogenic in-situ, U-Th, and even Pb-210 for the Anthropocene), luminescence dating, and electron spin resonance dating provide independent anchors for chronologies that span longer timescales. We particularly welcome contributions that aim to (1) reduce, quantify, and express dating uncertainties in any dating method, including high-resolution radiocarbon approaches; (2) use established geochronological methods to answer new questions; (3) use new methods including recognizing and critically examine their limitations to address longstanding issues, or; (4) combine different chronometric techniques for improved results, including the analysis of chronological datasets with novel methods, e.g., Bayesian age-depth modeling; (5) we also welcome contributions integrating multiple chronological and provenance tools including U-Pb geochronology and apatite fission track thermochronology to constrain sediment provenance and source to sink dynamics. Applications may aim to understand long-term landscape evolution, quantify rates of geomorphological processes, or provide chronologies for records of climate change and anthropogenic effects on Earth's system.

The analysis of datasets that represent comprehensive Earth-system processes can be greatly facilitated with the aid of existing tools and tutorials that have been developed within the global climate community. This session aims to bring together the developers and users of these resources to exchange knowledge, share best practices, and address scientific and technical challenges related to climate and Coupled Model Intercomparison Project (CMIP) data analysis. We welcome contributions presenting tools, workflows, tutorials, and practical approaches that support access, processing, analysis, visualization, and interpretation of climate and CMIP data.
This session is prepared together with the members of the CMIP Rapid Evaluation Framework (REF) and members of the Fresh Eyes on CMIP project on compiling existing tools and tutorials. An overview of currently collected tutorials and tools is available through the WCRP CMIP website:
https://wcrp-cmip.org/tutorials/
https://wcrp-cmip.org/tools/.

Regional climate modeling has experienced tremendous growth in the last decades, encompassing a large and diverse scientific community. Regional climate models (RCMs) can be run on a wide range of scales, from hydrostatic to convection-resolving resolutions, supporting various applications. This session welcomes papers on methodological developments in regional climate modelling, performance analysis of RCMs, use of RCMs for regional processes studies, past and future climate projections as well as studies on extreme events and impact assessment. Additionally, the session encourages submissions related to the CORDEX program, including the analysis of CORDEX-CORE experiments and simulations within the framework of different CORDEX Flagship Pilot Studies. The release of the CORDEX-CMIP6 simulations marks a significant milestone for regional climate modeling within the CORDEX community. This session highlights the latest progress in generating high-resolution regional climate projections and offers early insights from the newly available datasets. We anticipate that this session will provide a platform for discussing the progress of RCM-related research and fostering future collaborations.

Land surface processes play a crucial role in shaping Earth's climate system, mediating land-atmosphere interactions, and driving terrestrial water-carbon-energy feedbacks. Land Surface Models, as core components of Earth System Models (ESMs), influence climate projections in benchmarks such as the CMIP7. However, land hydrology and its interactions with other components of the Earth system (e.g. biosphere, biogeochemical cycles) remain poorly represented in most ESMs, potentially inducing erroneous responses to anthropogenic climate forcings at global to local scales and leading to misrepresentations of droughts and floods. For instance, ESMs do not represent the observed decline of groundwater levels in water-limited regions that threatens groundwater-dependent ecosystems and exacerbates drought persistence, thereby increasing the risk of ecosystem shifts and progressive desertification. This crosscutting session provides an open, interdisciplinary platform to bridge the gap between hydrologists, hydrogeologists, ecohydrologists, and climate modelers.

We invite observational, theoretical, and numerical modeling contributions that advance the integrated representation of hydrological, hydrogeological, biophysical, and ecosystem processes within land surface models across spatial and temporal scales. Key areas of focus include the representation of the soil-plant-atmosphere continuum, plant hydraulics, vegetation stress dynamics, and biosphere-mediated moisture recycling, alongside subsurface hydrogeology such as explicit groundwater-table dynamics, lateral flow, and deep aquifer linkages. Contributions addressing human-water-ecosystem interlinkages (e.g., groundwater abstraction, irrigation, land-use change), high-resolution ESM configurations, advanced observational networks, and emerging AI/machine learning techniques are also strongly encouraged.

The overarching aim of this session is to overcome historical disciplinary silos and establish a shared agenda across modeling communities. By aligning interdisciplinary priorities, addressing cross-scale parameterization challenges, and improving the evaluation of land-based mitigation and adaptation strategies, this session seeks to define future needs and collaborative opportunities for the next ESM generation.

As data-driven models increasingly rival or complement physics-based systems, a central question remains open: can AI reliably forecast the events that matter the most, the extremes that drive real-world impacts, and not just the average state of the atmosphere? This session brings together the latest advances in machine learning (ML) and artificial intelligence (AI) for forecasting weather, projecting climate, and simulating extreme events.

We invite contributions spanning the full range of timescales and methods, including but not limited to:
*data-driven and foundation weather models for short- and medium-range forecasting;
*generative and probabilistic approaches (e.g. diffusion models) for forecasting, downscaling, and uncertainty quantification;
*ML for sub-seasonal to seasonal (S2S) prediction and longer-term climate projections;
*hybrid AI-physics approaches that embed physical constraints into data-driven models or improve the representation of climate variables in numerical models and datasets;
*detection, attribution, and anticipation of extreme events such as hurricanes, floods, heatwaves, droughts, and compound extremes.

We particularly encourage submissions that go beyond forecast skill to address impacts on infrastructure, ecosystems, health, or energy systems, and that engage with questions of trust, explainability, and generalization to unseen or out-of-distribution extremes.

By bringing together experts from AI, data science, meteorology, climate science, and impact modelling, this session aims to foster interdisciplinary collaboration and push the boundaries of AI-driven understanding and prediction of extreme weather and climate events. We warmly welcome submissions from early-career scientists, established researchers, and industry professionals alike.

Stable, radiogenic, and radioactive isotopes are fundamental tools for understanding Earth’s climate system. Isotopic measurements trace the chemical reactions, mass transfers, and biogeochemical cycles that link climate to other components of the Earth system, and they underpin many past climate reconstructions. Analytical advances, such as triple oxygen isotopes and compound-specific isotope analysis, are opening new avenues for scientific study, while established isotopic methods are steadily being applied to new archives and environmental settings. This session welcomes researchers developing and applying isotopic tools for past and present climate studies. We encourage contributions presenting new analytical methods, calibration and proxy advances, applications to new or underused archives, and modern studies that improve the interpretation of isotopic records. We also welcome studies that integrate isotopic data with geochemical, geomorphic, or climatological evidence, including multi-proxy archive studies, or with modelling approaches such as source mixing and isotope-enabled climate models.

High-resolution, non-destructive imaging techniques—including 3D micro-CT, micro-XRF core scanning, hyperspectral imagery, and multi-sensor optical logging—have revolutionized paleoclimate and paleoenvironmental research across sedimentary, speleothem, ice core, tree-ring, and biological archives. However, community-wide data synthesis remains hindered by non-standardized calibration protocols, disparate operating procedures, and unaligned data formats.

Organized in conjunction with the PAGES PaleoIMAGING Working Group, this session brings together empirical researchers, laboratory specialists, and data managers to showcase innovative scientific applications, proxy reconstructions, and community-wide harmonization.

We invite contributions covering:
1. Applied paleo-environmental, paleoclimate, and sedimentological studies using high-resolution core imaging modalities.
2. Novel imaging applications, sensor developments, and analytical processing methods.
3. Interlaboratory comparisons, standard reference materials, and physical calibration protocols.
4. Best practices, standard operating procedures (SOPs), and image processing/segmentation pipelines.
5. Open-access repositories, standardised data formats, and multi-modal dataset integration.

Extreme events are difficult to understand because observations are sparse in both space and time, especially for the less frequent but most impactful and severe events. Inference on environmental extremes is becoming increasingly challenging as their behavior can change over time, they can occur across large spatial regions, and they can interact with one another. Extreme Value Theory (EVT) provides a strong theoretical framework for studying these events, but challenges remain in linking methodological advances with environmental applications, prediction, and risk assessment.
We welcome contributions spanning theory, methodology, and applications, including but not limited to:
Advancing EVT methods
• Extreme quantile regression and estimation, conformal prediction, and non-stationary tail models
• EVT-constrained machine learning, uncertainty quantification, extrapolation, and inference under limited extreme event observations
• Methods to evaluate the appropriateness of EVT estimates, impacts of violations of EVT assumptions, and alternative extreme value analysis approaches
Applying EVT to environmental extremes
• Applications to hydrology, climate, weather, coastal hazards, earthquakes, landslides, wildfires, and infrastructure related risk
• Compound, connected, and cascading extremes, including drought-flood sequences, heatwave clusters, extreme precipitation, storm surges, and other interacting hazards
• Novel and under explored applications of EVT to environmental processes and hazards, including snowmelt, air turbulence, environmental epidemiology, and other emerging areas
EVT for prediction, risk assessment, and decision support
• Synthetic extreme event generation and scenario design for stress testing
• Tail focused calibration, validation, and verification, including extremal scoring rules, return level skill, and reliability in the tails
• Quantification and communication of uncertainty relevant to hazards, exposure, impacts, and risk
• Approaches that translate tail behavior and return level information into decision relevant metrics and services
We encourage contributions that bridge methodological EVT developments with real world environmental applications. Contributions may include new theoretical or methodological developments, open datasets and tools, model evaluation frameworks, and real world case studies.

