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 analysing high-impact events under present and future conditions. Despite the considerable attention from the scientific community and stakeholders in recent years, several challenges and topics must still be addressed comprehensively.

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 for defining compound event boundaries, i.e. legitimate the ‘cut-offs’ in the considered number of hazard types 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; (6) Employing novel Single Model Initial-condition Large Ensemble simulations from climate models, which provide hundreds to thousands of years of weather, to better study compound events. (7) Developing novel statistical methods (e.g., machine learning, artificial intelligence, and climate model emulators) for 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 reducing uncertainties (e.g., multivariate bias correction and emergent 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.

Earth System Models (ESMs), climate forcing, and Earth system reconstructions are crucial for understanding climate dynamics. However, disparities in responses to forcing agents, system coupling - particularly across CMIP - as well as the integration of reconstructions, present significant challenges. This session combines insights from deep-time Earth system reconstructions with cutting-edge climate modeling to enhance our understanding of past, present, and future climate change. We highlight the role of anthropogenic and natural forcings, the importance of addressing model uncertainties in CMIP and beyond, opportunities to develop next-generation digital twins of our planet, and present CMIP7 forcings. This session features contributions that span the following themes:

1. Earth System Reconstructions and Digital Twins
- Integrating paleogeographic data and advanced modeling (e.g., machine learning) to reveal past environmental changes and major Earth system transitions.
- Building digital twins of the planet by fusing diverse datasets and numerical models, emphasizing open, community-driven approaches.

2. Anthropogenic and Natural Forcing for CMIP6, CMIP7, and beyond
- Developing and evaluating historical and future time series of climate drivers (e.g., greenhouse gases, aerosols, land-use changes).
- Investigating how changes in forcing propagate through the climate system, using both observational data and idealized or multi-model experiments (CMIP6, CMIP7, etc.).

3. Model Disparities and Uncertainty
- Identifying the causes of divergent outcomes within CMIP ensembles, including internal variability, parameterization, external forcings, and ESM architectures.
- Employing reduced-complexity models and emulators to capture underexplored regions of uncertainty and guide more robust climate projections.

4. Critical Model Development and Impact Research
- Refining ESMs to reduce uncertainties and improve model performance, with emphasis on interdisciplinary approaches.
- Addressing regional-scale challenges in using CMIP outputs for impact studies, ensuring that policymakers and non-experts can effectively interpret climate projections.

We encourage submissions that bridge these topics, highlight open research and interdisciplinary collaboration, and showcase the work of early career researchers.

As climate change causes impacts from weather extremes to increase around the world, decision makers in government and industry are increasingly required to address changes to climate hazards when considering, disclosing, and acting to mitigate risks. Given that risk is the nexus of hazard, vulnerability, and exposure, a complete understanding of risk requires an interdisciplinary approach with input from experts in changes to all three of these pillars. In this session we address specifically those risks related to extreme weather events, including temperature, precipitation, and wind extremes, with a focus on interdisciplinary approaches that bridge the gap between the physical sciences and decision makers. We invite contributions from interdisciplinary teams working to address these challenges, as well as from those working in single disciplines but seeking to make interdisciplinary connections. Topics of interest include storyline approaches in which societal challenges are considered alongside physical climate risks; addressing knowledge gaps in physical hazard understanding when providing information to decision makers; issues related to the financial and insurance sectors’ responses to extreme weather events; impact-based forecasting as a tool for risk understanding; and studies of early-warning systems and associated decision making.

The interconnection between climate, environment, and health is evident, with climate change posing significant threats to human welfare. As global temperature rise, extreme weather events such as heatwaves, floods, hurricanes, and droughts, directly and indirectly impact public health, alongside environmental exposures like air pollution. Climate and land use changes can influence the spread of vector-borne diseases such as malaria and increase the risk of waterborne illnesses. Additionally, climate change may result in severe wildfires and episodes of air pollution.
Addressing these complex challenges requires fostering interdisciplinary collaboration among climate researchers, epidemiologists, public health researchers, and social scientists, which is the primary focus of this session. The goal is to create a platform for presenting the latest innovations in using remote sensing and other large datasets to characterize exposures relevant to human health, especially in data-limited regions. The session encompasses various topics, including satellite data applications in human health, planetary epidemiology, risk mapping of infectious diseases, exposure mapping of heat and air pollution to quantify their impacts on human health, health co-benefits of mitigation actions, and the use of machine learning and AI for climate and health applications. The session emphasizes the examination of historical exposure-health outcome relationships, forecasts for the near future, and changes under progressive climate change.

Machine learning (ML) 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 in machine learning 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. The limitations of machine learning methods need to also be considered, such as requiring, in general, rather large training datasets, data leakage, and/or poor generalisation abilities, so that 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 ML 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 (causal) process, equations, and feature representations in observations or across models and observations
- Hybrid models (physically informed ML, emulation, data-model integration)
- Novel detection and attribution approaches, including for extreme events
- Probabilistic modelling and uncertainty quantification
- Super-resolution for climate downscaling
- Explainable AI applications to climate data science and climate modelling
- Distributional robustness, transfer learning and/or out-of-distribution generalisation tasks in climate science

Machine learning (ML) is being used throughout the geophysical sciences with a wide variety of applications. Advances in big data, deep learning, and other areas of artificial intelligence (AI) have opened up a number of new approaches to traditional problems.

Many fields (climate, ocean, NWP, space weather etc.) make use of large numerical models and are now seeking to enhance these by combining them with scientific ML/AI techniques. Examples include ML emulation of computationally intensive processes, data-driven parameterisations for sub-grid processes, ML assisted calibration and uncertainty quantification of parameters, amongst other applications.

Doing this brings a number of unique challenges, however, including but not limited to:
- enforcing physical compatibility and conservation laws, and incorporating physical intuition,
- ensuring numerical stability,
- coupling of numerical models to ML frameworks and language interoperation,
- handling computer architectures and data transfer,
- adaptation/generalisation to different models/resolutions/climatologies,
- explaining, understanding, and evaluating model performance and biases.
- quantifying uncertainties and their sources
- tuning of physical or ML parameters after coupling to numerical models (derivative-free optimisation, Bayesian optimisation, ensemble Kalman methods, etc.)

Addressing these requires knowledge of several areas and builds on advances already made in domain science, numerical simulation, machine learning, high performance computing, data assimilation etc.

We solicit talks that address any topics relating to the above. Anyone working to combine machine learning techniques with numerical modelling is encouraged to participate in this session.

Climate change and environmental degradation constitute a growing threat to the stability of societal and economical systems. The observed and anticipated escalation in the frequency and intensity of extreme weather events under future emission scenarios, combined with the projected long-term shifts in climate patterns and consequential impacts on biodiversity, have the potential to significantly affect specific sectors such as insurance and finance leading to significant economic damages on a local to global scale.

In recognition of this challenge climate risk assessments have experienced amplified attention in both the academic and private spheres, leading to initiatives such as the ‘Network for Greening the Financial Sector’ (NGFS) and the ‘Task Force on Climate-Related Financial Disclosure’ (TCFD) and a growth in climate risk services aiming at setting standards and frameworks as well as the provision of comprehensive climate impact information for the private sector and financial institutions.

The need for more adequate risk assessment poses new academic challenges: the accurate representing extreme events and their compounding and cascading effects on high spatial resolution and the integration of non-linearities associated with tipping elements in the climate system to avoid an underestimation of physical climate risks.

Therefore, providing a platform to foster interactions between scientists, economists and financial experts is urgently needed. With the goal of facilitating such dialogue, this session aims at providing a platform for actors from academia and the private sector to exchange information on strategies for assessing climate risk.

The session 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:
Innovative climate risk modeling for
-Chronic and Acute Climate Risks
-Compound Events and Cascading Impacts
-Model Evaluation of Extreme weather events
AI and Machine learning frameworks for
-Bias adjustment Methods
-Downscaling Methods
-Fast climate models and emulators
Climate hazard indicators and their projections for specific sectors:
-Food, Energy, Insurance, Real Estate
-Supply chains
Impact data collection and empirical damage assessments
Global and local damage functions
Climate – Nature nexus

Over the past 50 years, climate extremes have caused more than 2 million deaths and an estimated $3.64 trillion in economic losses worldwide. Beyond these direct impacts, the effects on population health have become an urgent concern. Research has highlighted far-reaching consequences, particularly in terms of excess mortality and morbidity associated with cardiovascular and respiratory diseases, associated with climate extremes. The burden of these health impacts is not evenly distributed. Socioeconomic, demographic, and geographical factors heavily influence vulnerability, leading to significant disparities in health outcomes across different populations. For example, marginalized and disadvantaged groups, including the elderly, children, individuals with pre-existing health conditions, and residents of low-income or geographically vulnerable regions bear a disproportionate share of the health burden. Intersectionality plays a key role in this disparity; including overlapping social factors such as race, gender, age, and income interact to intensify existing vulnerabilities to climate extremes, climatic factors and health inequalities. This differential vulnerability underscores the critical link between climate justice and population health, emphasizing the need to address inequalities to strengthen resilience and mitigate population health impacts of climate extremes. This session is a contribution to the Swedish centre for impacts of climate extremes (climes), and welcomes all contributions that explore the complex impacts of climate extremes on population health, including studies on how intersecting socioeconomic, demographic, and geographical factors shape vulnerability.

Environmental issues are not only ecological but also societal and cultural. To address them effectively, we need to understand how human societies interact with the environment. This session highlights the importance of social science in environmental research and vice versa, and invites contributions that explore how interdisciplinary collaboration can lead to innovative and sustainable solutions. We welcome scientists from all disciplines of environmental and social sciences, data analysts, methodologists, and metadata experts to share their insights, case studies, and challenges. We aim to foster meaningful discussions and exchange of ideas across academic groups, research infrastructures, the private sector, and policy makers. By integrating the expertise of social scientists with environmental research, we can develop a more comprehensive and holistic understanding of environmental problems leading to pathways for viable climate action plans and supporting policies. Let's work together to contribute to a more sustainable relationship between people and the environment.
Topics may include, but are not limited to:
– Climate action plans and solutions for green and sustainable cities
– Cultural heritage and environmental sustainability
– Environmental policy and governance
– Air quality and climate indicators
– Sustainable agriculture and land use
– Biodiversity conservation and ecosystem services
– Climate adaptation and resilience
– Development of resilient communities through disaster risk reduction
– Citizen and participatory science and public engagement
– Best practice methodologies for specific use cases
– Metadata standards for integration of data from different research domains
– Project reports or infrastructure requirements related to multidisciplinary use cases

Our solicited speaker is Bonnie Wolff-Boenisch, CEO of CESSDA ERIC. Bonnie has 25 years of work experience in research and infrastructures, management and advocacy across different cultures, countries and disciplines. She is a member of Scientific Advisory Boards in Germany, Italy, France and the US, and has a PhD in Isotope Geochemistry from the Max-Planck Institute in Mainz, Germany.

Life on earth evolved through various geological ages in close interaction with the climate system. While the past climate changes have played a crucial role in shaping the terrestrial life distribution by modifying habitat and resource availability, modern humans have compounded these impacts by inducing a dramatic shift in the global biodiversity patterns. The evolutionary history of terrestrial life is characterized by migrations, adaptations, speciation and mass extinctions, with constant restructuring of the global ecosystem. Understanding the complex linkage between climate and terrestrial life forms is crucial in managing the present environmental challenges and developing effective conservation strategies for addressing potential biodiversity crisis in the future.

This session aims at bringing together multidisciplinary research on how climate has impacted and will impact terrestrial life forms and ecosystem structure in the past, present and future.

Topics of interest include,
- Mass extinctions in the past
- Climate and human influences on global biodiversity patterns
- Climate-driven species migrations
- Genetic diversification and speciation
- Vegetation dynamics and biome shifts
- Habitat degradation and effects on species distribution
- Species interactions and changes in ecosystem composition
- Climate-ecosystem modelling
- Conservation ecology

This multidisciplinary session at the nexus between climate change research and ecology will provide an opportunity for researchers to interact, forge new collaborations and exchange knowledge.

The geological record provides insight into how climate processes operate and evolve in response to different than modern boundary conditions and forcings. Understanding deep-time 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 levels—relative to the Quaternary—, or the existence of climatic tipping points and thresholds. In recent years, geochemical techniques and Earth System Models complexity have been greatly improved and several international projects on deep-time climates (DeepMIP, MioMIP, PlioMIP) have been initiated, helping to bridge the gap between palaeoclimate modelling and data communities. This session invites work on deep-time climate, Earth System model simulations and proxy-based reconstructions from the Cambrian to the Pliocene. We especially encourage submissions featuring palaeoenvironmental reconstructions, palaeoclimate and carbon cycle modelling, and the integration of CO2 and (hydro)climate proxies and models of any complexity.

This session aims to bring together proxy-based, theoretical and/or modelling studies focused on both regional and global climate responses to astronomical forcing at different time scales throughout the history of Earth.

