Recent advances in computational science and data-intensive methods are significantly improving our ability to detect, model, and respond to natural hazards in real/near-real time. From earthquakes, tsunamis and floods to wildfires, volcanic eruptions, and extreme weather events, the integration of HPC, predictive modeling, and intelligent systems is enabling more effective and timely emergency response and operational frameworks and services, as illustrated from the outcomes of several EU-funded projects (e.g. ChEESE, doi: 10.3030/101093038; DT-GEO, doi:10.3030/101058129; GANANA, doi:10.3030/101196247).
This session focuses on the role of scalable, adaptive, and AI-enhanced computing approaches in supporting the entire natural hazard management cycle: from early detection and warning to modelling, impact forecasting and decision support. We invite contributions that explore but not limited to innovative methods and real-world applications across the areas such as: (i) Early detection and rapid warning systems, leveraging sensor networks, remote sensing, and predictive analytics, (ii)Time-critical simulations and forecasting models, (iii) AI applications in natural hazard contexts, including real-time/near real-time earthquake signal analysis, landslide and wildfire risk mapping, flood extent detection, and uncertainty-aware forecasting using ML-based ensemble models, (iv) Operational platforms and decision-support tools, integrating real-time data streams with adaptive modeling, (v) Climate change impacts on hydro-geological hazards, with a focus on floods, landslides, and droughts, (vi) Physics-informed learning and the integration of climate scenarios, (vii) AI-driven coupled hazard modeling using multi-source data, (viii) Representation of hydrological interactions among atmosphere, vegetation, and soil, and, (ix) Case studies demonstrating the application of such methods etc.
We invite contributions that showcase novel approaches in computational science, AI / machine learning, modeling systems, or hybrid workflows that improve readiness and responsiveness during natural disasters. We particularly encourage interdisciplinary submissions that highlight collaborative work across geoscience, computer science, and emergency management. This session aims to bring together researchers, practitioners, and system developers working at the intersection of geoscience and urgent computing to advance the state of natural hazard mitigation and civil protection.

Recent advances in advanced machine learning models, agentic systems, and generative AI are opening up possibilities for addressing complex geoscientific challenges. These approaches enable novel ways to analyse data, support decision-making, and enhance scientific workflows, while raising important questions about alignment with human expertise, values, and responsibility. Generative AI enables the creation of new content across modalities, agentic AI allows autonomous systems of agents to act with minimal supervision and leverage tools, and hybrid intelligence integrates human contextual, causal, and ethical reasoning with AI’s computational power. In practice, causal reasoning is often where stakeholders' experience and domain insight are most naturally expressed, beyond what can be captured by model architectures, metrics, or post-hoc explainability alone.

This session explores both practical applications and conceptual frameworks of generative, agentic, and hybrid AI (inclusive of advanced ML/DL models) in the geosciences, with a strong emphasis on human-centred design. Topics include AI-assisted data analysis and modelling, knowledge discovery and curation, decision support, science communication, and AI-enhanced workflows guided by domain expertise. We particularly encourage contributions that demonstrate how human insight and causal reasoning complement AI.

The session also addresses ethical and societal aspects of AI deployment in geosciences, including transparency, bias mitigation, accountability, sustainability, and trustworthiness. The overarching goal is to highlight AI as a tool to empower and extend human expertise—keeping scientists and domain experts at the centre of innovation. Contributions from research, industry, and policy communities are all welcome.

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, numerical weather prediction, 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, consistency, and conservation laws
- ensuring numerical stability,
- coupling of numerical models to ML frameworks and language interoperation,
- development and usage of differentiable models and model components,
- handling computer architectures and data transfer,
- adaptation/generalisation to different models, resolutions, or climates,
- 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.

Following success over the past two years at EGU, we again 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.

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
- ML-based super-resolution and bias-correction 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) methods have emerged as powerful tools to tackle various challenges in ocean science, encompassing physical oceanography, biogeochemistry, and sea ice research.
This session aims to explore the application of ML methods in ocean science, with a focus on advancing our understanding and addressing key challenges in the field. Our objective is to foster discussions, share recent advancements, and explore future directions in the field of ML methods for ocean science.
A wide range of machine learning techniques can be considered including supervised learning, unsupervised learning, interpretable techniques, and physics-informed and generative models. The applications to be addressed span both observational and modeling approaches.

Observational approaches include for example:
- Identifying patterns and features in oceanic fields
- Filling observational gaps of in-situ or satellite observations
- Inferring unobserved variables or unobserved scales
- Automating quality control of data

- Modeling approaches can address (but are not restricted to):
- Designing new parameterization schemes in ocean models
- Emulating partially or completely ocean models
- Parameter tuning and model uncertainty

The session also welcomes submissions at the interface between modeling and observations, such as data assimilation, data-model fusion, or bias correction.

Researchers and practitioners working in the domain of ocean science, as well as those interested in the application of ML methods, are encouraged to attend and participate in this session.

Carbon monitoring is becoming ever more critical as climate change accelerates and society turns to carbon management strategies, ranging from carbon credits to the preservation and restoration of natural carbon sinks. Yet the success of these approaches depends on robust science: measurements must be accurate, verification must be rigorous, and promises must be grounded in evidence. Machine learning (ML) is rapidly transforming carbon cycle research, offering new opportunities to integrate diverse data streams, harness remote sensing, and connect multiple lines of evidence across scales. This session will highlight recent advances in ML applications for investigating, monitoring, and managing the carbon cycle, spanning satellite-based greenhouse gas estimation, biomass and forest monitoring, soil and peatland carbon dynamics, wetland and ecosystem restoration, and the mapping of terrestrial and oceanic carbon storage. We particularly encourage contributions that address hybrid modeling, uncertainty quantification, ecological mapping, knowledge-guided and trustworthy ML in carbon markets and policy contexts. By bringing together advances from Earth observation, process modeling, and policy-relevant applications, this session aims to explore both the promises and challenges of ML in delivering actionable insights for carbon management and climate mitigation.

Digital Twins (DTs) are dynamic virtual representations of physical processes, already applied in engineering and industry. Their main strength lies in the continuous assimilation and visualisation of large, spatially distributed datasets, integrating different sources and types of data with numerical simulation models. This enables replication of system behaviour, provides an up-to-date status of ongoing physical processes, and supports informed decision-making. DTs represent powerful frameworks that bridge physics-based models, observational data, and AI to improve our understanding, forecasting and management of the subsurface. While a digital twin is often designed to address a specific question or topic, there is still no standardised workflow or consensus on the methodology to be used. Given the growing number of emerging projects, the complexity of workflows, and the wide range of disciplines involved, this remains an important topic for discussion.

This session invites contributions on methodologies, (semi)automated workflows, and applications of digital twins for the subsurface, with a special focus on uncertainty quantification, data assimilation, multi-source data streams, automated data cleaning, and decision support. We particularly welcome studies addressing subsurface workflows from multi-type data to decision-making, including advanced optimisation methods, Bayesian approaches, machine learning, hybrid modeling, as well as economic, social components and policy considerations. Case studies from groundwater, geothermal energy, energy storage, hydrogen, carbon storage, geomodelling, natural risks and other subsurface-related systems are also encouraged. The session aims to foster dialogue on methods across disciplines and highlight both challenges and opportunities in building reliable subsurface digital twins.

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

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

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

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

Understanding where people live, how populations and visitors are distributed across space, and how these patterns shift over time is central to planning in an era of climate change, natural hazards, and mounting pressures on natural environments. This session focuses on data-driven approaches that connect advances in gridded population and socio-demographic datasets with the management of nature-based tourism and outdoor recreation across rural communities, destinations, and protected landscapes. Emphasis is placed on methodological progress in building, validating, and integrating spatial population and human-activity data—along with assessing spatial accuracy, uncertainty, and data fusion methods for future projections under alternative scenarios. The session also focuses on real-world applications that translate these data products into actionable planning and governance, including climate change adaptation, disaster risk management, sustainable land-use planning, and destination resilience. Key thematic areas include geoscience methods for tourism and recreation; the role of biodiversity, geodiversity, and ecosystem services; natural hazards and risk communication; strategic decision-making and stakeholder trust in data; participatory and citizen approaches; and the use of local knowledge to support sustainable development and mitigation. Overall, the session highlights how robust spatial evidence can support transparent, impactful decisions for communities and environments under uncertainty.

Recent advances in Large Language Models (LLMs) and Natural Language Processing (NLP) are rapidly changing geosciences research, offering new opportunities for knowledge discovery, data analysis, and real-time monitoring. At the same time, the increasing availability of digital text and image data—from scientific literature and newspaper articles to social media and historical archives—offers unprecedented opportunities to explore new data sources in geosciences research.

This session examines how geoscientists are using LLMs, NLP, and text-as-data approaches across various hydrology, natural hazards research, and the broader earth system sciences research fields. We invite contributions that showcase innovative uses of LLMs and NLP, discuss methodological challenges, or integrate text mining techniques into geoscientific workflows.