Organic molecules preserved in sediments and other environmental archives record the organisms, environment, and process-specific dynamics from which they originated. Interpreting their signals, however, requires disentangling biological, physical, and chemical overprints from the original signal. Lipid biomarkers from diverse source organisms spanning archaea, bacteria, algae and higher plants to animals, together with their stable isotopic composition, remain one of the most powerful tools for this work. Analyses often integrate various compound classes such as n-alkanes, fatty acids, alkenones, sterols, hopanoids, HBIs (Highly Branched Isoprenoids), HGs (Heterocyst Glycolipids), GDGTs (Glycerol Dialkyl Glycerol Tetraethers), and intact polar lipids, applied across settings ranging from modern process studies to deep-time reconstructions.
This session draws together biomarker-based research across terrestrial, lacustrine, marine and anthropogenically influenced environments. We encourage submissions of studies using new biomarker tools, proxy development, compound-specific isotope analyses (e.g., δ¹³C, δ²H, δ18O, Δ¹⁴C), lipid biosynthesis and phylogeny of source organisms, and transport and diagenetic processes.
We also invite studies applying biomarker and isotopic evidence to reconstruct environmental variables such as temperature, hydroclimate, vegetation change, human impact, and biogeochemical cycling across modern and past environments. We particularly encourage contributions from early-career scientists.

Establishing reliable chronological frameworks is fundamental to the interpretation of sedimentary records and to reconstructing the timing, duration and rates of geological and environmental processes. Sedimentary archives span a wide range of timescales and depositional environments, and their chronological characterization often requires the integration of different dating techniques and stratigraphic approaches. However, the accuracy, precision and applicability of these methods may vary depending on the material, age range, depositional setting and preservation of the sedimentary record. This session aims to bring together researchers working on the development and application of absolute and relative dating techniques, geochronology and chronostratigraphy in sedimentary successions across different timescales. We welcome contributions using a broad range of approaches, including radiocarbon, luminescence, cosmogenic nuclides, tephrochronology, magnetostratigraphy, biostratigraphy, chemostratigraphy, cyclostratigraphy, event stratigraphy and other chronological and stratigraphic correlation methods.
Particular attention will be given to studies integrating multiple dating techniques, comparing independent chronological constraints, improving age models and stratigraphic correlations, and addressing methodological limitations, uncertainties and potential biases. We also encourage contributions presenting methodological advances, novel chronological markers, innovative analytical or modelling approaches, and strategies for dating challenging or discontinuous sedimentary records and contributing to environmental and paleoclimatic reconstructions.
Applications from terrestrial, lacustrine, fluvial, coastal and marine environments are welcome, from recent and Quaternary deposits to deep-time sedimentary successions. By bringing together geochronologists, stratigraphers, sedimentologists and researchers from related disciplines, this session seeks to promote interdisciplinary discussion on how different chronological approaches can be integrated to improve our understanding of time in the sedimentary record and its application to geological, palaeoenvironmental and palaeoclimatic research.

This session invites contributions on the latest developments and results in lidar remote sensing of the atmosphere, covering • new lidar techniques as well as applications of lidar data for model verification and assimilation, • ground-based, airborne, and space-borne lidar systems, • unique research systems as well as networks of instruments, • lidar observations of aerosols and clouds, thermodynamic parameters and wind, and trace-gases. Atmospheric lidar technologies have shown significant progress in recent years. While, some years ago, there were only a few research systems, mostly quite complex and difficult to operate on a longer-term basis because a team of experts was continuously required for their operation, advancements in laser transmitter and receiver technologies have resulted in much more rugged systems nowadays, many of which are already operated routinely in networks and several even being fully automated and commercially available. Consequently, also more and more data sets with very high resolution in range and time are becoming available for atmospheric science, which makes it attractive to consider lidar data not only for case studies but also for extended model comparison statistics and data assimilation. Here, ceilometers provide not only information on the cloud bottom height but also profiles of aerosol and cloud backscatter signals. Scanning Doppler lidars extend the data to horizontal and vertical wind profiles. Raman lidars and high-spectral resolution lidars provide more details than ceilometers and measure particle extinction and backscatter coefficients at multiple wavelengths. Other Raman lidars measure water vapor mixing ratio and temperature profiles. Differential absorption lidars give profiles of absolute humidity or other trace gases (like ozone, NOx, SO2, CO2, methane etc.). Depolarization lidars provide information on the shapes of aerosol and cloud particles. In addition to instruments on the ground, lidars are operated from airborne platforms in different altitudes. Even the first space-borne missions are now in orbit while more are currently in preparation. All these aspects of lidar remote sensing in the atmosphere will be part of this session.

Thermal remote sensing is an increasingly established technique employing passive sensors to deriveEarth’s surface properties from the radiation emitted in the Thermal Infrared (TIR) domain. Its main focus is the thermal state of an object or surface, together with the associated surface temperature and emissivity. These properties are relevant across geological, environmental, climatic, agricultural, biological, and engineering applications.

Recent technological advances have driven the development of TIR remote sensing: satellite sensors and data infrastructure systems can now acquire and manage large volumes of high-fidelity TIR data at a wide range of spatial and temporal resolutions. Besides airborne and ground-based systems, Unmanned Aerial Systems (UAS) are increasingly used as versatile platforms that combine high spatial resolution with flexible temporal revisit. Together with a growing catalogue of current and upcoming missions, this makes it a timely moment to take stock of where the field stands.

This session addresses established and emerging research directions in TIR remote sensing and discusses the community's upcoming challenges. We welcome contributions on new frontiers, case studies, and data-integration analysis related to:

• Geosciences: volcanoes, hydrothermal systems, geothermal potential, mineral exploration, rare earths, cryosphere.

• Climate, Urban Systems, and Ecosystems: urban heat islands, global warming impacts, ecosystem stress, forest health, fire risk assessment, water management.

• Agriculture and Precision Farming: crop stress monitoring, irrigation management, soil analysis and pest/disease monitoring.

• Technological and Methodological Innovations: new sensors for satellite, airborne, UAS and in-situ platforms, multi-platform and/or multi-sensor data integration, Cal/Val activities.

• Data Processing and Infrastructure: approaches for managing and processing large TIR datasets, data fusion techniques, advanced algorithms for atmospheric correction and temperature and emissivity separation.

Multi-disciplinary studies and contributions from Early Career Scientists are especially welcome.

Invited Speaker: Sabine Chabrillat, Helmholtz Centre for Geosciences (GFZ).

Time series are a common type of data generated by observational and modelling efforts across Earth, environmental and space sciences. Long-term observations are particularly important for understanding gradual changes and assessing risks, yet are often difficult to sustain and fund. Their characteristics can vary substantially, from short to long records, linear to nonlinear dynamics, univariate to multivariate data, and single- to multi-scale variability. These differences call for both tailored methodologies and general approaches.

A key challenge is distinguishing random fluctuations from long-term changes in order to better understand processes within and across Earth system components. This requires knowledge of temporal variability and, often, sufficiently long observations. For example, reliable sea-level trends may require several decades of continuous measurements because of decadal variability. Likewise, the stochastic variability of geophysical time series can exhibit power-law scaling, requiring long records for robust statistical assessment.

Time series analysis encompasses a broad range of tasks, including:
- characterizing nonlinear variability in the time and/or frequency domain;
- quantifying complexity, predictability and scaling properties;
- identifying statistical interdependencies within and between time series;
- distinguishing co-variability from causal relationships;
- reducing dimensionality and identifying meaningful modes of variability; and
- developing stochastic and deterministic statistical or dynamical models.

This session invites contributions on the development and application of modern methods for analysing observational and model time series across the EGU community, including geophysical, geodynamic, oceanographic, geodetic and climate observations from terrestrial observatories and remote sensing. Contributions addressing advances in sensors, instrumentation, monitoring, analysis and interpretation, as well as comparisons of different approaches, are welcome. Studies using novel methods, including AI, for the analysis of long time series are particularly encouraged. We aim to foster interdisciplinary exchange and cross-fertilization between different EGU divisions.

