This session welcomes papers on:

1) Forecasting and simulating high impact weather events - research on using advanced artificial intelligence and machine learning techniques to improve numerical weather model prediction of severe weather events (such as winter storms, tropical storms, and severe mesoscale convective storms);

2) Development and improvement of model numerics - basic research on advanced numerical techniques for weather and climate models (such as cloud resolving global model and high-resolution regional models specialized for extreme weather events on sub-synoptic scales);

3) Development and improvement of model physics - progress in research on advanced model physics parameterization schemes (such as stochastic physics, air-wave-oceans coupling physics, turbulent diffusion and interaction with the surface, sub-grid condensation and convection, grid-resolved cloud and precipitation, land-surface parameterization, and radiation);

4) Verification of model physics and forecast products against theories and observations;

5) Data assimilation systems - progress in the development of data assimilation systems for operational applications (such as reanalysis and climate services), research on advanced methods for data assimilation on various scales (such as treatment of model and observation errors in data assimilation, and observational network design and experiments);

6) Ensemble forecasts and predictability - strategies in ensemble construction, model resolution and forecast range-related issues, and applications to data assimilation;

7) Advances and challenges in applying data from various conventional and avant-garde observation platforms to evaluate and improve high-resolution simulations and forecasting.

8) Climate and Weather Interventions

Weather forecasting and its application is one of the most important subject in meteorology. This session will focus on R&D on weather forecasting techniques and applications, in particular those AI based techniques and application. Contributions related to nowcasting, meso-scale and convection permitting modelling, ensemble prediction techniques, and statistical post-processing are very welcome.

Topics may include:

- AI based Nowcasting methods and systems, use of observations and weather analysis
- Physics and AI driven Mesoscale and convection permitting modelling
- Development on AI for Ensemble prediction techniques and products
- AI for weather forecasting application
- AI for Seamless prediction and application
- Statistical and AI NWP Post-processing
- Use of machine learning, data mining and other advanced analytical techniques
- Presentation of results from relevant international research projects of EU, WMO, and EUMETNET etc.

Weather prediction and climate modelling extensively use numerical models of the Earth system. Both the atmosphere and ocean components of such models consist of a fluid dynamics solver (dynamical core) that solves a system of partial differential equations numerically. The dynamical core is coupled to physical parameterizations that represent processes that occur below the grid scale (physics). Enabled also by substantial improvements of the underlying numerical algorithms, these models can deliver accurate and efficient simulations.

Researchers are constantly working to further improve the accuracy, efficiency, and scalability of the dynamical core, the physics, and their coupling. The rapid development of computing systems towards massive use of graphics processing units and extreme parallelism requires adaptation of algorithms to further increase model efficiency via strong or weak parallel scaling. Recent years have also seen a rapid increase in hybrid approaches that combine physics-based modelling with data driven techniques, adopting techniques from scientific machine learning for Earth system modelling.

This session invites presentations on the development, testing, and application of novel numerical techniques for Earth system models in a broad sense. The scope includes modifications to the governing equations, horizontal and vertical discretizations, structure preserving methods, time stepping schemes (including parallel in time schemes), advection schemes, adaptive multi-scale models, physics-dynamics coupling, regional and global models, classical and stochastic physical parameterizations, as well as hybrid schemes combining numerical methods and machine learning.

Organic aerosols (OA) are a significant fraction of atmospheric particulate matter (PM) in different environments from urban landscapes to pristine regions, and from the boundary layer to the upper troposphere. Due to their complex chemical composition, OA remains one of the least understood parts of PM, with effects on Earth's climate and human health that are still inadequately characterized. Ongoing efforts enhance our understanding of the origin and (trans)formation processes of OA. This encompasses studying natural sources and assessing how anthropogenic emissions change the chemical composition and physical properties of organic aerosols.
This session welcomes submissions on ambient observations, chamber and modelling studies of OA, which contribute to a deeper understanding of their origins (such as secondary OA formation or biomass burning), analysis of the molecular composition (e.g. targeted analysis of organic pollutants), investigation of physico-chemical properties, exploration of atmospheric transformation reactions (for example aging or brown carbon formation), and examination of gas-to-particle partitioning of organic molecules.

he Earth Cloud, Aerosol and Radiation Explorer (EarthCARE) satellite, launched in May 2024, is an ESA-JAXA mission, designed to improve our understanding of clouds, aerosols and their role in modifying radiant energy fluxes. To achieve its objectives, EarthCARE employs a suite of coincident active and passive sensors to provide an unprecedented view of the three-dimensional structure of clouds, precipitation and aerosols along with collocated observations of solar and terrestrial radiation.
 
EarthCARE, provides co-registered observations from a suite of four unique instruments located on a common platform: (1) ATmospheric LIDar (ATLID), (2) Cloud Profiling Radar (CPR), (3) Multi- Spectral Imager (MSI) and (4) BroadBand Radiometer (BBR). EarthCARE global observations include vertical profiles of natural and anthropogenic aerosols, the vertical contribution of ice and liquid water content, the cloud mesoscale distribution, precipitation microphysics, estimates of particle size, convective vertical air motions, as well as atmospheric radiative heating and cooling profiles. In addition to providing novel measurements for a better understanding of processes shaping Earth’s weather and climate, EarthCARE continues the heritage measurements of CloudSat, CALIPSO, Aeolus and CERES.
 
