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.

Climate change results from atmosphere constituent modulation affecting the top-of-atmosphere energy balance, or land use changes at the Earth’s surface, altering surface albedo, amongst other “forced” changes. These natural or anthropogenic climate drivers are termed “climate forcing” agents. This session highlights research assessing and quantifying uncertainties in forcing agent evolution and their climate influence using Earth System Model simulations, or Earth observations. We invite contributions on all climate forcing research aspects, including the development of historical and future forcing time-series, analyses that use idealized, single- or multi-model approaches, or observational methods to evaluate the climate change impacts. We are especially interested in studies that examine the responses to forcing changes through time, using next-generation (CMIP7), current (CMIP6, CMIP6Plus), or previous CMIP phases. Research considering multiple components of the climate system (the ocean, atmosphere, cryosphere, land surface/subsurface, and biology) is highly encouraged.

The Coupled Model Intercomparison Project (CMIP) is instrumental in advancing our understanding of the Earth’s climate system and its future projections. However, Earth system models (ESM) exhibit disparities in critical aspects, particularly in their responses to anthropogenic forcings and the dynamical coupling of physical and biogeochemical systems. Given that the Earth system science community, and notably the IPCC, relies on CMIP outputs to inform policy and mitigation strategies, it becomes imperative to address these inherent uncertainties through a multidisciplinary approach that unites atmospheric, oceanic, and terrestrial modeling analyses. In this session, we invite studies that investigate uncertainties and model disagreements across all facets associated with the CMIP ensembles. These may include, but are not limited to, the following contributions:

1. Identification of processes and key entities with significant disparities across CMIP models: Quantifying sources of uncertainty across CMIP models, which may include i) internal variability, ii) process representations/model parameterization, iii) ESM architecture, and iv) external forcing.

2. Use of reduced complexity models and emulators: Exploring the uncertainty range with computationally fast model approaches, particularly the parts of the distribution not well represented by the CMIP ensembles.

3. Critical scientific priorities for future CMIP/Earth system model development: Recognizing and comprehending uncertainties and their underlying mechanisms are essential for guiding future model development and refining climate projections. We welcome contributions that focus on enhancing model performance and reducing uncertainties across disciplines for future CMIP iterations.

4. Opportunities, challenges, and constraints in using CMIP output for impact research: Uncertainties are amplified at regional scales; nevertheless, CMIP model projections are extensively utilized for impact studies by researchers unfamiliar with these sources of uncertainty and structural limitations of CMIP projections. We invite contributions that use innovative approaches to address these challenges in impact studies with CMIP output.

In summary, this session aims to foster collaboration and dialogue among climate scientists and modelers to increase the efficient use of CMIP output and meet the pressing challenges of climate change.

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.

Recent evaluations on the current states of the Earth system (e.g. the latest assessment of the nine Planetary Boundaries) and the integrity of the Earth system emphasize the alarming decline in Earth’s resilience, stability, and life support systems. Human activities are driving us beyond critical planetary boundaries, marking the onset of the Anthropocene—the current era in which humanity has become a geological force, significantly altering Earth's system processes and environments on a global scale. Earth’s resilience, stability, and life support systems are shaped by complex, non-linear interactions between biophysical processes and human influences. Such interactions encompass the carbon cycle, atmospheric systems, oceans, large-scale ecosystems, the cryosphere, and the increasing disruptions caused by socio-economic dynamics. In addition, as human pressures escalate, the risk of breaching key self-regulating feedbacks in the Earth system grows—potentially pushing critical components like the large ice sheets, the AMOC, and biomes such as the Amazon rainforest beyond tipping points. Crossing these thresholds could trigger abrupt, large-scale, and often irreversible changes that threaten ecosystems and human societies alike. Thus, a comprehensive understanding of the current state of planetary boundaries on a frequent basis is required. Owing to current technological advancements in Earth observation systems, as well as advanced AI-based solutions (e.g., large language models (LLMs) and Vision LLMs), such objectives can be attained. However, achieving this requires bringing together expertise from various disciplines, including geosciences, ecology, remote sensing, data science, socio-environmental sciences, and beyond.
In this session, we invite contributions from geoscientists, remote sensing specialists, data scientists, ecologists, climate modelers, and other relevant fields to explore how we can better measure and assess the planetary boundaries in the Earth system. We aim to foster interdisciplinary collaboration on identifying critical thresholds, understanding feedback mechanisms, and developing methods to quantify resilience at planetary scales. We are particularly interested in research utilizing diverse methodological approaches—ranging from Earth system modeling and remote sensing to data-driven analyses and conceptual frameworks—focused on stability and health indicators, as well as the cascading effects of system-wide shifts.

This session addresses the escalating challenges posed by climate change in diverse arid regions worldwide, including the Middle East, Northern Africa, Eastern and South Western Africa, Southwest United States, Northern Mexico, Atacama and Patagonia regions in South America, Turkestan and Gobi regions in Central Asia, and the Australian Outback. These regions face intensifying droughts, heatwaves, fires, and occasional unexpected flood events, as recently observed in the Arabian Peninsula. This session welcomes contributions exploring comprehensive strategies focusing on future climate forecasts and innovative practices for both mitigation and adaptation to climatic extremes. Central to the discussion are climate variability and climate change impacts specific to arid environments, emphasizing water-vegetation-climate interactions and their implications for the resilience of ecosystems and society. Participants will delve into the potential and the foreseen impacts of water management practices such as irrigation from rainwater harvesting, groundwater and desalination, land management practices such as agriculture, afforestation and reforestation as well as climate change mitigation practices such as carbon capturing and intensification of renewable energy in arid regions. This session underscores the critical role of drought monitoring systems, weather forecasts and climate projections in supporting the aforementioned practices as well as in predicting and preparing for extreme events that could jeopardize them, informing proactive risk reduction policies. Case studies from global regions facing similar challenges will illustrate successful applications of these strategies, sharing lessons learned and best practices for effective adaptation and resilience-building.

Climate change progresses fastest in Earth’s high latitude regions. As sea ice disappears and temperatures rise, increases in fetch length and heat fluxes strengthen wind and wave strength. At the same time, a combination of permafrost thaw and sea-level rise make the region’s coastal areas particularly vulnerable to these changes in storminess. And some impacts – notably the release of carbon from wave-driven coastal erosion and wind-driven changes in ocean ventilation – are global. But despite these consequences and their societal ramifications, future changes in storminess remain poorly constrained. This session will highlight how coastal archives like lake sediments or beach ridges can fill this critical knowledge gap, by providing long-term baseline data from the past. Emphasis will be placed on reconstructions, but we invite contributions that harness the potential of instrumental and modelling data to validate proxy work. We are particularly keen to showcase the potential of emerging biological (i.e. long-distance transported pollen, diatom transfer functions), geochemical (i.e. wind-driven evaporative isotope enrichment) or sedimentological (i.e. characterization of wind- or wave-blown particles invisible to the naked eye) methods. We furthermore encourage contributions from under-studied areas with global significance like the Southern Ocean or High Arctic, and studies that focus on extreme events like tsunamis. Also welcome are societal impact studies that assess the (economic) consequences of shifts in storminess on – for example – shipping and power generation.

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 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.

Climate change disproportionately affects vulnerable populations, with children being the most susceptible to its risks. They face heightened exposure to climate and environmental hazards such as extreme heat, air pollution, and natural disasters. Understanding the current and future risks that these young populations will face due to climate and environmental changes is essential for effective advocacy and informed decision-making. It also supports the development of strategies and operations aimed at reducing the adverse impacts on children's health, safety, and well-being.
Accurate assessment of these risks for children across various geographic locations requires comprehensive, continuous, and high-resolution data. Earth observation (EO) satellites and climate system models provide powerful resources to capture the spatial and temporal dynamics of climate and environmental factors affecting children. They offer insights into trends in temperature changes, land use alterations, pollution levels, and disaster patterns, all of which are critical for understanding the specific vulnerabilities of children to climate change. However, despite their potential, there are challenges in effectively leveraging them for this purpose. Issues such as data accessibility, integration with socio-economic and demographic information, and the technical capacity required to analyze observed and modelled data need to be addressed. Moreover, translating these data insights into actionable policies and interventions for child protection presents additional complexities.
This session will integrate Earth sciences applications that enhance our understanding of the disproportionate impact of climate change on children. We will discuss successful case studies, innovative methodologies, and interdisciplinary approaches that have been employed to utilize multisource data effectively. The session will also highlight the challenges and limitations of observations and modelling data applications, offering perspectives on how to overcome these obstacles. By exploring these aspects, we aim to support efforts in measuring, mitigating, and ultimately reducing the climate-related risks faced by children globally, thus safeguarding their future.