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), old 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 Neoproterozoic Era is known for rapid continental scale movements manifested by at least two major supercontinent assemblies: Rodinia and Gondwana. It is believed that the early-middle Proterozoic continental fragments grew to form Rodinia by a series of collisions at ~1000 Ma and broke up in stages from 1000 to 520 Ma. Before Rodinia had completely broken up, some of its segments had already begun to form Gondwana, which assembled completely by ~500 Ma.
The Neoproterozoic Era sandwiched between the Grenvillian and Pan-African orogenic activities, experienced dramatic changes in the global environment and the development and fragmentation of supercontinents. Significant crustal readjustments from Rodinia to Gondwana during the Neoproterozioc era (1000-542 Ma) have been reported. This interval of rapid plate configuration changes is often considered an important factor for the preceding biological changes. Therefore, it’s crucial to understand the paleogeographic distribution of cratons during the Neoproterozoic Era to understand the dawn of complex life. Despite significant developments, a major gap in our understanding exists between the breakup of Rodinia and the assembly of Gondwana.
This session invites Earth scientists to explore and investigate the 1100-500 million years ago interval to illuminate the intricate dynamics of this transformative era.

This session aims to bring together a diverse group of scientists who are interested in how life and planetary processes have co-evolved over geological time. This includes studies of how paleoenvironments have contributed to biological evolution and vice versa, linking fossil records to paleo-Earth processes and the influence of tectonic and magmatic processes on the evolution of climate and life. As an inherently multi-disciplinary subject, we aspire to better understand the complex coupling of biogeochemical cycles and life, the links between mass extinctions and their causal geological events, how fossil records shed light on ecosystem drivers over deep time, and how tectono-geomorphic processes impact biodiversity patterns at global or local scales. We aim to understand our planet and its biosphere through both observation- and modelling-based studies. We also invite contributions on general exoplanet-life co-evolution.

This session is co-organized by COST Action CA23150 - pan-EUROpean BIoGeodynamics network (EUROBIG)

The first half of Earth’s history (Hadean to Paleoproterozoic) laid the foundations for the planet we know today. But how and why it differed and how and why it evolved remain enduring questions.
In this session, we encourage the presentation of new approaches that improve our understanding on the formation, structure, and evolution of the early Earth ranging from the mantle and lithosphere to the atmosphere, oceans and biosphere, and interactions between these reservoirs.
This session aims to bring together scientists from a large range of disciplines to provide an interdisciplinary and comprehensive overview of the field. This includes, but is not limited to, fields such as early mantle dynamics, the formation, evolution and destruction of the early crust and lithosphere, early surface environments and the evolution of the early biosphere, mineral deposits, and how possible tectonic regimes impacted across the early Earth system.

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.

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.

Speleothems are key terrestrial archives of regional to global paleoclimatic and paleoenvironmental changes on sub-seasonal to orbital scales. They provide high temporally resolved records which can be accurately and precisely dated using a variety of proxies such as stable O and C isotopes and trace elements. 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 variables for data-model comparisons and evaluation. Beyond this, caves and karst areas additionally host an enormous suite of other valuable 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 or archaeological findings.
This session aims to integrate recent developments in the field, and invites 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 reconstruct precipitation, vegetation, fire frequency, temperature etc. across different climate zones,
(2) field- and lab-based developments of process-based methods to improve our application of proxy variables,
(3) process and proxy-system model studies as well as integrated research 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.

A key limitation of observational climate data is the length of the instrumental record. Palaeo-archives offer solutions to extend the instrumental data framework, as these record a variety of climatic parameters. The investigation of these natural archives can reveal at (sub)annual, multi-decadal and centennial resolutions the scale, range and amplitude of climate variability, as well as extreme and rare events poorly sampled up to now. Increasingly, Holocene climates (alongside other geological periods) are shown to be dynamic with the detection of low frequency climate variability operating as individual episodes and as recurring modes (e.g. NAO, ENSO, AMV, PDV), both altering temperature and precipitation patterns spatiotemporally. Low frequency climate variability during the Holocene can be related to long term changes in orbital forcing, solar forcing and volcanism with associated feedbacks, but also to internal variability from changes to ocean and atmospheric circulation patterns.

It is only through the proxy detection, and data assimilation, of the complete range of climate variability that we can begin feed this learnt climate data into climate models to not only better understand the mechanisms of variability during different time periods but also to test climate model capability to reproduce this low frequency climate variability. The detection of the complete range of Holocene climate variability, and by extension older time periods, and validation of both proxies and models is therefore important for near-term and multi-decadal climate predictions and projections. These analyses are crucial both scientifically, but also societally to underpin climate policy and climate services, given projected climate change.

This session welcomes:
- Traditional and novel approaches to reconstructing Earth’s climate at (sub)annual to centennial scales.
- Transient climate model simulations of climate and the evaluation of climate models for future climate projection.
- Methodological advancements in modelling, including innovations in isotope-enabled climate models, proxy system models, data assimilation and machine learning techniques that aim to reconcile differences in temporal variability and spatial representation between models and proxies.
- Inter-proxy and climate model validation approaches to test the robustness of climate reconstructions.
-Efforts to use resolved climate data as a tool for climate services and policy.

The 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.

Understanding the past climate and especially the associated feedback mechanisms involving clouds, vegetation, sea ice, ice sheets, ocean circulation, and the carbon cycle—such as those that substantially shaped the amplitude and timing of Quaternary deglaciations and the preceding glacial periods, as well as abrupt millennial-scale climate transitions during the last glacial period (the so-called Dansgaard–Oeschger, or ‘D-O’ events)—are crucial for constraining the future climate.

Many uncertainties remain about the role of these feedbacks and the associated interactions between different Earth system elements. This session will provide an opportunity to assess recent progress in documenting and understanding glacial-interglacial transitions and abrupt climate (including D-O events) events, and to evaluate the state of knowledge about model behaviour during these periods of major Earth system change.

We especially focus on the role of sea ice in abrupt climate shifts, but also include studies that explore both colder and warmer-than-modern climate states. Especially, we include proxy studies, such as IP25 from sediment cores or halogens from ice cores, covering past climatic periods that refine existing records and/or generate new data to advance the understanding of sea ice processes and associated climate changes, thereby enhancing or constraining cutting-edge climate models.

We encourage studies based on climate proxy data, and those using numerical models to submit abstracts with the aim of facilitating a comprehensive overview of processes, feedbacks, and tipping points during glacials and deglaciations; and particularly welcome CMIP-PMIP-relevant contributions.

Quaternary climate variability is characterised by changes in the carbon cycle on all timescales from seasonal to orbital (glacial-interglacial cycles), manifesting in large variations in the atmospheric CO2 concentrations. Studying the natural carbon cycle variability is essential to address the current challenges of climate change. However, interpreting past changes remains difficult due to the complex and poorly understood interactions between the different reservoirs of the climate system (ocean, atmosphere, biosphere, lithosphere, cryosphere) and their impacts on the carbon cycle. Among these are impacts of changes in oceanic circulation and productivity, and interactions between vegetation composition, wildfire regimes and atmospheric conditions. Paleo-environmental proxy records and Earth system models provide insights into natural variations in atmosphere-carbon exchange, ocean carbon storage, and vegetation-fire-climate interactions. In particular, they can inform on changed dynamics due to major climatic transitions during the Quaternary, and on changes due to anthropogenic climate change and human land management.

We invite contributions that focus on vegetation, wildfire and ocean dynamics during the Quaternary and their interactions with climate to understand changes in the continental and oceanic carbon cycle. This includes: (a) regional and global-scale reconstructions of fire regimes and vegetation cover from paleo-environmental data, (b) multi-tracer analyses (e.g., micropaleontology, geochemistry) of marine sediment cores to reconstruct variations in carbon stocks and fluxes between the atmosphere and the ocean, (c) the development and application of innovative proxies and archives, (d) Earth system model simulations and comparisons with proxy records, and (e) studies that can inform future land management policies.

Understanding the interplay between stratigraphy, sedimentology, and paleoclimate across various timescales is essential for reconstructing Earth’s history, and its relevance for i.a. human evolution, migration, and cultural innovation. Conventional approaches, such as sedimentological and stratigraphic analysis of outcrop-, lacustrine , and marine records, provide a foundational framework for understanding long-term paleoclimatic shifts and its link to archaeological and paleoanthropological contexts.
However, investigating processes and interactions on human-relevant timescales (seasonal to multi-decadal) requires methods providing high temporal and possibly spatial resolution. Recent advances in scanning and imaging techniques, including micro X-Ray Fluorescence (μXRF) scanning, Hyperspectral Imaging, Mass Spectrometry Imaging, and Micro-Computed Tomography (μCT) scanning, create new opportunities to explore geochemical and sedimentological records in unprecedented detail. These techniques complement traditional methods by enabling the integration of stratigraphic and sedimentological data with high-resolution paleoclimate reconstructions.
This session hosts all contributions that integrate conventional sedimentological, stratigraphic, and paleoclimatic methodologies, as well as contributions focusing on the development and use of cutting-edge imaging techniques to address methodological, sedimentological and paleoenvironmental research questions across timescales. We gathered and combined submissions highlighting innovative proxy applications, methodological advancements, and solutions to challenges in analyzing difficult archives. Our goal is to provide the platform to explore applications of conventional and imaging techniques in paleoclimate and geoarchaeology. By fostering discussions on integrating traditional and novel approaches, this session intends to spark interdisciplinary collaborations and inspire new research directions in understanding Earth and human history.

Sedimentary archives can be found across diverse environments worldwide, allowing investigation and disentanglement of past environmental processes over different setting. However, one key limitation in the investigation of such records is deciphering the complexity of how the different forcings acting in a natural system are manifested in the environment and consequently propagated into the studied archives. Interpretations derived from any sedimentary archive thus depend on a our understanding of the surrounding natural system itself and its web of feedbacks, the investigated sedimentary record, and the utilized proxies. Such interpretations often call for the integration of different disciplines, the development of new tools for sampling, novel laboratory methodologies and modelling. These studies need to integrate both modern and recent observations as well as reconciling these with numerical models to improve our predictions of coastal evolution in the future. Combining vast datasets from remote sensing, habitat mapping, geophysical surveys, and in situ monitoring, with advanced analytics and numerical models, provides a holistic view of coastal evolution.

For this session we welcome any contribution that integrates sedimentological, geochemical, biological, and geochronological methods, as well as modelling approaches, novel laboratory experiments and monitoring, for the interpretation of sedimentary systems, with a special focus on mechanism-oriented interpretation. Contributions that either focus on the development and calibration of novel proxies, analytical approaches (either destructive or non-destructive) and data analysis (statistics, machine learning, AI), or present interesting case studies, are welcome as well.

Micropaleontological data, such as assemblage composition, morphology, and evolutionary patterns, provide unique insights into the dynamics and tipping points of past environments and climate through changes in the fossil record. 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 gather a broad spectrum of micropaleontologists to showcase recent advances in applying micropaleontological data in 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, pollen) as proxies for paleoenvironmental and paleoclimatological reconstructions and tools for stratigraphic correlation. We particularly encourage the submission of multi-proxy approaches, merging micropaleontological information with geochemical and paleobiological information. The application of microfossils as stratigraphic markers and advancing multivariate statistical techniques with a focus on microfossil assemblages is encouraged.

Currently drylands are home to >40% of the world’s population, and many prehistoric and historic cultures developed in these regions. Drylands are characterized by limited water resources and are highly sensitive towards both human activities and extreme events such as droughts and floods, which affects regional water balances and geomorphic processes. Due to currently intensified climatic and human pressure such processes strongly intensified during the last decades, affecting the living conditions of local populations including freshwater availability from groundwater resources and water quality. However, the functioning of these processes and their feedbacks are poorly understood. To build up reliable future scenarios to achieve sustainable development goals in the future these processes and feedbacks need to be addressed in an interdisciplinary manner on timescales ranging from the Quaternary until today, as well as in future climate scenarios.
This session pools contributions dealing with past to future hydrometeorological, environmental and geomorphological processes understanding in drylands across a broad geographical range since the Quaternary studied on varied spatial and temporal scales. Besides case studies on individual regions and review studies, cross-disciplinary, methodical and conceptual contributions are especially welcome in this session.

Coastal areas are among the most dynamic elements of the physical landscape, strongly influenced by both short-term (e.g., catastrophic meteo-marine events, human impacts) and long-term (e.g., tectonics, climate change, volcanic activity) forcing factors. Therefore, the study of coastal proxies can offer a series of benchmarks for estimating processes and associated timescales.
Among the most studied processes in coastal areas are relative sea-level changes. Any landscape feature whose environment of formation is linked to a former sea level can be used as a sea level index point (SLIP). SLIPs can be of different types: geomorphological (e.g., marine terraces, shoreline angles), biological (e.g., coral reef terraces), sedimentary (e.g., beach deposits, saltmarshes or beach ridges).
Although there is a comprehensive understanding of the relative sea-level changes during the Holocene, our knowledge of such dynamics during past interglacials remains limited. This session invites the international sea-level community to present studies broadly related to Quaternary interglacials. We welcome contributions on new field or remote sensing data, synthesis and databases specifically related to sea-level changes (including geochronological methods). We also welcome contributions exploring other coastal processes at the same timescale, focussing on wave conditions, extreme coastal events, and coastal modelling.
This session falls under the purview of PALSEA-Next, a working group of the International Union for Quaternary Sciences (INQUA) and Past Global Changes (PAGES) and from the WARMCOASTS project, funded by the European Research Council under the EU Horizon 2020 Research and Innovation Programme (grant agreement n. 802414).