We particularly welcome submissions on topics including, but not limited to:
- Chatbots and AI assistants in geosciences
- Assessment of natural hazard impacts (e.g., floods, droughts, landslides, heatwaves, windstorms)
- Real-time disaster monitoring and early warning systems
- Evidence synthesis and literature mapping
- Public sentiment and perception analysis
- Policy tracking and narrative analysis
- Social media analyses
- Enhancement of metadata and data descriptions
- Automation of historical data rescue
- Integration of LLMs with remote sensing or image data
- Methodological challenges in using LLMs and NLP-based analyses, including bias, reproducibility, and interpretability

By sharing case studies, technical developments, and lessons learned, we aim to promote the effective use of these tools while also highlighting the challenges that newcomers may encounter, including issues with data coverage, quality control, and concerns about reproducibility. By sharing best practices, this session aims to inspire collaboration and innovation in harnessing LLMs, NLP, and text-as-data in geosciences.

Environmental challenges such as climate change, biodiversity loss, water scarcity, and ocean degradation demand new ways of observing, monitoring, and understanding the Earth system. Research Infrastructures (RIs) in the ENVRI community—spanning atmospheric, marine, terrestrial, and solid earth sciences—provide the backbone of European environmental observation and long-term data stewardship. Yet, the growing complexity of environmental change requires innovative technologies and services to enhance monitoring, strengthen interoperability, and accelerate the translation of knowledge into actionable insights.

This session brings together researchers, technologists, and stakeholders to showcase advances illustrating (1) the role of emerging technologies and (2) service-oriented approaches in shaping the future of environmental monitoring.

Emerging technologies include advanced instrumentation, miniaturized and autonomous sensors for atmospheric, hydrological, soil, and marine processes, as well as unmanned aerial systems, drones, satellite constellations, and IoT networks that link in-situ with remote sensing. Artificial intelligence (AI) is transforming how environmental data are processed, harmonized, and applied in predictive modelling.

The ocean, a key climate regulator, remains critically under-observed for carbon fluxes, particularly beyond shipping routes. Addressing this gap, the GEORGE project—a collaboration between EMSO ERIC, EURO-ARGO ERIC, ICOS ERIC, research institutions, universities, and industry—develops novel tools and methods to measure carbonate chemistry (e.g., pH, alkalinity, dissolved inorganic carbon, pCO₂) across diverse marine environments.

Services are equally vital. Trans-National Access (TNA) schemes offered by ENVRIs provide opportunities for researchers to use state-of-the-art facilities, advanced instrumentation, and high-quality data services beyond national systems. These services foster collaboration, accelerate innovation, and support co-created solutions to pressing challenges. The convergence of cloud-based infrastructures, FAIR data principles, interoperability frameworks, and user-centered service design ensures that resources are not only technically robust but also widely accessible and impactful for science, policy, and society.

Climate services are instrumental in translating local knowledge and scientific insights into practical applications, empowering communities at multiple scales to efficiently tackle climate change challenges.

The paradigm of Essential Variables (EVs) - ECVs, EOVs, EBVs - provides a data-driven foundation for global environmental monitoring (GCOS, GEO, UN SDGs). Yet, their full potential is hampered by interoperability gaps, fragmented governance, and siloed infrastructures, limiting integrated use and translation into local action.

Conversely, local demand for actionable information is growing. Earth Observation data, often as Analysis-Ready Data (ARD), must be transformed into locally relevant, co-created Action-Ready Information (ARI) for climate solutions. This requires integrating global EVs with local data and knowledge.

This session bridges these fronts. We explore all aspects of climate service development from the co-creation of climate services that emphasize inclusive and novel methodologies and the integration of multiple knowledge systems, through to the development of usable, equitable and impactful solutions for multiple stakeholder groups a focus on the use of technical, infrastructural, and socio-technical advancements to evolve EVs into a truly interoperable, global common language and ensure their effective translation for local decision-making. We welcome contributions on:

- Interoperability Foundations: Semantic frameworks (iADOPT, SOSA/SSN), FAIR principles, and lessons from research infrastructures (ENVRI, CRDCs) aligning EVs across domains and global programmes.
- From ARD to ARI: Case studies on transforming EV-based products into local insights via co-creation, integrating satellite data with in-situ, citizen science, and indigenous knowledge.
- Cross-Scale Infrastructure: Architectures and platforms (e.g., digital twins) enabling seamless data flow from global systems to local applications.
- Policy and Capacity: How interoperable EVs strengthen global policy (IPCC, SDGs) and how local insights inform action, including funding, capacity building, and governance models.

We invite scientists, data engineers, social scientists, and policymakers to connect the "essential" with the "actionable", forging a coherent path from global observation to local solution.

The advancement of Open Science and the democratization of computing services allow for the discovery and processing of large amounts of information, blurring traditional discipline boundaries. Being data heterogeneous in format and provenance, the ability to combine them and extract new knowledge to address complex challenges relies on standardisation, integration and interoperability.
Thanks to decades of work in this field, Research infrastructures (RI) worldwide, such as EPOS, Europe's RI for solid Earth science, are key enablers of this paradigm. By providing access to quality-vetted, curated open data, they enable scientists to combine data from different disciplines and data sources into innovative research and apply novel approaches such as Large Language Models (LLM) and AI/ML tools to obtain new insights and solve complex scientific and societal questions.
However, while data-driven science creates enormous opportunities to generate groundbreaking inter- and transdisciplinary results, many challenges and barriers remain.
This session aims to foster cross-fertilization by showcasing real-life scientific studies and research experiences in geosphere studies, especially from Early Career Scientists (ECS) worldwide. We also welcome contributions on challenges and user needs when establishing multi-disciplinary studies, including, e.g., need for reliable and trustworthy AI and the availability of training datasets. The session will not only focus on results, but also on challenges and solutions in connection to data availability, collection, processing, and inter-disciplinary methods.
A non-exhaustive list of topics includes:
- multi-disciplinary studies, involving data from different disciplines (e.g. combining seismology, geodesy, and petrology to understand subduction zone dynamics);
- inter-disciplinary research integrating two or more disciplines into new approaches (e.g. merging geophysics and geochemistry to probe mantle plumes);
- activities that advance interdisciplinarity and open science (e.g. enhancing FAIRness of data and services, enriching data provision, enabling cross-domain AI applications, software and workflows, transnational access and capacity building for ECS);
- experiences that cross disciplinary boundaries, integrate paradigms and engage diverse stakeholders (e.g. bringing together geologists, social scientists, civil engineers and urban planners to define risk maps and prevention measures in urban planning).

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

The growth and decay of large ice sheets on the Earth's surface during the past, present and future leads to Glacial isostatic adjustment (GIA) triggered by the redistribution of surface ice and ocean masses, and the flow of mantle rocks. It involves radial and tangential motion, changes in sea levels, the Earth's gravity field and rotational motion, lithospheric bending and the state of stress inside the Earth. Although this process is primarily driven by ice-sheet dynamics and Earth's structure, it impacts other Earth systems like the cryosphere and hydrosphere. GIA controls relative sea-level change through vertical land motion and gravitational–rotational effects, making it fundamental for ocean sciences, hydrological sciences, and climate investigations. Furthermore, differential uplift and tilting due to GIA reshapes landscapes and drainage networks, while emergent land and basin connections drive ecosystem succession and carbon burial. GIA-related stress redistribution influences a region’s seismicity and its seismic hazard, which must be considered in nuclear waste storage safety assessments. Similarly, such stress changes can alter volcanic activity even thousands of kilometres away from the glaciated area. GIA effects are present in a wealth of standardized observational data, such as GNSS measurements, tide gauges, relative sea levels, and terrestrial and satellite gravimetry. These data help refine GIA models, which enhance our understanding of ice-sheet history, sea-level changes, Earth's rheology and near-surface processes. The GIA theory can also be applied to study other planets such as Mars.

We welcome contributions on GIA's effects across various scales, including geodetic measurements, complex GIA modelling, GIA-induced sea-level changes, the Earth's response to current ice-mass changes, and overview on emerging GIA data collections. We also invite abstracts on GIA's impact on nuclear waste sites, volcanism, groundwater, permafrost, and carbon resources. We especially appreciate new model developments in local, high spatial and temporal resolution for GIA assessments, results of fully coupled ice dynamics-GIA models, studies of broader environmental relevance, and improved GIA corrections for other geoscientific fields.

Climate change is reshaping the conditions that sustain human health. Rising temperatures, shifting precipitation patterns, and intensifying extremes are linked to diverse risks, from heat-related illness, kidney disease, and suicide to mortality from wildfires, tropical cyclones, and infectious diseases. These impacts extend beyond health to affect labor capacity, energy demand, and economic productivity, underscoring the interconnectedness of climate and society.