This session invites contributions on EarthCARE science themes related to the exploitation of mission data. These include instrument characterization, new active and passive retrieval techniques; cloud and precipitation microphysics, process studies related to the effects of clouds, aerosol, and aersol-cloud interactions on Earth’s radiant energy budget; as well as synthesis with other methodological approaches including ground-based, air- or ship-borne field campaigns and modelling studies. A special focus will be on the synergy with modeling activities exploiting the next generation of km-scale climate models, as in ECOMIP and within the global km-scale hackathon, and observational studies in combination with Organized Convection and EarthCARE Studies over
the Tropical Atlantic (ORCESTRA).

Cities are hotspots for emissions of air pollutants and greenhouse gases from traffic, industry, household energy use, and other human activities. Many urban emissions originate indoors (e.g. cooking, heating, solvent use) before entering the outdoor atmosphere, while outdoor pollution infiltrates indoor environments where people spend most of their time. Indoor–outdoor exchange processes, together with urban meteorology and city geometry, influence pollutant concentrations, chemical transformations, human exposure, and urban carbon budgets. Air pollution impacts may be cumulative or episodic, and can be exacerbated during heat waves, while greenhouse gases are often co-emitted with air pollutants, making cities both major drivers of climate change and focal points of climate-related health impacts.

This session brings together researchers working on urban air quality, greenhouse gases, and the indoor–outdoor air pollution interface. We invite contributions on urban air pollution, heat stress, urban carbon budgets, indoor and outdoor emission sources, indoor–outdoor exchange processes, and air pollution impacts on health. Topics include sensor networks, personal monitoring, airborne observations, high-resolution modelling and downscaling, source apportionment and isotopic attribution, ambient and indoor atmospheric chemical processes, biogenic and anthropogenic precursors to secondary pollution formation, community and personal exposure quantification, allergens, and air pollution and climate-related health effects.

Microorganisms – comprising bacteria, archaea, viruses, protists, and fungi – play vital roles in nutrient cycling and maintaining ecological balance. Microbial cells from surface environments are continuously aerosolized, with the atmosphere playing a major role in their transport and redistribution across temporal and spatial scales.

While extensive research has been dedicated to characterizing the cryo-, litho-, hydro-, and phyllo-spheres as microbial habitats, studies on atmospheric microorganisms have largely focused on their abundance, diversity, and potential climatic and sanitary implications. However, the atmosphere is not merely an inert medium but instead hosts airborne living cells that both influence and are influenced by biological, chemical, and physical processes, contributing to the intricate web of life on our planet.

Understanding microbial life in the atmosphere is essential for deciphering drivers of atmospheric composition, processes, and biogeochemical cycles. Atmospheric microorganisms are closely interlinked with surface habitats and can shape local, regional, and global microbial biodiversity and biogeography. To develop a more complete understanding of the planet’s microbiome, it is therefore critical to identify the chemical, physical and biological factors that shape the diversity, activity, and functioning of atmospheric microbial populations. Such factors include emission and deposition, exposure and response to atmospheric stressors (e.g. oxidants, water and nutrient availability), and the intrinsic traits of the microorganisms themselves.
This session will provide an interdisciplinary platform for all atmospheric scientists, biogeoscientists, microbiologists, and others interested in aerial transport of living microorganisms, microbial processes in the atmosphere, and their feedbacks on the Earth’s surface systems (water, soil, vegetation, ice). We welcome contributions that advance understanding of atmospheric microbiome, its interactions with the atmosphere and surface environments, and the processes that shape microbial diversity, concentrations, interactions, survival, dispersal, and functioning.

The wave of the Information Technology revolution is propelling us into a new era of research on atmospheric and environmental sciences. New techniques including Artificial Intelligence/Machine Learning (AI/ML) are enabling a deeper understanding of the complex atmospheric and environmental systems, as well as the interactions between weather/climate, air quality, public health, and social-economics. At the same time, Cloud Computing, GPU Computing, and Digital Twin have greatly facilitated much faster and more accurate earth system modeling, especially the weather/climate and air quality modeling and forecasting. These cutting-edge techniques are therefore playing an increasingly important role in atmospheric, climate, and environmental research and governance.

In this session, we welcome submissions addressing the latest progress in new techniques applied to research on all aspects of atmospheric, climate, and environmental sciences, including but not limited to,
- The application of AI/ML and other techniques for:
• Advancing the understanding of the complex earth system, especially the underlying mechanisms of weather/climate system, atmospheric environmental system, and their interactions
• Facilitating faster and more accurate weather/climate/air quality modeling and forecasting, especially for extreme weather, climate change, and air pollution episodes
• Shedding new insights into the mechanisms of atmospheric chemistry and physics
• Achieving air pollution tracing and source attribution
• Assisting policymakers on decisions towards environmental sustainability (e.g., considering interactions between extreme weather, climate change, air quality, socio-economics, and public health
- The adaptation and development of AI/ML and other techniques by proposing:
• Explainable AI (XAI)
• Hybrid methods (e.g., hybrid ML, physics-integrated ML)
• Transfer learning
• New algorithms
• Advanced model frameworks

We believe that exchanges across research fields could help breaking down the limitations of thinking and enabling technological innovations. Therefore, contributions from fields other than atmospheric, climate, and environmental sciences are also encouraged.

Extreme weather and climate conditions, such as recent events unprecedented in the observational record, have extensive impact globally. Some of these events would have been nearly impossible without human-made climate change, and broke records by large margins. Furthermore, compounding hazards and cascading risks resulting from these high-impact extremes are becoming evident. Continued warming does not only increase the frequency and intensity of such extremes, it also potentially increases the risk of crossing tipping points and triggering abrupt unprecedented impacts. To increase preparedness for high-impact climate events, developing novel methods, models and process-understanding that capture these hazards and their associated impacts is paramount.