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

As global concerns grow over the depletion of finite natural resources and the escalating impacts of climate change, addressing the complex challenges of interdependencies between water and food security becomes increasingly urgent for present and future generations. Our session seeks to explore the nexus of water and food security in greater detail, investigating how their definitions and strategies for achievement may vary across various spatial scales, ranging from local to global.

Through interdisciplinary dialogue, our session aims to bridge the gap between science, policy, and community action, inviting scientists, decision-makers, practitioners, and communities to share insights, experiences, challenges and bottlenecks, and their innovative solutions. We welcome abstract submissions that explore the multifaceted dimensions of water and food security interlinkages, including but not limited to:

1- critical analysis of water security and food security definitions and their relevance to sustainable future
2- assess interdependencies of water and food security
3- assess policy frameworks and governance structures at regional, national and global scales in respect to water-food security nexus
4- explore community-driven initiatives and partnerships that enhance resilience to water-food insecurities in vulnerable regions.

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.

Oceanic anoxia developed during the latest Ordovician glacial pulse around 444 million years ago, concomitant with the Late Ordovician Mass Extinction, and lasted for several million years into the early Silurian, as testified by geochemical proxy records and large-scale organic-rich marine black shale deposition. Yet, the mechanisms responsible for this protracted period of oceanic deoxygenation and organic carbon burial, which was an order of magnitude longer than the ocean anoxic events of the Mesozoic, as well as its coupling with the evolution of Earth's habitability and the marine biosphere, remain poorly documented. This session intends to improve our understanding of the triggers, characteristics and consequences of oceanic anoxia around the Katian–Rhuddanian boundary. We welcome contributions using sedimentology, paleontology, geochemistry, and Earth system modeling to address these questions. We especially encourage submissions providing new and innovative insights regarding the mechanisms, feedbacks, or quantitative thresholds of black shale deposition at that time.

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.

Massive volcanism, particularly from Large Igneous Provinces (LIPs), is generally thought to have triggered significant disruptions in surface climate, environmental conditions and biological evolution and extinction throughout Earth’s history. While the effects of volcanic volatiles have been extensively studied, the impact of subsequent weathering of large amount of volcanic rocks (e.g. continental and submarine flood basalt) on surface elemental cycling, climate fluctuations, and biological evolution remains less understood, particularly also regarding the timescales involved in these processes.
This session is open to studies exploring the effect of (both modern and past) volcanic rock weathering on atmospheric CO2 concentration changes, cycling of metal elements, climatic and environmental perturbations, the evolution or extinction of terrestrial and marine organisms, etc. Topics include, but are not limited to, proxy calibration in modern or diagenetic systems, experimental constraints, Earth system modelling, data-model calibrations, big data machine learning and novel proxy applications in the ancient sedimentary record. We especially encourage submissions with new and innovative insights regarding mechanisms, feedbacks, or quantitative thresholds driving the weathering of volcanic rocks and its relationship with environmental, climatic, and biological evolution.

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 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.

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.

Archaea, belonging to the domain of prokaryotes, are a crucial component of the tree of life. They are ubiquitous in contemporary surface and near-surface environments, playing a vital role in maintaining Earth's ecological functions and mediating biogeochemical cycles. They are also considered one of the earliest forms of life and recognized as a significant force driving the development of the early Earth's biosphere. However, like bacteria, archaea have left few fossil records in ancient strata, limiting research on their evolution during Earth's early history and their role in geochemical cycles. This session aims to explore the feasibility of studying the co-evolution of archaea and the earth system by leveraging large-scale, high-completeness archaeal genome data, in conjunction with known major geological events (such as the Great Oxidation Event, Snowball Earth, and the formation and breakup of supercontinents) and biogeochemical modeling. Researchers from both earth and life sciences are welcome to contribute to this session.

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.

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.

This session invites contributions that focus on the study of regional climate dynamics, seasonally-distinct climate reconstructions that may help to expose seasonal biased climate changes and the study of environmental and climatic systems that may cross tipping points during the INTIMATE timeframe (~125 kyrs to present). This session has a particular interest in novel proxy-based reconstructions, state-of-the-art chronological techniques and statistical approaches, and innovative model-generated climate records that allow new insights into rapid (natural) climate variability and spatio-temporal differences.

A key limitation of observational climate data is the length of the instrumental record. Yet the annually resolved nature of instrumental data is vital to characterize the complete range of historical climate variability. The Holocene offers a solution to extend the instrumental data framework, as global archives attributable to the Holocene record different 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 during the present warm period, as well as extreme and rare events poorly sampled up to now. Increasingly, Holocene climates 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 Holocene climate that we can begin feed this learnt climate data into climate models to not only better understand the mechanisms of climate 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 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 future climate change.

This session welcomes:
- Traditional and novel approaches to reconstructing Holocene climate at (sub)annual to centennial scales.
- Transient climate model simulations of Holocene climate and the evaluation of climate models for future climate projection.
- Inter-proxy and climate model validation approaches to test the robustness of climate reconstructions.
- Approaches using data assimilation or machine learning to understand the total climate variability at different stages of the Holocene.
- Efforts to use resolved climate data as a tool for climate services and policy.

The Arctic Ocean is presently experiencing large amplitude changes with profound consequences for the cryosphere. However, the fate of the Arctic realm, including land and ocean, has very large uncertainties, with possible retroactions at large subcontinental to global scales. In this context, the knowledge of the Arctic history at time scales encompassing the Pliocene to the present could help narrow uncertainties. Despite difficulties in accessing the Arctic and the setting of the chronostratigraphic framework, new developments in geochronology, proxy data acquisition and numerical modelling may help to revise the paleoclimate history of the Arctic Ocean. We thus think that an update on the status of the Arctic Ocean in the paleoclimate system is timely. In this session, we invite contributions on the evolution and changes in the Arctic realm from several perspectives, including stratigraphy, palaeogeography, palaeoclimatology, paleoceanography, and palaeoecology, using proxy data and/or model simulations

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.

The Arctic and Antarctic regions have undergone profound changes over the observational period, with the polar and subpolar climates playing a critical role in regulating the Earth’s energy and water budget. These changes can have detrimental effects on the unique ecosystems and the marine carbon cycle at regional to global scales. The complex processes driving these changes operate on a wide spectrum of time scales, requiring insights from various research fields to unravel the underlying mechanisms, drivers, and impacts across the land-ocean-atmosphere-cryosphere continuum of the polar regions.

This session invites contributions from various disciplines that address Arctic and Antarctic variability and change across all time scales, using observational (remote and in-situ), historical, and geological data, along with proxy records, model simulations and climate forecasts for the past, present and future. The common denominator of these studies will be their focus on a better understanding of multi-scale mechanisms and feedbacks that drive polar climate change and their broader impact on local and global climate and society. Key areas of interest for discussion include the improvement of climate predictions at high latitudes at various time scales (e.g., usage of additional observations for initialization, improved initialization methods, improved parameterizations, novel verification approaches, etc.) and the study of potential teleconnections involving lower latitudes (such as the AMOC).

Contributions that explore high-resolution modelling, climate feedbacks and tipping points, and attribution analyses are particularly welcome, along with studies that investigate long-term polar climate change across different possible future emission scenarios. Additionally, this session seeks to highlight what past warm climates can teach us about future polar and subpolar climates. We encourage submissions linking high-latitude climate variability, change, predictions, and projections to potential ecological and socio-economic impacts.

The Greenland Ice Sheet (GrIS) is losing mass at a fast pace and is currently the largest single contributor to global sea level rise. The IPCC projects a sea level rise of 0.28-1.01 meters by 2100, of which between 0.01 to 0.18 meters isexpected from GrIS. However, these estimations exclude possible severe ice-sheet instability scenarios. Recent observations of record-high temperatures, accelerated ice melt, and increased freshwater flux, accentuate the risk of overstepping tipping points in GrIS which may destabilize ocean circulation, affect weather patterns, and increase sea level beyond current predictions.
Therefore, a better constraint on the past extent and variability of the GrIS is needed to improve our understanding of its observed and projected response to changes in climate forcing.
We therefore would like to invite contributions aiming on:
1) Analysing the ice margin’s retreat and recovery in response to temperature changes, determining whether this response is linear or non-linear.
2) Identifying the ocean-climate conditions that led to near-complete deglaciation of the GrIS in the past.
3) Assessing the timing and sequence of interactions between the GrIS and polar climate over annual to decadal periods
Topics will include, but not be limited to: multi-proxy data on ice-ocean interactions, such as iceberg production and meltwater fluxes, ice core and sediment archive analyses to assess ice sheet and climate variability across past warmer-than-present climates, studies that investigate Greenland Ice Sheet variability during anomalously warm periods of the Pleistocene and Pliocene, as well as climate/ice sheet model simulations relating past and future response of the Greenland ice sheet to a warmer climate.
This session aims to foster interdisciplinary discussions and collaborations, bringing together proxy records as well as climate and ice sheet models.
The session is supported by the Danish NNF PRECISE, the ERC synergy grant Green2Ice as well as several projects funded by H2020 and Horizon Europe.