This session invites contributions that investigate the different pathways linking climate extremes to human health and well-being worldwide. We particularly encourage studies that leverage diverse data sources, including observations, health and socio-economic data, reanalyses, climate models, large ensembles, and AI-based models, to deepen our understanding and improve prediction and projection across various time scales.

Works addressing vulnerability, inequality, early warning systems, and strategies for adaptation and resilience are especially welcome, as well as interdisciplinary approaches bridging climate science, epidemiology, economics, and public health.

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

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

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

Disturbances, such as extreme weather events, play a key role in shaping ecosystems. Under climate change, extreme weather hazards undergo changes in frequency, intensity and seasonality. While ecosystem-based adaptation and nature-based solutions are gaining traction, it is crucial to elucidate the diverse interactions between extreme weather risk, ecosystems, and their services.
This session seeks to highlight research on the nexus of weather and climate-related extreme events and ecosystems. We encourage submissions on: 1) investigations into the key attributes and patterns of extreme weather events which affect ecosystem composition, structure and functioning, 2) studies on how ecosystems respond to and recover from extreme weather events across past, present, and future climates, 3) Implications of extreme weather impacts on ecosystems for biodiversity and ecosystem service provision. We welcome a diverse array of contributions, including theoretical analyses, modelling approaches, field studies, experimental designs, and remote sensing analysis.

Key topics include:
- Identification of extreme weather risk hotspots, and subsequent ecosystem responses (terrestrial, coastal, or marine) in past, present and future climates
- Role of extreme weather in shaping ecosystem composition, biodiversity, structure and functioning, and its impact on ecosystems service provisions across temporal and spatial scales
- Interactions of natural hazard, anthropogenic and biogenic disturbances with ecosystems (including compounding events)
- Ecosystem vulnerability, resilience and recovery dynamics under weather extremes, including regime shifts / tipping points in ecosystems
- Impact and efficacy of nature-based solutions under extreme conditions, risk of maladaptation or disservices

Climate hazards consistently expose and often intensify socioeconomic inequalities. Vulnerability to extreme events is not evenly distributed within or across societies; rather, it is shaped by existing social, economic, and political conditions. As such, inequality, defined as the uneven distribution of resources, opportunities, and power has been recognised by the United Nations and other global policy frameworks as a central factor influencing progress toward the Sustainable Development Goals (SDGs).

This session invites interdisciplinary contributions, bringing together geoscientists, social scientists, economists, and policy experts to examine the complex and often compounding interactions between social inequalities and climate hazards such as floods, heatwaves, droughts, storms, landslides, and wildfires across different scales, including within countries, between countries, and across continents.

Topics of interest include (but are not limited to):

-Case studies illustrating how environmental and social inequalities intersect.

-Types of inequality: social, gender-based, infrastructural, recovery time, education, income source, wealth distribution, climate justice, food security

-Impacts of climate hazards: displacement, fatalities, psychological and physical health, developmental setbacks.

-Long-term recovery challenges: absence of recovery, prolonged recovery periods, slower developmental trajectories.

-Historical and political-ecological perspectives on disasters and their long-term societal impacts.

-Innovations in data, metrics, or methods (e.g., AI, remote sensing, socio-environmental modelling) for assessing inequality and disaster risk across spatial and temporal scales.

Extreme weather events such as tropical cyclones, heatwaves and floods threaten populations around the world. Climate change is increasing the frequency and intensity of extreme weather events, which can combine with community exposure, inequalities and vulnerabilities to cause substantial harm, including forced migration, human displacement, and other societal impacts. There is a growing literature at the intersection of the natural and social sciences studying the impacts of extreme weather events on populations as well as peoples’ behavioral, attitudinal, and emotional responses. For instance, studies have investigated how extreme weather events influence food and water security, conflict and security risks, climate action, and health outcomes. Additionally, the field of environmental human mobility has witnessed remarkable progress in data collection, analytical methods, and modeling techniques, advancing scientific understanding of the impacts of extreme weather on mobility and displacement.

Yet only few studies are currently harnessing the full potential of interdisciplinary collaborations in this space and several challenges pertaining to the choice of methods and the scale of analysis (e.g., regional, national) remain underexplored. This session aims to provide a platform for interdisciplinary work on extreme weather events and invites contributions from natural and social scientists interested in interdisciplinary studies on the societal impacts of and responses to extreme weather events. Furthermore, we highlight the topic of human (im)mobility with a perspective on addressing recent advancements, methodological innovations, novel use of data, challenges, or future prospects in modeling human mobility in the past, present, and future.

We invite contributions including but not limited to studies of:

Migration and displacement due to extreme events
Environmental attitudes and behaviors influenced by extreme events
Health and wellbeing effects of climate change and extreme events
Food production and security in relation to extreme weather
The interplay between climate change, environment, and conflict
Methodological challenges to interdisciplinary collaborations

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

We invite contributions that
-     use knowledge of past climates to advance our understanding of climate variability, abrupt changes and climate response to greenhouse gas changes and other forcing on spatio-temporal scales relevant for societies, ecosystems and the planet as a whole;
-     make use of information from paleoenvironmental proxy data, from past civilisations, from ESMs, and from rigorous theoretical approaches - individually or combined;
-     explore modern approaches to incorporate palaeoclimate information into the development processes of ESMs of varying complexity;

The session deals with scientific concepts and empirical studies in the natural and social sciences that address the societal pressures on the Earth system and/or the effects of Earth system changes on societies in the context of the Anthropocene. It involves descriptive and explanatory approaches for a better understanding of key interlinkages, feedbacks and natural and social tipping points as well as normative or ethical views of habitability such as planetary boundaries and social justice. Hereby, it focuses on the complexity, dynamics and uncertainties of the underlying Earth system processes and social, economic and political dynamics across spatial and temporal scales as well as preventive interventions for systemic sustainability transformations. The aim is to explore the potential of deeper integration of the different research strands with their ontological and epistemological knowledge for the advancement of Anthropocene research. The topics range from the analysis of stratigraphic archives of anthropogenic pressures and climate change impacts on human health and food security to secondary effects such as poverty, inequality and migration. Reflection of transformative capacities encompasses governance arrangements and policies with a particular emphasis on the communicative science-policy/society interface. Selected guiding questions are: What additional knowledge and methods are needed to more appropriately describe key interlinkages between Earth system and societies shaping the Anthropocene? What natural and social sciences evidence is needed as reference to further negotiate and agree on the future habitability of the planet for human societies and wild species? What science communication and education can facilitate the transfer of knowledge and strengthen societal capacities for sustainability transformations without destroying the hope for a liveable future? Approaches from all related disciplines and studies from around the world will be considered.

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

This session explores mythogenic landscapes as environments that generate and shape the creation, form, and content of myths, imaginaries, beliefs, and local narratives. In doing so, they exert a profound influence on communities and cultures. Within this context, one can refer to an abiotic cultural factor – the impact of geodiversity on humans and their cultural expressions. This factor often gives rise to distinctive forms of relationships between humans and the environment, operating at both symbolic and utilitarian levels. Mythogenic landscapes have shaped imaginaries and beliefs expressed in both verbal and non-verbal forms. Interpretations of extreme events and ideas about the origins of geomorphological features have contributed to the development of local geofolklore, including geomyths. Such cultural expressions form an important part of the intangible dimension of geoheritage, which should be evaluated not only in terms of scientific values but also for their cultural and culture-shaping significance. Traditional interpretations of the origins of landforms and geomorphological processes, geohazards and the causes of hydrometeorological events – together with the myths and legends associated with them – create a network of interrelations that vividly illustrate human and environment interactions. This synergy has strengthened the once-overlooked, but now increasingly recognized, need to protect geoheritage. Incorporating a humanities perspective into the study of geological processes, landforms, and hydrometeorological phenomena enhances the value of geosites as elements of the geo-cultural heritage of civilization. Such an approach not only supports the development of geotourism but also holds significant potential for geoeducation.
Proposed session topics
1. Meteor impacts, earthquakes, tsunamis, and volcanic eruptions in myths and oral traditions.
2. Local knowledge of landforms, hydrographic features, geological processes, and hydrometeorological phenomena.
3. Oral traditions as empirical evidence for dating geomorphological processes (e.g. rockfalls, landslides, extreme floods, karst phenomena, hailstorms).
4. Geomythical perspectives in oral traditions and cultural narratives.
5. From geomythology to geoheritage: exploring the symbolic meanings of geosites.
6. Geo-mytho-tourism: developing new local and regional geo-brands.
7. The potential of geomyths for geoeducation and public engagement.

Social-science and humanities (SSH) research is crucial for informing ambitious, effective, just or societally acceptable climate action. This session highlights how SSH insights on social metabolism, labor transitions, perceptions and societal readiness, institutional dynamics, justice, needs/capabilities, and power relations can enrich and reshape diverse modeling approaches. We aim to provide a platform for interdisciplinary work that broadens the scope of what models and scenarios can represent, clarifies their limits, and fosters connections across methods.