This session aims to bring together the latest research quantifying and understanding high-impact climate events in past, present and future climates. We welcome studies across all spatial and temporal scales, and covering compound, cascading, and connected extremes as well as worst-case scenarios, with the ultimate goal to provide actionable climate information to increase societal preparedness to such extreme high-impact events.

We invite work addressing high-impact extreme events via, but not limited to, model experiments and intercomparisons, diverse storyline approaches such as event-based or dynamical storylines, climate projections including large ensembles and unseen events, insights from paleo archives, and attribution studies. We also especially welcome contributions focusing on physical understanding of high-impact events, on their ecological and socioeconomic impacts, as well as on approaches to potentially limit societal impacts.

The session is sponsored and closely linked to the World Climate Research Programme lighthouse activitIES on 'Understanding High-Risk Events' and 'Explaining and Predicting Earth System Change'.

Fire is the primary terrestrial ecosystem disturbance globally and a critical Earth system process. Its frequency and intensity are expected to increase across most regions in the future, posing significant challenges for ecosystems, the carbon cycle, and society. Fire research is rapidly expanding across disciplines, underscoring the need to advance our understanding of fire's interactions with climate, the biosphere, and human systems. This session invites contributions investigating the role of fire in the Earth system at any spatiotemporal scale, using statistical (including AI) or process-based models, remote sensing, field and laboratory observations, proxy records, and data-model fusion techniques. We strongly encourage abstracts on fire's interactions with: (1) weather, climate, atmospheric composition, chemistry, and circulation, (2) vegetation composition and structure and biogeochemical cycle, ocean ecosystems; (3) cryosphere elements and processes (such as permafrost, sea ice), and (4) human health, land management, conservation, and livelihoods. Moreover, we welcome submissions that address: (5) spatiotemporal changes in fire (especially extreme fires) in the past, present, and future, 6) fire products and models, and their validation, error/bias assessment and correction, as well as (7) analytical tools designed to enhance situational awareness for fire practitioners and to improve fire early warning systems.

Ground-based networks for monitoring of atmospheric chemical composition and meteorology improve our understanding of local, regional, and continental scale atmospheric events and long-term trends, and inform decisions critical to air quality, climate change, weather forecasting, and human health. Monitoring networks serve an important role within the research community, providing a backbone of data to support modeling, satellite data product validation, and short-term measurement campaigns. Ongoing collaboration, communication, and promotion of monitoring network developments and data products is necessary in order to fully leverage benefits from such networks. This session explores how ground-based atmospheric monitoring networks can be utilized to:
- promote cross-network and -discipline engagement
- develop and test new technologies and sensors
- expand quality assurance methods and techniques
- support modeling and satellite data products

Geodesy contributes to atmospheric science by providing some of the essential climate variables of the Global Climate Observing System. Water vapor is currently under-sampled in meteorological and climate observing systems. Thus, obtaining more high-quality humidity observations is essential for weather forecasting and climate monitoring. The production, exploitation, and evaluation of operational GNSS Meteorology for weather forecasting is well established in Europe thanks to a long-lasting cooperation between the geodetic community and the meteorological services. Improving the skill of numerical weather prediction (NWP) models, e.g., to forecast extreme precipitation, requires GNSS products with higher spatio-temporal resolution and shorter turnaround. Homogeneously reprocessed GNSS data (e.g., IGS repro3) have high potential for monitoring water vapor climatic trends and variability. Advances in SLR atmospheric delay modelling are using NWP data and 3D ray-tracing to improve tropospheric corrections. With shorter orbit repeat periods, SAR measurements are a source of information to improve NWP models. Additionally, emerging LEO-PNT missions offer capabilities for atmospheric and environmental monitoring due to their dense geometry, rapid revisit times and new signals that will be defined. Their integration with GNSS and other geodetic techniques could open new possibilities for real-time correction models. Reflected signals of GNSS and future LEO-PNT provide additional opportunities for remote sensing of the Earth system. GNSS-R contributes to environmental monitoring with estimates of soil moisture, snow depth, ocean wind speed, sea ice concentration and can be used to retrieve near-surface water vapor. We welcome, but do not limit, contributions on:
-Estimates of the neutral atmosphere using ground- and space-based geodetic data
-Retrieval and comparison of tropospheric parameters from multi-GNSS, VLBI, DORIS and multi-sensor observations
-Nowcasting, forecasting, and climate research using RT and repro tropospheric products, employing NWP and machine learning
-Assimilation of GNSS tropospheric products in NWP and in climate reanalysis
-Production of SAR tropospheric parameters and assimilation in NWP
-Homogenization of long-term GNSS, VLBI tropospheric products
-Detection and characterization of sea level, snow depth, and sea ice changes, using GNSS-R
-Monitoring of soil moisture and ground-atmosphere boundary interactions using GNSS data

This session invites contributions spanning all aspects of prediction and predictability on the subseasonal (2 weeks to 2 months) forecasting timescale, also known as subseasonal-to-seasonal (S2S) prediction. We welcome interdisciplinary research that covers predictions, processes, early warning capabilities and which supports applications and decision-making across sectors (including, but not limited to, the examples listed below). In light of recent advances in artificial intelligence (AI) and machine learning (ML) techniques for subseasonal prediction, contributions on AI/ML model developments, benchmarking frameworks and applications are very welcome. Of special interest are contributions related to the AI Weather Quest, an open international competition benchmarking AI-based subseasonal forecasts in real-time.