Feedback mechanisms involving clouds, vegetation, sea ice, ice sheets, ocean circulation, and the carbon cycle 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). Many uncertainties remain about the role of these feedbacks, and 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 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 characterized by changes in atmospheric CO2 concentration (pCO2) from orbital (glacial-interglacial cycle) to centennial timescales. Studying this natural variability is essential to address the current challenges of climate change. However, interpreting these changes in pCO2 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. This session focuses on Quaternary climate changes and their interactions with the carbon cycle on various temporal scales (from orbital to centennial). Special attention will be given to contributions that explore variations in carbon stocks of the different reservoirs and carbon stocks vs. fluxes between these reservoirs using different approaches such as climate modelling, field studies and multi-tracer analyses (e.g. micropaleontology, geochemistry) of marine and terrestrial sediment cores and ice archives.

As the Earth's climate continues to change with anthropogenic forcing, rising temperatures and extreme hydrological events are impacting vegetation and soil, directly altering wildfire dynamics. Recent decades have witnessed large-scale human modifications of natural land cover, amplified rates of ecosystem changes, and an increase in the intensity, extent, and frequency of wildfires. Our understanding of the dynamics of vegetation and fire and their links with atmospheric and surface conditions is mainly derived from in-situ observations and remote sensing products which are limited to the past few decades. While historical records extend our knowledge, these only add a few centuries at most. Paleo-environmental proxy records provide insights into a wide range of interactions between land cover, wildfire and climate predating human land management and anthropogenic climate change. Documenting these interactions and inferring their drivers is of utmost importance for understanding ongoing and future changes in climate and continental ecosystems. Recent years have seen an increasing number of high-resolution and multi-proxy reconstructions of vegetation dynamics, land cover, and wildfire regimes as well as novel paleo-environmental proxies and improved analysis methods. Coupled with significant improvements in simulating ecosystem dynamics and land-atmosphere interactions, these advances allow fresh insights into spatio-temporal dynamics of ecosystems in response to climatic perturbations.

We invite contributions aimed at understanding land cover, vegetation, soil, sub-surface, and wildfire dynamics from present-day, through the Quaternary into deep time, and their interactions with climate on seasonal to orbital timescales. These include: (a) regional and global-scale reconstructions of vegetation cover and composition from paleo-environmental data, (b) the development and application of innovative proxies and archives, (c) Earth system model simulations, (d) studies combining data and models, and (e) proxy system modeling and novel statistical methods to constrain vegetation and wildfire dynamics and their drivers. We also welcome contributions related to technical and analytical advancements in organic and inorganic chemical analyses, and in-situ calibration studies. Special attention is given to studies focusing on understudied regions and time intervals, and research that has the potential to inform future land management policies.

Reconstruction of past interactions between climate and environment is among the key grand challenges of Earth System Science. The focus on past environmental and climatic reconstruction on subannual to multi-decadal timescales has been growing in light of rapid changes in the climate system due to global warming and the increasing occurrence of extreme events. The goal is that climate and environmental interactions from the past can be studied in the same resolution as current and projected trends of the 21st century (i.e., seasonal, annual and decadal resolution). However, obtaining high-resolution qualitative and quantitative information from annually or even seasonally laminated climate archives remains challenging due to the limitations of conventional analytical methodologies.
Recent developments in imaging techniques laid the foundations for a unique opportunity to unlock paleoclimate signals from geological archives at µm-resolution. These techniques can continuously explore geochemical and mineralogical compositions on the sample surface at µm-resolution and include, for example, micro X-Ray Florescence (μXRF) scanning, Hyperspectral Imaging, Mass Spectrometry Imaging, or Micro-Computed Tomography (μCT) scanning. When applied to annually resolved paleoclimate archives, imaging techniques provide 2D- or 3D- μm-scale maps of proxy distribution, paving the way to generate qualitative and quantitative information of subannually to interannually resolved climate and environmental evolution. Moreover, the unprecedented resolution of these techniques has great potential to contribute to a variety of fields in Earth System Sciences beyond climate reconstruction, including investigation of diagenetic processes and microbial communities, tracking of environmental contamination or detecting cryptotephras.
This session welcomes all contributions that utilize imaging techniques on, preferably but not exclusively, seasonally or annually resolved climate archives in various fields of Earth System Sciences. We encourage the submission of abstracts on research dedicated to method developments of imaging-based proxy applications, data postprocessing and calibration, and the combination of complementary or congruent imaging techniques. We especially hope that this session will also appeal to a broader audience of geoscientists who do not focus on developing imaging techniques but who might present research supported by high-resolution scanning/imaging data.

Accurate comparisons between climate models and proxy data are critical for refining our understanding of past climate variability and mechanisms. High-resolution proxy records such as δ18O in terrestrial and marine records, offer a detailed glimpse into past climates, providing essential benchmarks for model evaluation. However, discrepancies often arise between modeled and proxy data due to differences in spatial and temporal resolution, variability, and the complex interplay of climate forcings.

This session aims to explore recent advancements in data-model comparisons, focusing on the alignment and discrepancies between climate simulations and proxy records. By integrating multi-proxy data, isotope-enabled models, and novel modeling approaches, we seek to enhance the precision of climate reconstructions and improve the understanding of the underlying mechanisms driving observed differences.

We invite contributions from a broad range of studies that address:
(1) High-resolution reconstructions of past climatic variables such as temperature, precipitation, and isotopic compositions, and their implications for data-model comparisons across various timescales and regions.
(2) Methodological advancements in proxy development and modeling, including innovations in isotope-enabled climate models, proxy system models, and data assimilation techniques that aim to reconcile differences in temporal variability and spatial representation between models and proxies.
(3) Studies focused on the impact of external forcings, such as orbital parameters, sea-level changes, and remote climate phenomena on paleoclimate variability, highlighting the role of these factors in modulating discrepancies between proxy data and model simulations.

We further welcome interdisciplinary research that contributes to robust (quantitative) interpretations of proxy records, enhances the accuracy of model-proxy comparisons, or enables comprehensive analyses of climate dynamics at regional to global scales.

What role did climate dynamics play in human evolution, the dispersal of different Homo species within and beyond the African continent, and key cultural innovations? Were dry spells, stable humid conditions, or rapid climate fluctuations the main driver of human evolution and migration? In order to evaluate the impact that different timescales and magnitudes of climatic shifts might have had on the living conditions of prehistoric humans, we need reliable and continuous reconstructions of paleoenvironmental conditions and fluctuations from the vicinity of paleoanthropological and archaeological sites. The search for the environmental context of human evolution and mobility crucially depends on the interpretation of paleoclimate archives from outcrop geology, lacustrine and marine sediments. Linking archeological data to paleoenvironmental reconstructions and models becomes increasingly important.

As a contribution towards a better understanding of these human-climate interactions the conveners encourage submission of abstracts on their project’s research on (geo)archaeology, paleoecology, paleoclimate, stratigraphy, and paleoenvironmental reconstructions. We especially welcome contributions offering new methods for dealing with difficult archive conditions and dating challenges. We hope this session will appeal to a broad audience by highlighting the latest research on paleoenvironmental reconstructions in the vicinity of key sites of human evolution, showcasing a wide variety of analytical methods, and encouraging collaboration between different research groups. Conceptual models, modelling results and model-data comparisons are warmly welcomed, as well as collaborative and interdisciplinary research.

This session asks for well-dated geoarchives that document the physical stratal evidence of the transition from Late Holocene to Anthropocene conditions: such as artificial deposits, lake, estuary or marine sediments, peat, speleothems, ice core or biological hosts such as trees or corals. The evidence for transition to the Anthropocene may include various marker signals such as changes in the types and abundance of physical materials or biota or distinct geochemical signals; ideally providing multiple proxies and/or using innovative techniques. We are interested in continuous to near-continuous records that nevertheless can extend hundreds or even thousands of years back in time, while including comparable analysis through the mid-20th century to near the present day. Presentations should focus on how, if at all, the Anthropocene can be distinguished in these archives. Studies from any continent will be considered, though presentations on archives from the Global South are especially encouraged. This session is also part of UNESCO IGCP 732 LANGUAGE of the Anthropocene.

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.

