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.

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.

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.

Storm and convective-scale weather data analysis and prediction still present significant challenges for atmospheric sciences. Addressing these challenges requires a synergy of advances in high-resolution observations, modeling, and data assimilation.

This session invites contributions from developments in

• Convective-scale data assimilation techniques
• Use of machine learning in convective scale data assimilation
• Applications of machine learning to forecasting on convective scales
• Convective-scale model and observation uncertainty representation
• Ensembles and uncertainty quantification using machine learning
• Advances in convective-scale modeling and parameter estimation
• Assimilation of ground and space-based radar data
• Active and passive satellite data assimilation
• Assessment of the impact of convective-scale data assimilation on global and regional prediction
• Observation operators for remote sensing and data assimilation
• Observations at convective scales: new observing technologies and strategies

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.

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.

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

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 .

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.

Snow cover characteristics (e.g., spatial distribution, surface and internal physical properties) are continuously evolving over a wide range of scales due to meteorological conditions, such as precipitation, wind, and radiation.
Most processes occurring in the snow cover depend on the vertical and horizontal distribution of its physical properties, which are primarily controlled by the microstructure of snow (e.g., density and specific surface area). In turn, snow metamorphism changes the microstructure, leading to feedback loops that affect the snow cover on coarser scales. This can have far-reaching implications for a wide range of applications, including snow hydrology and rapid runoff and flooding, weather forecasting, climate modelling, avalanche hazard forecasting, and the remote sensing of snow. The characterization of snow thus demands synergistic investigations of the hierarchy of processes across the scales, ranging from explicit microstructure-based studies to sub-grid parameterizations for unresolved processes in large-scale phenomena (e.g., albedo and drifting snow).
This session is therefore devoted to modelling and measuring snow processes across scales. The aim is to gather researchers from various disciplines to share their expertise on snow processes in seasonal and perennial snowpacks. We invite contributions ranging from “small” scales, as encountered in microstructure studies, over “intermediate” scales typically relevant for 1D snowpack models, up to “coarse” scales, that typically emerge for spatially distributed modelling over mountainous or polar snow- and ice-covered regions. Specifically, we welcome contributions reporting results from field, laboratory, and numerical studies of the physical and chemical evolution of snowpacks as well as of rain-on-snow (ROS) events rapidly altering snow properties and changing snow microstructure. We also welcome contributions reporting statistical or dynamic downscaling methods of atmospheric driving data, assimilation of in-situ and remotely sensed observations, representation of sub-grid processes in coarse-scale models, and evaluation of model performance and associated uncertainties.

Precipitation, both liquid and solid, is central to the global water/energy cycle through its coupling of clouds, water vapor, atmospheric motion, ocean circulation, and land surface processes. While precipitation is the primary source of freshwater, it also has tremendous socio-economic impacts associated with extreme weather events such as hurricanes, floods, droughts, and landslides. Knowledge of precipitation characteristics from local to global scales is essential for understanding how the Earth system operates under changing climatic conditions and for improved societal applications that range from numerical weather prediction to freshwater resource management.
This session will host papers on all aspects of precipitation, especially contributions in the following four research areas:
1. Precipitation measurements (amount, duration, intensity etc) by ground-based in-situ sensors (e.g., rain gauges, disdrometers); estimation of accuracy of measurements, comparison of instrumentation.
2. Precipitation climatologies at regional to global scales; areal distribution of measured precipitation; classification of precipitation patterns; spatial and temporal characteristics of precipitation; methodologies adopted and their uncertainties; comparative studies.
3. Remote sensing of precipitation (spaceborne, airborne, ground-based, underwater, or shipborne sensors) and retrieval techniques; methodologies to estimate areal precipitation (interpolation, downscaling, combination of measurements and/or estimates of precipitation); methodologies used for the estimation (e.g., QPE), validation, and assessment of error and uncertainty of precipitation as estimated by remote sensors.
4. Contributions to current and future missions, such as the international Global Precipitation Measurement (GPM) mission, Atmospheric Observing System (AOS), EUMETSAT Polar System-Second Generation (EPS-SG), Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats (TROPICS), Arctic Weather Satellite (AWS), Earth Clouds, Aerosol and Radiation Explorer (EarthCARE), tomorrow.io constellation and the Advanced Microwave Scanning Radiometer-3 (AMSR-3).