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 and modelling papers on all aspects of radiation 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. This information may be obtained from direct measurements, satellite-derived products, climate modelling as well as 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.

Solicited speaker: Prof. Bill Collins, UC Berkeley

ENSO and the Tropical Pacific as well as their interactions with other tropical basins are the dominant source of interannual climate variability in the tropics and across the globe. Correctly modelling and understanding the dynamics, predictability, and impacts of ENSO, as well as anticipating their future changes are thus of vital importance for society. This session invites contributions regarding all aspects of ENSO, Tropical Pacific and tropical basins interactions, including: dynamics, multi-scale interactions; decadal and paleo variability; theoretical approaches; ENSO diversity; global teleconnections; impacts on climate, society and ecosystems; seasonal forecasting, climate change over the last few decades and climate change projections of tropical mean state changes, ENSO and its tropical basins interactions. Studies aimed at evaluating and improving model simulations of ENSO, the tropical mean state and the tropical basins interactions basin are especially welcomed.

Urban areas play a fundamental role in local- to large-scale planetary processes via modification of heat, moisture, and chemical budgets. With urbanisation continuing globally, it is essential to recognize the consequences of converting natural landscapes into a built environment. Given the capabilities of cities to serve as first responders to global change, considerable efforts are currently dedicated across cities to monitoring and understanding urban atmospheric dynamics. Various adaptation and mitigation strategies aimed to offset the impacts of rapidly expanding urban environments and influences of large-scale greenhouse gas emissions are developed, implemented, and evaluated. Tools and services tailored to cities that support climate action are rapidly evolving.

This session solicits submissions from the observational, modelling, and science-based tool development communities. Submissions are welcome that cover urban atmospheric and landscape dynamics, urban-climate conditions under global to regional climate change including uncertainty propagation, processes and impacts due to urban-induced climate change, the efficacy of various strategies to reduce such impacts, and human-biometeorological investigations in urban settings. We also welcome techniques highlighting how cities use novel science data products and tools, including those from humanities and social sciences, that facilitate planning and policies on urban adaptation to and mitigation of the effects of climate change. Emerging topics such as citizen science, crowdsourcing, machine learning, and urban-climate informatics are highly encouraged.

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.

The historical weather records are essential for improving our understanding of past climate variability and extreme weather events. These records, often stored in archives, in the form of ship logs, reports, personal diaries, and other documents, offer invaluable insights into weather patterns prior to modern observational networks. However, much of this data remains fragmented, undigitized and inaccessible, limiting its potential to inform long-term climate analyses. The data-rescue process—digitizing and transcribing these records—plays a crucial role in filling the gaps in historical weather datasets, enabling a deeper understanding of long-term climate trends, rainfall variability, and the progression of climate change.

This session will explore the exciting field of data-rescue and the focus will be on how these rescued datasets are critical in reconstructing and understanding weather events from the past, providing invaluable insights for historical reanalyses. It will explore innovative techniques for recovering and digitizing historical weather observations, focusing on extreme events such as droughts, floods and storms.

We encourage submission of talks that address these key topics (not exhaustive):
- Methodologies for identifying and analyzing extreme weather events in the pre-modern era.
- Best practices for rescuing, digitizing, and integrating historical weather data.
- The role of historical observations in extending and improving climate reanalyses.
- Applications of data-rescued observations in reconstructing past climates and validating models.
- Collaborative efforts in data-rescue: success stories, challenges, and future directions.
- Experiences with emerging technologies like artificial intelligence (AI) and machine learning (ML), to automate extraction of weather data from complex archival sources.

The integration of rescued historical observations with modern datasets underpins many fields of climate research – from estimating pre-industrial baseline from which current climate is compared, providing boundary conditions for number of climate variables to correctly run GCMs, accurately reconstructing past climate, extreme events by being assimilating into long-term reanalyses. Data-rescue thus serves as a crucial bridge between historical observations and modern climate science, enabling researchers to reconstruct and reanalyse the Earth's climate system with greater certainty.

The dynamics of the ocean and atmosphere are characterized by the coexistence of multiple fundamental processes spanning a variety of spatio-temporal scales. The details of interactions between processes in these two components of the climate system differ at different latitudes in persistence, and may lead to slow as well as fast changes in the mean state of the climate system. While slow changes may bear risks for irreversible changes (e.g. tipping points), climate and weather extremes create more short term but severe impacts and include droughts, floods, wildfires, heat waves, cold spells, extreme precipitation and compound events, whose occurrence has remarkably increased in recent times. Indeed, anthropogenic forcing-caused global warming has led to fundamental modifications of the oceanic and atmospheric circulations and ice conditions which favor more climate and weather extremes. To this extent, understanding exchanges of moisture, heat and momentum is important for the atmospheric and oceanic circulations, indicating that both a thermodynamic and a dynamic perspective are needed in order to better understand and predict climate and weather extreme events. Detection and careful understanding of these mechanisms is also crucial, in order to discern the impacts of anthropogenic climate change on the variability of the climate system.
In this session, we welcome contributions on: (a) characteristics and mechanisms of climate trends as well as climate and weather extreme events; (b) impacts of Arctic and tropical climate systems and their teleconnections on climate trends and on climate and weather extreme events; (c) predictions and projections on trends as well as on climate and weather extreme events; (d) atmosphere – ocean dynamics and thermodynamics, including the role of sea-ice, and both weather and climate timescales. We also encourage submissions that address and compare different methodologies, e.g. detection of dominant patterns or weather regimes, dimensionality reduction involving traditional techniques such as PCA and EOFs, or new methods such as random forest or other AI-based algorithms, and observational studies such as trend detection via Eulerian time series observations which also may serve the purpose of extremes characterization.

The tropical Atlantic exhibits significant ocean variability from daily to decadal time scales, driven by complex ocean dynamics and air-sea interactions. This session is devoted to advancing the understanding of these dynamics and their climatic impacts on both adjacent and remote regions, including their interactions with other tropical basins. In addition, we are interested in the effects of climate change and variability modes on the tropical Atlantic, with a particular focus on impacts on marine ecosystems.

Relevant ocean processes include upper and deep ocean circulation, eddies, tropical instability waves, mixing, and upwellings. For air-sea interactions, we welcome studies analyzing the seasonal cycle, marine heat waves, the development of variability modes on local to basin scale (e.g., Atlantic, Dakar and Benguela Niños, Atlantic Meridional Mode and South Atlantic Ocean Dipole) and interbasin teleconnections. Wind variations related to high-frequency events, cyclones, convective systems and those shaping air-sea coupled modes are encouraged.

Finally, we seek for studies that explore the causes and impacts of systematic model errors in simulating the local to regional Atlantic climate variability. Submissions based on direct observations, reanalysis, model simulations and machine learning techniques are welcome.

Traditionally, hydrologists focus on the partitioning of precipitation water on the surface, into evaporation and runoff, with these fluxes being the input to their hydrological models. However, more than half of the evaporation globally comes back as precipitation on land, ignoring an important feedback of the water cycle if the previous focus applied. Land-use and water-use changes, as well as climate variability and change alter, not only, the partitioning of water but also the atmospheric input of water as precipitation, related with this feedback, 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.

Typically, studies in this session are applied studies using 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 sources of data for atmospheric hydrology and implications for inter-comparison and meta-analysis. For example, observations networks, isotopic studies, conceptual models, Budyko-based hydro climatological assessments, back-trajectories, reanalysis and fully coupled Earth system model simulations.

The polar climate system is strongly affected by interactions between the atmosphere and the cryosphere. Processes that exchange heat, moisture and momentum between land ice, sea ice and the atmosphere, such as katabatic winds, blowing snow, ice melt, polynya formation and sea ice transport, play an important role in local-to-global processes. Atmosphere-ice interactions are also triggered by synoptic weather phenomena such as cold air outbreaks, polar lows, atmospheric rivers, Foehn winds and heatwaves. However, our understanding of these processes is still incomplete. Despite being a crucial milestone for reaching accurate projections of future climate change in Polar Regions, deciphering the interplay between the atmosphere, land ice and sea ice on different spatial and temporal scales, remains a major challenge.
This session aims at showcasing recent research progress and augmenting existing knowledge in polar meteorology and climate and the atmosphere-land ice-sea ice coupling in both the Northern and Southern Hemispheres. It will provide a setting to foster discussion and help identify gaps, tools, and studies that can be designed to address these open questions. It is also the 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,
- 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-ice 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,
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 the Arctic and in the Southern Ocean/Antarctica are also welcomed.

As our climate system climbs through its current warming path, temperature and precipitation are greatly affected also in their extremes. There is a general concern that climate change may also affect the magnitude and frequency of river floods and, as a consequence, that existing and planned hydraulic structures and flood defences may fail to provide the required protection level in the future. While a wide body of literature on the detection of flood changes is available, the identification of their underlying causes (i.e. flood change attribution) is still debated.
In this session, we invite contributions on works on how floods of different kinds (e.g., fluvial, pluvial, urban, coastal, …) and their impacts on the landscape are related to climate extremes (of precipitation and temperature) and how these extremes are related to large-scale predictors (e.g. climate oscillations, teleconnections) on different spatio-temporal scales. This session invites contributions on (but not limited to) the following questions:
- What are the large-scale predictors of climate extremes that are relevant to river floods and their change?
- What is the role of spatio-temporal scales when mapping climate to flood extremes?
- How are changes in mountain climate affecting downstream floods?
- How do changes in thunderstorms and convective precipitation alter flood risk associated with river floods?
- How are climate extremes and river floods of different types related to each other?
- What are the most useful methodologies for flood change attribution?
- What are the most useful datasets for flood change attribution?
Mapping climate to flood extremes is of interest from both theoretical and practical perspectives. From a theoretical point of view, a better understanding of the connection between climate extremes and floods will help to attribute flood changes to their underlying climatic drivers. From a practical point of view, the identification of climate indices relevant to flood extremes may allow to better incorporate climate projections in the assessment of flood hazard and risk, leading to a more informed selection of adaptation measures compared to what is now possible.

Accurate and reliable observational data are fundamental for understanding climate dynamics, assessing climate change impacts, and informing adaptation strategies. However, the quality and consistency of observational datasets depend on adherence to standardized measurement protocols and rigorous uncertainty assessment methodologies. Reference measurements are the only traceable to the International System of Units (SI) and are provided with a robust quantification of measurement uncertainty.
This Short Course will guide participants in enhancing their knowledge and application of reference measurements for climate studies, with particular focus on the following topics:
1. Reference upper air measurements, Ruud Dirksen (DWD - Deutscher Wetterdienst)
2. Near surface reference measurements, Graziano Coppa (INRiM - Istituto Nazionale di Ricerca Metrologica)
3. Precipitable water vapour from reference and reprocessed GNSS timeseries, Olivier Bock (IPGP - Institut de physique du globe de Paris)

Volcanic aerosol clouds from major tropical eruptions cause periods of strong surface cooling in the historical climate record and are dominant influences within decadal surface temperature trends. Advancing our understanding of the influence of volcanoes on climate relies upon better knowledge of:

(i) the radiative forcings of past eruptions and the microphysical, chemical and dynamical processes which affect the evolution of stratospheric aerosol properties and

(ii) the response mechanisms governing post-eruption climate variability and their dependency on the climate state at the time of the eruption.

This can only be achieved by combining information from satellite and in-situ observations of recent eruptions, stratospheric aerosol and climate modelling activities, and reconstructions of past volcanic histories and post-eruption climate state from proxies.
In recent years the smoke from intense wildfires in North America and Australia has also been an important component of the stratospheric aerosol layer, the presence of organic aerosol and meteoric particles in background conditions now also firmly established.

This session seeks presentations from research aimed at better understanding the stratospheric aerosol layer, its volcanic perturbations and the associated impacts on climate through the post-industrial period (1750-present) and also those further back in the historical record.

Observational and model studies on the stratosphere and climate impacts from the 2022 eruption of Hunga Tonga are also especially welcomed.

We also welcome contributions to understand the societal impacts of volcanic eruptions and the human responses to them. Contributions addressing volcanic influences on atmospheric composition, such as changes in stratospheric water vapour, ozone and other trace gases are also encouraged.

The session aims to bring together research contributing to several current international co-ordinated activities: SPARC-SSiRC, CMIP7-VolMIP, CMIP7-PMIP, and PAGES-VICS.

Abstracts are solicited related to the understanding, prediction and impacts of weather, climate and geophysical extremes, from both an applied and theoretical viewpoint.

In this session we propose to group together the traditional geophysical sciences and more mathematical/statistical and impacts-oriented approaches to the study of extremes. We aim to highlight the complementary nature of these viewpoints, with the aim of gaining a deeper understanding of extreme events. This session is a contribution to the EDIPI ITN, XAIDA and CLINT H2020 projects and to the Swedish Centre for Impacts of Climate Extremes. We welcome submissions from both project participants and the broader scientific community.

Potential topics of interest include but are not limited to the following:

· Dynamical systems theory and other theoretical perspectives on extreme events;
· Data-driven approaches to study extreme events and their impacts, incl. machine learning;
· Representation of extreme events in climate models;
· Downscaling of weather and climate extremes;
· How extremes have varied or are likely to vary under climate change;
· Attribution of extreme events;
· Early warning systems and forecasts of extreme events;
· Methodological and interdisciplinary advances for diagnosing impacts of extreme events.