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 arid to sub-humid regions are home to >40% of the world’s population, and many prehistoric and historic cultures developed in these regions. Due to the high sensitivity of drylands to also small-scale environmental changes and anthropogenic activities, ongoing geomorphological processes under the intensified climatic and human pressure of the Anthropocene, but also the Late Quaternary geomorphological and paleoenvironmental evolution as recorded in sediment archives, are becoming increasingly relevant for geological, geomorphological, paleoenvironmental, paleoclimatic and geoarchaeological research. Dryland research is constantly boosted by methodological advances, and especially by emerging linkages with other climatic and geomorphic systems that allow using dryland areas as indicator-regions of global environmental changes.
This session aims to pool contributions dealing with past to recent geomorphological processes and environmental changes spanning the entire Quaternary until today, as well as with all types of sedimentary and morphological archives in dryland areas (dunes, loess, slope deposits, fluvial sediments, alluvial fans, lake and playa sediments, desert pavements, soils, palaeosols etc.) studied on different spatial and temporal scales. Besides case studies on archives and landscapes from individual regions and review studies, cross-disciplinary, methodical and conceptual contributions are especially welcome in this session, e.g., dealing with the special role of aeolian, fluvial, gravitational and biological processes in dryland environments and their preservation in deposits and landforms, the role of such processes for past and present societies, methods to obtain chronological frameworks and process rates, and emerging geo-technologies.

The integration of geological and archaeological methodologies proves valuable for the study of human activity and landscape evolution, especially as the application of advanced analytical methods becomes more frequent. The formation of archaeological sites is closely coupled with geomorphological processes resulting in the deposition, preservation, reworking and exposure of sediments and remains of human activity. In addition to its anthropogenic record, an archaeological site can be investigated as an archive recording the interaction of fluvial, aeolian and tectonic events that operate on various temporal and spatial scales. However, despite the shared perspectives of archaeological and geomorphological studies, those two fields are not commonly integrated within a unified holistic framework, which limits their impact.

This session is open to a wide range of studies that integrate the study of geomorphological, sedimentological and environmental proxies at archaeological sites, alongside investigations that incorporate geological approaches to address archaeological and geomorphological questions. The goal is set to provide a platform for describing common challenges and achievements that may lead to synergistic outcomes and outline directions for future cooperation and for the establishment of a common language. The session is not restricted to any specific time period or geographical area, but rather wishes to highlight methodological novelties and common challenges shared by both disciplines.

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).

We are heading towards a climate state that has not been observed through human-made measurements before, making information on past climatic states increasingly important for anticipating future Earth System changes. Presently, sea ice is rapidly declining, and it plays a crucial role in the climate system, with proxy evidence suggesting its involvement in abrupt climate shifts.

In this session, we invite studies of past climates that aim to advance the understanding of sea ice processes and associated climate changes, thereby enhancing or constraining cutting-edge climate models. We are particularly interested in studies focusing on interglacials and warm periods, as well as other periods of climatic interest. Contributions that explore both colder and warmer-than-modern climate states are particularly encouraged.

We welcome:
-Studies that refine existing records or generate new time series from ice, terrestrial, and marine cores, including sea ice proxies such as IP25 or IPSO25 in marine cores, and Bromine, Iodine, MSA, water isotopes, and sea salt sodium from ice cores.
-Investigations into sea ice as both a driver and responder to high-frequency climate variability, with data from both polar oceans exploring Antarctic and Arctic sea ice extent alongside co-recorded climate feedbacks.
-Proxy evidence of past sea ice spatial and temporal changes.
-Both proxy and model studies that link past sea ice changes with other climatic processes, such as temperature changes, moisture source variations, or major ocean state changes like AMOC.

This session aims to bring together research on past sea ice dynamics during both colder and warmer-than-modern climate states, enhancing our understanding of sea ice processes and their role in climate systems. By refining existing records and generating new data, we seek to improve climate models and our ability to predict future changes. Join us in contributing to this critical area of research at EGU2025.

Global temperature reconstructions of the Holocene indicate a warm period typically between 10-5 ka BP, the Holocene Thermal Maximum (HTM). During the HTM, temperatures across the Arctic region are estimated to have been 1-3 Celsius degrees warmer than present, sea-ice cover was reduced, and the Greenland Ice Sheet retreated beyond its present-day margin. Although not globally synchronous, the HTM is a particularly interesting period to investigate the impacts of a warming climate and a dwindling cryosphere on Arctic ecosystems. This session is organized by the PAGES working group ACME (Arctic Cryosphere Change and Coastal Marine Ecosystems). We welcome observational (proxy-based) and/or modeling studies offering new insights into the timing, magnitude and impacts of the Holocene Thermal Maximum on the Arctic region. Studies from marine as well as terrestrial settings are welcome, and we encourage multi-proxy studies as well as studies combining classical and emerging approaches (e.g. microfossils, stable isotopes, biomarkers, eDNA, proxy-model comparison).

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 and feedbacks 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.

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 global ocean absorbs, stores, and redistributes vast amounts of heat, freshwater, carbon, oxygen, and nutrients and is a main driver for shaping the global climate. Anthropogenic forcing is superimposed on the ocean’s natural variability and complex interactions and feedback occur across scales and impacting multiple scientific disciplines. For detecting and subsequently understanding the signatures of climate variability in general, and the anthropogenic part in particular, probably the most established approach is using time series records.
In this session, we invite submissions on research that make use of Eulerian (fix-point) ocean time series of Essential Ocean Variables (EOV) from observational data and/or from modelling studies. Submissions are encouraged from all ocean science disciplines, across ocean compartments – from the air/sea interface, across the water column, to sea-floor processes –, and also from integration of different observing platforms (e.g., moorings, ships, satellites, Argo floats, gliders). Research on interaction of ocean processes, their forcing, and effects are most welcome and may address themes such air/sea heat and freshwater fluxes and carbon and oxygen uptake; ocean transport; biogeochemical and biological time series; as well as deep ocean and sea-floor processes.

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.

Water resources are a strategic issue in drylands globally as these environments are by definition water-limited, making them highly sensitive to changes in regional water balances and vulnerable to extreme events such as droughts and floods. Drylands face challenges from changing hydrological conditions and landscapes, driven by climatic and anthropogenic factors, affecting freshwater availability and quality. However, many aspects of the functioning of these systems are poorly understood or often treated in a disciplinary manner. Yet, interdisciplinary research is essential to improve the understanding of hydroclimatic processes in these regions and the human impacts on water resources, to achieve sustainable development goals. We welcome submissions focusing on processes in dryland research across a broad geographical range, from Mediterranean drylands to hyperarid deserts, to build an interdisciplinary session including topics such as:
Estimation of the spatiotemporal variability of water fluxes: rainfall, soil moisture, evapotranspiration, floods and droughts
Hydro-geomorphological impacts of extreme events
Transport and deposition of river sediments and their impact on channel morphology
Groundwater recharge process estimation
Quantification of the impacts of anthropogenic water abstraction?
Climate dynamics and their influence on dryland water balance including paleo-reconstructions and projected future scenarios
Transmission losses and intermittent stream functioning

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.

The Earth Radiation Budget is the global annual mean difference between the incoming solar and reflected solar and emitted terrestrial radiation. It is a small number coming for the difference of two comparably large numbers (TSI and TOR), making its estimation particularly challenging. A positive Earth Energy Imbalance corresponds to the heat continuously accumulated in the Earth's climate system – mainly the oceans, and which will - with a time delay - cause the global warming of the surface and the atmosphere. From the analysis of in-situ observations– mainly based on ARGO, from 2006 to 2020 the mean EEI is 0.76 +/- 0.2 Wm-2, to be compared to a mean EEI of 0.48  0.1 Wm-2 from 1971 to 2020. The exact knowledge of the EEI and its trend is key for a predictive understanding of global warming and assessing the efficiency of global carbon reduction policies. Up to now, heat content measurements of the ocean, land, and atmosphere are used to determine its absolute value. While these in-situ measurements have a great potential, their sampling and trend uncertainty is - despite great improvements over the recent years - not perfect. To determine the EEI with higher accuracy and stability, independent measurement approaches are required. In this session we invite contributions on existing and new measurement concepts with an emphasis on space observations, but also welcome ground-based and in-situ measurements. We also invite modeling efforts that help to better determine the energy storage in the Earth's system and the terrestrial outgoing radiation.

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 are contingent upon adherence to standardized measurement protocols and rigorous uncertainty assessment methodologies. Reference measurements are the only traceable to the International System of Units (SI) and provided with a robust quantification of measurement uncertainty. This Short Course will guide the participants on improving knowledge and usage of reference measurements for climate studies and applications, by introducing three subtopics:
1. Reference upper air measurements
2. Near surface reference measurements
3. Precipitable water vapour from reference and reprocessed GNSS timeseries
Participants will be introduced to the theory, the contest and the potential applications in using reference measurements to characterize the atmosphere and investigate climate variability. Practical example of how to use reference measurements will be shown and discussed, also exploring the Copernicus Climate Data Store, currently hosting a few reference datasets.

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.

Large-scale atmospheric dynamics and synoptic systems are a key driver 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.