Rainfall is a “collective” phenomenon emerging from numerous drops. It reaches the ground surface with varying intensity, drop size and velocity distribution. Understanding the relation between the physics of individual drops and that of a population of drops remains an open challenge, both scientifically and for practical implications. This remains true also for solid precipitation. Hence, it is much needed to better understand small scale space-time precipitation variability, which is a key driving force of the hydrological response, especially in highly heterogeneous areas (mountains, cities). This hydrological response at the catchment scale is the result of the interplay between the space-time variability of precipitation, the catchment geomorphological / pedological / ecological characteristics and antecedent hydrological conditions. Similarly to the small scales, accurate measurement and prediction of the spate-time distribution of precipitation at hydrologically relevant scales still remains an open challenge.

This session brings together scientists and practitioners who aim to measure and understand precipitation variability from drop scale to catchment scale as well as its hydrological consequences. Contributions addressing one or several of the following topics are encouraged:
- Novel techniques for measuring liquid and solid precipitation variability at hydrologically relevant space and time scales (from drop to catchment scale), from in-situ measurements to remote sensing techniques, and from ground-based devices to spaceborne platforms. Innovative comparison metrics are welcomed;
- Drop (or particle) size distributions, small scale variability of precipitation, and their consequences for precipitation rate retrieval algorithms for radars, commercial microwave links and other remote sensors;
- Novel modelling or characterization tools of precipitation variability from drop scale to catchment scale from various approaches (e.g. scaling, (multi-)fractal, statistic, deterministic, numerical modelling);
- Novel approaches to better identify, understand and simulate the dominant microphysical processes at work in liquid and solid precipitation.
- Applications of measured and/or modelled precipitation fields in catchment hydrological models for the purpose of process understanding or predicting hydrological response.
- Rainfall simulators developed to investigate the accuracy of disdrometer measurements in assessing drop size and fall velocity.

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 uncertain response of clouds to global warming is a major contributor to uncertainty in climate sensitivity. Cloud feedback uncertainty is related to a limited understanding of the coupling between clouds, convection and the large-scale circulation across various spatial and temporal scales. Today's wealth of advanced remote-sensing observations and high-resolution modelling data provides comprehensive and complementary information that enables detailed process and lifecycle-based analyses. This session focuses on (1) efforts to advance our understanding of the cloud-circulation coupling and its role in climate change, and (2) Lagrangian studies related to clouds and water vapour. We invite contributions from dedicated field campaigns, from ground-based and satellite remote sensing or in situ measurements, as well as modelling and theoretical studies. We particularly welcome the first results from the ORCESTRA field campaign and the various ongoing model intercomparisons, like EUREC4A-MIP, CP-MIP and Lagrangian LES MIP. We also invite abstracts focusing on the role of mesoscale convective organization, aerosol-cloud interactions, feature tracking, and Langrangian cloud modelling.

A longstanding pursuit in climate science is to better understand Earth’s climate sensitivity, which
quantifies how global mean surface temperature responds to changes in radiative forcing. Uncertainty
in climate sensitivity arises primarily due to uncertainty in radiative feedbacks, which can be influenced
by a large range of processes including cloud microphysics, large-scale circulation of the atmosphere and
ocean, or the pattern of surface temperature changes. This session solicits work on theory, modeling,
and observations related to Earth’s climate sensitivity, with a particular focus on recent advances in
understanding the causes and impacts of the surface temperature pattern effect. The pattern effect
describes how surface temperature changes with identical global mean values can have hugely different
effects on the radiation budget depending on their spatial distribution, having significant implications
for interpreting temperature changes from observations, paleo-climate proxies, and climate-change
projections.
We welcome contributions related, but not limited, to:
• Radiative feedbacks and their modulation by surface warming patterns
• Air-sea interactions and ocean dynamics relevant to surface temperature patterns
• Process studies of feedbacks from clouds and moist processes
• Ocean heat uptake and transient climate sensitivity
• Theoretical models of climate sensitivity
• Interbasin interactions and teleconnections spanning scales from sub-basin to global
This session serves as an exchange platform for the often more separated ocean and atmosphere communities, and we especially encourage contributions from the ocean community.