We welcome contributions that:

Integrate SSH concepts and methods into integrated assessment models (IAMs), energy–economy–environment models, or other analytical frameworks

Use empirical and participatory approaches to inform model assumptions, structures, and constraints

Engage with normative dimensions such as fairness, feasibility, and societal acceptance

Connect justice issues to marginalized or disadvantaged communities, especially in the Global South

Address the role of governance, institutions, finance, and critically evaluate material and human needs in shaping transition pathways

Investigate social impacts of modeled scenarios (e.g., income, labor, or demand modeling)

Just-transitions and equity analyses linked to real supply-chain data & green industrial policy

We particularly encourage work that incorporates procedural, recognitional, transitional and other forms of justice, identifies how data gaps map onto justice gaps, and provides bi-directional feedback between social science and modeling communities. By convening these perspectives, the session seeks to advance interdisciplinary approaches that make climate and energy scenarios more relevant, inclusive, and impactful.

This session calls for contributions from all disciplines and inter- and trans-disciplinary collaborations that are addressing complex problems of effects of climate change and environmental degradation on human, animal, and ecosystems health. These may include, but are not limited to, data analysis and modelling approaches and data- and model-based solutions, indicators development, nature-based solutions, wellbeing-centered and other planetary health interventions. Likewise, the contributions can provide better understanding of or insights into wide range of problems, from air or water pollution or biodiversity loss, to human, animal, and environmental health issues like infectious and zoonotic diseases, or plastic pollution and antimicrobial resistance, driven by climate change or environmental degradation.

Forests and surrounding landscapes are interconnected, and any human activities are integral elements of the socio-ecological system. Forest landscape management usually involves multi-stakeholder interventions to negotiate and implement management actions for local livelihoods, health and well-being. In this context integrated Decision Support Systems (DSS) are needed that help to address ecosystem services at the landscape scale by linking forest, agricultural and landscape interactions. The main aim of this inter- and transdisciplinary session is to identify solutions that use new and innovative methodological approaches in decision support, focusing on holistic planning to enhance sustainable ecosystem management and address ecosystem services, risks, and uncertainties. Computerized decision support systems (DSS) are know to support planning and decision making in semi- and unstructured decision problems. In that context database systems are often linked with analytical models and expert knowledge to take informed and data-driven decisions and allow managers visualizations by various graphical and tabular means. The first generation of DSSs was typically designed to address relatively narrow, well-defined problems for only one ecosystem service (e.g. timber production or increasing the resistance against storms). There has been a trend towards the development of more integrated DSS that simultaneously cover a broader range of ES such as habitat for biodiversity conservation and water provision, but there are still few examples for landscape management. This session invites contributions that bring together the scientific advances in this direction by presenting frameworks off integrated DSS and advandced combinations of methods, models and data to support decison making.

Cities are intricate multi-scale systems, composed of diverse sub-components such as population, energy, transport, and climate. These components interact on various time scales, from hourly to seasonal to annual and beyond. Effective urban models and digital twins, crucial for urban planning and policy-making, must account for these complex interactions as they govern the growth and functioning of cities, often giving rise to emergent large-scale phenomena. However, our ability to quantitatively describe city behaviour remains limited due to the myriad of processes, scales, and feedbacks involved.
This session invites studies focused on modelling and monitoring the dynamics of multiple sectors and city-biosphere interactions. Topics of interest include, but are not limited to:
• Demography
• Urban transport networks
• Energy consumption
• Anthropogenic emissions and Pollution
• Urban climate
• Urban hydrology
• Urban ecology

Our aim is to elucidate the complex dynamics within urban environments and explore how urban form and function can be optimised to enhance the liveability and well-being of their citizens.

Plastic pollution is ubiquitous in terrestrial, freshwater, and marine ecosystems. Reliable data on plastic abundance and fluxes are crucial to study its sources, sinks, transport dynamics, and impact. Furthermore, long-term and large-scale monitoring is required to design, implement, and assess plastic pollution prevention and reduction measures. In this session we invite contributions that present recent advances in plastic pollution monitoring across the entire Geosphere (atmosphere, land surface, soil, rivers, estuaries, oceans and beyond). Presentations may focus on:
• Novel monitoring methods, including advanced techniques (e.g. remote sensing, multi/hyperspectral cameras, acoustic sensors, artificial intelligence);
• Monitoring strategies, including large-scale and long-term efforts, and citizen science approaches;
• All plastic size ranges, from nano to macro;
• Baseline studies to assess current plastic pollution levels;
• Long-term trends or recent discoveries based on plastic monitoring data.
With this session we aim to bring together scientists that work on novel approaches to provide reliable data on environmental plastic pollution.

Mountains are complex social–ecological systems (MSES) and natural laboratories where the impacts of global environmental change become particularly visible. Rapid climate warming, cryosphere loss, shifting hydrological regimes, land-use change, and socio-economic transformation are jointly reshaping mountain environments. These changes affect MSES or specifics parts such as ecosystems, water resources, natural hazards, livelihoods, and human well-being, with consequences that extend far beyond mountain regions. As the planet’s water towers, mountains regulate freshwater availability along the mountain-to-lowland continuum and provide essential ecosystem-services. At the same time, mountain communities are often highly exposed and vulnerable to climate-related hazards such as floods, landslides, droughts, and compound or cascading events. Understanding how hazards, exposure, and vulnerability interact in space and time is therefore essential for effective climate risk management and long-term adaptation.
This session invites inter- and transdisciplinary contributions that examine past, present, and future environmental change in MSES and contributing from different perspectives to the understanding of MSES. Mountain regions present specific scientific and societal challenges.
Complex terrain remains difficult to adequately parameterize in models, high-elevation monitoring infrastructure is limited in many parts of the world, and socio-economic dynamics are often insufficiently captured in environmental assessments. Addressing these knowledge gaps is critical for developing robust and equitable adaptation strategies.
We particularly encourage contributions that integrate physical and social processes, explore cross-scale feedbacks and compound risks, advance high-elevation monitoring and remote sensing, apply climate downscaling approaches, and combine process-based, data-driven, and participatory methods. Studies engaging stakeholders, co-producing knowledge, and linking science to decision-making and policy are especially welcome.
By fostering dialogue across disciplines and between science and practice, this session aims to advance a systems-based understanding of MSES and support transferable approaches to sustainable adaptation under global environmental change.
This session is endorsed and supported by the Mountain Research Initiative and the Institute for Interdisciplinary Mountain Research of the Austrian Academy of Sciences.

During the last decades research in geosciences has become increasingly interdisciplinary. This is due to the fact that fundamental questions in science like “Which role did geological processes play in the origin of life on Earth?”, “How did the geosphere, biosphere and atmosphere interplay during the emergence and evolution of terrestrial life” and “Which geological and geophysical conditions ae necessary for the appearance of life on other celestial bodies” will not be answered by one discipline alone but require a concerted and coordinated approach involving many researchers with seemingly unrelated scientific backgrounds. Thus, boundaries between disciplines disappear and new cross-disciplinary fields like geochemistry, geobiology and astrobiology emerge. To be successful in such interdisciplinary fields the European research community needs to

• foster interdisciplinary research projects
• train the next generation of scientists in multidisciplinary research
• convince decision makers about the necessary of interdisciplinary research and training
• alert the general public to highlights of interdisciplinary research

Research in interdisciplinary fields opens a multitude of perspectives for researchers. Also, many of them meet lively interest of the general public. However, there are also challenges to be met: Firstly, researchers have to learn the language of fields seemingly unrelated to their own. Secondly, traditional curricular at universities might not always be open to or include interdisciplinary fields. Thirdly, there is always the chance of pseudoscience gaining ground.
In the proposed session following items could be discussed:

• Training in interdisciplinary fields like astrobiology: Experiences, chances, challenges and pitfalls
• Which channels and methods are apt to engage the general public (e.g. How can science fiction be used to interest people in research)
• How can we use interdisciplinary research areas to motivate young people to embark on a career in science?
• How to create efficient and sustainable European structures to coordinate and promote research in interdisciplinary fields

The experience of new structures like the European Astrobiology Institute in those areas could be of great value for other emerging interdisciplinary subjects. To our minds, such a session would be timely in a changing European science landscape.

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

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

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

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

Recent assessments of Earth system integrity highlight the deteriorating resilience of our planet, with planetary-scale human pressures pushing the Earth system into the uncharted territory of the Anthropocene. Earth resilience – the capacity of the system to resist, recover, and regenerate – is increasingly under pressure by global warming, weakening land and ocean carbon sinks and nonlinear dynamics across the Earth system. Of particular concern are tipping elements: large-scale components of the Earth system that can undergo abrupt, often irreversible state shifts once critical thresholds are crossed.