Climate modelling ensembles are fundamental for exploring and understanding uncertainty in future climate change projections. Uncertainty has manifold origins, including: process understanding and intermodel differences, model tuning strategies, parameterization choice and weak constraints on parameters, limited observations of initial conditions and climate model initialization strategy, and questions over the relationship between observations and model variables. These combine with unknowns such as future anthropogenic greenhouse gas emissions to give large climate prediction uncertainties which impact climate decision-making. Understanding them is also critical for advancing process understanding.

These uncertainties manifest themselves across the modelling hierarchy, from Earth system and cloud resolving models, to simple models for conceptual studies and interdisciplinary models for integrated assessment. In this context, this session invites wide-ranging and interdisciplinary contributions on the science, method, and application of long-term climate modelling ensembles, including but not restricted to:

Approaches to ensemble simulations: sampling uncertainty in large models (e.g., Earth System Models, cloud resolving models); model weighting and interpretation of small ensembles; characterising uncertainties from initial conditions & climate model initialization; data science approaches to sampling & emulation; future considerations in large ensemble simulations; uncertainty reduction in Earth system tipping elements; cross-cutting theories of ensemble design; anticipating future model evolution.

Comparing ensembles with observations: confronting model ensembles with observations including Palaeoclimate data; irreducible uncertainties in ensembles; emulators for characterizing uncertainty across scenarios; observational constraints with large forcing, slow dynamics, and internal variability; effects of model resolution on reliability; assessment and evaluation.

Ensembles and decision-making: Post-hoc emulation for uncertainty characterization; reducing generalization errors in simple models and emulators; consistent modelling hierarchies for mitigation and adaptation; irreducible errors in decision-relevant simulations; integrated assessment model ensembles; value of information from ensemble design; effects of scale on uncertainty; decision-sciences based approaches to ensemble design.

The global mean temperature in 2023 was almost 1.5 ˚C higher than preindustrial values; and temperatures in 2024 might even exceed 1.5 ˚C for the first time for an entire calendar year. Although this warming is partly explained by internal variability, it is now almost certain the 1.5 ˚C target of the Paris Agreement will be exceeded, and even higher warming levels will be breached unless greenhouse gas emissions are rapidly reduced in the coming decades.
It is therefore important to improve our understanding of the risks associated with exceeding such global warming levels, as well as investigate plausible pathways that result in global cooling, returning the Earth back to a safer temperature level at some later date. Key questions include; what feedbacks might occur once specific warming targets are exceeded and will these feedbacks make returning to a lower global temperature level more difficult? 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?
In addition, it is of the utmost importance to assess different negative emission pathways, such as those driven by Carbon Dioxide Removal (CDR) actions, that are necessary to return the Earth system to safer temperatures post-overshoot, focusing on the plausibility and efficacy of such pathways, including portfolios of CDR options, as well as any resulting climate, societal or environmental impacts.

We welcome:
- Integrated Assessment, Earth system and impact model experiments focused on overshoot pathways, including investigation of CDRs, their interaction with the global climate and carbon cycle, and potential societal and environmental impacts.
- Realization of warming overshoot pathways with Earth System Models (including idealized pathways such as suggested by TIPMIP) and analysis of the consequences of overshoot on climate, particularly the risk of rapid/abrupt Earth system change.
- Assessment of the societal and environmental impacts of overshoot, including impacts resulting from any triggered rapid/abrupt Earth system changes.
- Analysis of the potential reversibility of changes resulting from warming overshoot across the coupled Earth system, society and the ecosystem.

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 perturbes 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.

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.

Anthropogenic and natural aerosols play key roles in driving climate change over a range of spatial and temporal scales, both close to emission sources and also remotely through teleconnections. Aerosols can directly interact with radiation by scattering and absorption and indirectly through modulating cloud properties, and thereby modify the surface and atmospheric energy balance, cloud dynamics and precipitation patterns, and the atmospheric and oceanic circulation. Changes in regional aerosol emissions accelerate greenhouse gas-driven climate changes in some regions, counteract them in others, and may interact with natural variability to further stress human and ecological systems. However, our understanding of these impacts still lags those due to greenhouse gases. The poor aerosol integration in many climate risk and impact studies currently leads to potentially dangerous omissions in projections of near-term climate change impacts.

This session addresses: the strong and spatially complex trends in temperature, hydroclimate, air quality, and extreme events driven by aerosol changes over the historical era, and those expected in the near future; the interplay between aerosol-driven changes and those induced by other forcing factors; and their extensions to climate risk and impact studies. We encourage contributions based on model and observation-based approaches to investigate the effects of aerosols on regional decadal climate variability and extremes, tropical-extratropical interactions and teleconnections, and the interactions with modes of variability such as the NAO, ENSO, AMV, and PDO. This year we especially welcome analyses using the RAMIP dataset. We also welcome focused studies on monsoon systems, midlatitude and Arctic responses, extreme temperature and precipitation, atmospheric and oceanic circulation changes, tropical cyclones, and daily variability, using for example CMIP6 projections, large ensemble simulations, or specifically designed experiments. We also encourage studies focusing on climate risk and concrete regional impacts on nature and society resulting from changes in anthropogenic and natural aerosol emissions.

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.

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 is a distinct possibility. 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 at scale.

The prospects of such a global temperature overshoot raise important questions in relation to Earth system feedbacks under overshoot, and the feasibility and side-effects of large-scale deployment of carbon dioxide removal. Regional and sector specific climate and climate impact evolution under long-term global temperature decline and resulting implications for adaptation needs are poorly understood. Potential irreversibilities and hysteresis behavior of climate impacts under overshoot are a key research gap.

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 under global warming reversal. 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.

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 increasing transgression of planetary boundaries constituting a new geological epoch: the Anthropocene (Richardson et al., Science Advances, 2023). 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, planetary boundaries, 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

This session will explore the vital role of climate services and the active engagement of EU entities in aiding coastal and continental regions in adapting to the impacts of climate change. As these areas face diverse climate challenges, it is crucial to implement adaptive strategies informed by reliable climate data and supported by robust policy frameworks. Participants will gain insights into generating and applying climate information, understanding and participating in EU initiatives through citizen and stakeholder engagement, and seeing successful projects. Keynotes will provide expert perspectives, panels will facilitate stakeholder discussions, and Q&A sessions will offer opportunities for interactive learning. Strategies for planning, collaboration, and overcoming challenges in adaptation will be highlighted.

“The truth is almost ten years since the Paris Agreement was adopted, the target of limiting long-term global warming to 1.5 degrees Celsius is hanging by a thread.
"The truth is the world is spewing emissions so fast that by 2030, a far higher temperature rise would be all but guaranteed. …
"Now is the time to mobilise, now is the time to act, now is the time to deliver. This is our moment of truth.” (Guterres, 2024)

One of the surest ways to mobilise, to act and deliver is through geo-education, geo-communication and geoethics. Humanity is dependent on both the climate and the ocean, and on their interaction. The danger of climate and ocean change can be applied, mutatis mutandis, to related threats, such as biodiversity, pollution, food security and fossil-fuel-driven war. Humanity appears to be in the grip of manic growth and ecological overshoot.

Far greater numbers of citizens than is currently the case need to increase their knowledge and communication skills in climate and ocean change and their underlying causes. This is achieved through a broad variety of methods: encounters, meetings, field trips, associations, classes, publications, peer pressure, workshops, geoethical awakening, social media, direct experience of extreme weather, association memberships, legal action and so on.

We welcome abstracts on a broad range of topics, from hands-on geo-communication of all kinds, through pedagogical ideas and practices, best practices, research, programme implementation and activism. Come and share your experience, your ideas, your anger, your vision, your research, your drive, your actions, your successes – from hands-on pedagogical ideas and practices, through geo-communication, curriculum matters and research, to policy and its implementation.

This session is organised in parallel to, but independently of, the special issue of the EGU journal *Geoscience Communication*, see https://gc.copernicus.org/articles/special_issue1271.html. You are invited to submit an article; be in touch directly with David.