The atmospheric water cycle is a key component of the climate system, and links across many scientific disciplines. Processes interact with dynamics at different scales throughout the atmospheric life cycle of water vapour from evaporation to precipitation. This session sets the focus on understanding the interaction between processes, their dynamics and characteristics of the water cycle, covering the entire atmospheric life cycle from evaporation, atmospheric moisture transport, to cloud microphysics and precipitation processes as observed from in-situ and remote sensing instrumentation, recorded by paleo-/climate archives, and as simulated by models for past, present and future climates.

We invite studies

* focusing on the understanding and impacts of features of the atmospheric water cycle related to weather systems, with a special focus on the role of Atmospheric Rivers, Cold-Air Outbreaks, Warm Conveyor Belts, Tropical Moisture Exports, and the global Monsoon systems;

* investigating the large-scale drivers behind the past, ongoing and future variability and trends within the atmospheric water cycle, from field campaigns (CAESAR, NAWDIC, (AC)3, ISLAS, etc.), long-term observations, reanalysis data, regional to global model simulations, or (isotopic) data assimilation;

* reconstructing past hydroclimates based on paleo-proxy records from archives such as ice cores, lake sediments, tree-rings or speleothems;

* applying methods such as tagged water tracers and Lagrangian moisture source diagnostics to identify source-sink relationships and to evaluate model simulations of the water cycle;

* using the isotopic fingerprint of atmospheric processes and weather systems to obtain new mechanistic insights into changes in the water cycle;

* describing the global and regional state of the atmospheric water cycle (e.g. monsoon systems) with characteristics such as the recycling ratio, life time of water vapour, and moisture transport properties.

We particularly encourage contributions linking across neighbouring disciplines, such as atmospheric science, climate, paleoclimate, glaciology, and hydrology.

Traditionally, hydrologists focus on the partitioning of precipitation water on the land surface into evaporation and runoff, while ignoring factors that influence precipitation. However, more than half of the evaporation globally returns as precipitation on land. Given this important feedback of the water cycle, changes in land-use and water-use, as well as climate variability and change, impact not only the partitioning of precipitation water but also the atmospheric input of water as precipitation, at both remote and local scales.
This session aims to:
i. investigate the remote and local atmospheric feedbacks from human interventions such as greenhouse gasses, irrigation, deforestation, and reservoirs on the water cycle, precipitation and climate, based on observations and coupled modelling approaches,
ii. investigate the use of hydroclimatic frameworks such as the Budyko framework to understand the human and climate effects on both atmospheric water input and partitioning,
iii. explore the implications of atmospheric feedbacks on the hydrological cycle for land and water management.
Applied studies in this session may adopt fundamental characteristics of the atmospheric branch of the hydrological cycle on different scales. These fundamentals include, but are not limited to, atmospheric circulation, humidity, hydroclimate frameworks, residence times, recycling ratios, sources and sinks of atmospheric moisture, energy balance and climatic extremes. Studies may also evaluate different data sources for atmospheric hydrology and implications for inter-comparison and meta-analysis. Examples of data sources and methodological approaches include observation networks, isotopic studies, conceptual models, Budyko-based hydroclimatological assessments, back-trajectories, reanalysis and fully coupled Earth system model simulations.

Extra-tropical cyclones and storms are key drivers of weather variability, extremes, and associated socio-economic impacts across densely populated regions of the globe. Understanding their observed and projected trends is crucial for improving climate diagnostics, risk assessments, and adaptation strategies in a warming climate. Most of our fundamental theories for the large-scale atmospheric circulation in the extra-tropics are based on “dry” atmospheric dynamics. Despite these recent efforts, large uncertainties in representing diabatic processes and their impact remain, leading to upscale error growth and enhanced ensemble spread, highlighting the continued need to further our understanding and to develop new and revise existing paradigms. This session therefore addresses both fundamental scientific challenges and urgent societal needs by linking physical processes, climate change signals, and potential impacts.