Examples include the Greenland ice sheets, the Atlantic Meridional Overturning Circulation, monsoon systems, and major ecosystems such as the Amazon rainforest or boreal forests. Rising anthropogenic pressures, such as greenhouse gas emissions and land-use change, increase the likelihood of crossing such thresholds. Their interactions may trigger tipping cascades, where the destabilization of one element increases the risk of others tipping, thereby amplifying Earth system change and undermining long-term Earth resilience.

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

In this session, we invite contributions on all topics relating to Earth resilience, planetary boundaries, tipping points in the Earth system, positive (social) tipping, as well as their interactions and potential cascading domino effects. We particularly welcome studies that use Earth system modelling, conceptual approaches, or data-driven analysis to investigate nonlinear dynamics, abrupt shifts, and tipping points, as well as contributions exploring social tipping processes and their role in shaping a more sustainable future.

Decision-makers are increasingly required to address climate hazards related to extreme weather events when considering, disclosing, and acting to mitigate complex risks. An interdisciplinary approach is required to increase understanding and forge possible adaptation and mitigation solutions. In this session we address extreme weather events and their changes with an interdisciplinary lens. These events may include temperature, precipitation, wind, and compound extremes, and their impacts on humans, the built environment, or the natural world. We welcome contributions from interdisciplinary teams as well as those seeking to connect with such teams. Topics of interest include but are not limited to:

- early warning systems and their evaluation
- physical climate science knowledge gaps that affect decision making
- risk management in the financial and insurance sectors
- impact-based forecasting of weather extremes
- cross-boundary and trans-lateral effects
- assessment of dynamically varying vulnerabilities
- data-driven approaches using machine learning, and
- storyline approaches to risk understanding.

The focus of this session is on interdisciplinary approaches to translating physical science into decision-relevant information.

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

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

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

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

Nature-based Solutions (NbS) are “actions to protect, conserve, restore, sustainably use and manage natural or modified ecosystems, that address socio-economic and environmental challenges, while simultaneously providing human well-being, resilience and biodiversity benefits”. Within the framework of a global ecosystem approach, NbS must encompass ecological, societal, political, economic and cultural issues at all levels, from the individual to the collective, from local to national, from the public or private sphere.

As underlined by the IPCC and IPBES, climate change and biodiversity loss are deeply interconnected and must be addressed jointly. This session therefore focuses on how NbS can serve as adaptation strategies to climate change, while simultaneously preserving or restoring biodiversity. Considering various ecosystems (marine and coastal, urban, cropland, mountainous, forest, rivers…), NbS as climate change adaptation solutions includes the adaptation to: sea level rise (flooding and erosion), changes of the water regime (floods, droughts, water quality and availability), rise in temperatures (heat waves, forest fires, drought, energy consumption), plant stress and increase of pests (variation of yields, forest dieback), to minimize their associated social and economic negative impacts.

Therefore, this session aims to promote discussion integrating multiple disciplines related to ecosystem restoration, preservation and management, to put forward the complexity that is often hidden by simplifying hypotheses and approaches (sector-based silo approach, homogeneity of environments...).

Specific topics of interest are the followings:
- Complexity: nature of ecosystems and risk of oversimplification, interconnection between NbS and complementary areas, consideration of uncertainties
- Scales: spatial scales with the integration of NbS in their environment, and temporal scales considering sustainability over time, variability of bio-physical processes and climate change effects
- Ecosystem services: bio-geophysical processes, spatial shift between the location of NbS and the beneficiaries one, modification under climate change (tipping point), co-benefits or negative effects
- Assessment and indicators: measurement and modelling protocols, capacity to measure the complexity, resilience and stability of NbS
- Co-development with stakeholders, engaging civil society, and integrating NBS into education, aligned with IAHS Helping Decade objectives

Nature-based solutions (NBS) are increasingly recognized as transformative strategies for addressing the twin challenges of climate change and environmental degradation while promoting sustainable development. By harnessing the capacity of ecosystems, NBS such as wetlands, restored streams, floodplains, and green infrastructure can mitigate floods and droughts, improve water quality, enhance biodiversity, and support human well-being. Their implementation aligns with the European Green Deal, the UN Sustainable Development Goals (SDGs), and global climate adaptation commitments. Despite their growing prominence, many questions remain about how to design, implement, assess, and scale up NBS in diverse hydrological and socio-economic contexts. Evidence is still emerging on their long-term performance compared to conventional engineering approaches, the trade-offs and synergies among ecosystem services, and the enabling conditions for mainstreaming NBS in water and land management policies.
This session explicitly aims to foster interdisciplinary and transdisciplinary exchange by bringing together hydrologists, geomorphologists, ecologists, soil scientists, hazard researchers, and social scientists, alongside practitioners and policymakers. The goal is to advance both the scientific basis and the practical governance of NBS for resilience planning, land and water management, and climate adaptation across landscapes.
We welcome contributions that:
- Provide evidence of NBS performance in water storage, flood and drought resilience, sediment and nutrient retention, and ecosystem service delivery.
- Develop or apply innovative tools and frameworks for placement and site selection, designing, and monitoring NBS (e.g., modelling, remote sensing, decision-support systems, participatory approaches).
- Explore co-benefits and trade-offs, particularly in relation to hydrological performance, ecological, and socio-economic effects.
- Present case studies and comparative analyses from different climatic and geographical contexts or applied to specific anthropic elements such as long linear infrastructures.
- Identify governance, policy, and financial mechanisms that enable successful NBS implementation and upscaling.
By bridging science, practice, and policy, this session highlights NBS as key instruments for advancing water and land management, strengthening resilience, and creating sustainable futures.

Water underpins every aspect of life, from healthy ecosystems to economic prosperity and human well-being. People, ecosystems, and all living species depend on it for survival. As climate change intensifies droughts, floods, and water quality degradation, ensuring water resilience has become an urgent priority. The recently adopted EU Water Resilience Strategy (2025) responds to this challenge setting out an ambitious agenda to ensure Europe’s water systems can withstand growing climate-induced pressures, water reuse and preserving ecosystems while supporting human well-being and enabling water-smart economy. It calls for integrated water governance, and systemic and innovative solutions to reduce vulnerabilities, and build adaptive capacity across all sectors. Nature-Based Solutions (NbS) offer transformative means to achieve these objectives. By restoring ecosystems, enhancing natural water retention, and reinforcing the connectivity between terrestrial and aquatic systems, NbS help maintaining hydrological balance while delivering multi-faceted ecosystems services and biodiversity gains. Mainstreaming NbS requires bridging the gap between strategy design and implementation, through replicating and scaling up successful models, aligning policies and financing instruments while fostering participatory governance to ensure solutions are ecologically effective and socially acceptable. This session invites participants to explore how mainstreaming NbS can translate the EU Strategy into action by closing the implementation gap and advancing integrated water management frameworks that align governance, financing, and innovation under a shared ambition: achieving water resilience. Contributions are welcome from real-world NbS case studies, methodological approaches and tools for co-design and stakeholder engagement in water management planning and implementation. In particular, we seek insights into how NbS are valued and implemented as alternative and/or complementary investments to grey infrastructure, and which methods are agile, whilst robust, to undertake such comparative evaluations. Submissions demonstrating innovation and practical applications, monitoring and evaluation strategies, and measurable outcomes showcasing NbS co-benefits would be highly valued, ensuring that the discussion bridges scientific evidence with real-world impact to enhance water availability and quality, reduce disaster risk, while strengthening socio-ecological resilience.

Climate change poses a significant threat to sustainability. It disproportionately affects different social groups, intensifying interconnected risks across socio-ecological systems and challenging conventional approaches to disaster risk reduction and adaptation. These challenges are particularly pronounced in climate-sensitive ecosystems, such as arid and semi-arid regions, where land degradation, water scarcity, biodiversity loss, and socio-economic vulnerability intersect.

Nature-based and community-led strategies offer effective, context-specific solutions that reduce climate risks, restore ecosystems, enhance biodiversity and ecosystem services, and support local livelihoods, enabling sustainable and equitable adaptation even in highly constrained environments such as drylands.

This session invites contributions that explore how nature-based and community-led approaches support disaster risk reduction, ecosystem restoration, and climate change adaptation across diverse ecological and socio-economic contexts, with a particular focus on research that:
- Assesses the effectiveness of these strategies in reducing risk and enhancing climate resilience
- Examines socio-ecological trade-offs and synergies by integrating ecological and social science perspectives within systems-based approaches
- Evaluates long-term resilience and restoration outcomes across varied ecological and socio-economic contexts, including arid and semi-arid landscapes
- Engages with Indigenous and local knowledge systems, emphasizing culturally grounded and community-driven solutions
- Investigates governance challenges, structural barriers, and enabling conditions, and explores inclusive frameworks that support equity, participation, and sustainability
- Investigates synergies and trade-offs between nature-based approaches and conventional measures
- Examines the effectiveness, resilience, and scalability of specific nature-based solution typologies (e.g., water harvesting, vegetation restoration, agroforestry)
- Examines innovative monitoring and assessment tools (e.g., citizen science, remote sensing, hydrological modelling, eDNA, AI) to evaluate, optimize, and scale nature-based and community-led strategies

This session is supported by the RISK-KAN Working Group on “Nature-Based and Community-Led Climate Risk Strategies.” Contributions from diverse regions are welcome, with a particular emphasis on early-career researchers and practitioners from underrepresented areas.