Abstracts are solicited regarding the predictability and attribution of weather/ climate extremes and their impacts.
Weather and climate extremes often have large impacts, so it is critical that we better understand these events, improve their prediction, and gain knowledge of how and why they are changing as the planet warms. This session aims to bring together physics-based and data-driven approaches to the study of extremes and their impacts. Studies focusing on either hazards associated with extremes or directly on societal impacts (including health, insurance, energy, and other sectors) are welcome. A particular goal of this session is to explore novel approaches to the predictability of extremes, and facilitate a deeper understanding of their impacts in our changing climate. We particularly encourage submissions from early career scientists and underrepresented groups.
Topics of interest include but are not limited to:
Predictability of extremes, especially from forecasting and applied viewpoints.
Attribution of extreme events
Data-driven and AI approaches to forecasting extremes and impacts
Predictability and forecasting of the impacts of extreme events, particularly in the context of informing early warning systems
Attribution of extreme event impacts, losses etc.
Applications of attribution techniques e.g. climate litigation

The increased weather instability and the visible warming of the climate, in recent decades, are attracting more and more the attention of the public, which repositions itself regarding these topics of interest and is more or less willing to adapt and direct itself towards sustainable practices. In this context, it is necessary to diagnose the population's perception and reaction to climate change adaptation. Through environmental education, the population can be assured of transversal competence for sustainability and opportunities can be established for citizens to act and participate both in mitigating climate changes and in adapting to them, thus gaining, in a real way, climate citizenship. In order to implement successful programs for the promotion of climate change education (CCE) and to ensure meta-competencies (including learning, adapting, anticipating and creating change) to the population, there is a need for dialogue between stakeholders such as: the scientific community from various fields (hydroclimatic, educational sciences, etc.), economic agents, environmental authorities and, last but not least, citizens. Other determining factors for the orientation of the educational programs can be the geographical position, the environment of origin, the level of studies, the income, etc. As a result, this session intends to include studies that offer quantitative and qualitative methods for the assessment of several environmental, economic and/or social dimensions, through in-depth interviews, focus groups, case studies on climate change perception and education.

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. 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.

This session seeks to showcase innovative learning activities and programs that leverage real data from environmental monitoring and satellite observations, focusing on climate change, its causes, impacts, and mitigation efforts. One such initiative is the ERASMUS+ project Climademy. Participants are invited to explore how using real-world data can address diverse educational needs across various national curricula.

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.

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 dynamics of the atmosphere in the extratropics is characterized by the coexistence of multiple fundamental processes spanning a variety of spatio-temporal scales. The interactions between the atmosphere and the oceans are central to several of these, while the interaction with sea-ice also plays a major role in high latitudes. The thermal contrast between the ocean and land surface, the different thermal inertia of the ocean and the atmosphere, and the moisture and heat exchange between the two are important for the general circulation of the atmosphere and oceans, and indicate that both a thermodynamic and a dynamic perspective are needed for understanding this topic. For example the oceanic anomalies, through air-sea interactions, affect the atmospheric dynamics already at the weather scales, and the atmosphere can quickly transfer anomalies towards remote areas, as in the case of diabatic heating along frontal zones. Atmospheric rivers originating over oceanic surfaces affect the formation of synoptic systems in the mid-latitudes and trigger climate extremes. Careful understanding of these mechanisms is crucial, especially regarding the assessment and predictability of extreme events, and the capability to discern the impacts of anthropogenic climate change on the variability of the climate system.
We welcome all contributions on the interactions between the oceanic and atmospheric circulation. These include investigations of atmosphere – ocean dynamics and thermodynamics at hemispheric and regional scales, 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. Model intercomparisons, and evaluations of past and future climate projections, are also welcome.

The planet is warming due to human-made greenhouse gas emissions, which have increased drastically since the industrial revolution. To grasp potential pathways for future climate, we need to understand what the impacts of elevated greenhouse gas emissions are on the global heat budget and how the climate system functions in conditions warmer than today. Geological archives and model simulations of past climate states are the key to better understanding climate dynamics in different, warmer-than-today climate conditions.
In this session, we welcome contributions ranging from proxy data to model results aimed at reconstructing and understanding Earth’s climate state and its dynamics over the past 100 million years. We welcome submissions across a wide range of time scales, including those investigating long-term change, Milankovitch cyclicity and/or short-lived events, from the Cretaceous to the Present. Submissions working on chronological or stratigraphic fundamentals underpinning this interval are also encouraged. We invite contributions seeking to better assess Earth system sensitivity in past climate states by reconstructing atmospheric CO2 concentrations and global or regional temperatures. As analogues of biodiversity in a warmer world can only be found in the past, we encourage submissions on marine and terrestrial ecosystem dynamics and disruptions in warmer worlds.
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.

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.

Modelling warmer-than-present climates of the past is paramount to understanding the Earth System sensitivity to climate feedbacks deriving from changes in geography, atmospheric chemistry, orbital forcing and ocean circulation. The models offer possibilities to isolate boundary conditions and analyse their impact on the Earth’s climate. Analysing these paleoclimates through modelling also enables model improvements that strengthens our confidence in their ability of detecting and attributing future climate change which is essential for the habitability of most areas in our planet. With this session we aim to discuss current efforts in modelling past warm climates through application of different boundary conditions and modelling intercomparison projects, and to connect scientists in a joint effort of creating a network for informed decision-making on adaptation and mitigation measures under current and future climate change.

This session covers climate predictions from seasonal to multi-decadal timescales and their applications. Continuing to improve such predictions is of major importance to society. The session embraces advances in our understanding of the origins of seasonal to decadal predictability and of the limitations of such predictions. This includes advances in improving forecast skill and reliability and making the most of this information by developing and evaluating new applications and climate services.
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 therefore include more and more of physical, biogeochemical and biophysical processes to represent these couplings. There is therefore a need to credibly assess such developments and capabilities for effective research on climate variability and change. This calls for novel approaches for benchmarking and evaluation of ESMs including for cross-domain and process -based evaluation, observational uncertainties, science and performance metrics and benchmarks.

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 most advanced and novel Earth observational datasets and reanalysis datasets, and (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.

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.

Atmospheric circulation variability is a major determinant of daily weather fluctuations. It also plays a crucial role in governing climate and weather. This is essential for long-term planning and the effective implementation of climate adaptation and mitigation efforts. The ability to forecast periods with significant weather anomalies in the near term, ranging from weeks to months and even years ahead, relies on accurately predicting the development of anomalies in the large-scale preconditioning of atmospheric circulation and its predominant modes of variability. In order to determine and improve predictability, it is essential to improve our understanding of atmospheric variability and its controls. We therefore invite contributions that investigate the modes and mechanisms of atmospheric variability, explore their implications for seasonal and regional climate predictability, and examine the links between seasonal prediction, climate forecasting and atmospheric dynamics. Furthermore, we seek research addressing the challenges posed by atmospheric circulation variability in climate modelling, as well as studies that enhance our understanding of past variability and improve our ability to anticipate future changes in the context of a warming climate.

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. The global ocean oxygen inventory has been declining and oxygen minimum zones have been expanding over the past decades of ocean warming, a trend that is predicted to continue through the end of this century. 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, 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.

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.

The Arctic cryosphere is the epicentre of acute global change – it is turning “blue” (ice free). Abrupt Arctic warming and amplification – four times the planet’s mean rate since the 1980s – is driving rapid sea ice decline and accelerating deglaciation of Greenland. The wider consequences for the planet and society are profound, and yet, model-based projections of these vary considerably and lack validation. The key challenge for humanity is how a blue Arctic will respond to and drive an increasingly warmer future climate.
Solving this “Arctic Challenge” requires beyond state-of-the-art empirical and numerical knowledge on how the cryosphere evolved under Arctic greenhouse climate conditions during the geological past

We invite contributions that apply a holistic approach to (1) quantify Arctic cryosphere changes in a warmer world using geological records, (2) provide in-depth understanding of dynamics of Arctic cryosphere and ocean changes through new numerical simulations, and (3) determine the impact of Arctic change on the ocean biosphere, climate extremes and society.

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.

In recent decades, a variety of multi-timescale, multi-faceted climate and weather extremes, including droughts, floods, wildfires, heat waves, cold spells, extreme precipitation and compound events, have been observed globally. These impactful and usually devastating climate and weather extreme events have posed severe challenges to both natural environments and human societies. The rarity of these climate and weather extremes is a fundamental feature and is driven by human-activities but also has connection with the Arctic and tropical forcing. The Arctic changes statistically indicate that a ‘new Arctic’ climate is emerging, implies great potential to change the ocean conditions, atmosphere circulations and climate patterns. The tug-of-war between contrasting effects of the Arctic and the tropics brings more challenges to the implementation of existing knowledge on the prediction on climate and weather extreme events. This session will synergize global climate community’s important and novel work on investigating, predicting and projecting these climate and weather extreme events, especially to understand the role of Arctic and tropics in these processes.

The session will use the Processes, Prediction and Projection framework to showcase the latest and most compelling research on advancing understanding and prediction of climate and weather extremes. The session will be focusing on climate and weather extremes occurring in land areas manifesting as extreme precipitation, intense droughts, and intense and sustained heat waves/cold spells, wildfires, etc. Contributions are welcome from but are not limited to novel studies on (a) characteristics and mechanisms of climate and weather extreme events; (b) impacts of Arctic and tropical climate systems and their teleconnections on the climate and weather extreme events; (c) predictions and projections on the climate and weather extreme events.

Studies addressing competing driving roles of Arctic climate changes and tropical forcing as well as isolating natural and human-driving influences are highly encouraged to contribute. We also highly encourage contributions from studies revealing new characteristics of Arctic climate changes and the impacts of interaction between the Arctic and the tropics on the climate and weather extreme events. Studies undertaking concepts, e.g. artificial intelligence, to push understanding and prediction of climate and weather extremes are also encouraged to submit an abstract.