Physical drivers and processes
-Role of the atmosphere, ocean, land, and ice processes in extended-range/S2S predictability;
-Modes of variability (e.g., Madden Julian Oscillation (MJO), quasi-biennial oscillation (QBO), polar vortex strength, and others) impacting the extended-range/S2S predictability;
-Impact of global warming on early warning systems, changes in risks.

Prediction systems
-Evaluation and improvement of S2S prediction systems, including advancements in model physics and comparison between dynamical and data-driven prediction models, data assimilation, ensemble forecasting, and initialization techniques;
-Use of AI/ML methods for S2S prediction, data-driven models, post-processing, and attribution, including innovative techniques for improving forecast accuracy.

Extreme events and early warnings
-Early warnings for single- and multi-hazard events;
-Sources of predictability for extreme events, including multi-hazards events, on the S2S timescale (including driver identification and teleconnections);
-Case studies of extreme or high-impact event prediction and impacts on early warnings;
-Predictability and predictive skill of atmospheric or surface variables, and other variables relevant for socio-economic sectors, such as sea ice, snow cover, soil moisture, and land surface.

Applications and societal relevance
-Sector-specific applications, impact studies on the S2S/extended range timescale;
-Integration of S2S predictions into decision support systems at local, regional, or global levels and co-production of knowledge with stake-holders and decision-makers.

This session welcomes contributions on atmospheric convection, including dry, shallow, or deep convection. A particular session focus is the organization of convection, such as mesoscale convective systems, convectively-coupled waves, idealized studies of self-aggregation, or research on the importance of organization for climate sensitivity. Additionally, submissions that address other aspects of convection like the convective lifecycle and structures including cold pools, interactions of convection with other physical processes or the representation of convection in numerical weather prediction and climate models are strongly encouraged. The research can use any tool, from idealized theoretical models, large-eddy simulations, convection-permitting simulations, to coarser-resolution simulations using parameterised convection, machine learning techniques, or observations and field campaigns.

TEAMx (www.teamx-programme.org) is an international research programme that aims at improving our qualitative and quantitative understanding of transport and exchange processes in the atmosphere over mountainous terrain and at evaluating how well these processes are represented in numerical weather and climate prediction models. One of its main scientific goals is to provide a unique observational dataset to study the exchange processes over a broad range of spatial and temporal scales. To this purpose, several measurement campaigns were conducted in the European Alps, including the one-year long TEAMx Observational Campaign (TOC) that took place between 2024 and 2025 targeting multiple processes contributing to the total exchange within the atmosphere, the HEFEX campaigns on Hintereisferner investigating glacier-atmosphere exchange processes, and additional smaller test campaigns in preparation for the TOC.

This session welcomes all contributions related to the TEAMx research programme, including observational studies resulting from one of the measurement campaigns as well as model and climatological studies.

Aerosol particles are key components of the Earth system; important in dictating radiative balance, human health, and other areas of key societal concern. Understanding their formation, evolution, properties and impacts relies on developments from multiple disciplines covering both experimental laboratory work, field studies and numerical modelling. This session covers all aspects of Aerosol Chemistry and Physics. Contributions from aerosol laboratory, field, remote sensing and model studies are all highly encouraged.

Beyond the general topics, we recognize the rapid development of digital technologies has begun to transform and even lead new directions in aerosol research. Cloud computing, digital twins, and artificial intelligence are providing unprecedented capabilities for this field. These approaches span multiple scales, from single particles to global systems, and from process-level understanding to impact attribution. This session will spotlight the growing role of digital technologies in aerosol chemistry and physics. We invite contributions that explore the application and highlight key discoveries enabled by digital technologies. At the same time, we also emphasize the importance of balancing innovation with rigor: conclusions and processes must be carefully validated, uncertainties explicitly assessed, and data-driven methods integrated with theory, process models, and experimental observations to ensure reliability and reproducibility. Through this lens, this session aims to discuss both the opportunities and responsibilities of integrating digital technologies into aerosol research.

We welcome submissions that fall under a broad range of atmospheric aerosol applications. This could include work on the role and impact of:
- Advance fundamental understanding of aerosol chemistry and physics
- Development of hybrid process-machine learning based aerosol models
- Increased resolution and/or computational efficiency of numerical methods
- Applications of AI-enabled (e.g., GenAI, foundation models) and new-generation tools in aerosol research
- AI-enabled interpretation/prediction of aerosol variability and consequences, from characterizing properties to forecasting extreme events and quantifying impacts
- Development of new physical and digital platforms/technologies for aerosol research
- Open science practices: benchmark datasets, reproducible workflows, model sharing, and evaluation standards

Organic compounds play a key role in biosphere-atmosphere exchange, anthropogenic emissions, and the reactive chemistry responsible for ozone and particulate matter production. Coming from diverse sources and constituting thousands of individual compounds, with varying oxidation mechanisms, the organic composition of the troposphere is complex. With their wide range of lifetimes and volatilities, these species partition between gas and particle phases and make up a substantial fraction of fine particulate matter. Organics are also a major source of atmospheric reactivity, with implications for the oxidative capacity of the atmosphere. Some individual organic compounds are of interest due to their toxicity or use as specific source tracers. Because of organics’ role in secondary pollutant formation and reactivity, this chemistry is highly relevant to air quality from urban to remote regions. Finally, while global budgets of organic species are central to understanding tropospheric oxidative chemistry and aerosol budgets, they remain poorly constrained.