This session welcomes contributions covering mid-latitude storm systems, including but not limited to the following topics:

• Fundamental dynamics of cyclones - in all different stages of their life cycle - and their mesoscale features (fronts, jets, precipitation structures, dry intrusions)
• Role of diabatic processes for the dynamics, predictability, and future changes of extratropical weather system
• Representation of mid-latitude storms in AI-based weather and climate models
• Diagnostics of observed and projected trends in cyclone frequency, intensity, and storm tracks; including potential insights from contributions from measurement campaigns
• Predictability and forecasting on synoptic to sub-seasonal time scales
• Innovative methods, including AI/ML approaches, for cyclone detection, classification, or impact assessment
• Storm-related impacts, vulnerabilities, and risk-transfer mechanisms under a changing climate

By bringing together communities working on dynamics, diagnostics, impacts, field campaigns, and new methodologies, this session aims to provide a comprehensive platform for advancing our understanding of mid-latitude cyclones and their role in the past, present, and future climate system.

Solicited authors:
Suzanne L. Gray, Julian F. Quinting

Rossby wave dynamics stands at the intersection of several open research questions, ranging from our basic understanding of mid-latitude variability, to the short- and medium-range predictability of high-impact weather events, and to the circulation changes expected from anthropogenic global warming. Rossby waves exist and propagate along vorticity gradients such as the one related to the tropopause-level jet stream, whose complex meandering often "breaks" creating nonlinear circulation features, such as atmospheric blocking.

Recent extreme weather and climate episodes, like heavy rainfall events leading to flash floods, recurrent and concurrent summer heatwaves or unforeseen winter cold spells, highlight the need to improve our understanding of jet streams and of the associated linear and non-linear, planetary and synoptic-scale Rossby wave dynamics in the atmosphere to better constrain the impacts of Rossby waves and of atmospheric blocking on extreme weather and climate events.

Abstracts are invited on a wide range of topics, with a focus on, but not limited to, the following areas:

(1) Theoretical developments in the dry and moist dynamics of Rossby waves, wave breaking, atmospheric blocking, and of jet streams acting as atmospheric Rossby waveguides. This includes the role of local and remote drivers (e.g., the tropics, Arctic, or stratosphere) in affecting Rossby wave evolution.
(2) Linkages between extreme weather/climate events and the jet stream, as well as the associated linear and non-linear Rossby wave evolution during such events, including wave breaking, cut-off formation and re-absorption, and atmospheric blocking.
(3) Application of cutting-edge methods to study the multi-scale interaction of Rossby waves from the convective scale to the large-scale dynamics, and its representation in existing weather and climate models (e.g. hierarchical and/or high-resolution modelling, machine learning/AI-based approaches).
(4) Exploring the effect of Rossby wave packets on predictability at lead times from medium range (~2 weeks) to seasonal time-scales. This includes the potential role of blocking and of teleconnections involving Rossby wave propagation.
(5) Projected future changes in planetary or synoptic-scale Rossby waves, or in their future connection to weather and climate events.

Connect with colleagues across disciplines at the 4th Lagrangian session!

This session provides an open venue for scientists to share the latest advances in Lagrangian techniques, explore diverse applications, and build new connections.

We invite presentations on topics including, but not limited to:
- Planetary circulations and variability (fundamental processes shaping jets, gyres, waveguides, overturning circulations, transport barriers across atmosphere and ocean)
- Mesoscale eddies and coherent structures (eddy transport, wave-mean flow interactions, blocking)
- Turbulence and mixing (turbulent and convective entrainment, breaking internal waves, boundary layers)
- Numerical and computational advances (incl. data-driven techniques, GPU acceleration, graph-theoretical formulations, adaptive methods, data assimilation)
- Inverse modeling techniques (long-range transport of volcanic plumes, wildfire smoke, hazardous material, aerosols, plastics, micro-organisms, and their impacts on global composition, health, and climate)
- Field campaigns (drifters, floats, superpressure balloons, etc)

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.

Mountains cover approximately one-quarter of the total land surface on the planet, and a significant fraction of the world’s population lives within them, in their vicinity, and downstream. Orography critically affects weather and climate processes at all scales and, in connection with factors such as land-cover heterogeneity, is responsible for high spatial variability in mountain weather and climate. This session showcases research that contributes to improving our understanding of weather and climate processes in mountain and high-elevation areas around the globe, as well as their modification induced by global environmental change. This includes the interaction of mountain weather and climate with the terrestrial cryosphere.

