The Earth’s magnetic field is produced by dynamo action in the liquid iron core, which has profound influence on our habitable planet. One of the most striking manifestations of the geodynamo are complete reversals of the dipole. Numerical simulations indicate that the lower mantle has a manifold impact on the dynamo whereby the absolute value and pattern of the heat flux through the core-mantle boundary affects the field strength, field geometry and reversal rate. However, neither the structure and the long-term evolution of the lower mantle and the core, nor the coupling between the two, are well understood. Moreover, field strength and reversal rate likely influence the survival and evolution of magnetoreceptive organisms, especially magnetotatic bacteria. We invite contributions that aim at understanding the long-term evolution of the geomagnetic field and Earth's core dynamics, deep mantle dynamics and its influence on the geodynamo. This interdisciplinary session aims to bring together paleomagnetists, seismologists, dynamo modellers, mantle dynamicists, mineral physicists, and biologists.

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

In recent years, technologies based on Artificial Intelligence (AI), such as image processing, smart sensors, and intelligent inversion, have garnered significant attention from researchers in the geosciences community. These technologies offer the promise of transitioning geosciences from qualitative to quantitative analysis, unlocking new insights and capabilities previously thought unattainable.
One of the key reasons for the growing popularity of AI in geosciences is its unparalleled ability to efficiently analyze vast datasets within remarkably short timeframes. This capability empowers scientists and researchers to tackle some of the most intricate and challenging issues in fields like Geophysics, Seismology, Hydrology, Planetary Science, Remote Sensing, and Disaster Risk Reduction.
As we stand on the cusp of a new era in geosciences, the integration of artificial intelligence promises to deliver more accurate estimations, efficient predictions, and innovative solutions. By leveraging algorithms and machine learning, AI empowers geoscientists to uncover intricate patterns and relationships within complex data sources, ultimately advancing our understanding of the Earth's dynamic systems. In essence, artificial intelligence has become an indispensable tool in the pursuit of quantitative precision and deeper insights in the fascinating world of geosciences.
For this reason, aim of this session is to explore new advances and approaches of AI in Geosciences.

The radioactive materials are known as polluting materials that are hazardous for human society, but are also ideal markers in understanding dynamics and physical/chemical/biological reactions chains in the environment. Therefore, man-made radioactive contamination involves regional and global transport and local reactions of radioactive materials through atmosphere, soil and water system, ocean, and organic ecosystem, and its relations with human and non-human biota. The topic also involves hazard prediction, risk assessment, nowcast, and countermeasures, which is now urgent important for the nuclear power plants in Ukraine, the Middle East, etc.

By combining long monitoring data (> halftime of Cesium 137 after the Chornobyl Accident in 1986, 16 years after the Fukushima Accident in 2011, and other events), we can improve our knowledgebase on the environmental behavior of radioactive materials and its environmental/biological impact. This should lead to improved monitoring systems in the future including emergency response systems, acute sampling/measurement methodology, and remediation schemes for any future nuclear accidents. Furthermore, the discharge of ALPS-treated water into the ocean, carried out as part of the decommissioning of the Fukushima Daiichi Nuclear Power Station, has attracted international attention and demonstrated that decommissioning a nuclear power plant that has suffered an accident requires a fundamentally different approach from that of a conventional decommissioning. Studies on past nuclear contamination events and other environmental radioactivity datasets are also welcome.

The following specific topics have traditionally been discussed:
(a) Atmospheric Science (emissions, transport, deposition, pollution);
(b) Hydrology (transport in surface and ground water system, soil-water interactions);
(c) Oceanology (transport, bio-system interaction);
(d) Soil System (transport, chemical interaction, transfer to organic system);
(e) Forestry;
(f) Natural Hazards (warning systems, health risk assessments, geophysical variability);
(g) Measurement Techniques (instrumentation, multipoint data measurements);
(h) Ecosystems (migration/decay of radionuclides).

The MacGyver session focuses on novel sensors made, or data sources unlocked, by scientists. All geoscientists are invited to present:
- new sensor systems, using technologies in novel or unintended ways,
- new data storage or transmission solutions sending data from the field with LoRa, WIFI, GSM, or any other nifty approach,
- started initiatives (e.g., Open-Sensing.org) that facilitate the creation and sharing of novel sensors, data acquisition and transmission systems.