Machine learning is reshaping the representation of complex physical processes in Earth system models, offering new avenues for parameterisation, emulation, and hybrid modelling. This session focuses on the use of machine learning to emulate computationally expensive or unresolved processes, accelerate physical simulations, enable data-driven discoveries, and improve representation across domains such as convection, turbulence, radiation, hydrology, sea ice, and other Earth system components. Topics include (but are not limited to):

- Subgrid-scale parameterisations via machine learning
- Emulators of physical processes, model components, or whole weather and climate models (including end-to-end learning and foundation models)
- Data-driven discoveries
- Hybrid ML-physics modelling frameworks
- Physics-informed neural networks, neural operators, and differentiable programming
- Reinforcement learning and other approaches for ensuring physical consistency, stability, and optimising model behaviour
- Calibration and parameter optimisation using ML
- Physical behaviour, encoding and analysis of ML models
- Verification and explainability (XAI) of data-driven models (including AI forecasting)
- Representation of extremes and downscaling
- Coupling of ML models with physical models
- Cross-domain applications (atmosphere, ocean, cryosphere, land)
- Impacts of architecture choices and design on physical behaviour
- Links between ML methods and fundamental physics or applied mathematics
- Novel AI methods and applications

Nonlinear waves transfer energy, momentum, and information across scales in the atmosphere and ocean. Rossby waves, atmospheric gravity waves, and ocean surface and internal waves interact with mean flows, turbulence, and other waves, influencing circulation, atmospheric blocking, teleconnections, ocean mixing, predictability, and extreme events. Their multiscale behaviour, nonlinear interactions, and limited observability remain challenging for conventional analysis and modelling.

This session invites contributions exploring how artificial intelligence, machine learning, and data-driven methods can improve the understanding, representation, and prediction of atmospheric and oceanic waves.

We welcome studies on Rossby-wave propagation and breaking, wave packets, wave–mean-flow interactions, blocking, teleconnections, circulation regimes, extremes, and predictability. Contributions addressing atmospheric gravity waves, ocean surface and internal waves, planetary and topographic waves, and wave–wave interactions are also encouraged.

Relevant approaches may include deep learning, neural operators, physics-informed AI, computer vision, explainable AI, reduced-order modelling, causal discovery, hybrid modelling, and machine-learning parameterizations. Applications may address wave detection, reconstruction from sparse observations, simulation acceleration, unresolved processes, prediction of wave evolution, and forecasting of wave-related extremes.
We also welcome assessments of the physical consistency, interpretability, uncertainty, and generalizability of AI models under changing climatic conditions.

Potential topics include:
* AI-based detection and tracking of waves and wave packets
* Rossby-wave breaking, blocking, and circulation regimes
* Wave–mean-flow and wave–wave interactions
* Gravity-wave detection and parameterization
* Data-driven modelling of ocean waves
* Neural operators and reduced-order models
* Physics-informed and physics-constrained AI
* AI-based simulation and prediction of wave evolution
* Waves, teleconnections, and climate variability
* Wave-related extreme and compound events
* Explainability and uncertainty quantification
* Comparisons of AI, numerical, and theoretical models

This session presents key findings from the IPCC Special Report on Climate Change and Cities and invites research on the physical science basis of urban climate change and its implications for policy. Topics include two-way interactions between cities and weather and climate, urban emissions of greenhouse gases and air pollutants, urban climate hazards and risks, and the observations, models and climate services that underpin urban climate information and decision-making. Additional topics include urban adaptation and mitigation solutions, their effectiveness, challenges and prospects.

Solicited talks by report authors will highlight key findings from the assessment, followed by contributed presentations addressing its core physical science topics. We invite contributions on: interactions between cities and the climate system across scales, including urban modification of temperature, precipitation, wind and boundary layer processes; urban climate hazards and risks, including heat, flooding, water scarcity, storms and compound and cascading events under historical and future climates; the knowledge base for urban climate information, namely through observations, urban climate projections, high-resolution and city-scale modelling and climate services that support urban climate information; and how urban climate science can support decision-making across multiple levels of governance. We also welcome contributions on urban adaptation and mitigation solutions, including assessments of their effectiveness, barriers and enabling conditions, and their implications for policy.

We particularly welcome contributions from under-represented regions and works with a focus on rapidly developing and small and medium sized cities.

The Atlantic Meridional Overturning Circulation (AMOC) plays a critical role in regulating Earth’s climate. Therefore, a potential future weakening or even collapse of the AMOC could have major climatic and societal impacts. While some of these changes and impacts have been investigated, their wide-ranging nature has led to scattered knowledge with limited intercomparisons between different lines of evidence. In this session, we bridge multiple disciplines and bring together the latest knowledge on AMOC changes and their impacts.

We welcome all contributions that investigate changes in the AMOC and their Earth System impacts. These can include direct physical impacts, such as atmospheric, oceanic, or cryospheric; biogeochemical as well as marine and terrestrial ecosystem responses; and socioeconomic impacts, such as health, agricultural, and economic repercussions. Contributions can cover any timescale, from paleoclimate and the recent past to future projections, from seasonal and decadal changes to long-term (centennial to millennial), both past and future. In addition, the AMOC can be studied in a range of settings, from internal variability to forced trends or abrupt/tipping behaviour, affecting both mean and extreme variables.

We call for contributions employing a broad range of tools, from Earth System, regional, and simple models to reanalyses and observations/proxies, as well as socioeconomic and impact-related models. Finally, as the Atlantic subpolar gyre (SPG) is an ocean system whose strength, stability, and impact on the climate are strongly connected to the AMOC, we also welcome contributions discussing the impacts of SPG changes on the Earth System.

The growing scientific and policy focus on tipping points in the Earth system reflects their potential for profound physical and socio-economic consequences. If crossed, tipping points could trigger abrupt changes that are effectively irreversible on human timescales. Continued Global Warming is predicted to drive major changes across the North Atlantic, pushing key components of the climate system towards potential critical thresholds and abrupt reorganisation. Yet, the nonlinear nature of these systems means that future change is difficult to observe, model, predict, and govern. Early Warning Systems (EWS) have emerged as a potential method of translating our understanding of abrupt changes in the climate and their impacts into useful and actionable information for relevant stakeholders and decision makers.
Important questions remain around how best to inform and govern the response to North Atlantic tipping and what information can be robustly provided considering deep uncertainty.

To address these challenges, this session aims to bring together interdisciplinary perspectives to inform the co-design of EWS that can support tipping point governance. We welcome contributions from observations, modelling, impact studies, and governance. We have particular interest in modern approaches able to inform governance and response, including under deep uncertainty. Our primary focus is on North Atlantic tipping elements, including the Atlantic Meridional Overturning Circulation, Subpolar Gyre and Greenland Ice Sheet. Studies of other tipping elements and their interactions are also welcome. This session builds on themes being explored by the UK Advanced Research and Invention Agency (ARIA) Forecasting Tipping Points programme.

High-impact climate and weather events typically result from the interaction of multiple climate and weather drivers, as well as vulnerability and exposure, across various spatial and temporal scales. Such compound events often cause more severe socio-economic impacts than single-hazard events, rendering traditional univariate extreme event analyses and risk assessment techniques insufficient. It is, therefore, crucial to develop new methodologies that account for the possible interaction of multiple physical and societal drivers when analyzing high-impact events under present and future conditions. This session aims to address several challenges and topics.
These include: (1) identifying the compounding drivers, including physical drivers (e.g., modes of variability) and/or drivers of vulnerability and exposure, of the most impactful events; (2) Developing methods to better shape the definition and classification of compound events, i.e. legitimate the ‘cut-offs’ in the considered number of hazard types or variables to ultimately disentangle enough information for decision-making; (3) Understanding whether and how often novel compound events, including record-shattering events, will emerge in the future; (4) Explicitly addressing and communicating uncertainties in present-day and future assessments (e.g., via climate storylines/scenarios); (5) Disentangling the contribution of climate change in recently observed events and future projections (attribution); (6) Employing novel Single Model Initial-condition Large Ensemble simulations, which provide hundreds to thousands of years of plausible weather, to better study compound events. (7) Developing novel statistical methods (e.g., machine learning, artificial intelligence, and climate model emulators) for studying compound events; (8) Assessing the weather forecast skill for compound events at different temporal scales; (9) Evaluating the performance of novel statistical methods, climate and impact models, in representing compound events and developing novel methods for constraining/reducing uncertainties (e.g., multivariate bias correction and observational constraints); and (10) engaging with stakeholders to ensure the relevance of the aforementioned analyses.
We invite presentations on all aspects of compound events, including but not limited to the topics and research challenges described above.