We welcome contributions describing the influence of mountains on the atmosphere on meteorological and climate time scales, including terrain-induced airflow, orographic gravity waves, orographic precipitation, land-atmosphere exchange over mountains, forecasting, and predictability of mountain weather. We also encourage theoretical, modeling and observational studies on orographic gravity waves and their effects on the weather and the climate. Furthermore, we invite studies that investigate climate processes and climate change in mountain areas based on monitoring and modeling activities.

Particularly welcome are contributions that align with and address the interdisciplinary objectives of the Elevation-Dependent Climate Change (EDCC) working group of the Mountain Research Initiative, as well as the application and development of high-resolution (kilometer-scale) climate models over complex mountainous terrain, including advances in model design, challenges, and observational gaps needed for robust model evaluation and improvement.

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.

The understanding of tropical phenomena and their representation in numerical models still raise important scientific and technical questions, particularly in the coupling between the dynamics and diabatic processes. Among these phenomena, tropical cyclones (TC) are of critical interest because of their societal impacts and because of uncertainties in how their characteristics (cyclogenesis processes, occurrence, intensity, latitudinal extension, translation speed) will change in the framework of global climate change. The monitoring of TCs, their forecasts at short to medium ranges, and the prediction of TC activity at extended range (15-30 days) and seasonal range are also of great societal interest.
The aim of the session is to promote discussions between scientists focusing on the physics and dynamics of tropical phenomena. This session is thus open to contributions on all aspects of tropical meteorology between the convective and planetary scale, such as:

- Tropical cyclones,
- Convective organisation,
- Diurnal variations,
- Local circulations (i.e. island, see-breeze, etc.),
- Monsoon depressions,
- Equatorial waves and other synoptic waves (African easterly waves, etc.),
- The Madden-Julian oscillation,
- etc.

We especially encourage contributions of observational analyses and modelling studies of tropical cyclones and other synoptic-scale tropical disturbances including the physics and dynamics of their formation, structure, and intensity, and mechanisms of variability of these disturbances on intraseasonal to interannual and climate time scales.

Findings from recent field campaigns are also encouraged.

Regional monsoons have profound impacts on water, energy, and food security. Monsoons cause severe floods and droughts as well as undergoing variability on subseasonal, seasonal-to-decadal and palaeoclimate time scales. In addition to their profound local effects, monsoon variability also causes global-scale impacts via teleconnections, and the monsoons are linked together as part of the global monsoon via the divergent circulation, with aspects of coherent variability and interactions with planetary scale transports of heat and moisture.

Monsoons are complex phenomena involving coupled atmosphere-ocean-land interactions and remain notoriously difficult to forecast at NWP, subseasonal and seasonal scales, casting doubt also on our future climate projections. A better understanding of monsoon physics and dynamics and their response to forcing, with more accurate simulation, prediction and projection of monsoon systems is therefore of great importance.

This session invites presentations on any aspects of monsoon research in present-day, future and palaeoclimate periods, involving observations, modelling, attribution, prediction and climate projection. Topics ranging from theoretical works based on idealized planets and ITCZ frameworks to the latest field campaign results are equally welcomed, as is work on impacts, extremes and compound weather events, NWP modelling, S2S and decadal forecasting, and the latest CMIP findings to help inform the IPCC AR7.

Atmospheric processes in both the tropics and midlatitudes are central to shaping weather, climate, and extreme events in the subtropics. The complexity of these processes and their interactions give rise to a unique hydroclimate characterized by strong spatial gradients, distinct seasonal cycles, and high sensitivity to variability and change. Subtropical regions are global hotspot regions of climate change, and yet, remain plagued by large uncertainty in climate model simulations. They are also home to a large share of the world’s population, including communities in the Global South that are disproportionately at risk from extreme events and climate change. Despite their societal and scientific importance, subtropical weather and climate processes remain comparatively understudied.