Nature-based coastal solutions (NBCS) – such as saltmarsh and mangrove restoration, living shorelines, beach and dune rehabilitation, and reef structures (artificial and natural) – are increasingly promoted as sustainable responses to the complex challenges of coastal zone management. These approaches aim to harness natural processes to stabilise coastlines, reduce flood and erosion risk, enhance biodiversity, and provide co-benefits, including carbon storage and improved water quality. While the physical and ecological advantages of NBCS are supported by growing evidence, significant uncertainties remain about their long-term effectiveness, particularly under changing climate and socioeconomic conditions. These knowledge gaps are especially critical for informing policy and investment decisions in coastal infrastructure and adaptation strategies. We invite contributions that integrate coastal geoscience, engineering, and broader system-level thinking to evaluate the long-term performance, risks, and trade-offs of NBCS across diverse environmental and governance contexts. We encourage submissions that include, but are not limited to:

(a) Case studies on NBCS implementation across varied coastal geomorphologies and hydroclimatic regimes, with evidence of long-term outcomes or monitoring data;
(b) Modelling studies that assess NBCS performance under future climate and sea-level rise scenarios;
(c) Innovations in field methods, remote sensing, and data integration for evaluating NBCS impacts on geomorphic and ecological processes;
(d) Systems-based approaches (e.g., coupled human–natural models, scenario planning) that address feedbacks between NBCS, coastal dynamics, and socioeconomic systems;
(e) Studies that focus on advancing the engineering design of NBCS and may include recommendations for types and values of design parameters and criteria;
(f) Perspectives on the institutional, regulatory, and financial frameworks shaping the deployment and long-term maintenance of NBCS.

We particularly (a) welcome interdisciplinary studies that combine geoscientific analysis with insights from ecology, engineering, planning, and policy, and (b) encourage dialogue on how transdisciplinary approaches can help guide the design, implementation, and long-term governance of effective NBCS.

Cities are increasingly challenged by rapid expansion and climate change, placing growing pressure on urban water systems in particular. Nature-based solutions (NbS), often implemented as blue-green infrastructure, are particularly relevant in contemporary urban environments since they promote on-site water infiltration and storage, thereby improving water quality and reducing flood risk. They are also widely recognized as multifunctional solutions that can deliver a range of ecosystem services, including urban climate regulation, protection of human health, biodiversity restoration, and the provision of accessible public spaces.
Despite this multifunctional potential, the design, planning, and implementation of NbS often remain sector-specific and fail to adequately account for multiple environmental, social, and economic objectives. Addressing these challenges requires interdisciplinary perspectives not only across environmental engineering, urban planning, and governance, but also within each of these domains, where diverse methodological, conceptual, and institutional approaches must be better integrated.
This session focuses on integrated approaches for the implementation of multifunctional NbS in urban areas. We invite contributions from engineering, planning, and policy that examine how NbS can be designed, evaluated, and governed to address multiple objectives simultaneously, including sustainable water management, urban climate regulation, biodiversity enhancement, and the use of public spaces.

Topics of Interest:
• Quantitative assessments and integrated modeling frameworks evaluating multiple benefits of blue-green infrastructure and other NBS
• Identification of synergies and trade-offs in the design and implementation of multifunctional NBS
• Methodological, institutional, and conceptual challenges of interdisciplinary research and practice
• Governance, planning, and policy dimensions shaping the adoption, performance, and scaling of NBS across urban sectors

As cities and human settlements face increasing pressures from climate change, environmental degradation, biodiversity loss, pollution, and growing social inequalities, there is a rising need for inclusive, data-informed and integrated approaches to climate and environmental action. This session explores how citizen science, participatory data generation, and innovative analytical tools can support climate adaptation and mitigation and other environmental priorities, while improving understanding of interdependencies, synergies, and trade-offs across sectors and policy domains. It highlights how citizen-generated data and qualitative and quantitative approaches such as indicator-based assessments, system dynamics and integrated modeling can enhance environmental monitoring, hazard detection, and evidence-based decision-making, while also strengthening community engagement in climate research and action.

The session invites contributions that demonstrate the use of citizen science datasets, participatory sensing technologies, and the integration of citizen science with Earth Observations, AI, modeling, and system-based approaches to assess both adaptation and mitigation measures in the context of climate change and broader environmental challenges. At the same time, it emphasizes processes, methods, and tools that help identify and incorporate interdependencies across climate mitigation and adaptation and environmental domains, moving beyond sectoral silos to support coordinated urban planning and policy development. Particular interest lies in innovative engagement models involving underrepresented or vulnerable groups, stakeholder-driven approaches that raise awareness of cross-sector interactions, and case studies showing how participatory and integrative methods can address data gaps, support community-led action, and inform local policies—including in resource-constrained settings and low- and middle-income countries. The session fosters cross-disciplinary and cross-regional dialogue among researchers, practitioners, policymakers, technologists, and data scientists working toward climate-resilient, low-carbon, and inclusive cities.

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

Over the past five decades, climate extremes have caused more than two million reported deaths and at least US$4.3 trillion in losses. In 2024, global temperatures reached their highest on record, about 1.55 °C above the pre-industrial baseline, according to recent meteorological. Beyond fatalities, extremes drive substantial morbidity, particularly cardiorespiratory illness, and disrupt access to care. In Europe alone, an estimated 61,672 heat-related deaths occurred in summer 2022. Hazardous heat exposure among workers is associated with approximately 23 million injuries and about 19,000 deaths globally each year.
These impacts are unevenly distributed and are expected to escalate. Socioeconomic position, age, sex/gender, ethnicity, pre-existing conditions, occupation and place intersect to shape exposure, sensitivity and adaptive capacity. Marginalised groups, including older adults, children, people with chronic conditions, outdoor workers and residents of low-income or geographically exposed areas, bear a disproportionate burden. An intersectional, climate-justice lens is therefore essential across public health, early warning, urban planning and health-system adaptation.
This session, organised in collaboration with the Swedish Centre for Impacts of Climate Extremes (CLIMES), invites contributions that investigate the complex and uneven impacts of climate extremes on population health. We particularly welcome studies that (i) characterise past impacts and future risks from single and compound extremes; (ii) map intersecting socioeconomic, demographic and spatial vulnerabilities; (iii) evaluate adaptation and early-warning interventions (including occupational heat); and (iv) integrate health, climate and social data to inform equitable climate adaptation and public health responses.

This session focuses on the concept of extreme heat events, specifically how high temperature coupled with humidity (wet-bulb temperature extremes) exponentially increases heat-related health impacts and mortality risk. Recent research indicates that oppressive (high-humidity, high-temperature) heatwaves may increase sharply with overshoot, up to five- to eight-fold under 1.5 °C to 2 °C warming. Understanding these trends is critical to adaptation planning, early warning systems, and health policy, especially in vulnerable regions. Presentations are invited on modeling projections of potentially lethal heat events, under future climate scenarios, and on methodologies to quantify associated health impacts, from heat-related mortality to compromised labor productivity and disease vulnerability. The session welcomes rigorous climate modeling studies, epidemiological analyses, and datasets that map extreme heat thresholds or events, especially those grounded in human thermoregulatory physiology. We also encourage contributions that analyze urban–rural differences, compounding effects with air pollution or disease outbreaks, inequities in vulnerability, adaptation limits, and health system implications in overshoot scenarios. By bringing together climate scientists, health researchers, urban planners, and policymakers, this session aims to highlight urgent, interdisciplinary challenges at the intersection of heat extremes and human health in a warming world.

The IPCC highlights climate resilience as key for regions to absorb, anticipate, accommodate or recover from the effects of a hazardous event, clearly communicating the potential of resilience to better withstand climate hazards and reduce their impacts. While individual adaptation measures focus on decreasing the risk related to a specific hazard to a defined object, resilience frameworks and their suggested areas tackle general regional structures, enhancing the region’s ability to withhold any kind of shock – also in the future. In recent years, multiple resilience assessment tools and scorecards have been developed, many of which rely heavily on local stakeholder input and participatory processes. However, objective and quantitative climate resilience indicators remain relatively rare.

Within this section we encourage contributions to present their resilience assessment approaches, both qualitatively and quantitatively, their processes and findings. As well as their interactive formats to engage with local stakeholders and ensure a common understanding of resilience, it’s strengths and potential weaknesses.