Connected a sensor to an Arduino or Raspberri Pi? Used the new Lidar in the new iPhone to measure something relevant for hydrology? 3D printed an automated water quality sampler? Or build a Cloud Storage system from Open Source Components? Show it!

New methods in hydrology, plant physiology, seismology, remote sensing, ecology, etc. are all welcome. Bring prototypes and demonstrations to make this the most exciting Poster Only (!) session of the General Assembly.

This session is co-sponsered by MOXXI, the working group on novel observational methods of the IAHS.

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

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

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

The terrestrial water cycle is usually studied one compartment at a time: precipitation by meteorologists, runoff and recharge by hydrologists, aquifers by hydrogeologists, and evapotranspiration by land-surface scientists. Yet climate change, land-use change and human water use act mainly on the links between these compartments. They change how rainfall is partitioned at the surface, how much reaches aquifers and how long it is stored there, and how much returns to the atmosphere to fall again as rain.

This session invites studies that cross at least one of these boundaries. Relevant topics include precipitation extremes, monsoons and atmospheric rivers and their imprint on runoff and recharge; soil moisture, infiltration, and snow and glacier melt; groundwater recharge, surface water–groundwater exchange, and storage change from GRACE and in-situ networks; evapotranspiration, moisture recycling and irrigation feedbacks; and the carbon, solutes and pollutants that water carries along its flow paths, including greenhouse-gas emissions from reservoirs. We also welcome interventions that deliberately reconnect the loop, such as managed aquifer recharge and nature-based solutions. Methods that link compartments are equally welcome: isotopes and tracers, remote sensing, coupled and hybrid models, and explainable machine learning.

We particularly encourage work on water-balance closure across scales, studies from data-scarce and monsoon-dominated regions, and research that turns whole-cycle understanding into water-security decisions. Early-career scientists are strongly encouraged to submit.

The study of water-related ecosystems covers a wide range of applicative contexts, entailing many scientific challenges and several diversified technological solutions.
Nowadays, the sustainable management of water resources requires a holistic approach, which attains to the soil, vegetation and all the living things interacting with the water.
The transition from the mere monitoring of the processes related to water systems to the wider concept of “water habitats”, implies the study of such ecological interactions in various possible scenarios, which are often characterised by a strong relationship between natural and anthropogenic contexts.
In this challenging framework, research activities aimed at developing efficient monitoring technologies and management strategies are encouraged to embrace a highly multidisciplinary approach. Here, water management meets noticeable ecological, economic and social implications, and the public awareness of such implications is rapidly growing.
Accordingly, scientific/technological advancements have to go beyond the observation of water bodies and their related processes and infrastructures, by extending the scope to the water habitats and the many measurable indicators of their functions and health status, directly or indirectly related to water, such as water quality, biodiversity, plant ecophysiology, and resilience to environmental extremes.

This session welcomes contributions related to the monitoring of water systems and their characteristic habitats about:
• design of field measurement instrumentation
• development of new sensing techniques, innovative field experiments
• application of remote sensing products
• advancements in sensor networks
• Integration between sensor systems and computational tasks
• Investigations about data science aspects, e.g. geospatial analyses, big data and AI applications.

Contributions may regard (but are not limited to) rivers & lakes, wetlands, irrigated areas, forests and natural habitats, coastal zone, urban habitats and water infrastructures, including distribution networks. Both qualitative and quantitative assessments are appreciated.
Studies regarding groundwater monitoring and management and its interaction with surface processes are also relevant to this session and are very encouraged.

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

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

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

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

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

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

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

Biogeodynamics, the study of the co-evolution of geo- and biosphere over geological time, brings together a diverse group of scientists, interested in how life and and planetary processes have co-evolved from the Precambrian to the present-day. This session highlights the interplay between biological evolution and tectonic, magmatic, and surface processes, exploring how changes in paleoenvironments and -geography have influenced the evolution of complex life - including animals, plants, and marine ecosystems - and how, in turn, biological processes reshape the solid Earth system. As a link between the two spheres, we seek to explore how greenhouse-icehouse climatic transitions have influenced biodiversity and ecosystems and how fossil records are linked to Earth system processes. As paleogeography exerts a fundamental control on Earth’s climate and the evolution of life, we welcome contributions that reconstruct paleogeography and explore its impacts, from the reconstruction of ancient supercontinents to the controls of ocean gateways on climate and biotic dispersals.
Biogeodynamics as an inherently multi-disciplinary subject aspires to better understand the complex coupling of biogeochemical cycles and life, the links between mass extinction and their causal geological events, how fossil records shed light on ecosystem drivers over deep time, and how tectono-geomorphic processes impact biodiversity patterns at global or local scales. We further encourage submissions that use new approaches to unravel the interplay between geodynamics, paleogeography, paleoclimate, and biological evolution across Earth’s history. We aim to understand our planet and its biosphere and climate through both observation- and modelling-based studies.