The oxygen dissolved in the ocean is crucial for sustaining most marine life and plays a key role in many biogeochemical cycles. However, 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 also 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. Understanding these dynamics is crucial for predicting current and future oxygen trends and developing effective mitigation and adaptation strategies. The geological archive presents a unique opportunity to study past deoxygenation on a broad spectrum of timescales, offering insights into the intricate feedback mechanisms and biogeochemical dynamics that control ocean oxygen levels.
This session aims to bring together contributions that address ocean deoxygenation and the consequent formation of organic-rich sediments from the Paleozoic to the present, based on paleoceanographic and paleoclimatic proxy-based reconstructions and numerical modeling. The session aims at emphasizing: (1) Novel proxy developments in organic, inorganic, and isotope geochemistry; (2) Advancements in fossil and mineral indicators of past deoxygenation events; (3) Innovative modeling approaches and model-data integration to quantify and resolve the mechanisms driving ocean deoxygenation across different timescales. We encourage contributions focusing on laminated sediments, which can provide high-resolution glimpses into the timing and progression of marine deoxygenation. 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.

Polar oceans include spatial variability across a multitude of scales. From the large scale circulation, down to eddies and sub-mesoscale processes. Temporal variability includes long-term trends, climate variability and ocean extremes, as well as seasonal and high-frequency variability. Many studies of polar oceans focus on variability at a particular scale, but there is a lack of understanding of the interactions between different scales, both spatial and temporal. Furthermore, biogeochemical processes and ecosystems, which are being impacted by the rapidly changing polar oceans, respond to these changes across a range of scales. Loss of sea-ice is leading to enhanced variability at the ocean surface. This session aims to advance the understanding of polar ocean variability at different scales, with a particular focus on interactions and impacts. We encourage submissions looking at both polar regions (northern and southern hemisphere) and covering a range of approaches from observational to modelling. Associated studies on air-sea ice processes and interdisciplinary backgrounds are also welcome.

Projections of future climate rely on increasingly complex, high-resolution earth system models (ESMs). At the same time, nonlinearities and emergent phenomena in the climate system are often studied by means of simple conceptual models, which offer qualitative process understanding and allow for a broad range of theoretical approaches. Simple climate models are also widely used as physics-based emulators of computationally expensive ESMs, forming the basis of many probabilistic assessments in the IPCC 6th Assessment Report.

Between these two approaches, a persistent “gap between simulation and understanding” (Held 2005, see also Balaji et al. 2022) challenges our ability to transfer insight from simple models to reality, and distill the physical mechanisms underlying the behavior of state-of-the-art ESMs. This calls for a concerted effort to learn from the entire model hierarchy, striving to understand the differences and similarities across its various levels of complexity for increased confidence in climate projections.

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

Processes and phenomena of interest include, but are not limited to:
* Earth system response to forcing scenarios (policy-relevant, extreme, counterfactual)
* Tipping points and abrupt transitions (e.g. Dansgaard-Oeschger events)
* Coupled modes of climate variability (e.g. ENSO, AMV, MJO)
* Emergent and transient phenomena (e.g. cloud organization)
* Extreme weather events

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 and modelling results that examine ice sheet interactions with other components of the climate system over several time scales. Among other topics, issues to be addressed in this session include ice sheet-climate interactions from glacial-interglacial to millennial and centennial time scales, the role of ice sheets in Cenozoic global cooling and the mid-Pleistocene transition, reconstructions of past ice sheets and sea level, 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.

Over recent decades we have gained a robust understanding of climate change fundamentals, but its specific and localized impacts are anything but certain. The need to provide boundary conditions for forecasting and computational modelling has increased the importance of quantitative methods in the field of palaeoenvironmental, palaeoclimatic and palaeohydrological reconstruction.

Continental environmental archives (e.g., speleothems, lake and river sediments, peatlands, and vertebrate and invertebrate remains) are often highly temporally resolved (subdecadal to seasonal) and provide more direct information about atmospheric and hydrological processes than marine archives. The wide variety of continental archives allows for intercomparison and ground-truthing of results from different environments, while multi-proxy reconstructions from the same archive can disentangle local and supra-regional environmental conditions. This approach is particularly useful when dealing with high spatial variability, signal buffering, nonlinearities, and uncertainties in the proxy sensitivity.

This session aims to highlight recent advances in the use of innovative and quantitative proxies to reconstruct past environmental change on land. We welcome studies of all continental archives, including but not limited to carbonates (cave deposits, palaeosols, snails), sediments (lakes, peatlands, rivers, alluvial fans), and biological materials (tree rings, fossil assemblages, bones, biomarkers). If you calibrate physical and chemical proxies that incorporate modern transfer functions, perform forward modeling and/or geochemical modeling to predict proxy signals, or attempt at quantitative estimates of past temperature and palaeohydrological dynamics you are mostly welcomed in our session! We are keen to invite reconstructions of temperature and hydrologic variability, palaeoclimate data assimilation, and monitoring and modelling studies leading to calibration or simply better understanding of climate proxies. We are also keen to learn about limitations, failed approaches and negative results. Our session provides a forum for discussing recent innovations and future directions in the for continental palaeoenvironmental studies on seasonal to multi-millennial timescales.

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.

New and emerging technologies have always been used in climate science, and current trends in advanced computing and new data and data driven methods are no exception. Advanced modelling efforts seeking to represent the global Earth system in ever finer detail are targeting cloud-resolving, km-scale resolutions using the latest computing architectures. At the same time, there have been advances in novel observations relevant to such high resolution model processes and model observation simulators and in new classes of observations from distributed sensors or satellite constellations. Machine Learning and Artificial Intelligence approaches are now being integrated into Earth System Models (ESM) and earth observation frameworks, and being used increasingly to augment or emulate models in various ways. Increased resolution and more complex process representation in ESMs has implications for observations that are required to initialise, evaluate, and develop traditional ESMs. New data requirements for training, validating, and critically assessing biases in AI models and model emulators are increasingly incorporating a diverse range of Earth Observation (EO) data. Similarly, ESM use cases are driving development for upcoming or proposed EO missions as well as enabling reprocessing of preexisting data for process understanding. Such advancements have highlighted the need for improvements in communication between these two pillars of climate research and identified new avenues for collaboration. In this session organised by WCRP ESMO and Digital Earth LHA, we invite presentations that discuss the fusion of models and observations, especially those using new technologies such as AI and exascale computing. The presentations will include contributions from several WCRP projects and will help guide a later discussion on improving collaborations in the topic.

This session will enhance climate services by tackling challenges and translating climate science into actionable insights. It will address key issues such as stakeholder engagement, funding, and practices, while focusing on innovative solutions and bridging science and policy for effective global climate action.

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.

Water and climate-related risks, including changing rainfall patterns and an increase in extreme events such as floods, droughts, heatwaves, and fires, pose significant challenges to various sectors of society. In order to mitigate these risks and support adaptive planning and management, the development and provision of hydroclimatic information services play a crucial role. Water and climate information services (WCISs) have potential to reduce the impacts of water and climate-related risks by providing timely and accurate information in advance. As a result, substantial resources and research efforts have been dedicated to the development of global and regional WCISs. These services encompass a wide range of initiatives, from the establishment of natural hazard early warning systems (EWSs) to the creation of platforms and dashboards that support decision-making in sectors such as agriculture, tourism, and transportation.

The session aims to provide a platform for showcasing the current developments in WCIS for adaptation planning and management. The session will cover various topics with diverse applications, including the development of both natural hazard and multi hazard EWSs, decision support system (DSS), the creation of mobile apps and dashboards for forecasting extreme weather events, and the facilitation of WCIS for sector-specific decision-making processes such as farmer support app.

Contributions related to co-designing of WCIS, the involvement of stakeholders in the development of WCIS, and innovative applications of WCIS for adaptation planning and management are also encouraged. This session will facilitate the exchange of knowledge and expertise among scientists, practitioners, and users of WCISs.

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 very 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, public policymaking on climate change and to the performance of modern applications such as Machine Learning (ML) and forecasting.

The storage and shareability of ESS datasets have become an important discussion point in the scientific community. It is apparent that datasets produced by state-of-the-art applications are becoming so large that even current high-capacity data centres and infrastructures are incapable of storing, let alone ensuring the usability and processability of such datasets. The needs of ongoing and upcoming community activities, such as various digital twin centred projects or the 7th Phase of the Coupled Model Intercomparison Project (CMIP7) already stretch the abilities of current infrastructures. With future investment in hardware being limited, a viable way forward is to explore the possibilities of data reduction and compression with the needs of stakeholders in mind. Therefore, the use of data compression has grown in interest to 1) make the data weight more manageable, 2) speed up data transfer times and resource needs and 3) without reducing the quality of scientific analyses.