The impacts of weather and climate extremes depend on interactions between physical hazards, exposure, and vulnerability. Beyond intensity, the duration, timing, spatial extent, and co-occurrence of extremes can strongly influence their consequences. Understanding these relationships is essential for assessing how climate change alters risks to societies and ecosystems.
This interdisciplinary session connects research on the physical drivers of weather and climate extremes with assessments of their societal and environmental impacts. We particularly welcome studies that investigate how the mechanisms and characteristics of extremes shape their consequences, and how these relationships change under different climatic and socioeconomic conditions.
Contributions are invited on:
- Physical drivers and impact pathways: Atmospheric dynamics, ocean–atmosphere interactions, land–atmosphere coupling, and thermodynamic processes shaping extremes and their consequences. Topics include the roles of persistence, spatial extent, antecedent conditions, and compound or sequential hazards in determining impacts.
- Attribution of extremes and their consequences: Assessments of how anthropogenic climate change and natural variability influence extremes and associated impacts, including approaches that distinguish climatic influences from changes in exposure and vulnerability.
- Prediction and assessment of climate risks: Integration of observations, climate simulations, statistical approaches, and impact models to understand and anticipate risks under present and future conditions. Contributions may address cross-sector and cascading impacts, impact-based forecasting, and the implications of improved physical understanding for preparedness and adaptation.
We welcome observational, modelling, theoretical, and empirical studies addressing heatwaves, droughts, heavy precipitation, floods, fire weather, and compound extremes. Contributions may examine individual links between physical drivers, hazards, and impacts; interdisciplinary studies connecting these elements are particularly encouraged. The session aims to strengthen dialogue between extreme-event science and impact research, advancing understanding of how physical climate processes translate into societal and environmental risks.

Decision-makers are increasingly required to consider extreme weather events as part of evaluating, disclosing, and responding to complex climate risks. Interdisciplinary approaches are required to properly understand these complex risks and to inform the best responses, including mitigation and adaptation approaches. In this session we examine how interdisciplinary teams across academic, industry, and government sectors are working to understand extreme weather events and their changes in a warming climate. Event types can include but are not limited to temperature, precipitation, wind, and compound extremes, and their impacts on people, the built environment, or the natural world. A specific focus will be on collaborative efforts to find and solve shared challenges across disciplines.

Topics of interest include

- physical climate science required for decision making
- early warning systems and their use in real-world scenarios
- risk management in the financial and insurance sectors
- impact-based understanding of extreme weather events
- assessment of varying hazard, exposure, and/or vulnerability
- storyline approaches to risk understanding.

Scientific assessments play a critical role in translating rapidly evolving climate research into actionable knowledge for decision-makers. From the Intergovernmental Panel on Climate Change (IPCC) to national, regional, sectoral, and local assessment efforts, assessments provide structured syntheses of evidence that help governments, communities, businesses, and civil society evaluate climate risks, identify response options, and make informed decisions under uncertainty. Assessments increasingly serve as a bridge between scientific understanding and practical action, supporting planning processes ranging from national adaptation strategies to community resilience and infrastructure investments.

At the same time, data systems have become foundational to assessment practice. The growing availability of observations, model outputs, socioeconomic datasets, and decision-support tools creates new opportunities for assessment, while also raising challenges related to transparency, traceability, accessibility, stewardship, and long-term usability. International data support activities underscore the importance of robust data infrastructure in enabling credible and policy-relevant assessments.

This session invites contributions on the development, application, and future of climate assessment activities across all scales. We welcome presentations from national and international assessment programs, regional and local assessment initiatives, Indigenous and community-led assessment efforts, and organizations that employ assessments to support planning and decision-making. Contributions addressing assessment methodologies, uncertainty communication, stakeholder engagement, knowledge synthesis, data stewardship, data rescue, emerging data products, and assessment-informed policy or practice are especially encouraged. The session will also highlight emerging initiatives, including efforts by scientific societies such as the American Geophysical Union’s Science Assessment Initiative, that seek to strengthen the global assessment ecosystem and accelerate the delivery of decision-relevant climate knowledge.

The interconnections between climate, environment, and human health are becoming increasingly apparent, as climate change poses growing threats to public welfare worldwide. Rising temperatures, more frequent and intense extreme weather events (e.g., heatwaves, floods, droughts), and environmental stressors such as air pollution, degraded ecosystems, or shifting land use patterns have direct and indirect impacts on population health. Climate-related changes also affect the distribution of vector- and waterborne diseases, contribute to the severity of wildfires, and influence mental and physical health outcomes.
Addressing these multifaceted challenges requires close collaboration between disciplines, bringing together climate scientists, epidemiologists, environmental and public health researchers, as well as social scientists. This session provides a platform for presenting recent advances in understanding and quantifying environment- and climate-related health risks through the integration of diverse data sources, including remote sensing, environmental monitoring, climatological measurements, health records, and socio-demographic information.
We welcome contributions that explore methods to assess climate-sensitive exposures (e.g., heat, air pollution, allergens), model health impacts across different temporal and spatial scales, develop risk maps, and evaluate adaptation or mitigation strategies. Approaches using machine learning, statistical modelling, scenario analysis, and other innovative tools are encouraged. Both empirical studies and methodological advances, whether focused on local, regional, or global scales, are invited. The session aims to foster cross-sectoral exchange and support the development of data-driven strategies for climate-resilient and equitable public health.

Extreme heat is a leading weather-related threat to human health, with risk projected to intensify as the climate warms. Robust and transferable estimates of heat-related health risk require an understanding of how socioeconomic and demographic contexts influence who is most vulnerable in addition to the role confounding environmental stressors such as humidity and air pollution play in exacerbating dangerous conditions. This session brings together environmental epidemiologists, data scientists, climate scientists, and human physiologists to advance methods for predicting and forecasting heat-related morbidity and mortality, and to better understand the factors that might modify risk beyond temperature.

We seek machine-learning, statistical, physiological or hybrid approaches that provide new insights into heat-related health risks and/or translate these insights into improved predictive frameworks. Emphasis is placed on novel methodologies improving the validation and transferability of models across regions, climates, and populations. We are particularly interested in approaches that address limited or heterogeneous health data to enable prediction in data-sparse settings, where populations highly vulnerable to extreme heat may be poorly represented. These include physiologically based approaches that derive limits of human heat tolerance from thermoregulation rather than from local health records, and that resolve risk across distinct population cohorts. We also welcome contributions improving predictions under anthropogenic warming, extending model transferability into different climates. Advances in our understanding of compound risks, prediction methods and model transferability can support more effective and equitable Heat-Health Warning Systems.

Human health risks in a changing climate: observed impacts, adaptation and future risks
Climate change is increasingly affecting population health through heat, cold, floods, droughts, wildfires, storms and rapidly changing, or compound, hazards. These events contribute not only to premature mortality but also to cardiorespiratory and infectious diseases, injuries, adverse mental health outcomes and disruption of healthcare and other essential services. An estimated 489,000 heat-related deaths occur globally each year, and more than 181,000 heat-related deaths were recorded across Europe during the summers of 2022–2024. Occupational heat exposure also affects more than 2.4 billion workers globally and is associated with nearly 23 million injuries each year.
These impacts are unevenly distributed. Socioeconomic position, age, sex and gender, ethnicity, pre-existing health conditions, occupation and place intersect to shape exposure, susceptibility and adaptive capacity. Marginalised populations, including older adults, children, people with chronic conditions, outdoor and manual workers, and communities living in low-income or geographically exposed areas, often bear a disproportionate burden. An intersectional and climate-justice perspective is therefore essential for understanding health risks and developing effective and equitable responses.
This session, organised in collaboration with the Swedish Centre for Impacts of Climate Extremes (CLIMES), invites contributions examining the diverse and unequal effects of climate variability, climate change and extreme events on human health. We particularly welcome studies that:
1. quantify observed impacts and future health risks from single, compound and cascading climate hazards;
2. investigate the attribution of health impacts to anthropogenic climate change;
3. identify intersecting socioeconomic, demographic, occupational and spatial vulnerabilities;
4. develop or evaluate health early-warning systems, impact-based forecasting and other climate services;
5. assess the effectiveness, equity and potential unintended consequences of adaptation interventions; and
6. integrate climate, environmental, health and social data to strengthen public health preparedness, resilient health systems and equitable adaptation.
7. storylines methods and their capacity to inform decision makers.
We welcome contributions using epidemiological, modelling, qualitative, participatory and interdisciplinary approaches.

Causal inference provides a powerful framework for unraveling cause-effect relationships, disentangling complex processes within Earth system sciences and quantifying causal effects by combining domain knowledge, machine learning (ML) models, and data from observations and climate model simulations. Learning causal relationships from Earth system data across different timescales is crucial for understanding its complex emergent dynamics and validating climate models, which we count on to simulate future changes. A better understanding of the Earth system helps us design more effective mitigation and adaptation strategies to address open risks with environmental and societal relevance. This session welcomes contributions that highlight innovative approaches, methodologies, and case studies employing causality across Earth sciences. The overall aim is to foster interdisciplinary discussions, encourage collaborations, and promote the development of robust analysis frameworks. We would like to initiate discussions on experiences, challenges, and future development of causal methodologies in Earth system sciences.