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

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

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

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

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

The concept of Earth as the sole body in the Solar System with liquid water that can harbor microbial life has been overturned by the discovery of multiple 'ocean worlds'. The Solar System is home to several planetary bodies with subsurface oceans of liquid water, including icy satellites such as Europa, Ganymede, Callisto, Enceladus, Titan and Triton, as well as dwarf planets like Pluto, and chief among these ocean worlds, the Earth. Furthermore, new icy and ocean worlds are being continuously discovered in other planetary systems as well. Like Earth, the exploration of these oceans includes both aspects of planetary evolution and habitability. The geodynamic role of oceans in planetary evolution is thus a crucial aspect of understanding not only planet formation, but the onset of biological activity as well. In what ways can the oceans of Earth serve as analogs for other oceans of the Solar System? What instrumentation can be implemented on the Earth now to further our understanding of these ocean worlds, and what technological advances might we expect in future exploration of subsurface liquid water environments beyond Earth?

This session focuses on analog sites, laboratory simulation, modeling, instrumentation and mission proposals. Coordination between Earth, marine and planetary science communities is encouraged, as well as emphasis on upcoming (e.g. JUICE and Dragonfly) and proposed missions (e.g. Enceladus Orbilander). Analog sites might encompass either geological or biological themes in the broader frame of habitability. Interfaces of ice-water (e.g. underside of floating ice shelfs and subglacial lakes), clathrate-water (e.g. ocean floor sediments, veins/fractures/faults, layered horizons and atmosphere particulates), seafloor-ocean, and rock-ice (i.e. glaciers) are of particular curiosity. Instrumentation includes sensors, buoys, submersibles, drilling and coring, as well as satellite instrumentation (e.g. spectrometers, magnetometers and gravimeters).

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

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

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

Forests are dynamic systems increasingly affected by natural and anthropogenic disturbances, including wildfire, drought, storms, insects, disease, logging and land-use change. These disturbances influence individual trees, forest structure and composition, carbon storage, biodiversity, and ecosystem functioning, while forest recovery varies across spatial and temporal scales. Understanding these dynamics across scales is critical for assessing ecosystem resilience, quantifying forests’ contributions to the global carbon cycle, and supporting sustainable forest management under a changing climate.
This session highlights advances in remote sensing and artificial intelligence (AI) for detecting, characterizing and predicting forest disturbance, recovery and resilience across scales. We welcome contributions using optical, SAR, LiDAR, hyperspectral and thermal observations, together with time-series analysis, machine learning, ecological modeling, and data fusion. We particularly encourage studies that: (1) identify early warning signals of tree- and forest-level changes; (2) detect and quantify disturbance and recovery at tree, plot, forest, and landscape scales; (3) characterize changes in tree and forest structure, biomass, carbon, and function; (4) integrate observations across spatial and temporal scales; and (5) combine field measurements, process-oriented models and multi-source Earth observations to assess and simulate forest dynamics and resilience. Contributions using emerging satellite missions and novel AI approaches to connect tree-level processes with forest- and landscape-scale patterns are especially welcome.