This session invites contributions about tropospheric organics on local, regional and global scales, from theoretical studies, laboratory experiments, field measurements, modeling studies, satellite studies, and including measurement technique development. The emphasis of this session is on gas-phase organics, including aerosol precursors and semi-volatile species.

Lightning is the energetic manifestation of electrical breakdown in the atmosphere, occurring as a result of charge separation processes operating on micro and macro-scales, leading to strong electric fields within thunderstorms. Lightning is associated with tropical storms and severe weather, torrential rains and flash floods. Lightning is also responsible for a vast number of wildfires, burned area, and fire emissions to the atmosphere. It has significant effects on various atmospheric layers and drives the fair-weather electric field. It is a strong indicator of convective processes on regional and global scales, potentially associated with climate change. Lightning produces nitrogen oxides, which are a precursor to ozone production. Thunderstorms and lightning are essential parts of the Global Electrical Circuit (GEC) and control the fair weather electric field. They are also associated with the production of energetic radiation up to tens of MeV on time scales from sub-millisecond (Terrestrial Gamma-ray Flashes) to tens of seconds (gamma-ray glows).

This session seeks contributions from research in atmospheric electricity with emphasis on:

Atmospheric electricity in fair weather and the global electrical circuit
Effects of dust and volcanic ash on atmospheric electricity
Thunderstorm dynamics and microphysics
Middle atmospheric Transient Luminous Events
Energetic radiation from thunderstorms and lightning
Experimental investigations of lightning discharge physics processes
Remote sensing of lightning and related phenomena by space-based sensors
Thunderstorms, flash floods, tropical storms and severe weather
Lightning-ignited wildfires and ecological effects of lightning
Connections between lightning, climate and atmospheric chemistry
Modeling of thunderstorms and lightning
Now-casting and forecasting of thunderstorms using machine learning and AI
Regional and global lightning detection networks
Lightning Safety and its societal effects
Planetary lightning in the solar system and beyond

Atmosphere-ice interactions are triggered by synoptic weather phenomena such as cold air outbreaks, polar lows, atmospheric rivers, Foehn winds, and heatwaves, and they impact snow, ice, and permafrost.

However, our understanding of these processes is still incomplete. Despite being a crucial milestone for reaching accurate projections of future climate change in Polar Regions, deciphering the interplay between the atmosphere, land ice and sea ice on different spatial and temporal scales, remains a major challenge.

This session aims at showcasing recent research progress and augmenting existing knowledge in polar meteorology and climate and the atmosphere-land ice-sea ice coupling in both the Northern and Southern Hemispheres. It will provide a setting to foster discussion and help identify gaps, tools, and studies that can be designed to address these open questions. It is also the opportunity to convey newly acquired knowledge to the community.

We invite contributions on all observational and numerical modelling aspects of Arctic and Antarctic meteorology and climatology, that address atmospheric interactions with the cryosphere. This may include but is not limited to studies on past, present and future of:

- Atmospheric processes that influence sea-ice (snow on sea ice, sea ice melt, polynya formation and sea ice production and transport) and associated feedbacks,

- The variability of the polar large-scale atmospheric circulation (such as polar jets, the circumpolar trough and storm tracks) and impact on the cryosphere (sea ice and land ice),

- Atmosphere-ice interactions triggered by synoptic and meso-scale weather phenomena such as cold air outbreaks, katabatic winds, extratropical cyclones, polar cyclones, atmospheric rivers, Foehn winds, and heatwaves,

- Role of clouds in polar climate.

- Role of aerosols, such as black carbon, organic carbon, dust, volcanic ash, microplastics, pollen, sea salt, diatoms, bioaerosols, bacteria, in snow/ice melt and albedo changes.

- Teleconnections and climate indices and their role in land ice/sea ice variability.

Presentations that include new observational (ground and satellite-based) and modeling methodologies specific to polar regions are encouraged. Contributions related to results from recent field campaigns in the Arctic and in the Southern Ocean/Antarctica are also welcome.

The CTBT's International Monitoring System (IMS) uses a global network of seismic, hydroacoustic, and infrasound sensors, as well as air sampling of radionuclides, to detect nuclear tests worldwide. The data from the IMS stations undergoes a multi-step processing and analysis procedure at the International Data Centre (IDC) to detect and locate natural and human-made events in any environment - underground, underwater, or in the atmosphere. By using atmospheric transport modelling (ATM), a link between a radionuclide detection and a possible source region can be estimated. On-site inspection (OSI) technologies utilize similar seismo-acoustic methods on a smaller scale, as well as geophysical methods like ground penetrating radar and geomagnetic surveying, to identify evidence of a nuclear test.

This session invites studies focused on methods and applications for event detection and location using seismic, hydroacoustic, infrasound, and radionuclide technologies. Contributions on the enhancement of seismic and acoustic velocity models, as well as the modeling of acoustic wave propagation, ATM of radionuclides, and contributions regarding the data fusion of various technologies are welcome. The session invites contributions on Nuclear-Test-Ban Monitoring using either IMS or OSI instrumentation, data or methods. This can be either in the context of explosion monitoring of actual or historic events or by taking into account fictitious scenarios like the National Data Centre Preparedness Exercises (NPE).