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. Recent regional extreme weather events (e.g. floods and heatwave in Europe in September 2023) underline the 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). 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.

Climate extremes are usually driven by complex regional interplays among human influence, internal climate variability, land-atmosphere interactions, and other factors like Arctic sea ice loss and polar amplification.
The accurate detection of changes in regional climate extremes is sometimes challenging due to observational uncertainties, such as non-climatic series discontinuities or station scarcity in regions like Africa or high altitudes. Reliable attribution of regional climate extremes usually relies on model skills in simulating the extremes. Global models actually provide some useful evidence for the role of human influence, while regional climate models could boost confidence in attribution to regional forcings such as land use/cover or urbanization. The attribution uncertainties could be caused by different attribution methodologies used, e.g., optimal fingerprinting or Bayesian statistics, and different model strategies employed, e.g., multi-models or single-model large ensembles. Besides, how to address internal climate variability remains a key source of the attribution uncertainties. Emerging advanced techniques like artificial intelligence (AI), have the great potential to substantially reduce these uncertainties.
This session provides a venue to present the latest progress in reliable detection, modelling, and attribution of regional climate extremes, especially in quantifying or reducing their uncertainties for better risk management. We welcome abstracts focused on, but not limited to:
- address the quality issue of daily observation data relevant at the regional scale
- assess the fitness of global or regional modelling by designing tailored diagnostics for climate extremes and their drivers in a regional context
- improve climate models to realistically represent regional climate extremes, in particular to convection-permitting scale at a fine resolution or to mega-heatwaves by adding relevant land-atmosphere feedbacks such as through dynamic downscaling
- reveal and evaluate the strengths and weaknesses of attribution methodologies used for different regional climate extremes
- develop new detection and attribution techniques for regional climate extremes, including large ensemble and AI algorithms
- find key physical or causal processes to constrain the attribution uncertainties
Finally, abstracts associated with projection uncertainties of regional climate extremes are also appreciated.

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. Driven by complex mechanisms, internal variability can itself change under external forcing, complicating D&A analyses and the projection of future changes. 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.

The Paris Agreement long-term temperature goal of limiting warming to 1.5°C sets ambitions for global climate action to avoid the most devastating impacts of climate change. However, due to past and present climate inaction, exceeding a global mean temperature increase of 1.5°C above pre-industrial levels has become almost inevitable; in 2024 the global mean temperature was for the first time 1.5 ˚C higher than pre-industrial values. This has led to an increased interest in so-called overshoot pathways that exceed a global warming level before returning to or below it in the long-run, commonly by deploying net-negative carbon dioxide removal methodologies.

The prospects of such a global temperature overshoot raise important questions in relation to Earth system feedbacks under overshoot.
Key questions include: what feedbacks might occur once specific warming targets are exceeded? What is the likelihood of rapid or abrupt change (including tipping points) occurring due to overshoot? What are the consequent risks for society and the natural environment? And, how reversible will these changes be if global mean temperature returns to a lower temperature level at some later date?
Further, it is important to understand the feasibility and side-effects of large-scale deployment of carbon dioxide removal that are necessary to return the Earth system to safer temperatures post-overshoot.
In this session, we welcome abstract submissions on global climate dynamics under peak and decline pathways, on regional to global climate impacts in overshoot scenarios, and mechanisms of non-linearity, particularly the risk of rapid/abrupt Earth system change. We welcome Integrated Assessment, Earth system and impact model experiments focused on overshoot pathways, including investigation of carbon dioxide removal, and realization of warming overshoot pathways with Earth System Models (including idealized pathways such as suggested by TIPMIP). We also invite analysis focussing on consequences in a wide range of sectors, from ocean dynamics to the cryosphere, biodiversity and biosphere changes to human systems and economic consequences of overshoot. Contributions that consider the socio-economic conditions and feasibility of overshoot scenarios, climate effects of large scale carbon dioxide removal, as well as the implications of overshoots for climate change adaptation planning are also strongly encouraged.

The oceans are changing rapidly in response to the changing climate manifested in record-breaking temperatures in the North Atlantic, altered ocean currents, and changes in the marine carbon system. Further changes are expected in a warmer future climate. Understanding the mechanisms of oceanic climate change are crucial to develop realistic ocean projections. The latest 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 projections are essential to quantify the impacts of oceanic climate change and in developing successful adaptation strategies. This session will bring together people with the common interest of what the future ocean circulation will look like.

We encourage submissions from studies covering global, basin wide, regional, or coastal changes. Topics covering changing 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 but submissions using other modelling datasets and statistical projections are very much encouraged.

The ocean has stored vast amounts of carbon and heat due to anthropogenic CO2 emissions and climate change. We need to understand the processes driving this storage, that is uptake from the atmosphere, transfer to the ocean interior, redistribution within the ocean, and return to the ocean surface and the atmosphere. Also, ocean storage of carbon and heat are not independent: oceanic CO2 storage affects atmospheric CO2 levels, thereby atmospheric and oceanic warming. Ocean warming importantly, besides others changes ocean circulation and mixing which influences further uptake of both anthropogenic heat and carbon, and also perturbs the preindustrial ocean-atmosphere exchange of both, heat and carbon.

This session invites observational, numerical modeling and analytical studies that enhance the process understanding of ocean storage of carbon and/or heat under various climate scenarios: the contemporary situation of net-positive CO2 emissions and global warming, as well as future scenarios involving the gradual phasing out of CO2 emissions or a warming overshoot followed by net-negative emissions and global cooling. We also seek studies that explore the similarities and differences between ocean storage of carbon and heat, and how ocean uptake —and potential future release— affect climate.

Solicited author: Roland Séférian

Mountains cover approximately one-quarter of the total land surface on the planet, and a significant fraction of the world’s population lives within, in their vicinity, and downstream. Orography critically affects weather and climate processes at 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 is devoted to showcasing 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. This includes the interaction of mountain weather and climate with the terrestrial cryosphere.

We welcome contributions describing the influence of mountains on the atmosphere on meteorological and climate time scales, including terrain-induced airflow, orographic gravity waves, orographic precipitation, land-atmosphere exchange over mountains, forecasting, and predictability of mountain weather. Contributions connected with the TEAMx research programme (http://www.teamx-programme.org/) are encouraged.
We also encourage theoretical, modeling and observational studies on orographic gravity waves and their effects on the weather and the climate.

Furthermore, we invite studies that investigate climate processes and climate change in mountain areas based on monitoring and modeling activities. Particularly welcomed are contributions that connect with and address the interdisciplinary objectives of the Elevation-Dependent Climate Change (EDCC) working group of the Mountain Research Initiative ( https://mountainresearchinitiative.org/our-activities/community-led-activities/active-working-groups/elevation-dependent-climate-change/).

In the face of climate change, Africa is more than ever in need of climate services, scientific infrastructure and skilled people who are trained in providing solutions for their countries in how best deal with the adverse impacts of climate change. Over the past years, European governments and funding agencies have invested in climate change research and capacity building in various regions of Africa. However, these initiatives, mostly work independently and do not seek for synergies or collaborations.
This session aims to bring these capacity building initiatives together, provide them a stage to present themselves and a platform for networking, finding synergies and collaborations. We invite initiatives of any kind to present their work related to climate change capacity development in Africa. This also includes climate change-related topics such as, floods, droughts, natural hazards, land degradation, and so on. We welcome the full-variety of capacity building initiatives, including small-scale teaching or workshops (online or on site), co-development of research or monitoring infrastructure, master programmes, doctoral programmes, training of local communities or single research projects that include a capacity development component.
After getting an insight in the full bandwidth of capacity development initiatives in this session, we aim to follow-up with a splinter meeting in which the foundation of a European-African Network for Capacity Development in climate change Adaptation research in Africa (NetCDA) will be discussed. The NetCDA network should provide the basis for future exchange, sharing best practices and finding collaborations between various initiatives and institutions. We invite all session participants and other interested climate scientists from both continents to attend this splinter meeting. More details of the timing and location of this splinter meeting will follow.

This session investigates mid-latitude cyclones and storms on both hemispheres. We invite studies considering cyclones in all different stages of their life cycles, from initial generation to the final development, including studies to large- and synoptic-scale conditions influencing cyclones’ growth to a severe storm, their dissipation, and related socioeconomic impacts.
Papers are welcome, which focus also on the diagnostic of observed past and recent trends, long- and short-term natural variability, as well as on future storm development under changed climate conditions. This will include storm predictability studies on different time and spatial scales. The session also invites studies investigating storm related impacts: Papers are welcome dealing with vulnerability, diagnostics of sensitive social and infrastructural categories and affected areas of risk for property damages and loss. Which novel risk transfer mechanisms are currently developed or used? Which novel mechanisms (e.g., adapted re-insurance products) are already implemented or will be developed in order to adapt to future loss expectations under anthropogenic climate change?

Regional monsoons and the global monsoon circulation to which they belong 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.

Monsoons are complex phenomena involving coupled atmosphere-ocean-land interactions and remain notoriously difficult to forecast at leads times ranging from numerical weather prediction (NWP) to long-term 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 CMIP6 findings to help inform the IPCC AR7. Applications of AI/ML to monsoon studies are also encouraged.

Achieving the climate goals of the Paris Agreement requires deep greenhouse gas emissions reductions towards a net-zero world. Advancements in mitigation-relevant science continuously inform the strategies and measures that society pursues to achieve this goal. This session aims to further our understanding of the science surrounding the achievement of net-zero emissions and the Paris Agreement mitigation goal with particular interest in remaining carbon budgets, emission pathways entailing net-zero targets, carbon dioxide removal strategies, the theoretical underpinnings of these concepts, and their policy implications. We invite contributions that use a variety of tools, including fully coupled Earth System Models (ESMs), Integrated Assessment Models (IAMs), or simple climate model emulators.

We welcome studies exploring all aspects of climate change in response to ambitious mitigation scenarios, including 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. 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.

Agriculture is an important sector of any economy of the world. Agriculture productions are highly dependent on the climate change and variability. Changes in hydro-meteorological variables can influence crop yield and productivity at many places. Further, climate change can influence nutrient levels, soil moisture, water availability and other terrestrial parameters related to the agricultural productivity. Changes in the frequency and severity of droughts and floods could pose challenges for farmers and ranchers and threaten food safety. Further, changes in climate can influence meteorological conditions and thus can influence the crop growth pattern. It may also influence irrigation scheduling and water demand of the crops. The effects of climate change also need to be considered along with other evolving factors that affect agricultural production, such as changes in farming practices and technology.
The purpose of the proposed session is to gather scientific researchers related to this topic aiming to highlight ongoing researches and new applications in the field of climate change and agriculture. In this framework, original works concerned with the development or exploitation of advanced techniques for understanding the impact of climate change on agriculture will be invited. The conveners of this session will encourage both applied and theoretical research in this area.

All steps in estimating future climate impacts from emission scenarios are computationally expensive: running Earth System Models, downscaling and/or bias-correcting the outputs, and running process-based impact models. Altogether, these processes can take months. The latest evolution of reduced complexity climate models, or simple climate models, can project global climate from the latest emissions scenarios for tens of thousands of physical realizations in seconds. Novel methods are being developed to leverage the outputs from simple climate models to carry out risk assessments, and quantify climate impacts beyond the global mean temperature and even climate extremes. Concurrently, the latest advances in machine learning have enabled end-to-end simulation of climate dynamics at a fraction of the computing cost of physically-based systems. Impacts may be spatially resolved, enabling policy-relevant analyses to be carried out based on emissions scenarios which have never been run through fully-coupled Earth-system models, such as Network for Greening the Financial System (NGFS) scenarios. Applications of impact emulation extend to economic and integrated assessment models of climate change. With the rise in application of machine learning for Earth system model emulation and downscaling, this session aims to bring together research on statistical, physical and hybrid emulators with a focus on climate impacts.

Extreme weather and climate conditions, such as recent events unprecedented in the observational record, have high-impact consequences globally. Some of these events would have been arguably nearly impossible without human-made climate change, and broke records by large margins. Furthermore, compounding hazards and cascading risks are becoming evident. Continuing warming does not only increase the frequency and intensity of events like these, or other until now unprecedented extremes, it also potentially increases the risk of crossing tipping points and triggering abrupt unprecedented impacts. To increase preparedness for high impact climate events, developing novel methods, models and process-understanding that capture these events and their 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 ranging across spatial and temporal scales, and covering compound, cascading, and connected extremes as well as worst-case scenarios and storylines, with the ultimate goal to provide actionable climate information to increase preparedness to such extreme high-impact events.

We invite work addressing high impact extreme events via, but not limited to, observations, model experiments and intercomparisons, climate projections including large ensembles and unseen events, diverse storyline approaches such as event-based or dynamical storylines, 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 such impacts

The session is sponsored by the World Climate Research Programme lighthouse activity on Understanding High-Risk Events.

Recent assessments on the integrity of the Earth system and planetary health recognize the deteriorating resilience of the Earth system, with planetary-scale human impacts leading to a new epoch: the Anthropocene. Earth resilience, the capacity of the Earth system to resist, recover and regenerate from anthropogenic pressures, critically depends on the nonlinear interplay of positive and negative feedbacks of biophysical and increasingly also socio-economic processes and human-Earth system interactions. These include dynamics and interactions between the carbon cycle, the atmosphere, oceans, large-scale ecosystems, and the cryosphere, as well as the dynamics and perturbations associated with human activities. Studying Earth resilience requires a deeply integrated perspective on the human-Earth system in the Anthropocene and, hence, strong collaboration between diverse subdisciplines of Earth system science.