This session invites contributions that advance process understanding and prediction of weather and climate with a particular focus on the subtropics. We welcome studies based on observations, theory, numerical models, and machine learning. Topics of interest include, but are not limited to:
• Atmospheric processes shaping clouds, circulation patterns, dust and air pollution transport, and surface weather such as tropical–extratropical interactions, subtropical jet fluctuations, Rossby wave dynamics, transient eddies, monsoon circulations, and convergence zones.
• Weather, climate, and compound extremes – droughts, heatwaves, wildfires, heavy precipitation, flooding, dust storms, and windstorms – spanning their drivers, future changes, and impacts on society and ecosystems.
• The water cycle – rainfall, evapotranspiration, and moisture transport – modulated by weather systems such as cyclones, cutoff lows, cold air outbreaks, mesoscale convective systems, easterly waves, and atmospheric rivers.
• Coupled interactions between Earth system components, including land-atmosphere and ocean-atmosphere feedbacks, and the role of sea surface temperature patterns in shaping subtropical climate.
• Climate variability and remote linkages with ENSO, the Madden-Julian Oscillation (MJO), and the Hadley circulation.
• Observations and climate model simulations addressing past and future changes in regional circulation patterns and surface weather, and novel approaches for identifying model biases and for reducing uncertainties in projections.

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.

In recent decades, dry-hot compound extremes, characterized by concurrent droughts and heatwaves, have significantly changed in their intensity, spatial modes, and temporal evolution. These emerging changes may reflect that the climatic boundary conditions causing dry-hot compound extremes could cross critical thresholds, with potential cascading effects that are fundamentally shifting the pattern of dry-hot compound extremes toward a new regime. This poses novel and often unanticipated extreme disasters, severely challenging the adaptability of local ecosystems and human health. This session aims to advance our understanding of dry-hot compound extremes by integrating observational analyses, climate modeling, and artificial intelligence frameworks. Key focuses include: 1) Novel theories and methodologies for heatwave understanding—elucidating mechanisms from the perspective of land-atmosphere-ocean coupling; 2) Drivers and mechanisms—elucidating dynamic (e.g., atmospheric circulation shifts) and thermodynamic (e.g., direct warming effect of greenhouse gases) processes changing compound events; 3) Long-term changes—quantifying historical trends, current intensification, and future trajectories under emission scenarios; 4) Climate effects—assessing impacts on vegetation, ecosystem carbon cycling, and its modulation on aerosol formation.

The circulation of the stratosphere significantly impacts tropospheric weather and climate. Key phenomena, including the stratospheric polar vortex, the Brewer-Dobson circulation, and the Quasi-Biennial Oscillation, are particularly influential. Variations in these phenomena modulate the propagation of atmospheric waves, exert a dynamical downward influence on the troposphere, and facilitate the transport of climatically important chemical constituents. Understanding, observing, and accurately simulating the dynamics of the stratosphere are therefore essential for predicting changes in tropospheric weather and climate. This session focuses on the causes and consequences of variations in the stratospheric circulation, including its natural and anthropogenic drivers, chemical transport and mixing processes, and its role for the prediction of weather and climate. We welcome abstracts that address these topics from observational, modeling, or theoretical perspectives across all scales.

Complementary middle-atmosphere sounding techniques—such as infrasound, lidar, radar, microwave spectrometry, and mesospheric airglow observations, further strengthened by satellite measurements—have become significantly more accessible over the past decade. It is expected that developing multi-instrument platforms will expand the community involved in operational infrasound monitoring for near-real-time observation of high-impact natural hazards—including volcanic eruptions, earthquakes, meteoroid entries, and bright fireballs—while creating new opportunities for atmospheric remote sensing research, such as improving gravity wave parameterizations.

In particular, global and regional infrasound station networks have proven highly effective in detecting and locating a wide range of natural and anthropogenic phenomena. Recent studies have shown that multi-technology analyses provide foundations for addressing geophysical inverse problems, enabling novel probing of both global-scale and small-scale structures in the middle atmosphere for enhanced weather prediction and climate modeling.
In addition to data-driven contributions, this session invites model-based papers dealing with the dynamics of the middle atmosphere across scales and altitudes, as well as its predictability. We welcome contributions on the characterization of atmospheric phenomena (gravity or planetary waves for example), using complementary observational methods across both local and global scales. Contributions addressing advances in wave propagation modeling, signal processing, and machine learning applications are also of great interest. Additional areas of focus include the development of derived data products and services for scientific and civilian use, as well as innovative instrumentation, including sensors deployed on mobile or elevated platforms such as balloons on Earth or other planets. Seismo-acoustic studies investigating the coupled Earth–ocean–atmosphere system, particularly focusing on ionospheric responses to processes originating from the ocean and solid Earth, are also encouraged.