Contributions to the civil and scientific use of IMS data are encouraged. Civil applications include disaster risk reduction through early warning or hazard assessments for earthquakes, tsunamis, and volcanic activity. Earth science applications encompass analyses on different natural or anthropogenic sources as well as studies on climate change, ocean processes, solid Earth structure, and atmospheric circulation. Finally, contributions on the application of machine learning in event detection, localization, discrimination, and monitoring are highly encouraged.

Clouds are ubiquitous and play an important role in modulating Earth's climate by modulating incoming and outgoing radiation. A challenge in understanding the impact of clouds arises from the multi-scale nature of cloud processes, which span from aerosol activation at the nanometer scale to the dynamics of cloud systems at the scale of hundreds of kilometers. Key microphysical processes, including droplet collision-coalescence, ice crystal formation, and their modulation by turbulence, occur at scales smaller than 100\;m, which poses a challenge to observe or simulate them. The uncertainty is further exacerbated by turbulent interactions with the environment through entrainment, mixing of air, and radiative changes within the cloud. Hence, we need to improve our understanding on the small-scale to increase our confidence in climate projections.

The superposition of small-scale processes calls for an integrated approach that combines laboratory experiments, field observations, and numerical modeling. Field observations characterize cloud processes within their natural, dynamic environment using a combination of remote sensing and in-situ measurements. Recent advances in observational platforms (e.g., uncrewed aerial systems), measurement techniques (e.g., multi-frequency cloud radar), and experimental designs have enhanced these capabilities. Controlled laboratory experiments allow for the isolation and systematic study of specific cloud processes under defined and repeatable conditions. High-resolution, process-oriented numerical modeling enables the study of fundamental interactions, can test hypotheses, and synthesizes datasets. These models need constraints and validation by data from both laboratory and field campaigns.

This session invites contributions that advance the understanding of small-scale cloud processes. A particular emphasis is placed on synergistic studies that combines laboratory experiments, field observations and/or numerical modeling .

Surface exchange fluxes of heat, momentum and mass above the global oceans and at the poles (snowpack, sea-ice, ocean and land) have significant impacts on atmospheric composition, biogeochemistry and climate at regional to global scales. Atmospheric boundary layer processes mediate these chemical and physical fluxes. This session is intended to provide an interdisciplinary forum to bring together researchers working in the areas of meteorology, atmospheric chemistry, air quality, biogeochemistry, stable isotope research, oceanography, and climate above the global oceans and in the polar regions.

The session focuses on new research in several areas which include: air-sea fluxes of climate-active trace gases (CO2, CH4, N2O) mediated by the atmospheric boundary layer above the oceans and in polar regions; regional emission and vertical mixing of aerosol, such as cloud-forming particles (CCN/INP) and their precursors (including dimethyl sulfide (DMS), marine organic compounds and halogenated species) and their impacts on atmospheric composition and climate; atmospheric deposition of nutrients (e.g., nitrogen, phosphorus, iron) and its impact on ocean biological systems; and biogeochemistry-climate feedback loops in the ocean-atmosphere system. We also welcome studies on how these surface fluxes may change in response to climate warming, as well as the local to large-scale influences on these exchanges. An adequate understanding and quantification of these processes is necessary to improve modeling and prediction of future changes above the oceans and in the polar regions, their teleconnections with mid-latitude weather and climate (including meridional transport of heat, moisture, chemical trace species, aerosols and isotopic tracers), and the coupling between local and large-scale dynamics.

The session has strong links to the Surface Ocean ̶ Lower Atmosphere Study (SOLAS) and the GESAMP Working Group 38 on atmospheric input of chemicals to the ocean. Submissions are encouraged from all areas covered by these programs, using a range of analysis approaches including field measurements, remote sensing, laboratory studies, and atmospheric and oceanic numerical models.

This year we particularly welcome studies on the impact of extreme events on air-sea gas exchange of climate-relevant compounds in marine systems. Here we invite contributions addressing physical drivers such as marine heatwaves, storms and tropical cyclones, circulation anomalies or sea ice changes; biogeochemical drivers such as hypoxic or anoxic conditions and acidification pulses; biological drivers such as harmful algal blooms; or compound events. Relevant studies may address impacts in all oceanic domains; e.g., open ocean, shelf waters and shallow (< 20 m depth) coastal ecosystems. The reporting on progress as well as critical knowledge gaps in polar regions will help define upcoming research programmes as part of Antarctica InSync and the International Polar Year 2032-33.

This session aims to bring together the scientific community within air pollution modelling, focusing on modelling the atmospheric transport and transformation of air pollutants and precursors on global, regional and local scales.

Semi-arid regions are among the most vulnerable environments to climate change, characterized by limited water resources, high hydrological variability, and susceptibility to extreme events such as droughts, heatwaves, and intense precipitation. These extremes pose severe threats to water security, ecosystem stability, and socio-economic development. A critical yet not fully understood driver of this variability is the remote and local influence of ocean-atmosphere interactions (e.g., ENSO, IPO, Atlantic Multidecadal Oscillation, Indian Ocean Dipole) on the energy and water cycles of these regions.

The connection between atmospheric science and public policy is more important now than ever. Poor air quality and climate hazards create compounding risks that impact public health and equity, demanding effective, science-informed policy solutions. This session calls for research that explores how mitigation and adaptation strategies for air pollution and climate change may influence atmospheric composition and dynamics in the present and future.

