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).

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

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

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

The Earth system is a complex, multiphysics system with nonlinear interactions on multiple spatial and temporal scales. Understanding constituent processes (linear, nonlinear, stochastic, etc.) on the one hand, and the complexity of individual subsystems or the full integrated system on the other, is key to being able to better model the Earth System in a predictive fashion. The renaissance of machine and deep-learning in the past decade has led to rapid progress in the development of advanced approaches in, e.g., nonlinear time series analysis, dynamical and stochastic systems theory, critical slowing down theory, complex systems theory, and these approaches, in turn show promise in facilitating further advances in modeling the Earth system.



In this context, this session seeks contributions on all aspects of complexity, nonlinearity, tipping points and stochastic dynamics of the Earth system, including the atmosphere, the hydrosphere, the cryosphere, the solid earth, etc. Communications on theoretical, experimental and modeling studies are all welcome, where the latter modeling studies can span the range of model hierarchy from idealized models to complex Earth System Models (ESM). Studies based on emerging approaches such as data driven models, Artificial Intelligence approaches, complex network methods, critical slowing down analysis, dynamical and stochastic systems theory, etc., are particularly encouraged.

The year 2026 marks the centenary of Richardson’s seminal paper on turbulent diffusion. In this pioneering work, several fundamental ideas were introduced. Richardson notably recognized the non-differentiable nature of turbulent velocity and suggested that a fractal-like process could be used to represent it, proposing a Weierstrass function as an example. Based on experimental evidence, he also proposed that turbulent diffusivity follows a scaling law with an exponent of 4/3. Fifteen years before Kolmogorov’s 1941 theory, this result is equivalent to a velocity scaling characterized by a Hurst exponent of 1/3.

To mark the centenary of this landmark paper, which led the basis of modern theory of turbulent diffusion, we propose a EGU session devoted to this topic. In particular, we aim to address ocean and atmospheric applications, from small-to-large scale processes, in light of more recent results about the presence of intermittent corrections, or recent approaches in terms of continuous-time random walk or ballistic cascade phenomenologies.

We welcome contributions addressing turbulent transport and dispersion from both Eulerian and Lagrangian perspectives, including the diffusion of chemical and biological tracers, pair dispersion, and turbulent mixing. Theoretical, experimental, numerical, and observational studies are all welcome, across a broad range of spatial and temporal scales.

We also particularly encourage contributions addressing the historical development of ideas on turbulent diffusion, from Richardson’s pioneering work to contemporary approaches in oceanic and atmospheric turbulence.

Geophysical and astrophysical flows in stratified media exhibit stratified turbulence that gives rise to a variety of flow phenomena spanning a range of spatial scales from the Kolmogorov to planetary scales. Stratified turbulence significantly influences the flow dynamics on various temporal scales via complex nonlinear interactions, which continue to be challenging to understand, diagnose, and quantify from both theory and numerics. This understanding is fundamental to advance our knowledge of turbulent flow dynamics, and a prerequisite for improved turbulent closures and parameterizations for robust predictions of weather and climate. This session aims at bringing together the recent advancements in the field of fluid dynamics, with a focus on geophysical and astrophysical flows, as well as magneto-hydro dynamics.

Our session invites fundamental and applied contributions on stratified turbulence in fluids from theoretical, numerical, and experimental observational perspectives. The topics include, but are not limited to: two dimensional, three dimensional, isotropic, and anisotropic turbulence; regime transitions and energy cascades in turbulent flows; turbulent fluxes and transports; turbulent decay, mixing, and dissipation; stable atmospheric boundary layer flows and intermittent turbulence; wave-vortex dynamics in various turbulent regimes; wave turbulence; clear air turbulence; turbulence in weakly and strongly stratified flows and stratified shear flows.

We particularly encourage participation from early career researchers.

The Navier-Stokes equations, initially formulated in the early 19th century, have since become the cornerstone of fluid mechanics, subsequently extending their relevance to fluid geophysics. The existence and regularity of their solutions pose a significant challenge within a substantial domain of geophysics.

Over the years, a series of partial results have been obtained, particularly in the pursuit of proving one of the four statements proposed by Charles L. Fefferman for the Millennium Clay Prize. A definitive proof of the third statement regarding the breakdown of the Navier-Stokes equations was unveiled by OpenAI on September 8th, utilising extensive IA resources. This revelation has sparked a substantial debate, encompassing various aspects such as the physical significance of the blowing-up singularity, the utilisation of intensive AI resources in disruptive research, and the connections with concepts like intermittency, cascades, multifractals and enstrophy catastrophe. It may also inspire new approaches to resolve fundamental questions of geosciences.

This PICO session seeks to provide the geophysical community with an opportunity to contribute to this ongoing discourse.

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

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

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

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

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

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

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

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

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.

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

Sitting under a tree, you feel the spark of an idea, and suddenly everything falls into place. The following days and tests confirm: you have made a magnificent discovery — so the classical story of scientific genius goes…

But science as a human activity is error-prone, and might be more adequately described as "trial and error". Handling mistakes and setbacks is therefore a key skill of scientists. Yet, we publish only those parts of our research that did work. That is also because a study may have better chances to be accepted for scientific publication if it confirms an accepted theory or reaches a positive result (publication bias). Conversely, the cases that fail in their test of a new method or idea often end up in a drawer (which is why publication bias is also sometimes called the "file drawer effect"). This is potentially a waste of time and resources within our community, as other scientists may set about testing the same idea or model setup without being aware of previous failed attempts.

Thus, we want to turn the story around, and ask you to share 1) those ideas that seemed magnificent but turned out not to be, and 2) the errors, bugs, and mistakes in your work that made the scientific road bumpy. In the spirit of open science and in an interdisciplinary setting, we want to bring the BUGS out of the drawers and into the spotlight. What ideas were torn down or did not work, and what concepts survived in the ashes or were robust despite errors?

We explicitly solicit Blunders, Unexpected Glitches, and Surprises (BUGS) from modeling and field or lab experiments and from all disciplines of the Geosciences.

In a friendly atmosphere, we will learn from each other’s mistakes, understand the impact of errors and abandoned paths on our work, give each other ideas for shared problems, and generate new insights for our science or scientific practice.

Here are some ideas for contributions that we would love to see:
- Ideas that sounded good at first, but turned out to not work.
- Results that presented themselves as great in the first place but turned out to be caused by a bug or measurement error.
- Errors and slip-ups that resulted in insights.
- Failed experiments and negative results.
- Obstacles and dead ends you found and would like to warn others about.

For inspiration, see the collection of BUGS - ranging from clay bricks to atmospheric temperature extremes - at https://meetingorganizer.copernicus.org/EGU25/session/52496

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

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

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

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

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

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