The topics of interest for this session include, but are not limited to:
• Causal discovery and inference: algorithms and methods for uncovering causal networks among Earth system processes (e.g., weather, climate, clouds and aerosols, teleconnections, chemical-dynamical interactions);
• Causal effect estimation: statistical techniques to estimate causal effects of anthropogenic or natural forcings in the Earth system;
• Case studies investigating causal pathways and mechanisms driving natural and anthropogenic perturbations such as climate change, land-ocean interactions, teleconnections, extreme events, volcanic eruptions, wildfires, etc.;
• Causal modelling, network analysis, and causal model evaluation: development and application of causal models, network analysis, and graphical models to capture the intricate interconnections and feedbacks within dynamical systems;
• Integration of causal discovery with deep learning (DL) as a promising avenue for improving climate simulations;
• Merging of explainable and causal Artificial Intelligence (AI): discovering governing equations, parameterizations, and relationships based on climate data;
• Challenges and limitations: difficulties associated with the application of causal inference, such as data preprocessing, violations of assumptions, or uncertainty quantification.

Mathematical models offer an imperfect and uncertain guide to future real-world climate impacts. These models (climate models, climate impact and hazard models, and catastrophe models) and their uncertainties influence how risks are understood, anticipated and managed, and therefore also play a direct role in shaping the human experience of climate risk. When informing real world decisions about climate mitigation and adaptation, the uncertainty of projections should be clearly communicated. However, open questions remain about the construction and use of these uncertainties. This includes explorations of how to navigate modelling approaches, the socio-scientific process of informing expectations of real-world outcomes and normative questions of how our uncertain expectations should inform decision making, now and in the future.

This session invites contributions from individuals and teams focused on exploring model uncertainty and decision making relating to future climate impacts, addressing topics such as:

1. Going beyond in-model uncertainty quantification (through e.g., ensemble methods, sensitivity analysis, Bayesian inference, expert judgement, scenario analysis, combining multiple lines of evidence, etc.)
2. Informing expectations of future climate impacts in the real world (e.g., escaping from model land, communicating uncertainty, social perspectives on uncertainty, storylines, etc.)
3. Informing decisions in the context of uncertainty (eg DMDU approaches, examples of co-production, ethical and responsible modelling research, integration of diverse knowledge and decision systems)

In particular, we welcome contributions which consider how modelling approaches situate themselves within a broader social context when informing decisions.

Deep learning is causing a major paradigm shift in weather forecasting from physical modelling to data-driven or hybrid approaches. While the first ML-systems are now used in operational medium-range weather forecasting, the adaptation of deep learning techniques to the subseasonal-to-seasonal (S2S), decadal and multidecadal range is still lagging behind. New approaches are needed for S2S since atmospheric initial conditions are no longer the main driver of predictability. Similarly, deep-learning approaches are emerging for the decadal and multidecadal timescales, when climate forcing becomes a dominant influence on the atmosphere. The scarcity of simulation data and the lack of ground truth pose serious challenges at these time ranges. For this session, we solicit abstracts that present current ideas and results at the intersection of deep learning, S2S-forecasting and climate emulation and simulation.

In particular, we welcome contributions from the following areas.
- Generative modelling for time-scales beyond medium-range
- Calibration and uncertainty estimation for data-driven long-term forecasting
- Coupled generative models of earth system components
- Predictability limits and failure modes in data-driven long-term forecasting
- Out-of distribution emulation and forecasting
- Benchmarking and validation of long-term forecasts with data-driven models
- Identification of drivers of increased predictability and forecast skill for data-driven models (XAI)

Understanding and responding to Europe’s climate risks requires sustained investment in science, from fundamental research and the development of research talent to long-term observations, advanced analytical capabilities and world-class research infrastructures. Climate risks are increasingly interconnected across ecosystems, food systems, human health, infrastructure, and the economy and finance, highlighting the need for robust knowledge, data and research capabilities to understand their interactions and strengthen climate resilience.
Across the Horizon Europe programming period, Pillar I – Excellent Science has contributed to this knowledge base through frontier research supported by the European Research Council (ERC), researcher training, mobility and interdisciplinary collaboration through the Marie Skłodowska-Curie Actions (MSCA), and the development, access and integration of European Research Infrastructures (RIs).
The session welcomes contributions on how frontier science, research talent and research infrastructures provide the knowledge, data, methods and scientific capabilities needed to address these risks areas and interactions among them, including compound, cascading and cross-border risks. Research highlighting risks associated with heat, drought, floods, wildfires and changes affecting marine and terrestrial environments are particularly encouraged.
By bringing together researchers, projects and infrastructures supported across the different components of Horizon Europe Pillar I, the session aims to connect complementary expertise and capabilities and explore how Excellent Science can provide the knowledge, people, observations and research capacity needed to better understand Europe’s interconnected climate risks and strengthen the scientific foundations for a climate-resilient Europe.

Climate projections, reanalyses and Earth observation products are increasingly available, but their spatial resolution, biases, uncertainties and limited connection to sector-specific needs often constrain their direct use in societal risk and impact assessments. At the same time, advances in artificial intelligence, statistical modelling and data integration offer new opportunities to translate climate information into actionable indicators of hazards, exposure, vulnerability and risk.
This session invites inter- and transdisciplinary contributions that connect high-resolution climate information with impacts on human health, agriculture and food systems, water resources and vulnerable populations. Relevant topics include statistical and machine-learning downscaling; integration of climate, environmental, health and socioeconomic data; satellite-derived exposure indicators; climate-sensitive health outcomes; crop and hydrological impact modelling; extreme, compound and cascading risks; vulnerability mapping; uncertainty propagation; early-warning systems; and the co-development of climate services and adaptation strategies.
We particularly welcome studies that evaluate whether climate information is fit for its intended societal application, connect methods and evidence across disciplines, compare alternative modelling or data-integration approaches, and address challenges faced by data-scarce and highly vulnerable regions. Contributions that address the needs of, collaborate with, or generate relevant information for public-health agencies, agricultural and water-management organizations, education systems, humanitarian actors, local communities and policy stakeholders are especially encouraged.

Climate risk and adaptation assessments generally estimate aggregate damages, avoided impacts, or cost-effectiveness. Yet aggregate metrics mask who is exposed, who can adapt, who benefits from adaptation investments, and who bears residual, transferred, or cascading risk. This session asks how conclusions about climate risk and adaptation change when distributional outcomes, adaptive capacity and adaptation limits become explicit components of assessment and decision-making.

We invite quantitative, data-driven and mixed-method contributions representing inequality throughout the assessment chain, from hazard, exposure and vulnerability to impacts, adaptation appraisal and decision-making. Of particular interest are studies moving beyond generic exposure and vulnerability to capture differentiated and dynamic adaptive capacity linked to income, wealth, access to services and infrastructure, housing tenure, mobility, informality and demography.

A central focus is the operationalisation of equity and justice as measurable outcomes. This includes inequality in baseline climate risk (e.g. via revised exposure and vulnerability functions), the distribution of adaptation costs and benefits, inequalities created or exacerbated by adaptation itself, and limits to adaptation. We welcome work that stratifies impacts and avoided losses across population groups, embeds equity metrics in cost-benefit and multi-criteria assessment, examines non-monetised losses, or tests whether conventional welfare and efficiency metrics underrepresent particular populations. Contributions on adaptation-induced inequalities, including displacement, green gentrification, unequal infrastructure protection, and the exclusion of underreported populations, are especially welcome.

The session spans hazards, sectors and scales, including urban systems, critical infrastructure, health, accessibility, macroeconomic impacts, and loss and damage. We particularly encourage assessments of direct, indirect and cascading risks, asking who inherits risk when adaptation protects particular places, infrastructures or groups while shifting impacts elsewhere. We also welcome methodological work on data challenges in distributional risk assessment, including high-resolution socioeconomic data, Earth observation, mobility and geospatial data, citizen science, and alternative sources complementing conventional statistics.

Climate change, biodiversity loss, pollution, natural hazards and other forms of environmental change present challenges not only for understanding Earth systems, but also for how environmental knowledge is produced, interpreted and shared. Across the Earth and environmental sciences, researchers are increasingly collaborating with artists and creative practitioners to develop new ways of engaging with environmental processes, data, places and communities.

Art-science collaboration can extend beyond communicating completed scientific findings. Creative practices may contribute to observation and sensing, working with environmental data, visualisation and representation, field-based inquiry, interpretation of uncertainty and change, participatory research, and engagement with place-based and experiential knowledge. At the same time, a growing range of projects provides practical experience of how such collaborations work in different research and environmental contexts.

This session brings together empirical case studies, methodological contributions and critical reflections on art-science collaboration in Earth and environmental research. We welcome contributions from across the geosciences and environmental sciences, together with collaborating artists, creative practitioners, and humanities and social science researchers, particularly addressing:

(1) art-science collaborations concerning climate, water, biodiversity and ecosystems, pollution, landscapes, natural hazards and other Earth and environmental processes;

(2) creative and arts-based approaches to environmental observation, fieldwork, sensing, mapping, visualisation, sonification, environmental data, modelling and interpretation;

(3) methods combining scientific observations and evidence with local, Indigenous, experiential or other forms of knowledge;

(4) participatory and place-based approaches involving scientists, artists, communities and other partners;

(5) methodological and comparative studies examining how creative practices can be integrated into different stages of Earth and environmental research;

(6) different models of collaboration, including artist residencies, field-based collaborations, museums and cultural institutions, research programmes, laboratories and community partnerships.