Abstracts should investigate the efficacy of climate mitigation and air pollution controls by linking them to impacts on air quality, climate, public health, or environmental justice. Of particular interest is research examining both intended outcomes and potential unintended consequences of emission reduction strategies—including unexpected changes in atmospheric chemical composition such as ozone increases or unforeseen climate impacts. Submissions that consider interactions between air quality, climate, health, and environmental justice, connecting the environmental and social sciences, are especially valued.

Submissions may employ a wide range of techniques including remote sensing, statistical and Earth-system modeling, ground-based observations, machine learning, and policy analysis. Contributions examining historical, current, and projected future changes in anthropogenic emissions and their atmospheric responses are encouraged, particularly those investigating how effectively policies can address poor air quality, climate change, health impacts, and environmental injustices. Novel research that identifies areas of policy need through advances in atmospheric science is also sought, ultimately supporting more holistic and effective strategies that balance pollution reduction with comprehensive understanding of atmospheric system responses.

NOTE: The session AS3.25 - Atmospheric composition responses to historical, current, and future changes in anthropogenic emissions has merged with this one.

The statistical characterization and modelling of precipitation are crucial in a variety of applications, such as flood forecasting, water resource assessments, evaluation of climate change impacts, infrastructure design, and hydrological modelling. This session aims to gather contributions on research, advanced applications, and future needs in the understanding and modelling of precipitation, including its variability at different scales and its sources of uncertainty.

Contributions focusing on one or more of the following issues are particularly welcome:
- Process conceptualization and approaches to modelling precipitation at different spatial and temporal scales, including model parameter identification, calibration and regionalisation, and sensitivity analyses to parameterization and scales of process representation.
- Novel studies aimed at the assessment and representation of different sources of uncertainty of precipitation, including natural climate variability and changes caused by global warming.
- Uncertainty and variability in spatially and temporally heterogeneous multi-source ground-based, remotely sensed, and model-derived precipitation products.
- Estimation of precipitation variability and uncertainty at ungauged sites.
- Modelling, forecasting and nowcasting approaches based on ensemble simulations for synthetic representation of precipitation variability and uncertainty.
- Machine-learning approaches for precipitation modelling, forecasting, and downscaling: Machine-learning and hybrid (physics-informed) methods for precipitation simulation, uncertainty quantification, bias correction, and spatio-temporal downscaling, including baseline comparisons, cross-climate transfer tests, and evaluations of explainability and robustness.
- Scaling and scale invariance properties of precipitation fields in space and/or in time.
- Dynamical and statistical downscaling approaches to generate precipitation at fine spatial and temporal scales from coarse-scale information from meteorological and climate models.

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 and 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.

By combining long monitoring data (> halftime of Cesium 137 after the Chernobyl Accident in 1986, 15 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, as part of the decommissioning of the Fukushima Daiichi Nuclear Power Station, the discharge of ALPS-treated water is being carried out, which has attracted international attention. The discharge rate is published in real time and monitoring is being conducted, providing a valuable opportunity for analyzing the behavior of radionuclides in the ocean. In addition, past nuclear contamination events and other data sets 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).

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 last year's collection of BUGS - ranging from clay bricks to atmospheric temperature extremes - at https://meetingorganizer.copernicus.org/EGU25/session/52496.

Mesoscale and severe convection are known to be important precipitation producing processes over land. They are often associated with hazardous weather (e.g. damaging winds, hail, lightning, tornadoes, extreme precipitation, and flooding), which we already see is becoming more frequent in many regions with climate change. At the same time, these storms remain difficult to predict throughout all lifecycle stages from initiation to upscale growth and dissipation.
The aim of this session is to gain an improved understanding of mesoscale and severe convective processes over land from a non-idealised perspective for current and future periods.
We invite contributions focussing on the underlying storm dynamics and microphysics, upscale effects, advances in modelling and predictability of these storm systems, and their impacts. We also invite contributions on the driving processes of the formation and evolution of severe convection, and how these factors explain spatio-temporal patterns of storm intensity, precipitation, and on-the-ground hazards. This includes contributions on land-convection interactions in connection with mesoscale and severe storms, e.g. effects of complex topography, soil moisture feedbacks, or land use / land use change including e.g. urbanisation, deforestation, or irrigation.
Contributions focussing on individual extreme events or giving climatological perspectives including future climates are welcome, as are studies relying on remote sensing data, in-situ observations, or high-resolution models, especially those that explicitly resolve convection.

Cold clouds (mixed-phase and ice) play an important role in the Earth’s radiation budget because of their high temporal and spatial coverage and their interaction with long wave and short wave radiation. Yet, the variability and complexity of their macro- and microphysical properties, the consequence of intricate ice particle nucleation and growth processes, make their study extremely challenging. As a result, large uncertainties still exist in our understanding of cold cloud processes, their radiative effects, and their interaction with their environment (in particular, aerosols).

This session aims to advance our comprehension of cold clouds by bringing observation- and modelling-based research together.

A diversity of research topics shall be covered, highlighting recent advances in cloud observation techniques, modelling, and subsequent process studies:

(1) Airborne, space borne, ground- or laboratory-based measurements and their derived products (retrievals), which are useful to constrain cloud properties like extent, emissivity, or crystal size distributions, to clarify formation mechanisms, and to provide climatology.

(2) Process-based, regional, and global model simulations that employ observations for better representation of cloud microphysical properties and radiative forcing under both current and future climate.

The synthesis of these approaches can uniquely answer questions regarding dynamical influence on cloud formation, life cycle, coverage, microphysical and radiative properties, crystal shapes, sizes, and variability of ice particles in mixed-phase as well as ice clouds. Joint observation-modelling contributions are therefore particularly encouraged.