With rising anthropogenic pressures, there is an increasing risk of the human-Earth system hitting the ceiling of some of the self-regulating feedbacks of the Earth System, and of crossing tipping points in the large ice sheets, atmosphere-ocean circulation systems (e.g. the Atlantic Meridional Overturning Circulation) and biomes such as the Amazon rainforest. Transgressing these critical thresholds in human pressures such as greenhouse gas emissions and land-use changes could trigger large-scale and often abrupt and irreversible impacts on the biosphere and the livelihoods of millions of people. Potential domino effects or tipping cascades could arise due to the interactions between these tipping elements and lead to a further decline of Earth resilience. At the same time, there is growing evidence supporting the potential of positive (social) tipping points that could propel rapid decarbonization and transformative change towards global sustainability.

In this session, we invite contributions on all topics relating to Earth resilience, tipping points in the Earth system, positive (social) tipping, as well as their interactions and potential cascading domino effects. We are particularly interested in diverse methodological and quantitative approaches, from Earth system modelling to conceptual modelling and data analysis of nonlinearities, tipping points and abrupt shifts in the Earth system.

This session, which is co-organised by the Green Cluster (TRIQUETRA, THETIDA, RescueME, STECCI Horizon Europe projects funded under topic HORIZON-CL2-2022-HERITAGE-01-08) and the FPCUP action, aims to host discussions focused on the identification and quantification of the impacts of Climate Change on Cultural Heritage, using novel and state-of-the-art techniques. At the same time, the session serves as an opportunity to showcase the latest advances in the field of Cultural Heritage protection and preservation, through systematic monitoring and documentation, while simultaneously encouraging citizen engagement and the development of crowdsourcing applications and activities. The session will also highlight the importance of EU initiatives and funding in the field of Cultural Heritage, which faces a series of new challenges as a result of Climate Change. Finally, presentations will provide all interested parties with valuable insight into new strategies and applied technologies that may serve as paradigms moving forward.

In recent decades, extreme fire events have become increasingly common, exemplified by the recent fire seasons in Greece, Canada, Hawaii, California, Australia, Amazonia, the Arctic and the Pantanal. While these extremes and megafires have an exponential impact on society and all aspects of the Earth system, there is much to learn about their characteristics, drivers, links to climate change, and how to quantify their impacts, as well as mitigation and prevention strategies and tools.

One area of attention is how extreme fires are currently represented by different fire models. Due to their stochastic nature, uncertainty in observations, and the challenge of representing local processes within global models, extreme fires and their impacts still present a challenge to coupled modelling. The big data science models and machine learning approaches show promise in representing extremes but are weak in coupling feedbacks to vegetation, soils and the wider Earth System.

We also welcome case studies of regional extreme wildfire events, their impacts, and prevention and mitigation strategy experiences worldwide. We encourage contributions from a wide range of disciplines, including global, regional, and landscape modelling, statistical and process-based modelling, observations and field studies, science and social science studies on all temporal scales. In this session, we aim to share knowledge across multiple disciplines, from science to decision-makers and practitioners, to help overcome the challenges that wildfires pose to our models and our society.

We aim to explore the significance and interactions of extreme wildfires and their impacts on society and the earth system and identify the current gaps in our understanding to help us prepare for and mitigate future extreme wildfire events.

The Silk Road was a network of trade routes that stretched from central China to the Pamir Mountains, through Central Asia and Arabia to India and Rome, and played a key role in facilitating economic, cultural, political and religious exchanges between East and West. The central part of the Silk Road, located in arid Central Asia, is highly sensitive to environmental changes. Climate and environmental changes, especially changes in water availability, could significantly influence the spatio-temporal distribution of the Silk Road network, trans-Eurasian exchanges and human migration, as well as the civilizational development. This session aims to deepen understanding of the impact of environmental change in shaping long-term trans-Eurasian exchange and Silk Road civilization by promoting interdisciplinary research in the natural sciences, social sciences and humanities across Eurasia. We welcome presentations on these topics from multidisciplinary perspectives to promote the advancement of research in this area.

Atmospheric hazards can cause significant socio-economic damages and therefore it is of paramount importance that their impacts and historical variability are well understood by those in the insurance and financial sectors. These groups are expected to deal with climate risk on multiple timescales, for example through enhanced risk assessments.

As the climate continues to change, an understanding of changes to frequency, severity, exposure, and vulnerability are all required for a multitude of different perils. Furthermore, attention needs to be paid to emerging risks, and also to global regions that may be more vulnerable in the future. This understanding will aid planning and potential operational changes for those in the private sector.

This session will explore studies on historical impacts, modelling of hazards, understanding of variability, risks from climate change, and quantifications of exposure and vulnerability. Submissions are encouraged from both academic studies, and research projects from within the insurance and financial sectors. In particular, submissions are encouraged that focus on:

- Quantification of historical variability in hazards around the globe
- High resolution modelling of impactful perils
- Studies on compound or correlated risks
- Assessments of future changes or trends in either hazard, exposure, or vulnerability with climate change
- Techniques for assessing hazards in climate models
- Use of large ensembles for modelling risks
- Studies on emerging hazards such as drought/wildfire

Human activities on land (LULCC) shape climate by altering land-atmosphere fluxes of carbon, water, energy, and momentum. An increasing focus on land-based climate mitigation and adaptation strategies to meet more stringent targets has expanded the range of land management practices considered specifically for their potential to alter terrestrial carbon cycling or mediate favorable environmental conditions. This focus has also called attention to potential tradeoffs between climate-centric aspects of LULCC and its influences on biodiversity, hydrology and other environmental factors. Advancements in modeling and measurement techniques are opening new possibilities to better describe LULCC and its effects on the Earth system at multiple temporal and spatial scales.

This session welcomes all contributions aimed at furthering our understanding of LULCC in the Earth system, including those addressing LULCC effects on carbon, climate, hydrology, and/or biodiversity, and aims to present studies that can inform adoption of appropriate land-based strategies for climate mitigation, adaptation, and ecosystem restoration.

Climate change education and citizen engagement are crucial drivers in the shift toward a decarbonized society. Informal learning environments—such as research centres, science labs, and especially environmental observatories—are well positioned to rise to this challenge. By incorporating real-world data from environmental monitoring stations and satellites, educators can offer students both a clear understanding of climate change and an immersive experience in climate research. One such initiative is the ERASMUS+ project Climademy. Using authentic climate data in educational activities is a proven strategy for delivering accurate information, cultivating personal connections to the issue, and fostering scientific inquiry and critical thinking. Data owners are encouraged to contribute by sharing their datasets and illustrating how they are turning them into educational tools, combating misinformation, and building trust in scientific evidence.

However, effective climate education goes beyond presenting scientific data—it also requires understanding how different populations perceive and respond to climate change. People’s attitudes and adaptation strategies vary based on geographical location, environmental background, education level, income, and other socio-economic factors. Diagnosing these variations is essential for designing targeted and impactful educational approaches.

This session invites studies that employ quantitative and qualitative methods to assess environmental, economic, and social dimensions of climate change perception. Through case studies, participants will explore how real-world data can be leveraged to meet diverse educational needs across various national curricula.

All science has uncertainty. Global challenges such as the Covid-19 pandemic and climate change illustrate that an effective dialogue between science and society requires clear communication of uncertainty. Responsible science communication conveys the challenges of managing uncertainty that is inherent in data, models and predictions, facilitating the society to understand the contexts where uncertainty emerges and enabling active participation in discussions. This session invites presentations by individuals and teams on communicating scientific uncertainty to non-expert audiences, addressing topics such as:

(1) Innovative and practical tools (e.g. from social or statistical research) for communicating uncertainty
(2) Pitfalls, challenges and solutions to communicating uncertainty with non-experts
(3) Communicating uncertainty in risk and crisis situations (e.g., natural hazards, climate change, public health crises)

Examples of research fitting into the categories above include a) new, creative ways to visualize different aspects of uncertainty, b) new frameworks to communicate the level of confidence associated with research, c) testing the effectiveness of existing tools and frameworks, such as the categories of “confidence” used in expert reports (e.g., IPCC), or d) research addressing the challenges of communicating high-uncertainty high-impact events.

This session encourages you to share your work and join a community of practice to inform and advance the effective communication of uncertainty in earth and space science.

The rising concept “Climate resilience” can be defined as the capacity of actors, economies, ecologies or social-ecological systems to cope with and adapt to hazardous events associated with climate change and to transform in ways that secure possibilities for future generations to do it alike. Increasing studies are warning that climate change is a major threat to human societies and is projected to cause even greater loss and damage in near future, even if the currently planned mitigation goals are met. The question of how to maintain and enhance social resilience to climate change impacts is of utmost importance. Addressing climate resilience has become a key priority in fields like civil protection, urban planning, health care and others.
Against this background, this session aims to promote research exchanges of scholars from multiple disciplines on the status and dynamics of climate resilience studies. The relevant topics include, but are not limited to, the following:
• Theoretical explorations of scientific frameworks and components in climate resilience studies.
• Reviews of the research progresses in the field of climate resilience
• Methodological development for assessing and/or modeling climate resilience
• Local case studies, regional- and global-level perspectives of social resilience to climate impacts
• Particular focus on the resilience to climate-related hazards, e.g. flood, heat, drought, sea level rise
• Comparison studies of climate resilience over space and time
• Social, economic, technological, and political strategies for resilience building at all scales of society
• Practical implementations of resilience measures in various sectors, e.g. food, water and agriculture, transportation infrastructure, energy system, human settlements
• Possible future scenarios for enhancing social resilience to climate impacts

How can scientists and governments ensure that their communication resonates more deeply with citizens without resorting to the manipulative tactics used by those who seek to undermine liberal democracy? How can scientific and government actors ensure their communications are equally meaningful and ethical?

This Short Course will combine insights from state-of-the-art scientific knowledge, novel empirical research on values-targeted communication strategies, and a deep understanding of practitioners’ and citizens’ attitudes on these topics. Examples from the European Commission’s Joint Research Centre will be used to share practical guidance for scientists who need to successfully navigate the policy world.

Scientists have now been sounding the alarm about the climate and ecological crisis for decades. Each new report further outlines the necessity to radically change course, to rapidly reduce CO2 emissions and more generally human impacts on the environment if we are to avoid disastrous consequences on societies and ecosystems. Yet, these warnings have invariably been met with insufficient responses, political inertia, or worse active denial or institutionalised efforts to delay action. Meanwhile, a strong climate movement has emerged, led primarily by young activists demanding immediate climate action to ensure a liveable planet and a just future for all. A growing number of scientists and academics have also been starting to contemplate which roles they could most effectively take on in these movements, either from joining or providing external.

The growing interest and associated curiosity towards these movements from the scientific community was confirmed by the large attendance to EGU24’s events about academic activism. At the same time, many academics are unsure about where to start, how and where to find like-minded colleagues and grass-root organisations, or how to set up campaigns and actions to push for change at their institutions and beyond. This short course aims at bridging this gap by providing first-hand experience and practical tools to academics eager to organise within or outside their institution, and/or mobilise fellow colleagues to join climate actions. Equally important, the course will touch on relevant aspects of mental health: From the perspective of climate anxiety, to difficult-to-navigate dynamics within the movement, to a more general activist fatigue.

The course will be divided into 3 parts:
1. A starters part, with a short introduction on possible roles for academics in the climate movement, followed by presentations from experienced organisers about setting up a campaign at your own university, mobilising colleagues and organising events
2. A group work part, where participants will choose one proposed case as an example for the organisation of a campaign or event, and discuss it as a group, based on the input part and their own knowledge
3. A debriefing part, where some of the groups will present their work to the rest of the participants. Potential critical aspects related to organisational roadblocks, internal group dynamics, or repercussions that might come with certain forms of activism will be discussed

The planet is warming due to human-made greenhouse gas emissions, which have increased drastically since the industrial revolution. Understanding future climate pathways requires knowing the effects of these emissions on the global heat budget and climate system in warmer conditions. Modeling past climates is essential for assessing the Earth's sensitivity to climate feedbacks from changes in geography, atmospheric chemistry, orbital forcing, and ocean circulation. Geological proxy data are crucial for validating models and understanding climate dynamics in warmer conditions. This session invites contributions using proxy data and modeling to reconstruct past climates. We seek submissions on various time scales, from the Cretaceous to the present. Contributions assessing Earth system sensitivity by reconstructing past atmospheric CO2 and temperature are welcomed. The session intends to bring together the diverse community studying the nature of the warm climate states found in the Cretaceous and Cenozoic. We consciously welcome a broad range of approaches to facilitate synergies to learn from past warm climate conditions to navigate into the future warmer world.

Stable and radiogenic isotopic records have been successfully used for investigating various terrestrial and marine sequences, fossils, evaporative rocks, palaeosols, lacustrine, loess, caves, peatlands. In this session we are looking for contributions using isotopes along with sedimentological, biological, paleontological, mineralogical, chemical records in order to unravel past and present climate and environmental changes or as tracers for determining the source of phases involved. Novel directions using triple isotopes, clumped isotopes, biomarkers are welcomed.
The session invites contributions presenting an applied as well as a theoretical approach. We welcome papers related to reconstructions (at various time and space scales), fractionation factors, measurement methods, proxy calibration, and verification.