Artificial intelligence (AI) is currently transforming data analysis and modelling of the Earth system. While statistical and data-driven models have been used for a long time, recent advances now allow for encoding non-linear, spatio-temporal relationships robustly without sacrificing interpretability. This has the potential to accelerate climate science by providing new physics-based modelling approaches; improving our understanding of the underlying processes; reducing and better quantifying climate signals, variability, and uncertainty; and even making predictions directly from observations across different spatio-temporal scales. We encourage participants to discuss the limitations of AI methods (including their often substantial training-data requirements, susceptibility to data leakage, poor generalisation, and physical inconsistencies) to help ensure that these methods are applied where they are fit for purpose and add value.


This session aims to provide a venue to present the latest progress in the use of AI applied to all aspects of climate science and we welcome abstracts focussed on, but not limited to:
- Causal discovery and inference: causal impact assessment, interventions, counterfactual analysis
- Learning processes, equations, and feature representations across models and observations
- Hybrid physics-AI and differentiable models, climate model emulators, data-model integration
- AI-based detection and attribution approaches, including for extreme events
- Probabilistic modelling and uncertainty quantification
- AI-based climate downscaling, including super-resolution and bias-correction
- Climate model analysis in the AI era, including benchmarking and stress-testing
- Explainable AI applications to climate data science and climate modelling
- Distributional robustness and transfer learning, including out-of-distribution generalisation tasks
- AI reasoning and agent-based workflows for analysing climate data, developing, improving, testing, and porting scientific code, and climate information

Climate change and environmental degradation constitute a growing threat to the stability of societal and economical systems. The observed and anticipated increase in the frequency and intensity of extreme weather events under future emission scenarios, combined with the projected long-term shifts in climate patterns are already leading to significant economic damages on a local to global scale with repercussions in insurance and finance sectors.

To mitigate systemic risks from extreme weather events an improved model representation of extreme weather and climate hazards at impact relevant scales and a better understanding of their often compounding ways they cause impacts is urgently needed. In recognition of this challenge climate risk assessments for the financial and insurance sectors have experienced amplified attention in both the academic and private spheres.

This session aims at providing a platform for actors from academia and the private sector to exchange information on strategies for assessing climate risk, and is organised under three main pillars:

-Physical Climate Risks: Trends, Processes and Modelling
-Identifying and Managing Climate Risks
-Quantifying Damages and Impacts from Climate Risks

We encourage submissions on a wide range of topics including innovative climate risk modeling and model evaluation, damage functions, integrated assessment modelling, bias adjustment and downscaling methods, climate emulators, climate hazard indicators and their projections for specific sectors (e.g. food, energy, insurance, real estate, supply chains), impact data collection and categorization.

This session aims to showcase recent research progress and augment existing knowledge in polar meteorology and climate, and the atmosphere-land ice-sea ice coupling in both Hemispheres. It will provide a setting to foster discussion and help identify gaps, tools, and studies needed to address these open questions. It is also an opportunity to convey newly acquired knowledge to the community.
We invite contributions on all observational and numerical modelling aspects of Arctic and Antarctic meteorology and climatology that address atmospheric interactions with the cryosphere. This may include but is not limited to studies on past, present and future of:
- Atmospheric processes that influence sea ice (snow on sea ice, sea ice melt, polynya formation and sea ice production and transport) and associated feedbacks,
- Surface energy balance above the snow/ice surface.
- The variability of the polar large-scale atmospheric circulation (such as polar jets, the circumpolar trough and storm tracks) and impact on the cryosphere (sea ice and land ice),
- Atmosphere-cryosphere interactions triggered by synoptic and meso-scale weather phenomena such as cold air outbreaks, katabatic winds, extratropical cyclones, polar cyclones, atmospheric rivers, Foehn winds, and heatwaves,
- Role of clouds in polar climate and impact on the land ice and sea ice through interactions with radiation,
- High-latitude dust and pollution, deposition on snow and ice, and related impacts.
- Teleconnections and climate indices and their role in land ice/sea ice variability.
Presentations including new observational (ground- and satellite-based) and modelling methodologies specific to polar regions are encouraged. Contributions related to results from recent field campaigns in Greenland, the Arctic, and in the Southern Ocean/Antarctica are most welcome.

Disturbances, such as extreme weather events, play a key role in shaping ecosystems. Under climate change, extreme weather hazards undergo changes in frequency, intensity and seasonality. While ecosystem-based adaptation and nature-based solutions are gaining traction, it is crucial to investigate the diverse interactions between extreme weather risk, ecosystems, and their services.

This session seeks to highlight research on the nexus of weather and climate related extreme events and ecosystems. We encourage submissions on: 1) investigations into the key attributes and patterns of extreme weather events which affect ecosystem composition, structure and functioning, 2) studies on how ecosystems respond to and recover from extreme weather events across past, present, and future climates, 3) Implications of extreme weather impacts on ecosystems for biodiversity and ecosystem service provision. We welcome a diverse array of contributions, including theoretical analyses, modelling approaches, field studies, experimental designs, and remote sensing analysis.

Key topics include:
- Identification of extreme weather risk hotspots, and subsequent ecosystem responses (terrestrial, coastal, or marine) in past, present and future climates

- Role of extreme weather in shaping ecosystem composition, biodiversity, structure and functioning, and its impact on ecosystems service provisions across temporal and spatial scales
Interactions of natural hazard, anthropogenic and biogenic disturbances with ecosystems (including compounding events)

- Ecosystem vulnerability, resilience and recovery dynamics under weather extremes, including regime shifts / tipping points in ecosystems
Impact and efficacy of nature-based solutions under extreme conditions, risk of maladaptation or disservices

As a result of a warming Arctic, there is an increased frequency and intensity of extreme weather events such as marine and terrestrial heatwaves, rain-on-snow events, and intense windstorms. Such extreme weather events can trigger cascading, multidisciplinary impacts across the Arctic system. This session bridges the gap between physical mechanisms and on-the-ground realities by investigating the physical drivers of extreme events within oceanic, atmospheric, and cryospheric systems, alongside their wide spectrum of impacts. These impacts range from rapid physical shifts, such as enhanced meltwater runoff, sudden sea-ice loss, and snowpack depletion, to societal and ecological disruptions, including infrastructure damage, traffic disruptions, and threats to reindeer herding and Indigenous livelihoods.
We welcome submissions based on modeling, observations, or interdisciplinary frameworks, such as those incorporating local and Indigenous knowledge systems, that investigate extreme weather phenomena, their physical drivers, and their direct and cascading impacts on the Arctic environment, ecosystems, and local communities.

Several subsystems of the Earth have been suggested to possibly react abruptly at critical levels of anthropogenic forcing. Examples of such potential Tipping Elements include the Atlantic Meridional Overturning Circulation, the polar ice sheets, tropical and boreal forests, as well as the tropical monsoon systems. Interactions between the different Tipping Elements may either have stabilizing or destabilizing effects on the other subsystems, potentially leading to cascades of abrupt transitions. The critical forcing levels at which abrupt transitions occur have recently been associated with Tipping Points.

It is paramount to determine the critical forcing levels (and the associated uncertainties) beyond which the systems in question will abruptly change their state, with potentially devastating climatic, ecological, and societal impacts. For this purpose, we need to substantially enhance our understanding of the dynamics of the Tipping Elements and their interactions, on the basis of paleoclimatic evidence, present-day observations, and models spanning the entire hierarchy of complexity. Moreover, to be able to mitigate - or prepare for - potential future transitions, early warning signals have to be identified and monitored in both observations and models.