Internal gravity waves (IGWs) still pose major questions in the study of both atmospheric and ocean sciences, and stellar physics. Important issues include IGW radiation from their various relevant sources, IGW reflection at boundaries, their propagation through and interaction
with a larger-scale flow, wave-induced mean flow, wave-wave interactions in general, wave breaking and its implications for mixing, and the parameterization of these processes in models not explicitly resolving IGWs. The observational record, both on a global scale and with respect to local small-scale processes, is not yet sufficiently able to yield appropriate constraints. The session is intended to bring together experts from all fields of geophysical and astrophysical fluid dynamics working on related problems. Presentations on theoretical, modelling, experimental, and observational work with regard to all aspects of IGWs are most welcome, including those on major collaborative projects, which seek to accurately parameterize the role of IGWs in numerical models.

Biological particles significantly impact various aspects of life, including health, the economy, and the environment. Currently, up to 30% of Europe’s population suffers from pollen allergies and asthma, with the number of allergy sufferers steadily increasing over the past few decades. This growing prevalence poses a substantial burden on public health systems and economies, with the annual costs related to allergies in Europe estimated to range between €50 and €150 billion.

Accurately quantifying bioaerosol and understanding their impacts is of importance to an increasingly diverse range of research communities as they pose scientific questions relating to their influence on climate via cloud-aerosol interactions; the effects of allergenic species on public health and air quality and how this may be impacted by changes introduced by net zero policy; and the efficacy of early warning capabilities for national security and defense. In addition to their effects on human health and climate, pollen and fungal spores negatively affect agriculture and forestry, contributing to reduced crop yields and forest health. Climate change exacerbates these issues, as rising temperatures and increased CO2 emissions alter plant life cycles and fungal emissions.

Given these increasing concerns, there has been a paradigm shift in bioaerosol monitoring techniques. Traditional manual measurements are being progressively replaced by automated in situ measurements, advanced omics techniques and remote sensing technologies. These advanced approaches do not only provide more accurate information about bioaerosols but also enhance model predictions and forecasts. However, the detection and classification of bioaerosol remains a significant technical challenge, where real-time methods capable of high temporal resolution are often limited by their discriminative capabilities, and offline methods which provide rich taxonomic information suffer from poor time resolution and difficulties in producing atmospheric concentrations.

The aim of this session is to bring together expertise from a wide range of disciplines broadly studying bioaerosols. We welcome presentations covering topics on real-time detection methods and machine learning data processing techniques, validation, laboratory studies, indoor and outdoor ambient observations, the application and development of models, forecasting and nowcasting, exposure assessment and associated health impacts.

We welcome contributions involving the use of stable isotopes of light elements (C, H, O, N, S) or novel tracers (such as COS) in field and laboratory experiments, the latest instrument developments, as well as theoretical and modelling activities, which advance our understanding of biogeochemical and atmospheric processes. We are particularly interested in the latest findings and insights from research involving:

- Isotopologues of carbon dioxide (CO2), water (H2O), methane (CH4), carbon monoxide (CO), oxygen (O2), carbonyl sulfide (COS), and nitrous oxide (N2O)
- Novel tracers and biological analogues
- Polyisotopocules including "clumped isotopes"
- Non-mass-dependent isotopic fractionation and related isotope anomalies
- Intramolecular stable isotope distributions ("isotopomer abundances")
- Quantification of isotope effects
- Analytical, methodological, and modelling developments
- Flux measurements

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.

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.

Motivation

Although in some communities (e.g., meteorology, climate science) the tradition of software writing has a long history, most scientists are not trained software engineers. For early-stage scientific software projects, which are typically developed within small research groups, there is often little expectation that the code will (1) be used by a larger community, (2) be further developed or extended by others, or (3) be integrated into larger projects. This can lead to an “organic” evolution of code bases that result in challenges related to documentation, maintainability, usability, reusability, and the overall quality of the software and its results.

The wider availability of large computing resources in recent decades, along with the emergence of large datasets and increasingly complex numerical models, has made it more important than ever for scientific software to be well-designed, documented, and maintainable. However, (1) established practices in scientific programming, (2) pressures to produce high-quality results efficiently, and (3) rapidly growing user and developer communities, can make it challenging for scientific software projects to

- follow a common set of standards and a style,
- are fully documented,
- are user-friendly, and
- can be maintained, easily extended or reused.

Session content and objectives

We invite developers or users of software projects to prepare presentations about the challenges and successes in the following topics

- Good practices for developing scientific software
- Modularization
- Documentation
- Linting
- Version control
- Open source and open development
- Automatization of quality checks and unit testing
- Planning new projects
- User requirements and the user-turned-developer problem
- Painless and energy-efficient programming solutions across computing architectures
- Modularization and reliability vs performance and multiplatform capacity
- Large-dataset compression and storage workflows

These presentations will show how different projects across geoscientific fields tackle these problems. We can discuss new strategies for bettering scientific software development and raising awareness within the scientific community that robust and well-structured software development enables meaningful and reproducible results, supports researchers —especially doctoral and post-doctoral students— in their work, and accelerates advances in data- and modelling-driven science.

In this session we celebrate the 2026 awardees of the Atmospheric Sciences division through the Vilhelm Bjerknes Medal Lecture by Jonathan Williams and the Atmospheric Sciences Division Outstanding ECS Award Lecture by Eva Pfannerstill.