INTIMATE (INTegrating Ice core, Marine and TErrestrial records) is a large, diverse, international scientific network interested in better understanding abrupt and extreme climate changes in the Northern Hemisphere during the Quaternary. INTIMATE’s fundamental approach is the synchronisation and comparison of high resolution palaeoclimate and environmental records based on their independent timescales.

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.

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.
The session welcomes contributions from dynamical models, 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 long-term 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 modeling of the Earth Climate System has undergone outstanding advances to the point of resolving atmospheric and oceanic processes on kilometer-scale, thanks to the development of high-performance computing systems. Models resolving km-scale processes (or storm-and-eddy-resolving models) on a global scale are also able to resolve the interaction between the large and small-scale processes, as evidenced by atmosphere- and ocean-only simulations. More importantly, this added value comes at the expense of avoiding the use of parameterizations that interrupts the interaction between scales, i.e., convective parameterization in the atmosphere or mesoscale eddy parameterization in the ocean. These advantages are the bases for the development of global-coupled storm-and-eddy-resolving models, and even at their first steps, such simulations can offer new insights into the importance of capturing the air-sea interface and their associated small-scale processes in the representation of the climate system.
The objective of this session is to have an overview of the added values of global simulations using storm-resolving atmosphere-only configuration, eddy-resolving ocean-only models, and to identify which added values stay after coupling both components, i.e., mechanisms not distorted by the misrepresentation of sub-grid scale processes in the atmosphere and ocean. In addition to highlighting the importance of the already resolved processes in shaping the climate system in global storm-and-eddy-resolving models, this session is also dedicated to presenting the current challenges in global storm-and-eddy-resolving models (identification of biases and possible solutions) by pointing to the role of the sub-grid scale processes in shaping processes on the large scale.
We call for studies contributing to highlighting the advantages and challenges of using global storm-and-eddy-resolving models in ocean-only, atmosphere-only, and coupled configurations, such as the ones proposed by NextGEMS, EERIE, DestinE, and WarmWorld, as well as studies coming from independent institutions around the world

One of the big challenges in Earth system science consists in providing reliable climate predictions on sub-seasonal, seasonal, decadal and longer timescales. The resulting data have the potential to be translated into climate information leading to a better assessment of global and regional climate-related risks.
The main goals of the session is (i) to identify gaps in current climate prediction methods and (ii) to report and evaluate the latest progress in climate forecasting on subseasonal-to-decadal and longer timescales. This will include presentations and discussions of developments in the predictions for the different time horizons from dynamical ensemble and statistical/empirical forecast systems, as well as the aspects required for their application: forecast quality assessment, multi-model combination, bias adjustment, downscaling, exploration of artificial-intelligence methods, etc.
Following the new WCRP strategic plan for 2019-2029, prediction enhancements are solicited from contributions embracing climate forecasting from an Earth system science perspective. This includes the study of coupled processes between atmosphere, land, ocean, and sea-ice components, as well as the impacts of coupling and feedbacks in physical, hydrological, chemical, biological, and human dimensions. Contributions are also sought on initialization methods that optimally use observations from different Earth system components, on assessing and mitigating the impacts of model errors on skill, and on ensemble methods.
We also encourage contributions on the use of climate predictions for climate impact assessment, demonstrations of end-user value for climate risk applications and climate-change adaptation and the development of early warning systems.
A special focus will be put on the use of operational climate predictions (C3S, NMME, S2S), results from the CMIP5-CMIP6 decadal prediction experiments, and climate-prediction research and application projects.
An increasingly important aspect for climate forecast's applications is the use of most appropriate downscaling methods, based on dynamical, statistical, artificial-intelligence approaches or their combination, that are needed to generate time series and fields with an appropriate spatial or temporal resolution. This is extensively considered in the session, which therefore brings together scientists from all geoscientific disciplines working on the prediction and application problems.

Coupled Earth system interactions such as feedbacks and potential abrupt changes are a significant source of uncertainty in our current understanding of the Earth system and how it might respond to future human interventions. These coupled interactions involve and influence many components of the Earth system, such as the terrestrial biosphere, oceans, cryosphere, and atmosphere. They induce not only important controls on the exchange of CO2, CH4, N2O, and biogenic VOCs, but also on major high impact events such as compound extremes, ice sheet and ocean circulation collapse, extreme wildfires and forest dieback. State-of-the-art Earth System Models (ESMs) therefore include more and more of physical, biogeochemical and biophysical processes to represent these couplings. In addition, ensembles of these models, such as CMIP6 or the upcoming CMIP7, are vital to assess uncertainties in past and future changes. However, using all available models from a multi-model ensemble is often not feasible and does not necessarily provide the best possible representation of climate, its changes, and its uncertainties. There is therefore a need to credibly assess developments and capabilities of individual ESMs as well as their joined distribution for effective research on climate variability and change. This calls for novel and improved approaches for benchmarking, evaluating, and constraining ESMs based on their representation of climate compared to observations and other performance and science metrics.

For this session we therefore invite studies that focus on
(a) the latest advances in the representation of new couplings and interactions within state-of-the-art Earth system models
(b) novel experimental designs to help improve quantification of these feedbacks, including those targeting CMIP7 activities
(c) novel approaches for evaluation and benchmarking of ESMs with the Earth observational datasets and reanalysis datasets, including their application to constrain uncertainty in future changes
(d) methods that include Artificial Intelligence and Machine Learning to progress ESM representations or the evaluation and benchmarking of ESMs.

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.

Modelling past climate states, and the transient evolution of Earth’s climate remains challenging. Time periods such as the Paleocene, Eocene, Pliocene, the Last Interglacial, the Last Glacial Maximum or the mid-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. However, 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 (e.g. transient simulations covering the entire last glacial cycle as per the goal of the PalMod project). 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 from the latest phase of PMIP4-CMIP6, and early-stage tests of new models or simulations for PMIP5/CMIP7 are particularly encouraged. 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.

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 primarily due to uncertainty in radiative feedbacks, which can be influenced
by a large range of processes including cloud microphysics, large-scale circulation of the atmosphere and
ocean, or the pattern of surface temperature changes. This session solicits work on theory, modeling,
and observations related to Earth’s climate sensitivity, with a particular focus on recent advances in
understanding the causes and impacts of the surface temperature pattern effect. The pattern effect
describes how surface temperature changes with identical global mean values can have hugely different
effects on the radiation budget depending on their spatial distribution, having significant implications
for interpreting temperature changes from observations, paleo-climate proxies, and climate-change
projections.
We welcome contributions related, but not limited, to:
• Radiative feedbacks and their modulation by surface warming patterns
• Air-sea interactions and ocean dynamics relevant to surface temperature patterns
• Process studies of feedbacks from clouds and moist processes
• Ocean heat uptake and transient climate sensitivity
• Theoretical models of climate sensitivity
• Interbasin interactions and teleconnections spanning scales from sub-basin to global
This session serves as an exchange platform for the often more separated ocean and atmosphere communities, and we especially encourage contributions from the ocean community.

The session will assemble current knowledge on Transient Climate Response to cumulative carbon Emissions (TCRE) and Zero Emissions Commitment (ZEC) in the context of reducing uncertainty in remaining carbon budgets and reversibility.

Specific topics could include:
- Understanding TCRE and ZEC components, frameworks for investigating the processes and contributions to TCRE, ZEC, and identifying where uncertainty comes from, focus on Land/Ocean processes (e.g., CO2 fertilization, permafrost; ocean co-uptake of heat/CO2)
- Observational or Emergent constraints
- Use of simple models/emulators and model hierarchy.

The interactions between aerosols, climate, weather, and society are among the large uncertainties of current atmospheric research. Mineral dust is an important natural source of aerosol with significant implications on radiation, cloud microphysics, atmospheric chemistry, and the carbon cycle via the fertilization of marine and terrestrial ecosystems. Together with other light-absorbing particles, dust impacts snow and ice albedo and can accelerate glacier melt. In addition, properties of dust deposited in sediments and ice cores are important (paleo-)climate indicators.

This interdivisional session -- building bridges between the EGU divisions AS, CL, CR, SSP, BG and GM -- had its first edition in 2004 and it is open to contributions dealing with:

(1) measurements of all aspects of the dust cycle (emission, transport, deposition, size distribution, particle characteristics) with in situ and remote sensing techniques,
(2) numerical simulations of dust on global, regional, and local scales,
(3) meteorological conditions for dust storms, dust transport and deposition,
(4) interactions of dust with clouds and radiation,
(5) influence of dust on atmospheric chemistry,
(6) fertilization of ecosystems through dust deposition,
(7) interactions with the cryosphere, including also aerosols other than dust,
(8) any study using dust as a (paleo-)climate indicator, including sediment archives in loess, ice cores, lake sediments, ocean sediments and dunes,
(9) impacts of dust on climate and climate change, and associated feedbacks and uncertainties,
(10) implications of dust for health, transport, energy systems, agriculture, infrastructure, etc.

We especially encourage the submission of papers that integrate different disciplines and/or address the modelling of past, present, and future climates.

We are delighted to announce that in the 22nd edition of the dust session, Dr Patricia Castellanos (NASA) will provide a solicited talk about her work on airborne observations of dust.

The climate system exhibits complex variability across different timescales. Part of this complexity is influenced by the teleconnections, recurring patterns in the atmosphere and ocean that strongly shape the regional climate variability and climate change. However, given the large internal variability and strong external forcings involved, understanding the role of teleconnections in climate variability and change remains challenging. Statistical, dynamical and modelling approaches have provided many insights to date. More recently, the integration of these approaches has developed rapidly, and new data-driven approaches are becoming widespread. This session aims to bring together researchers using any combination of these approaches to explore climate variability, teleconnections across timescales from synoptic scale to long-term change, and in particular, how variability on different timescales is connected. The physical explainability and interpretability of statistical and modelling results as well as the accurate and appropriate use of statistics in physics-centred research are a focus of the session.
We invite contributions that address one or more of the following topics: disentangling variability in teleconnections and their influence on regional climate, dynamics and predictive potential of teleconnections, the influence of large-scale changes in driving future regional climate change, understanding model-observation discrepancies in climate variability and teleconnections.
Studies that employ innovative approaches to bridge statistical analysis and physical understanding are particularly encouraged, including but not limited to machine learning techniques, causal inference methods, storyline approaches, Bayesian methods, and novel diagnostics for teleconnections.

To address societal concerns over rising sea levels and associated extreme events and to quantify the impacts of sea-level changes on coastal communities, ecosystems and the global economy it is key to understand the contributions to these changes. In this session, we respond to this need and invite contributions from the international sea level community that improve our knowledge of the past, present and future changes in global and regional sea levels, extreme events and coastal impacts.

The session focuses on studies exploring the physical mechanisms for sea level rise and variability as well as the drivers of these changes, at any time scale (from paleo sea level to high-frequency phenomena to long-term projections), using observations and/or model simulations. Investigations on linkages between variability in sea level, heat and freshwater content, ocean dynamics, land subsidence and mass exchanges between the land and the ocean associated with ice sheet and glacier mass loss and changes in the terrestrial water storage are welcome. Studies focusing on future sea level changes are encouraged, as well as those assessing short-, medium-, and long-term impacts on coastal environments and their implications.

Oxygen in the ocean is key to biogeochemical cycling in the marine environment and is a fundamental requirement for most marine life. Additionally, human-induced global temperature rise and nutrient runoff from land are causing a significant decline in oxygen levels in marine settings. Ocean’s oxygen has declined in the past, when so-called “deoxygenation events” have perturbed the ocean carbon cycle, leading to the deposition of organic-rich layers both in marginal seas (sapropels events) and open ocean (oceanic anoxic events) settings. The drivers behind marine deoxygenation are complex, involving diverse biogeochemical processes operating over different timescales. This prompts the need for interdisciplinary research on marine ocean oxygen dynamics to better contextualize current and future scenarios, combining expertise from modern and paleo-oceanography, geochemistry, sedimentology, and Earth system modeling across various temporal and spatial scales. This session encourages contributions that enhance our understanding of the nature, drivers, and timing of changes in ocean oxygen dynamics in the past, present and future globally and/or locally and across various timescales (seasonal to multimillion-year). We particularly welcome studies that 1) provide new insights into the response of marine oxygen to shifting climate states and environmental conditions, and/or links to the biogeochemical cycling of carbon and nutrients in the ocean from geological archives and/or modern settings, and 2) assess future oxygen dynamics with possible implications for marine ecosystems, marine productivity, global carbon cycling, and/or the evolution of oxygen minimum zones. We invite studies based on both observational data and numerical model simulations, and on innovation and advancement in proxy development and -application specific to the investigation of marine oxygenation. By broadening our perspective on the mechanisms and timescales of ocean deoxygenation, this session aims to deliver key, quantitative information on the oxygen dynamics in the past oceans that will contribute to projections of future ocean oxygen levels in a warming world.

The Southern Ocean and Antarctic ice sheet stability play a critical role for global ocean circulation, climate, 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, stratification, sea ice, nutrient distribution and utilization, lithogenic inputs and oceanic fronts 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 for reconstructing polar paleoclimate.