This multidisciplinary session invites contributions that address Tipping Points in the Earth system from the different perspectives of all relevant disciplines, including

- the mathematical theory of tipping points
- methods to anticipate critical transitions from data
- tipping points in climate models across the hierarchy, including comprehensive Earth system models
- climatic, ecological and socioeconomic impacts of tipping events
- decision theory in the presence of uncertain tipping point estimates and uncertain impacts

The Mediterranean is a climate change hotspot where warming and changes in the hydrological cycle are reshaping high-impact weather and climate extremes. Heatwaves, droughts, extreme precipitation and floods, wildfires, marine extremes, and compound and cascading events interact with exposure and vulnerability, generating complex environmental and societal risks.
Addressing these challenges requires connecting advances in observations, physical processes, modelling, prediction and climate projections with impact and risk assessment. Understanding exposure, vulnerability and adaptive capacity is equally essential for translating climate knowledge into effective early warning, decision-support and adaptation.
This session brings together physical and social sciences, technological developments and stakeholder perspectives to advance integrated understanding of Mediterranean extremes, their impacts and pathways to resilience.
We welcome contributions on:
• Physical processes, observations, modelling, attribution, prediction and projections of Mediterranean weather and climate extremes.
• Single, compound and cascading hazards and their interactions across spatial and temporal scales.
• Impacts, exposure, vulnerability and risk across health, water, agriculture, energy, ecosystems, infrastructure and urban areas.
• Methods integrating physical, environmental, social and economic dimensions of climate risk.
• Climate services, impact-based forecasting, early-warning systems and decision-support tools, including Earth observation, AI and digital twins.
• Adaptation and risk-reduction strategies, including nature-based solutions, and evidence of their effectiveness, limitations and trade-offs.
• Co-production of knowledge, stakeholder and citizen engagement, communication and capacity building.
We particularly encourage contributions bridging disciplines, sectors and Mediterranean regions, including approaches addressing inequalities in data, vulnerability and adaptive capacity.
Supported by the FutureMed COST Action (CA22162), this session welcomes contributions from within and beyond the network. It aims to strengthen transdisciplinary collaboration and connect climate science with societal needs, adaptation and resilience.

Global initiatives such as REDD+, afforestation, reforestation, and restoration place forests at the centre of climate action. Yet these measures are highly context dependent and can create synergies and trade-offs across carbon sequestration, water availability, biodiversity, ecosystem functions, and human well-being.
Afforestation can enhance carbon sequestration, reduce erosion, regulate soil moisture, and support atmospheric moisture recycling, while in some contexts reducing streamflow, altering surface albedo, or changing groundwater recharge. Forest change can also affect evapotranspiration, precipitation recycling, and downwind water availability, highlighting the importance of green water processes and governance across spatial scales, administrative boundaries, and sectors.
The long-term effectiveness of forest-based climate action also depends on the capacity of forests as social–ecological systems to cope with, adapt to, and transform in response to disturbances and changing conditions. Compound and cascading disturbances, including drought, wildfire, heat, pests, and land-use pressures, can interact with institutional constraints and competing societal demands to undermine resilience.

This session aims to advance understanding of how forests can contribute to climate mitigation and adaptation while maintaining or strengthening social–ecological resilience under changing hydroclimatic and societal conditions. We welcome interdisciplinary studies, modelling approaches, case studies, governance analyses, and decision-support tools addressing trade-offs, compound and cascading risks, and green water governance, including:

· Social–ecological resilience, including adaptation, learning, participation, and cross-sectoral and cross-scale governance of the forest-water nexus
· Forest–water–climate interactions, including soil moisture, evapotranspiration, moisture recycling, and blue–green water linkages
· Co-benefits and trade-offs of forest-based mitigation for carbon sequestration, water availability, biodiversity, ecosystem functions, and society
· Forest disturbances, compound and cascading impacts, institutional capacity, and adaptation
· New indicators, scenarios, and decision-support approaches for resilient forest management
. Forest–green and blue water governance, including monitoring, transboundary dependencies, cross-scale coordination, and cross-sectoral decision-making.

Extreme weather and climate events can disrupt many aspects of human societies, including physical and mental health, livelihoods, food and water service, infrastructure, and human mobility. Yet these impacts are still often assessed one hazard at a time, even though severe consequences frequently arise from interacting hazards. Compound events may involve concurrent, sequential, spatially connected, or preconditioned hazards, and their impacts can be nonlinear, cascading, and greater than the sum of impacts associated with individual hazards.

This session focuses on the impacts of compound weather and climate events on human societies. We welcome research on diverse types of compound events, including, but not limited to, heat and drought; drought followed by wildfire; extreme heat combined with wildfire; tropical cyclones accompanied or followed by extreme rainfall, flooding, and storm surge; and rapid transitions between opposing climate extremes. Contributions may examine mortality and morbidity, mental health, migration and displacement, food and water insecurity, livelihood losses and financial security, health-system burdens, infrastructure failure, conflict, and structural inequality. We particularly encourage work addressing unequal exposure, vulnerability, adaptive capacity, resilience, and recovery.

This session welcomes empirical, modelling, qualitative, participatory, and mixed-methods studies at any spatial scale. Relevant topics include definitions and metrics; detection and attribution; historical trends and future projections; evidence linking compound events to human outcomes; causal inference and uncertainty assessment; integration of climate data with administrative records, surveys, remote sensing, and community knowledge; and applications to early warning, anticipatory action, adaptation, preparedness, risk communication, and equitable risk reduction.

By bringing together climate and Earth-system science, epidemiology, public health, geography, economics, sociology, demography, engineering, disaster-risk research, and public policy and practice, the session aims to advance knowledge of how compound events are anticipated, measured, experienced, and managed.

Cities worldwide are increasingly exposed to compound extreme weather and climate events—hazard combinations that occur concurrently, in close sequence, or across connected regions, such as heatwave–drought co-occurrence, storm surge coinciding with pluvial flooding, or extreme heat following tropical cyclones. Because their drivers interact and their impacts cascade through critical infrastructure, ecosystems, and vulnerable populations, compound events often inflict damages far exceeding the sum of individual hazards, challenging conventional single-hazard approaches to urban risk management.

This session aims to bring together researchers across climate science, hydrology, urban studies, engineering, and disaster risk reduction to advance the understanding, prediction, and governance of compound extremes in urban environments. We welcome contributions addressing, but not limited to:

1. Physical drivers and dynamics of compound events (concurrent, sequential, and spatially compounding) in a changing climate;

2. Detection, attribution, and projection of compound extremes using observations, reanalyses, climate model ensembles, and event storylines;

3. Novel analytical and modeling approaches, including statistical dependence modeling, machine learning, and AI-based methods;

4. Impacts of compound events on urban systems, including infrastructure networks, public health, energy and water security, and cascading or compounding risks;

5. Assessment and enhancement of urban resilience, including risk assessment frameworks, early warning systems, adaptation planning, nature-based solutions, and governance strategies;

6. Case studies from diverse urban contexts—including the Global South—and co-production approaches engaging stakeholders and practitioners.

We particularly encourage interdisciplinary submissions, contributions from early-career scientists, and studies that bridge the gap between hazard science and actionable resilience planning for cities.

Agricultural production depends on climatic conditions such as precipitation and temperature, as well as their interactions with each other and with non-climatic factors. Disentangling these effects and understanding which climatic conditions affect agriculture, how strongly, and how future production could change under global warming is crucial for safeguarding future food production, supporting timely climate adaptation through management practices, and improving impact models and assessments. We invite submissions across a broad spectrum of approaches for assessment of climate change impacts on agriculture. Submissions may include, but are not limited to, the following themes:
1- Assessment of climatic conditions, including extremes (droughts, heatwaves) and averages, and their effect on agricultural production, variability and anomalies.
2- Assessment of adaptation practices, including but not limited to crop diversification, irrigation, and fertilization in crop production.
3- Projections of future agricultural production using multi-model climate simulations as well as single-model initial conditions and assessment of time of emergence.
4- Spatial and temporal variability and the role of teleconnections in climate risks to agriculture.
5- Supply chains, financial losses, and the role of insurance in alleviating financial losses in the agriculture sector.
6- Methodological advancements and intercomparison of process-based, statistical, and AI-based models for agricultural production and climate impact assessments.

Downscaling aims to process and refine global climate model output to provide information at spatial and temporal scales suitable for impact studies. In response to the current challenges posed by climate change and variability, downscaling techniques continue to play an important role in the development of new services and products. While the refinement of downscaling techniques proceeds at an unprecedented pace, users of climate information are facing the novel challenge of how to select amongst the choice of available datasets or how to assess their credibility with respect to a particular application. In this context, model evaluation and verification is growing in relevance and advances in the field will likely require close collaboration between various disciplines.

Recent developments, including the integration of AI and machine learning applications, the emergence of kilometre-scale simulations, and the widespread availability of open-source downscaling products, add new dimensions to this challenge. These advances raise important questions about the ‘added value’ of downscaling, especially in light of the cascade of uncertainty and the need for robust evaluation frameworks.

In our session, we aim to bring together scientists from the various geoscientific disciplines interrelated through downscaling: atmospheric modeling, climate change impact modeling, machine learning and verification research. We also invite philosophers of climate science to stimulate our discussion about the novel challenges that arise from evaluating complex models and modelling chains in the face of the increasingly heterogeneous needs of the growing user communities.

Contributions to this session may address, but are not limited to:
- newly available downscaling products,
- applications relying on downscaled data and impact assessments,
- downscaling method development and machine learning,
- bias correction and statistical postprocessing,
- challenges in the data management of kilometer-scale simulations,
- verification, uncertainty quantification and the added value of downscaling,
- downscaling approaches in light of computational epistemology.