Natural hazards have been an inherent aspect of Earth’s history, shaping ecosystems, landscapes, and human societies from ancient times to the present, with climate variability and fire playing particularly influential roles. Urbanisation has increased climate risk in densely populated areas, but also created new possibilities for shaping resilience through technological improvements, environmental management, and changes in societal structures. Understanding how societies in the past responded to climate-related and fire hazards, and how social resilience emerged, provides valuable insights into today’s challenges. These historical perspectives inform strategies for sustainable adaptation amid ongoing global environmental change. Drawing on insights from archaeology, climatology, anthropology, history, and geography, scholars can elucidate the complex interconnections between climate variability, human adaptation, and societal resilience across different temporal and spatial scales.
Data-driven methods—including spatial analysis and statistical modelling of spatiotemporal information—can detect patterns of change over time, informing how resources were allocated and adaptive strategies developed over time. Results from case studies can detect how social, built environment, and infrastructure systems (co-)evolved, contributing to a deeper understanding of systemic change in hazard-prone areas. At the same time, Indigenous perspectives, community-based approaches, and participatory methodologies can enhance the resilience of vulnerable populations, improve understanding of past fire stewardship, and foster sustainable responses to climate change in the twenty-first century.
This session explores how societies have historically responded to climate-related hazards and environmental challenges. Key themes include, but are not limited to:
• Historical perspectives on climate variability and societal change
• Cultural pyroscapes: landscapes shaped by the interactions between societies and fire
• Case studies of resilience in ancient and medieval societies
• The development of adaptive strategies in relation to urbanisation processes
• Indigenous knowledge and adaptive strategies
• Technological innovations and agricultural practices change over time
• Adaptive strategies for responding to historical hazards and their transformation
• Case studies on the (co-)evolution of social and environmental systems in hazard-prone areas

Resilience assessments provide critical insights into how societies and ecosystems drive, withstand and adapt to hydrological change. Although freshwater is embedded within social and ecological systems, freshwater resilience is still predominantly studied within disciplinary silos or within pairwise human-water and ecosystem-water frameworks. It is imperative to build on and integrate these disciplinary foundations to develop more comprehensive theories of system change, characterize systemic risks, and identify opportunities for improved governance and management.

This session invites interdisciplinary and transdisciplinary contributions that investigate or support freshwater resilience assessments through the integrated representation of hydrological, social, and ecological processes. Examples of contributions that we hope to receive include, but are not limited to:

[•] Analysis of empirical Earth observations, such as remote sensing, or field-collected social and ecological data to evaluate and track resilience across catchments, regions, and global freshwater systems.
[•] Development or use of process-based models to assess interactions and feedbacks between hydrological, ecological, and societal dynamics.
[•] Applications of machine learning or artificial intelligence techniques to detect, model, and forecast freshwater resilience.
[•] Transdisciplinary case studies that work with practitioners, communities, or policy-makers to define system boundaries, support knowledge co-production, or advance frameworks that strengthen freshwater resilience in practice.
[•] Any other studies that work to build a more holistic and actionable understanding of freshwater resilience with insights that may inform strategies to safeguard freshwater’s role in sustaining ecosystems, societies, and Earth systems.

By bringing together researchers across hydrology, ecology, climate science, governance, and social-ecological systems research, this session is motivated to bridge methods and perspectives that are often fragmented and would benefit from greater integration and collaboration.

A number of countries develop and disseminate ‘National Climate Scenario’ products to inform a range of applications, including climate risk assessments and impacts assessments and the development of adaptation plans.
Different nations have taken a range of approaches to the provision of their National Scenarios to provide decision-relevant information. Common challenges encountered by the providers of National Scenarios include how to capture, quantify and communicate uncertainties, the provision of information at high enough resolution to inform relevant applications, how to update and revise National Projections to capture new and emerging science, and understanding the user landscape to provide information of both the type and format that is relevant and accessible to a wide range of ‘next users’ and ‘end users’ with different levels of technical capacity and different specific requirements.
The session will take an inter-disciplinary view of the landscape of the provision and use of National Projections, and we particularly encourage submissions that consider:
• Latest plans and opportunities for developing new or updated National Projections products and services;
• Challenges in the provision of National climate information – including technical hurdles, information gaps and the challenges in providing information in ways that is relevant and accessible;
• New developments in the science or scenario products drawing from novel types of information that could form part of a National Climate information package – e.g. drawing from event Attribution, exploiting decadal forecasts to provide near-term projection information, provision of ‘High Impact, Low Likelihood’ scenarios, exploitation of convection-permitting downscaling and global high resolution models, the use of storylines approaches;
• Understanding user needs and the co-development of climate information and services;
• The future outlook and opportunities for national climate services, including developments such as CMIP7 and CORDEX, potential to use of AI emulation in projections products, and the implications of wider climate science and or policy developments.

Early Warning Systems (EWS) represent a critical cornerstone of disaster risk reduction as they provide an essential foundation for protecting lives and livelihoods through the timely provision of actionable information. However, the efficacy of EWS is dependent not only on scientific robustness but also on seamless integration across disciplines, from disaster risk knowledge and hazard detection to communication strategies and community response. Subsequently, these systems require innovative advancements across the warning chain to meet the ambitious targets outlined in the Early Warnings for All (EW4ALL) initiative action plan and the Sendai Framework towards multi-hazard, all-vulnerability, and impact-based EWS. This session aims to foster a dialogue on the implementation and methodological innovations surrounding EWS, particularly between researchers working toward more effective, inclusive, and actionable EWS.

This interdisciplinary session invites contributions from a wide range of disciplines and sectors involved with the full spectrum of EWS development and implementation, including but not limited to natural hazards science, atmospheric and hydrologic research, social sciences, and disaster management practice. We encourage submissions addressing the following key themes and sharing of lessons from successes and failures:
● Early warning and anticipatory action: Frameworks and multi-stakeholder implementation in translating early warnings/EWS into effective disaster response and preparedness mechanisms;
● Impact-based approaches: methodologies and approaches for design and implementation of impact-based EWS;
● Technological innovations: advances in AI, machine learning, Earth observation, IoT and other cutting-edge technologies in components of EWS;
● Risk communication and community engagement: strategies that integrate behavioral and psychological insights, building trust, and ensure effective warning communication and dissemination, particularly at the community level;
● Data integration and system interoperability: approaches to integrate diverse data sources that address challenges in cross-agency data sharing and platform integration.

The Aegean Sea is a dynamic convergent-margin exhibiting shallow subduction, back-arc volcanism and a long history of coupled geo-marine extreme events, including earthquakes, volcanic activity, submarine landslides, and tsunamis. These extreme events often occur in a cascading manner, posing a significant hazard to densely populated coastal areas, tourism-focused economies and critical infrastructure. To understand, characterize and mitigate the compounding hazards requires a transdisciplinary approach, integrating marine earth sciences, geophysics, hazard modelling, social sciences, engineering and stakeholder engagement to foster participatory research in the Aegean Sea.
This session invites contributions (particularly from Early Career Scientists), that will broaden and deepen scientific and societal understanding of marine and coastal geohazards in the Aegean Sea, adjacent Mediterranean regions and similar environments worldwide.
Topics of interest include:
• Geohazard processes and cascading events: seismic, volcanic, and submarine mechanisms leading to multi-hazard cascades, such as tsunamis.
• Monitoring and early warning systems: advances in seafloor instrumentation, seismic and geodetic networks, satellite remote sensing, and real-time modeling.
• Scenario development and risk assessment: earthquake, landslides, tsunami and coupled simulations, probabilistic hazard assessments, and uncertainty quantifications.
• Societal integration and resilience: participatory approaches, co-designed risk strategies, innovative communication tools (e.g., Augmented and Virtual Realities), and their applications to tourism, public safety and cultural heritage protection.
• Comparative perspectives from other tectonically active coastal regions.
This session builds on the ongoing MULTI-MAREX consortium of the German Marine Research Alliance’s (DAM) third research mission, which is developing integrated 'living laboratories' in the Aegean Sea to study and communicate risks of cascading marine geohazards. We encourage contributions from other research initiatives and independent studies, providing a platform for transdisciplinary exchange and dialogue between geoscientists, engineers, social scientists, tourism researchers and stakeholders.

Achieving carbon neutrality, and ultimately net carbon removal, is a central pillar of climate mitigation, but it increasingly entails complex scientific, technological, and societal challenges. Pathways consistent with limiting global warming to 1.5°C or 2°C are expected to rely heavily on the deployment of negative emission strategies, including afforestation and reforestation, bioenergy with carbon capture and storage (BECCS), enhanced rock weathering, and direct air carbon capture and storage. While these approaches offer substantial mitigation potential, they are constrained by biogeophysical limits, technological feasibility, governance challenges, and uneven social impacts across regions and communities. At the same time, the transition toward carbon neutrality is reshaping industrial structures, land use, and everyday life, with significant implications for the distribution of costs and benefits. These transformations can intensify social conflicts, disproportionately affect vulnerable groups, and shape public perceptions and acceptance of climate policies and technologies. Understanding the interactions between technological deployment, societal responses, and governance is therefore essential for assessing the feasibility and inclusiveness of carbon neutrality pathways. This session examines carbon neutrality pathways from inter- and trans-disciplinary perspectives, focusing on the potentials and limits of negative emission technologies and their societal implications, including issues of social conflict, governance, and inclusion.