Mediterranean climate regions of the world are located in transitional midlatitude zones like the Mediterranean basin, western North America and small coastal areas of western South America, southern Africa and southern Australia. This transitional character makes them highly vulnerable to climate change. In all these Mediterranean climate regions, the future holds high risks and uncertainty on biodiversity, aridity, ecosystems, and on the sustainability and resilience of socio-economic systems. Innovative approaches to develop and test effective and sustainable climate adaptation and mitigation are, therefore, required. Understanding the past, characterizing the present and modeling the future are essential steps to estimate the risks and to assess the impacts of climate change.

This session intends to strengthen the exchanges among the communities studying the Mediterranean climate regions of the world to promote a multi-disciplinary approach in identifying and preparing shared solutions and practices. Studies of observed past changes and/or future climate projections focused on physical (including extremes, teleconnections, hydrological cycle) and biogeochemical (including biodiversity) aspects of Mediterranean climate regions are welcome. Similarly, climate change related social aspects including indigenous knowledge in mitigating climate risks are well received. Analyses where multiple Mediterranean climate-type regions are considered and compared are highly appreciated. In addition, as a multidisciplinary MedCLIVAR session we encourage contributions from a broad range of disciplines and topics dealing with dynamics and processes of the climate system, sectoral impacts of climate change, climate change adaptation and innovative methods and approaches in climate science.

The Arctic Ocean is experiencing significant amplitude changes with profound consequences for the cryosphere and exchanges through Pacific and Atlantic gateways. However, the fate of the Arctic realm, including land, ocean and gateways, has very large uncertainties, with possible retroactions at large subcontinental to global scales. Knowledge about the Arctic changes at time scales encompassing from the early Cenozoic to the present and beyond, based on observations and modelling, are instrumental to narrow uncertainties for the future. The objective of the session is to bring together the diverse community of experts, including biologists, physical oceanographers, modelers, paleoclimatologists, and others, to encourage interdisciplinary dialogue and enhance knowledge of the processes influencing Arctic changes.

While significant advances have been made recently in our understanding of the Indian Ocean’s physical, biogeochemical, and ecological characteristics and their variability across a range of spatial and temporal scales, significant gaps in our knowledge remain in observing, modeling, and predicting the Indian Ocean’s changing environmental conditions and its role in regional and global climate.
This session invites contributions based on observations, modelling, theory, and palaeo proxy reconstructions in the Indian Ocean 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 links between Indian Ocean variability and monsoon systems. We especially encourage submissions on weather and climate extremes of societal relevance in the Indian Ocean and surrounding regions, their prediction, as well as the evaluation of climate risks, vulnerability, resilience, and adaptation and mitigation strategies. We also welcome contributions that address research on the Indian Ocean, using advanced techniques such as machine learning.

The preservation, protection, and fruition of cultural heritage are closely related to the scientific knowledge of the component materials, their history and surrounding environment, and how these affect the characteristics and transformation of historical objects, structures, and sites. Geosciences represent a valuable partner for studies in conservation science and archaeometry, providing a solid background for addressing a number of questions revolving around natural and artificial geomaterials (stones, ceramics, mortars, pigments, glasses, metals, etc.), their features and settings. This session welcomes contributions showcasing the application of geosciences to the following topics:
- properties, provenance, production, use, and durability of historical materials;
- weathering processes, simulations, modeling, vulnerability assessment, and risk scenarios;
- field and laboratory methods of analysis and testing, especially by non-destructive and non-invasive techniques;
- novel and sustainable methods and products for conservation and restoration;
- impact of environmental variables (related to microclimate, climate, climate change, and composition of air, waters, and soils) outdoors, indoors, underground, or underwater;
- identification of possible adaptation measures;
- hardware/software design for collecting and processing compositional and environmental databases.

The Southern Ocean is vital to our understanding of the climate system. It is a key region for vertical and lateral exchanges of heat, freshwater, carbon, oxygen, and nutrients, with significant past and potential future global climate implications, especially around the latitudes of the Antarctic Circumpolar Current, which is the focus region for this session. The role of the Southern Ocean as a dominant player in heat and biogeochemical exchanges as well as its response to changing atmospheric forcing and increased Antarctic melting remains uncertain. Indeed, the sparsity of observations of this system and its inherent sensitivity to small-scale physical processes, not fully represented in current Earth System Models, result in large climate projection uncertainties and considerable discrepancies between observations and models. To address these knowledge gaps, the Southern Ocean is currently subject to investigations with increasingly advanced observational platforms as well as theoretical, numerical and machine learning techniques. These efforts are providing deeper insight into the three-dimensional patterns of Southern Ocean changes on sub-annual, multi-decadal and millennial timescales, as well as their potential future modifications under a changing climate. In this session, we welcome contributions concerning the role of the Southern Ocean in past, present, and future climates. These include (but are not limited to) small-scale physics and mixing, water mass transformation, gyre-scale processes, nutrient and carbon cycling, ventilation, ocean productivity, climate-carbon feedbacks, and ocean-ice-atmosphere interactions. We also welcome contributions on how changes in Southern Ocean circulation as well as heat and carbon transport affect lower latitudes and global climate more generally.

Ice sheets play an active role in the climate system by amplifying, pacing, and potentially driving global climate change over a wide range of time scales. The impact of interactions between ice sheets and climate include changes in atmospheric and ocean temperatures and circulation, global biogeochemical cycles, the global hydrological cycle, vegetation, sea level, and land-surface albedo, which in turn cause additional feedbacks in the climate system. This session will present data from climate proxies and direct measurements and modelling results that examine ice sheet interactions with other components of the climate system over several time scales, ranging from millennial to centennial and even decadal timescales to investigate climate variability. Among other topics, issues to be addressed in this session include ice sheet-climate interactions from glacial-interglacial cycles, the role of ice sheets in Cenozoic global cooling and the mid-Pleistocene transition, reconstructions of past ice sheets and sea level during warmer and colder periods than pre-industrial times, the current and future evolution of the ice sheets, and the role of ice sheets in abrupt climate change.

The atmospheric water cycle is a key component of the climate system, and links across many scientific disciplines. Processes interact with dynamics at different scales throughout the atmospheric life cycle of water vapour from evaporation to precipitation. This session sets the focus on understanding the interaction between processes, their dynamics and characteristics of the water cycle, covering the entire atmospheric life cycle from evaporation, atmospheric moisture transport, to cloud microphysics and precipitation processes as observed from in-situ and remote sensing instrumentation, recorded by paleo-/climate archives, and as simulated by models for past, present and future climates.

We invite studies

* focusing on the understanding and impacts of features of the atmospheric water cycle related to weather systems, with a special focus on the role of Atmospheric Rivers, Cold-Air Outbreaks, Warm Conveyor Belts, Tropical Moisture Exports, and the global Monsoon systems;

* investigating the large-scale drivers behind the past, ongoing and future variability and trends within the atmospheric water cycle, from field campaigns (YOPP, MOSAiC, (AC)3, ISLAS, EUREC4A etc.), long-term observations, reanalysis data, regional to global model simulations, or (isotopic) data assimilation;

* reconstructing past hydroclimates based on paleo-proxy records from archives such as ice cores, lake sediments, tree-rings or speleothems;

* applying methods such as tagged water tracers and Lagrangian moisture source diagnostics to identify source-sink relationships and to evaluate model simulations of the water cycle;

* using the isotopic fingerprint of atmospheric processes and weather systems to obtain new mechanistic insights into changes in the water cycle;

* describing the global and regional state of the atmospheric water cycle (e.g. monsoon systems) with characteristics such as the recycling ratio, life time of water vapour, and moisture transport properties.

We particularly encourage contributions linking across neighbouring disciplines, such as atmospheric science, climate, paleoclimate, glaciology, and hydrology.

Atmospheric rivers (ARs) are narrow and transient filaments of intense water vapor transport in the lower troposphere. They account for 90% of poleward moisture transport and drive high-impact weather extremes all around the globe. Future projections suggest that landfalling ARs will become even more hazardous as they further intensify in a warmer climate. Given the fundamental role of ARs in the global water cycle, relevant research is rapidly expanding across different disciplines. With new data sources and novel methodological approaches, the multidisciplinary AR community has been breaking ground and posing fundamental questions for the understanding of AR processes and impacts.

By bringing together experts from diverse disciplines, this session aims to provide a comprehensive platform for discussing the latest advances in AR science. We invite all contributions that aim at a better understanding of AR uncertainties, processes, and impacts across past, present, and future climates. Relevant topics of the session include, but are not limited to:

• Observation, identification, and monitoring of ARs
• Physical, dynamical, & microphysical aspects of ARs
• Aerosol & biochemical aspects of ARs
• Environmental and socioeconomic impacts of AR-induced weather extremes
• ARs as a component of compound events
• AR dynamics and impacts in understudied regions
• Role of ARs in the changing Cryosphere
• Forecasting of ARs
• ARs in past, present, and future climates

The Quaternary Period (last 2.6 million years) is characterized by frequent and abrupt climate swings and rapid environmental change. Studying these changes requires accurate and precise dating methods that can be effectively applied 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 luminescence 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 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. 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.

Homogeneous long-term data records (i.e., well calibrated quality-controlled data that are forced to look like a common reference) are essential for researching, monitoring, or attenuating changes in climate, for example to describe the state of climate or to detect climate extremes. Likewise, reanalysis requires harmonized data records (i.e., well calibrated quality-controlled data that maintained the unique nature of each sensor). Climate data records need to be screened and cleared from artificial non-climatic temporal and/or spatial effects, such as gradual degradation of instruments, jumps due to instruments changes, jumps due to observation practices changes, or jumps due to changes of station location and exposure. The magnitude and uncertainty of these gradual and/or abrupt changes determines their suitability for climate trend analyses. Therefore, data intended for applications, such as making a realistic and reliable assessment of historical climate trends and variability, require consistently homogenized and/or harmonized data records including measurement uncertainties.

The above described artificial non-climatic effects influence the quality of different Essential Climate Variables (ECVs), including atmospheric (e.g., air temperature, precipitation, wind speed), oceanic (e.g., sea surface temperature), and terrestrial (e.g., albedo, snow cover) variables.

Our session calls for contributions, using data records from i) in-situ observing networks, ii) satellite observing systems, iii) reanalysis products, and/or iii) climate/earth-system model simulations based data records, on the:
• calibration, quality control, homogenization/harmonization and validation of either Fundamental Climate Data Records (FCDRs) and/or Essential Climate Variables data records (CDRs);
• development of new data records and their analysis (spatial and temporal characteristics, particularly of extremes);
• examination of observed trends and variability, as well as studies that explore the applicability of techniques/algorithms to data of different temporal resolutions (annual, seasonal, monthly, daily, and sub-daily);
• rescue and analysis of centennial meteorological observations, with focus on data prior to the 1960s, as a unique source to fill in the gap of knowledge of climate variability over century time-scales.

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. We anticipate that this session will provide a platform for discussing the progress of RCM-related research and fostering future collaborations.

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.

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 growing private sector playing the role of service provider is important to understand what are the roles and the responsibilities of the publicly funded provision of climate data and information and 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 strongly encouraged from international efforts (GFCS, CSP, …); European Initiatives (HE, ERA4CS, C3S, ClimatEurope, ECRA, JPI-Climate…) as well as national, regional and local experiences.

In recent years, machine learning (ML) and artificial intelligence (AI) have emerged as powerful tools for weather forecasting and detection of extreme weather and climate events. The application of data-driven algorithms across different temporal and spatial scales has shown great promise in predicting phenomena such as hurricanes, floods, heatwaves, and droughts and improving the accuracy and timeliness of climate projections.



This session seeks contributions exploring the development and application of ML or ML-enhanced algorithms for forecasting weather and climate at multiple timescales and for detecting and forecasting extreme weather and climate events. We encourage submissions that address the use of AI for meteorological forecasts, extended-range forecasts, sub-seasonal to seasonal climate forecasts, or longer-term climate projections, spanning local to global spatial scales. We also welcome studies that integrate ML with physical mechanisms, leading to AI-driven advancements that improve the representation of climate variables in numerical models or climate datasets.

By bringing together experts from AI, data science, meteorology, and climate science, this session aims to foster interdisciplinary collaborations that push the boundaries of weather and climate forecasting and understanding extreme weather and climate events. We encourage submissions from early-career scientists, established researchers, and industry professionals alike.

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.