Measuring progress in climate adaptation is essential to track resilience-building, guide investments, and inform policy. Yet, adaptation measurement remains fragmented and contested: while some frameworks focus on process indicators (e.g., planning, governance, capacity), others emphasize outputs (e.g., implemented measures), or outcomes and impacts (e.g., reduced vulnerability, enhanced resilience). Each approach has strengths and limitations, and their combination is critical to capturing the complexity of adaptation and informing adaptation action.

This session invites contributions that advance understanding and practice in measuring and evaluating progress in climate adaptation across scales, hazards and sectors. We welcome research that develops or applies frameworks, methods, and tools for adaptation monitoring, evaluation, and learning (MEL), as well as critical reflections on their usability, comparability, and policy relevance.

Topics of interest include (but are not limited to):
- Development and application of process, output, outcome, and impact indicators for adaptation, with a focus on outcomes and impacts.
- Approaches to integrating multiple indicator types for holistic assessment.
- Use of novel data sources and methods (Earth observation, citizen science, AI, participatory surveys) for MEL.
- Cross-scale measurement: from local initiatives to national reporting and global stocktake.
- Addressing uncertainty, attribution, and time horizons in adaptation measurement within the MEL process.
- Considerations of equity, justice, and governance in defining and applying adaptation metrics.
- Case studies showcasing practical experiences of tracking adaptation progress across geographies and contexts.

By bringing together conceptual, methodological, and applied perspectives, this session seeks to identify pathways towards robust, inclusive, and actionable adaptation metrics that can guide decision-making and enhance accountability under the EU Mission on Adaptation, the Paris Agreement, and other global frameworks.

Mountain regions are changing rapidly as climate warming, cryosphere loss, hydrological and ecosystem change, and socio-economic transformations interact. Looking toward 2050 provides a shared near-term horizon for asking how mountain social-ecological systems may evolve, which risks and opportunities may emerge, and how knowledge about possible futures can inform decisions today. The session addresses key and emerging themes in mountain research while remaining open to contributions from across the wider mountain research community.
A cross-cutting focus is on interactions between environmental and socio-economic change in mountain regions, including their implications for hazards, vulnerability, exposure and risk. We welcome conceptual and empirical research using observations, monitoring networks, remote sensing, models, scenarios, storylines and comparative studies to understand current trajectories and explore possible mountain futures. Contributions may address physical, ecological and societal dimensions of mountain change, from climate, cryosphere, water, ecosystems and hazards to land use, economies and governance, including mountain-lowland linkages.
We particularly encourage work that connects long-term observations with future scenarios and decision-making, investigates interactions and feedbacks between biophysical and human systems, or co-produces knowledge with communities, practitioners and decision-makers. Contributions that advance integrated approaches to monitoring, risk and adaptation, governance and the translation of knowledge into action are particularly welcome. By bringing these strands together, the session aims to clarify what different mountain futures could mean by 2050 and how choices made today may shape risks, resilience and sustainable development.
This session is endorsed and supported by the Mountain Research Initiative and the Institute for Interdisciplinary Mountain Research of the Austrian Academy of Sciences.

Social-science and humanities (SSH) research is crucial for informing ambitious, effective, just and societally acceptable climate action. This session highlights how SSH insights on social metabolism, labor transitions, perceptions and societal readiness, institutional dynamics, justice, needs and capabilities, and power relations can enrich and reshape diverse modeling approaches. We aim to provide a platform for interdisciplinary work that broadens what models and scenarios can represent, clarifies their limits, and strengthens connections across methods and disciplines.
We welcome contributions that:
integrate SSH concepts and methods into integrated assessment models (IAMs), energy–economy–environment models, energy-system models, or other analytical frameworks;
use empirical, qualitative or participatory approaches to inform model assumptions, structures, constraints and scenario design;
engage with normative dimensions such as fairness, feasibility, responsibility and societal acceptance, including in emerging areas such as carbon dioxide removal and other climate-response strategies;
connect justice questions to marginalized or disadvantaged communities, particularly in the Global South;
examine how governance, institutions, finance, law, power relations, and material and human needs shape transition pathways;
investigate social outcomes of modeled scenarios, including distributional, labor, health and wellbeing implications; and
explore how new data, methods and technologies can address, or reproduce, gaps in whose experiences and priorities are represented in climate analysis.
We particularly encourage work engaging with distributive, procedural, recognitional, transitional and other dimensions of justice, as well as studies that provide meaningful two-way connections between social science and modeling communities. Contributions need not themselves be modeling studies where they provide empirical, conceptual or normative insights that can inform how climate and energy scenarios are developed, evaluated or interpreted.
By convening these perspectives, the session seeks to advance interdisciplinary approaches that make climate and energy modeling more relevant, inclusive and transparent about both what it represents and what lies beyond its scope.

Scientists and researchers are more and more finding new ways to present their work to a broad audience. This includes presenting data through a diverse array of visual forms, from conventional graphs and maps to interactive web applications, physical models, art installations, and other forms of tangible media. These approaches to data visualisation can make complex datasets and systems more accessible and approachable to a wider audience. Oftentimes they can reveal patterns that are difficult to see in raw data and they provide new ways of communicating scientific results to both specialised and general audiences. At the same time, the choice of which specific visual medium is used influences what can be shown, what is emphasised, and how the data are interpreted.

This session invites contributions exploring the use of physical and digital media to visualise scientific data. We welcome work that showcases data visualisation in unique ways including, but not limited to; maps, interactive visualisations, virtual and augmented environments, physical or tactile representations, and artistic approaches. Contributions may focus on the development of new techniques, the application of existing approaches to scientific problems or data, or reflections on how different visual forms affect the interpretation and communication of scientific data and research.
We particularly encourage contributions that consider the relationship between the data, the medium through which they are presented, and the people using or experiencing the visualisation. Examples from all scientific disciplines supported by EGU are welcome, as are approaches that cross the boundaries between scientific visualisation, design, art, and public engagement. And we particularly encourage contributions from underrepresented groups and countries.

Despite unprecedented scientific understanding of the environmental system, translating environmental science knowledge into sustained societal action remains a major challenge. More than a decade after Stoknes (2014) described this as a psychological paradox, ecological crises are intensifying while environmental protection continues to compete with other societal priorities. Science communication research has shown that communicating more scientific facts, more clearly or more frequently, is not sufficient on its own.
Environmental science communication is consequently undergoing experimentation and transformation. Alongside established approaches, researchers are exploring storytelling, emotions, humor, aesthetics, identities, popular culture, participatory practices and novel visual formats. Digital platforms have accelerated these developments, creating spaces where scientific knowledge intersects with internet culture, entertainment, influencer practices and vernacular communication. Innovative approaches are also emerging beyond social media, including through museums, art-science initiatives, journalism and innovative institutional communication.
These developments raise questions about how environmental science communication is changing. How are communicators adapting to changing media environments and audiences? Which actors and practices are driving innovation? How are emotions, identities, aesthetics, humour and storytelling incorporated into environmental communication, and how do these approaches interact with traditional information-centred models? How are scientific institutions and researchers responding?
This session invites contributions studying and engaging with emerging forms of environmental science communication. We particularly welcome interdisciplinary research connecting environmental science with communication studies, social sciences, humanities, arts and design.

Topics may include:
• novel approaches to communicating environmental science;
• emotions, identities, aesthetics, storytelling and humor;
• visual, creative and artistic approaches;
• social media, short-form video and influencers;
• popular culture, memes and entertainment;
• participatory approaches;
• communication targeting younger audiences;
• institutional responses to changing communication environments;
• critical perspectives on the ethics and power relations of environmental communication;

Art makes use of materials of geological origin: stones, pigments, mortars, metals, etc.; geology, in turn, has been depicted in various ways in art throughout art history; geosciences present their observations and discoveries in a visual form that can be regarded as an artistic expression. The entanglements of art and natural sciences are multiple, bidirectional, and have given rise to hybrid fields of research: Technical Art History, considering the materiality of artworks; archaeometry exploiting the intrinsic information contained in the artistic matter to trace back its origin and fates; Eco-critical art history, which draws on the environmental dimension of works of art – such as historical landscape painting – to critically explore the history of the environment and its changes.
In this session, we aim for a rich and diverse transdisciplinary dialogue of colleagues with multiple backgrounds and thus welcome a broad range of contributions in fields such as:
- Geosciences in artistic representation, e.g. as sources to study environmental changes, as indicators of the evolution of symbolic and scientific perception of geological objects and phenomena, natural hazards, etc.
- Artwork materials and their transformations over time as physical/chemical repositories or archives of environmental history, including air, water and soil pollution (e.g. stone degradation in urban areas)
- Geomaterials (stone, pigments, metals, precious stones) used in works of art (sculptures, metal objects, paintings, jewellery, etc.) and their intrinsic properties as an indicator of provenance or as a criterion of authenticity; the conservation issues specific to these materials.
- Artistic production and networks in geological landscapes with indigenous/local artistic use of geomaterials, artist migration to geo-resource-rich regions, transport of geomaterials to artistic centres, artistic geomaterials as indicators of power and prestige…