Climate- and weather-related losses continue to rise, even as scientific understanding and risk management efforts expand. While climate change intensifies the frequency and magnitude of many hazards, evolving exposure patterns and the multidimensional nature of vulnerability are equally decisive drivers of risk. This session examines the dynamic interplay of these factors across physical, social, environmental and institutional dimensions to understand how hazards, exposure, and vulnerability co-evolve in space and time, and how those dynamics shape risk outcomes in the Anthropocene.

We invite contributions that move beyond static assumptions and address nonstationarity, compounding events, and cascading failures. Hazard regimes are changing, and their interactions can amplify impacts in the built environment. Submissions that analyze triggers, propagation, and recovery processes are particularly welcome.

Exposure is growing as urbanization intensifies, economies expand, and infrastructure networks densify, yet its spatio-temporal dynamics remain under-characterized. We encourage work that maps and models exposure trajectories under shared socio-economic pathways, evaluates the effectiveness and unintended consequences of mitigation and land-use measures, and explores how mobility, land-use change, and supply-chain linkages redistribute risk.

Understanding the vulnerability of elements at risk is crucial, because it governs the severity of impacts from climate hazards and is key to reducing future losses. The challenges of the Anthropocene require widening definitions and assessing shifts across multiple interacting hazards and contexts to address the multidimensional, dynamic character of vulnerability. However, the growing complexity of managing multiple domains, scales, and disciplines can impede holistic perspectives. We welcome studies that integrate socio-ecological, behavioral, engineering, institutional, and contextual information. Interdisciplinary and mixed-method approaches that bridge datasets and improve data interoperability, validation of vulnerability functions, and synthesis of evidence are encouraged.

We aim to foster transferable, adaptive risk management that connects landscape processes with human activities and supports equitable climate adaptation. By integrating the dynamics of hazards, exposure and vulnerability, this session advances coherent pathways to manage climate risk in the Anthropocene.

Over the past few decades, landslide research has expanded considerably, producing a wealth of scientific insights. Our understanding of slope failure processes has advanced significantly, yet it remains unclear how effectively engineering geologists and geotechnical engineers focused on slope stabilization and landslide risk reduction are translating this knowledge into practice.
This session aims to bring together researchers and practitioners from diverse backgrounds to:
1. Foster collaboration and networking across disciplinary boundaries
2. Encourage the exchange of theoretical insights and practical approaches to landslide investigation and mitigation
3. Promote more efficient use of limited resources for landslide risk reduction

We particularly welcome contributions on topics such as:
• Expanding the affordable use of innovative technologies for landslide detection and mapping (e.g., optical and radar satellite remote sensing)
• Advances in subsurface characterization using customized geophysical methods (e.g., electrical resistivity, seismic tomography)
• Integration of remote sensing and ground-based data for improved landslide monitoring
• Engineering geological models as integrative tools for site-specific landslide risk mitigation
• Data availability, quality issues, and handling geological uncertainty in slope stability modeling
• Approaches to slope stability analysis, from empirical methods to advanced numerical models
• Impacts of climate variability on landslide occurrence and engineered slope performance
• Low-cost, reconnaissance-level hazard assessments in data-scarce or disaster-affected regions (e.g., co- and post-seismic landslide events)
• Case histories of slope stabilization and landslide mitigation - including both successful and unsuccessful interventions - to highlight the limitations of “one-size-fits-all” solutions
• Knowledge transfer between scientists and engineers, and effective communication of landslide risk to civil protection authorities, policymakers, media, and the general public
Session sponsored by the International Association of Engineering Geology and the Environment (IAEG – https://iaeg.info)

Across Africa, failure to adapt to unintended global change processes, are creating urgent environmental challenges that demand scientific attention. Building the capacity for high-quality research in Africa is therefore critical, requiring not only skilled people and scientific infrastructure, but also inclusive opportunities for sustained collaboration across regions, disciplines, and sectors. Over the past years, a variety of European and African initiatives have supported capacity development, ranging from training programmes and research infrastructure to collaborative projects and community engagement. Yet these efforts often remain scattered and unsustainable, limiting their visibility and long-term impact.
This interdisciplinary session invites contributions that strengthen Africa’s research capacity in the environmental, and climate sciences. We welcome initiatives that address all stages of the research cycle: the collection of in situ and remotely sensed data; the development of models and analytical frameworks; the translation of research into practical applications; and the communication of results to stakeholders, policy makers, and communities. Submissions may include co-designed monitoring systems, field and training networks, open science and FAIR data initiatives, cross-continental partnerships, and efforts to embed research within global policy frameworks such as the SDGs, Paris Agreement and Sendai Framework. Submissions across the full range of sub-disciplines are encouraged, including but not limited to global change, natural hazards, land and ecosystem dynamics and sustainable resource use.
We particularly encourage examples that highlight inclusivity, equity, and African leadership - such as programmes empowering early-career researchers, women scientists, and underrepresented institutions. By showcasing diverse initiatives, this session aims to share effective practices, identify common challenges, and inspire new pathways for collaboration within and beyond Africa - Europe partnerships. A follow-up splinter meeting will provide additional space for discussion, networking and exchange among interested participants.

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.

To accurately understand climate risks, baseline historical understanding of hazard is required and what large-scale factors influence this for different geographic regions. Then 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. To avoid an underestimation of future physical climate risks. Further challenges include the accurate representation of extreme events, their compounding and cascading effects, and the integration of non-linearities associated with tipping points in the climate system.

In recognition of this challenge climate risk assessments have experienced amplified attention in both the academic and private spheres 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.

Therefore, providing a platform to foster interactions between scientists, risk modellers and assessors, 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 a wide range of topics including innovative climate risk modeling and model evaluation, damage functions, integrated assessment modelling, bias adjustment and downscaling methods, climate emulators, climate hazard indicators and their projections for specific sectors (e.g. food, energy, insurance, real estate, supply chains), impact data collection and categorization.

Scenarios and storylines provide complementary frameworks to explore, quantify, and communicate climate risks under deep uncertainty, and to support decision-making across science, policy and practice. Storylines, defined as “physically self-consistent unfoldings of past events, or of plausible future events or pathways,” can be used to systematically describe climate-driven trends or extreme events, and the associated risk while accounting for uncertainty. Socioeconomic scenarios explore long-term alternative development pathways, exposure and vulnerability dynamics, and societal responses. Together, they provide a powerful framework to investigate short to long-term climate risk estimates and projections, including compound and cascading risks, stress-test systems, intervention options in uncertain futures. They allow us to explore multiple plausible futures, supporting decision-making in high-uncertainty conditions and helping prioritize and optimize interventions to reduce negative impacts.

This session brings together researchers and practitioners working across climate science, impacts and risk assessment, and social sciences to advance the development and application of climate risk storylines and scenarios. We welcome contributions that span the full chain from physical climate modelling and event attribution to the co-production of narratives with stakeholders, and the use of scenarios in real-world decision contexts.

We invite abstracts that address, among others:

a) Physical and impact-based climate storylines, including past events, attribution studies, and plausible future extremes
b) Development and use of socioeconomic scenarios, including qualitative narratives and their quantification
c) Methods for integrating quantitative and qualitative knowledge, and linking climate and non-climate risk drivers
d) Conceptual models and frameworks for combining hazards, exposure, vulnerability and response
e) Applications of storylines and scenarios for stress testing, impact and risk assessment, early warning systems, adaptation planning and policy support
f) Participatory and co-production approaches that enhance relevance, robustness and uptake for decision-making

By bridging physical modelling, socioeconomic pathways and stakeholder-driven approaches, this session aims to strengthen the role of storylines and scenarios as actionable tools for managing climate risks in a rapidly changing world.

Scientific drilling in the ocean and on continents provides unique window into the workings of the interior of our planet, Earth surface processes, paleoclimates, natural hazards and the distribution of subsurface microbial life. The past and current scientific drilling programs of the International Ocean Discovery Program (IODP), the International Ocean Drilling Programme (IODP3) and the International Continental Scientific Drilling Program (ICDP) continue to foster major advances in many interdisciplinary fields of socio-economic relevance, such as climate and ecosystem evolution, palaeoceanography, the deep biosphere, sustainable georesources, crustal and tectonic processes, geodynamics and geohazards. This session invites contributions that present and/or review recent scientific results from deep Earth sampling and monitoring through ocean and continental drilling projects. Furthermore, we encourage contributions outlining visions for future drilling projects, as well as new research emerging from scientific drilling legacy data.