Concurrently, replicability is another major concern for ESS and downstream applications. Being able to reproduce the most recent ML and forecasting results and analyses thereof has become mandatory to develop new methods and integrated workflows for operational settings. On the other hand, the data accuracy needed to produce reliable downstream products has not yet been thoroughly investigated. Therefore, research on data reduction and prediction interpretability helps to 1) understand the relationship between the datasets and the resulting prediction and 2) increase the stability of prediction.

This session discusses the latest advances in both data compression and reduction for ESS datasets, focusing on:
1) Approaches and techniques to enhance shareability of high-volume ESS datasets: data compression (lossless and lossy) or reduction approaches.
2) Understanding the effects of reduction and replicability: feature selection, feature fusion, sensitivity to data, active learning.
3) Analyses of the effect of reduced/compressed data on numerical weather prediction and/or machine learning methods.

Pangeo (pangeo.io) is a global community of researchers and developers that tackle big geoscience data challenges in a collaborative manner using laptop to HPC and Cloud infrastructure. This session's aim is:
to motivate researchers who are using or developing in the Pangeo ecosystem to share their endeavours with a broader community that can benefit from these new tools.
to contribute to the Pangeo community in terms of potential new applications for the Pangeo ecosystem, containing the following core packages: Xarray, Iris, Dask, Jupyter, Zarr, Kerchunk and Intake.

We warmly welcome contributions that detail various Cloud computing initiatives within the domains of Earth Observation and Earth System Modelling, including but not limited to:
- Cloud federations, scalability and interoperability initiatives across different domains, multi-provenance data, security, privacy and green and sustainable computing.
- Cloud applications, infrastructure and platforms (IaaS, PaaS SaaS and XaaS).
- Cloud-native AI/ML frameworks and tools for processing data.
- Operational systems on the cloud.
- Cloud computing and HPC convergence and workload unification for EO data processing.

Also, presentations using at least one of Pangeo’s core packages in any of the following domains:
- Atmosphere, Ocean and Land Models
- Satellite Observations
- Machine Learning
- And other related applications

We welcome any contributions in the above themes presented as science-based in other EGU sessions, but more focused on research, data management, software and/or infrastructure aspects. For instance, you can showcase your implementation through live executable notebooks.

This session explores the transformative potential of large language models (LLMs) in geosciences. LLMs are revolutionising the field by enabling researchers to process and interpret complex geological, climatological, environmental, hydrological and other earth systems data with unprecedented speed and accuracy, leading to new discoveries and insights. Presenters are encouraged to share how LLMs have accelerated research by analysing vast datasets, automating data interpretation, and uncovering hidden patterns. Case studies highlighting breakthroughs in geology, climate science, and environmental monitoring are particularly welcome. This session will provide a platform for geoscientists to discuss the integration of LLMs into their workflows, enhancing both efficiency and discovery while addressing challenges such as model accuracy and data bias. We invite presentations that explore the transformative potential of large language models (LLMs) in the geosciences. Join us in contributing to this cutting-edge dialogue and helping shape the future of geosciences through AI.

This session aims to unite scientists employing stable isotope analyses of light elements (e.g., carbon, oxygen, hydrogen, nitrogen) to address ecophysiological questions concerning climate change and other abiotic and biotic stressors.

We invite researchers studying a variety of compounds (e.g., lipids, cellulose, lignin, non-structural carbohydrates, water) from both aquatic (e.g., fish, micro and macroalgae) and terrestrial (e.g., mosses, grasses, crops, trees) ecosystems. Contributions that span all spatiotemporal scales and archival materials (e.g., herbarium samples, peat, sediments, loess, tree rings) are welcome.

Researchers utilising a range of analytical isotopic techniques, including but not limited to IRMS, NMR, Orbitrap and spectroscopy-based methods, are encouraged to present their methodological advancements. By showcasing cutting-edge research and methodological innovations, we aim to highlight the crucial role of stable isotope analyses in ecophysiological studies and foster interdisciplinary collaboration.

We look forward to your contributions to this exciting and recurring session.

Ensemble climate projections are a vital tool for understanding historical and future changes, informing regional and local modeling efforts, as well as for conducting impact assessments. However, using all available models from a multi-model ensemble such as CMIP6 is often not feasible and does not necessarily provide the best possible representation of climate, its changes, and its uncertainties.
Therefore, many methods have been developed to aggregate, weight, filter, constrain, and sub-select models in recent years. These methods are based on internal model consistency, comparing models with observations, or an assessment of model inter-dependencies among other things. They cover a range of spatial scales from global to local and temporal scales from near-term predictions to long-term projections.

This session welcomes contributions focusing on, but not limited to, aggregating, weighting, filtering, constraining, and sub-selecting multi-model ensembles. This includes:

- application-oriented work including model constraining and sub-selection for impacts and regional applications
- work on observational and emergent constraints, weighting and filtering approaches, as well as qualitative and quantitative model sub-selection
- work on methods to aggregate multi-model ensembles and quantify uncertainties using classical statistics as well as machine learning
- verification of model constraining and sub-selection methods using, for example, out-of-sample historical observations, pseudo-observations, or explainable artificial intelligence (XAI) methods

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.

The microclimate within terrestrial ecosystems is highly heterogeneous as it responds to a multitude of local and landscape-scale factors such as foliage density, micro-topography, distance to a forest edge or a water body. This diversity of microclimates, and the potential buffering of climate extremes in the landscape, are key to understand terrestrial biodiversity and ecosystem functioning (notably carbon, water and nutrient cycling), but also ecosystem resilience and feedback onto regional climate. Despite our good understanding of the biophysical processes driving microclimate, it is still very challenging to describe and predict how microclimate varies across the landscape, and anticipate the impact of changes in climate, land use or ecosystem management.
In this session, we welcome observational, experimental and modelling studies on terrestrial microclimate, its role on biodiversity, biogeochemical cycles, ecosystem resilience and its response to climate and land use change.

For the last two decades Earth System Models (ESMs) have been applied to predict the future climate in ranges of decades to century timescales. More recently, advanced technology has been allowing the growth of computing power and the development of new techniques, like Machine Learning (ML). Enhanced computing capacity and techniques enable more complex modeling systems and larger ensembles. Complex modeling systems like ESMs are increasingly being used in weather and climate applications in a more seamless way in the last few years, setting the frame for a new generation of operational weather and climate prediction systems. This has brought more accurate and reliable forecasts, making weather and climate information more valuable for stakeholders and policymakers. However, in addition to errors within individual ESM components, complex inter-component interactions can lead to the growth of errors whose root causes are difficult to identify and correct. Despite the evolution of ESMs and the increase in the understanding of physical, dynamical and biogeochemical processes of the Earth System, the observational network does not provide enough information to constrain ESMs in ways that allow fully understanding and resolution of model errors. The efforts to assess, test, and enhance models have reduced major systematic errors, but some persist, and new ones have emerged. Therefore, there is a continued need to improve the representation of different processes in ESMs by identifying and correcting systematic errors.
This session invites contributions that help to increase understanding of the nature and cause of systematic errors in ESMs. Of particular interest are studies that consider:
-model errors across space and time scales; the use of hierarchies of models, including single column models and constrained ESM components;
-physics-dynamics and physics-physics cross-component coupling;
-initialized predictions;
-climatology of weather prediction models;
-data assimilation methodologies to identify systematic errors and constrain parameters;
-use of ML to identify systematic errors and/or to detect causal connections between seemingly disparate parameters; stochastic parameterization to represent uncertainty.
Verifying diagnostics and metrics to identify and characterize systematic errors and process understanding across different modeling communities (regional and global km-scale modeling) are also welcomed.

Statistical post-processing techniques for weather, climate, and hydrological forecasts are powerful approaches to compensate for effects of errors in model structure or initial conditions, and to calibrate inaccurately dispersed ensembles. These techniques are now an integral part of many forecasting suites and are used in many end-user applications such as wind energy production or flood warning systems. Many of these techniques are flourishing in the statistical, meteorological, climatological, hydrological, and engineering communities. The methods range in complexity from simple bias correction up to very sophisticated machine learning and/or distribution-adjusting techniques that take into account correlations among the prognostic variables.

At the same time, a lot of efforts are put in combining multiple forecasting sources in order to get reliable and seamless forecasts on time ranges from minutes to weeks. Such blending techniques are currently developed in many meteorological centers. These forecasting systems are indispensable for societal decision making, for instance to help better prepare for adverse weather. Thus, there is a need for objective statistical framework for "forecast verification'', i.e. qualitative and quantitative assessment of forecast performance.

In this session, we invite presentations dealing with both theoretical developments in statistical post-processing and evaluation of their performances in different practical applications oriented toward environmental predictions, and new developments dealing with the problem of combining or blending different types of forecasts in order to improve reliability from very short to long time scales.

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!