Geodesy contributes to atmospheric science by providing some of the essential climate variables of the Global Climate Observing System. In particular, water vapor is currently under-sampled in meteorological and climate observing systems. Thus, obtaining more high-quality humidity observations is essential for weather forecasting and climate monitoring. The production, exploitation and evaluation of operational GNSS Meteorology for weather forecasting is well established in Europe thanks to over 20 years+ of cooperation between the geodetic community and the national meteorological services. Improving the skill of NWP models, e.g., to forecast extreme precipitation, requires GNSS products with a higher spatio-temporal resolution and shorter turnaround. Homogeneously reprocessed GNSS data have high potential for monitoring water vapor climatic trends and variability. With shorter orbit repeat periods, SAR measurements are a new source of information to improve NWP models. Using NWP data within RT GNSS data analysis can initialize PPP algorithms, thus reducing convergence times and improving positioning. GNSS signals can also be used for L-band remote sensing when Earth-surface reflected signals are considered. GNSS-R contributes to environmental monitoring with estimates of soil moisture, snow depth, ocean wind speed, sea ice concentration and can potentially be used to retrieve near-surface water vapor.
We welcome, but not limit, contributions on:
• Estimates of the neutral atmosphere using ground- and space-based geodetic data and their use in weather forecasting and climate monitoring
• Retrieval and comparison of tropospheric parameters from multi-GNSS, VLBI, DORIS and multi-sensor observations
• Now-casting, forecasting, and climate research using RT and reprocessed tropospheric products, employing NWP and machine learning
• Assimilation of GNSS tropospheric products in NWP and in climate reanalysis
• Production of SAR tropospheric parameters and assimilation thereof in NWP
• Homogenization of long-term GNSS and VLBI tropospheric products
• Delay properties of GNSS signals for propagation experiments
• Exploitation of NWP data in GNSS data processing
• Techniques for soil moisture retrieval from GNSS data and for ground-atmosphere boundary interactions
• Detection and characterization of sea level, snow depth and sea ice changes, using GNSS-R
• Investigating the atmospheric water cycle using satellite gravimetry

Recent Earth System Sciences (ESS) datasets, such as those resulting from high-resolution numerical modelling, have increased both in terms of precision and size. These datasets are central to the advancement of ESS for the benefit of all stakeholders, and public policymaking on climate change. Extracting the full value from these datasets requires novel approaches to access, process, and share data. It is apparent that datasets produced by state-of-the-art applications are becoming so large that even current high-capacity data infrastructures are incapable of storing, let alone ensuring their usability. With future investment in hardware being limited, a viable way forward is to explore the possibilities of data compression and new data space implementation.

Data compression has gained interest for making data more manageable, speeding up transfer times, and reducing resource needs without affecting the quality of scientific analyses. Reproducing recent ML and forecasting results has become essential for developing new methods in operational settings. At the same time, replicability is a major concern for ESS and downstream applications and the necessary data accuracy needs further investigation. Research on data reduction and prediction interpretability helps improve understanding of data relationships and prediction stability.

In addition, new data spaces are being developed in Europe, such as the Copernicus Data Space Ecosystem and Green Deal Data Space, as well as multiple national data spaces. These provide access to data, through streamlined access, cloud processing and online visualization generating actionable knowledge enabling more effective decision-making. Analysis ready data can easily be accessed via API transforming data access and processing scalability. Developers and users will share opportunities and challenges of designing and using data spaces for research and industry.

This session connects developers and users of ESS big data, discussing how to facilitate the sharing, integration, and compression of these datasets, focusing on:
1) Approaches and techniques to enhance shareability of high-volume ESS datasets: data compression, novel data space implementation and evolution.
2) The effect of reduced data on the quality of scientific analyses.
3) Ongoing efforts to build data spaces and connect with existing initiatives on data sharing and processing, and examples of innovative services that can be built upon data spaces.

Cloud computing has emerged as a dominant paradigm, supporting industrial applications and academic research on an unprecedented scale. Despite its transformative potential, transitioning to the cloud continues to challenge organizations striving to leverage its capabilities for big data processing. Integrating cloud technologies with high-performance computing (HPC) unlocks powerful possibilities, particularly for computation-intensive AI/ML workloads. With innovations like GPUs, containerization, and microservice architectures, this convergence enables scalable solutions for Earth Observation (EO) and Earth System Modeling domains.
Pangeo (pangeo.io) represents a global, open-source community of researchers and developers collaborating to tackle big data challenges in geoscience. By leveraging a range of tools—from laptops to HPC and cloud infrastructure—the Pangeo ecosystem empowers researchers with an array of core packages, including Xarray, Dask, Jupyter, Zarr, Kerchunk, and Intake.
This session focuses on use cases involving both Cloud and HPC computing and showcasing applications of Pangeo’s core packages. The goal is to assess the current landscape and outline the steps needed to facilitate the broader adoption of cloud computing in Earth Observation and Earth Modeling data processing. We invite contributions that explore various cloud computing initiatives within these domains, including but not limited to:
This session aims to:
• Assess the current landscape and outline the steps needed to facilitate the broader adoption of cloud computing in Earth Observation and Earth Modeling data processing.
• Inspire researchers using or contributing to the Pangeo ecosystem to share their insights with the broader geoscience community and showcasenew applications of Pangeo tools addressing computational and data-intensive challenges.
We warmly welcome contributions that explore:
• Cloud Computing Initiatives: Federations, scalability, interoperability, multi-provenance data, security, privacy, and sustainable computing.
• Cloud Applications and Platforms: Development and deployment of IaaS, PaaS, SaaS, and XaaS solutions.
• Cloud-Native AI/ML Frameworks: Tools designed for AI/ML applications in EO and ESM.
• Operational Systems and Workflows: Cloud-based operational systems, data lakes, and storage solutions.
• HPC and Cloud Integration: Converging workloads to leverage the strengths of both computational paradigms.
In addition, we invite presentations showcasing applications of Pangeo’s core packages in:
• Atmosphere, Ocean, and Land Modeling
• Satellite Observations
• Machine Learning
• Cross-Domain Geoscience Challenges
This session emphasizes real-world use cases at the intersection of cloud and HPC computing. By sharing interactive workflows, reproducible research practices, and live executable notebooks, contributors can help map the current landscape and outline actionable pathways toward broader adoption of these transformative technologies in geoscience.

The Arctic region has undergone drastic changes over the last decades, with sea ice decline being the most obvious and prominent example. The ice cover has become thinner and more fragile, drifting faster and more freely. Extreme temperatures are now more common, with 2023 recording the warmest summer temperatures ever. The Arctic has warmed nearly four times faster than the rest of the world, accelerating ice sheet melting, sea ice loss in the Kara and Laptev Seas, permafrost thawing, glacier retreat, and forest fires. The resulting changes in the Arctic Ocean include an increased freshwater volume, heightened coastal runoff from Siberia and Greenland, and greater exchanges with the Atlantic and Pacific Oceans, all of which have significant consequences for the fragile Arctic ecosystems.

As global temperatures continue to rise, model projections suggest that the Arctic Ocean could become seasonally ice-free by mid-century, raising critical questions for the Arctic research community: What could the Arctic Ocean look like in the future? How will the present changes in the Arctic affect and be affected by the lower latitudes? Which oceanic processes drive this sea-ice loss and how will they change in a sea ice-free Arctic? What aspects of the changing Arctic should observational, remote sensing and modeling programs prioritize?

In this session, we invite contributions from a variety of studies on the recent past, present and future Arctic. We welcome submissions that explore interactions between the ocean, atmosphere, and sea ice; Arctic processes and feedbacks; small-scale processes, internal waves, and mixing; and the interactions between the Arctic and global oceans. We especially welcome submissions that take a cross-disciplinary approach, focusing on new oceanic, cryospheric, and biogeochemical processes as well as their connections to land.

We want to spark discussions on future plans for Arctic Ocean measurement, remote sensing, and modeling strategies, including the upcoming CMIP7 cycle and ways to validate and improve models using observations. We encourage submissions on CMIP modeling approaches and recent observational programs like MOSAiC, the Nansen Legacy Project and the Synoptic Arctic Survey. We also welcome anyone involved in planning the upcoming International Polar Year 2032-33 to participate in our session and contribute to the discussions.

All science has uncertainty. Global challenges such as the Covid-19 pandemic and climate change illustrate that an effective dialogue between science and society requires clear communication of uncertainty. Responsible science communication conveys the challenges of managing uncertainty that is inherent in data, models and predictions, facilitating the society to understand the contexts where uncertainty emerges and enabling active participation in discussions. This session invites presentations by individuals and teams on communicating scientific uncertainty to non-expert audiences, addressing topics such as:

(1) Innovative and practical tools (e.g. from social or statistical research) for communicating uncertainty
(2) Pitfalls, challenges and solutions to communicating uncertainty with non-experts
(3) Communicating uncertainty in risk and crisis situations (e.g., natural hazards, climate change, public health crises)

Examples of research fitting into the categories above include a) new, creative ways to visualize different aspects of uncertainty, b) new frameworks to communicate the level of confidence associated with research, c) testing the effectiveness of existing tools and frameworks, such as the categories of “confidence” used in expert reports (e.g., IPCC), or d) research addressing the challenges of communicating high-uncertainty high-impact events.

This session encourages you to share your work and join a community of practice to inform and advance the effective communication of uncertainty in earth and space science.

Extreme event attribution (EEA) emerged in the early 2000s to assess the impact of human-induced climate change on extreme weather events. Since then, EEA has expanded into different approaches that help us understand how climate change influences these events.

In unconditional approaches, such as the risk-based method, the oceanic and atmospheric conditions are largely left unconstrained. In contrast, conditional approaches focus on constraining the specific dynamics that lead to an event. One example is the analogues approach, where the synoptic atmospheric circulation is held relatively fixed. Both approaches can be used to assess changes in the likelihood, intensity, or both, of extreme events.

In this short course, we will examine the robustness of the analogues method for EEA, explore different strategies for defining analogues, and discuss their applications in attribution studies.

The concepts and tools of algebraic topology can be applied to the evolution of systems in both phase space and physical space, as well as to the interesting back-and-forth excursions between these two spaces. The way that dynamics and topology interact is at the core of the present course.

Starting with the early contributions of knot theory to nonlinear dynamics, we introduce the templex, a novel concept in algebraic topology that considers a flow in physical or phase space with no restrictions to its dimensions, drawing on both homology groups and graph theory. The templex approach is illustrated through its application to paradigmatic chaotic attractors – like the Lorenz or Rössler attractors – as well as to non-chaotic flows. Applications to kinematic and dynamic models of the ocean gyres and to idealized models of the Atlantic Meridional Overturning Circulation (AMOC) are presented, along with the topological analysis of oceanographic time series derived from altimetric velocity fields. Lagrangian ocean analysis is a key element of the course.

The extension of the templex concept to the noise-perturbed chaotic attractors of random dynamical systems theory is presented, leading to the definition of topological tipping points (TTPs). TTPs enable the study of successive bifurcations of climate models beyond those known from the classical theory of autonomous dynamical systems, as well as of those more recently added by consideration of tipping points in nonautonomous systems.

We thus propose to start a journey through the mathematical concepts and tools that characterize the topological approach to nonlinear dynamics. This approach goes beyond purely metric, i.e., non-topological, descriptions of the mechanisms that are responsible for higher and higher versions of irregular behavior, from deterministic chaos to various forms of turbulence. These novel tools provide challenging and promising inroads for understanding the effects of anthropogenic forcing on the climate system’s intrinsic variability.

During the past 75 years, radiocarbon dating has been applied across a wide range of disciplines, including, e.g. archaeology, geology, hydrology, geophysics, atmospheric science, oceanography, and paleoclimatology, to name but a few. Radiocarbon analysis is extensively used in environmental research as a chronometer (geochronology) or as a tracer for carbon sources and natural pathways. In the last two decades, advances in accelerator mass spectrometry (AMS) have enabled the analysis of very small quantities, as small as tens of micrograms of carbon. This has opened new possibilities, such as dating specific compounds (biomarkers) in sediments and soils. Other innovative applications include distinguishing between old (fossil) and natural (biogenic) carbon or detecting illegal trafficking of wildlife products such as ivory, tortoiseshells, and fur skins. Despite the wide range of applications, archives, and systems studied with the help of radiocarbon dating, the method has a standard workflow, starting from sampling through the preparation and analysis, arriving at the final data that require potential reservoir corrections and calibration.

This short course will provide an overview of radiocarbon dating, highlighting the state-of-the-art methods and their potential in environmental research, particularly in paleoclimatology. After a brief introduction to the method, participants will delve into practical examples of its application in the study of past climates, focusing on the 14C method and how we arrive at the radiocarbon age.
Applications in paleoclimate research and other environmental fields
Sampling and preparation
Calibration programs
We strongly encourage discussions around radiocarbon research and will actively address problems related to sampling and calibration. This collaborative approach will enhance the understanding and application of radiocarbon dating in the respective fields.

In a changing climate world, extreme weather and climate events have become more frequent and severe, and are expected to continue increasing in this century and beyond. Unprecedented extremes in temperature, heavy precipitation, droughts, storms, river floodings and related hot and dry compound events have increased over the last decades, impacting negatively broad socio-economic spheres (such as agriculture), producing several damages to infrastructure, but also putting in risk human well-being, to name but a few. The above have raised many concerns in our society and within the scientific community about our current climate but our projected future. Thus, a better understanding of the climate and the possible changes we will face, is strongly needed. . In order to give answers to those questions, and address a wide range of uncertainties, very large data volumes are needed across different spatial (from local-regional to global) and temporal scales (past, current, future), but sources are multiple (observations, satellite, models, reanalysis, etc), and their resolution may vary each other. To deal with huge amounts of information, and take advantage of their different resolution and properties, high-computational techniques within Artificial Intelligence models are explored in climate and weather research. In this short-course, a novel method using Deep Learning models to detect and characterize extreme weather and climate events will be presented. This method can be applied to several types of extreme events, but a first implementation on which we will focus in the short-course, is its ability to detect past heatwaves. Discussions will take place on the method, and also its applicability to different types of extreme events. The course will be developed in python, but we encourage the climate and weather community to join the short-course and the discussion!