Remote sensing data has become an essential tool for forest analysis, enabling observation of forest cover, structure, and change across large areas and over time. Satellite, airborne, and ground based sensors provide complementary views of forest ecosystems, capturing canopy structure, spectral reflectance, and biomass. A wide range of artificial intelligence and machine learning models, from classical statistical approaches to deep learning architectures such as convolutional networks and transformers, extract meaningful information from these data sources individually. Another direction is to combine these sources through multimodal fusion strategies, at the input, feature, or decision level, bringing together optical, radar, LiDAR, hyperspectral, and UAV based data to capture aspects of forest condition that no single sensor can reveal on its own, while environmental information such as climate, soil, topography, and hydrology can further help explain the underlying drivers of forest dynamics. Building on this, advances in deep learning, self-supervised learning, and foundation models offer new opportunities to learn from such large and heterogeneous datasets and transfer information across sensors, regions, and applications.
Several key questions remain around which data sources and combinations are most informative, how different modalities can be effectively integrated, what training and reference data are needed, and how emerging models can achieve robust and transferable performance across forest ecosystems. This session aims to bring these perspectives together, identify current needs and opportunities, and foster approaches that enable more transferable and scalable forest applications.

Topics of interest include, but are not limited to:
• Foundation models and pretraining strategies for forest applications
• Multimodal data fusion for forest monitoring
• Deep learning and novel AI and machine learning architectures for forest analysis
• Integration of remote sensing, environmental, and field data
• Forest health and disturbance detection, such as drought, fire, pests, and logging
• Tree and forest species mapping and classification
• Forest dynamics and change over time

We particularly encourage contributions that explore the use of different data sources, multimodal data fusion, foundation models, or new methodological approaches, and we welcome early career scientists and researchers from diverse backgrounds and institutions.

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

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

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

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

The radioactive materials are known as polluting materials that are hazardous for human society, but are also ideal markers in understanding dynamics and physical/chemical/biological reactions chains in the environment. Therefore, man-made radioactive contamination involves regional and global transport and local reactions of radioactive materials through atmosphere, soil and water system, ocean, and organic ecosystem, and its relations with human and non-human biota. The topic also involves hazard prediction, risk assessment, nowcast, and countermeasures, which is now urgent important for the nuclear power plants in Ukraine, the Middle East, etc.

By combining long monitoring data (> halftime of Cesium 137 after the Chornobyl Accident in 1986, 16 years after the Fukushima Accident in 2011, and other events), we can improve our knowledgebase on the environmental behavior of radioactive materials and its environmental/biological impact. This should lead to improved monitoring systems in the future including emergency response systems, acute sampling/measurement methodology, and remediation schemes for any future nuclear accidents. Furthermore, the discharge of ALPS-treated water into the ocean, carried out as part of the decommissioning of the Fukushima Daiichi Nuclear Power Station, has attracted international attention and demonstrated that decommissioning a nuclear power plant that has suffered an accident requires a fundamentally different approach from that of a conventional decommissioning. Studies on past nuclear contamination events and other environmental radioactivity datasets are also welcome.

The following specific topics have traditionally been discussed:
(a) Atmospheric Science (emissions, transport, deposition, pollution);
(b) Hydrology (transport in surface and ground water system, soil-water interactions);
(c) Oceanology (transport, bio-system interaction);
(d) Soil System (transport, chemical interaction, transfer to organic system);
(e) Forestry;
(f) Natural Hazards (warning systems, health risk assessments, geophysical variability);
(g) Measurement Techniques (instrumentation, multipoint data measurements);
(h) Ecosystems (migration/decay of radionuclides).

In recent years, technologies based on Artificial Intelligence (AI), such as image processing, smart sensors, and intelligent inversion, have garnered significant attention from researchers in the geosciences community. These technologies offer the promise of transitioning geosciences from qualitative to quantitative analysis, unlocking new insights and capabilities previously thought unattainable.
One of the key reasons for the growing popularity of AI in geosciences is its unparalleled ability to efficiently analyze vast datasets within remarkably short timeframes. This capability empowers scientists and researchers to tackle some of the most intricate and challenging issues in fields like Geophysics, Seismology, Hydrology, Planetary Science, Remote Sensing, and Disaster Risk Reduction.
As we stand on the cusp of a new era in geosciences, the integration of artificial intelligence promises to deliver more accurate estimations, efficient predictions, and innovative solutions. By leveraging algorithms and machine learning, AI empowers geoscientists to uncover intricate patterns and relationships within complex data sources, ultimately advancing our understanding of the Earth's dynamic systems. In essence, artificial intelligence has become an indispensable tool in the pursuit of quantitative precision and deeper insights in the fascinating world of geosciences.
For this reason, aim of this session is to explore new advances and approaches of AI in Geosciences.

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

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

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

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

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