Atmospheric rivers (ARs) are narrow and transient channels of intense water vapor transport in the lower troposphere. They account for 90% of poleward moisture transport and drive high-impact weather extremes all around the globe. Future projections suggest that landfalling ARs will become even more hazardous as they further intensify in a warmer climate. Given the fundamental role of ARs in the global water cycle, relevant research is rapidly expanding across different disciplines. With new data sources and novel methodological approaches, the multidisciplinary AR community has been breaking ground and posing fundamental questions for the understanding of AR processes and impacts.

By bringing together experts from diverse disciplines, this session aims to provide a comprehensive platform for discussing the latest advances in AR science. We invite all contributions that aim at a better understanding of AR uncertainties, processes, and impacts across past, present, and future climates at regional to global scales. Relevant topics of the session include, but are not limited to:

• Observation, identification, and monitoring of ARs
• Physical, dynamical, & microphysical aspects of ARs
• Aerosol & biochemical aspects of ARs
• ARs and the surface energy budget
• Environmental and socioeconomic impacts of AR-induced weather extremes
• ARs as a component of compound events
• AR dynamics and impacts in understudied regions
• Role of ARs in the changing Cryosphere
• Forecasting of ARs
• ARs in past, present, and future climates

The large-scale atmospheric circulation is an essential component of the climate system. Understanding the drivers, variability and the dynamical processes of this circulation is important for improving global and regional climate projections under anthropogenic climate change, and for predicting the associated impacts on extreme weather and climate events. This session encourages theoretical, modelling and observational research on the large-scale atmospheric circulation, including (but not limited to) the following topics:
-Response of the large-scale atmospheric circulation to climate change, including shifts and changes in intensity of the jet stream, Hadley and Walker cells, intertropical convergence zone, and monsoons;
-Changes in storm track intensity and structure in response to climate change and/or internal variability;
-Representation of the large-scale atmospheric circulation in climate models: inter-model variability, model biases, and methodologies for reducing uncertainty in model projections;
-Novel metrics and analysis methods for studying the large-scale atmospheric circulation;
-Interactions between the different components of the large-scale circulation, including tropical-extratropical interactions and teleconnection patterns;
-Role of moisture in the large-scale atmospheric circulation;
-Energy transport by the large-scale atmospheric circulation;
-Stratospheric-tropospheric interactions affecting the large-scale circulation.

Large-scale atmospheric dynamics and synoptic systems are key drivers of near-surface variables (e.g., air temperature, precipitation), their variability and their extremes such as heatwaves, floods, and droughts. To be prepared for potential future extreme weather events, we need to further study the link between regional extremes and features of the large-scale atmospheric circulation (e.g., circulation patterns, weather regimes, blocking patterns, extra-tropical cyclones, teleconnection indices) and if and how these dynamics are changing. Various linear and non-linear approaches of synoptic climatology (e.g., multiple regression, canonical correlation, neural networks) can be applied to relate the circulation dynamics to diverse climatic and environmental elements and extremes. This session focuses on understanding regional extremes, their link to atmospheric dynamics, and their future evolution under climate change while welcoming contributions from various methodological approaches.
We welcome contributions that explore:
- The links between large-scale atmospheric circulation features (e.g., circulation patterns, weather regimes, blocking patterns, extra-tropical cyclones, teleconnection indices, NAO) and various types of regional extreme weather events (such as heat waves, heavy precipitation, floods, droughts)
- Past, recent and future trends in frequency, intensity, and variability of regional extremes or surface environmental variables and their associated atmospheric features under climate change
- The influence of internal climate variability on the occurrence of regional extreme events associated with large-scale atmospheric circulation features
- The use of innovative methods, including large ensembles, and AI for circulation type classification
This session invites contributions that explore the connections between different types of regional extremes and the atmospheric circulation, as well as studies from general synoptic climatology that focus on the relationship between atmospheric circulation dynamics and near surface environmental variables, their variability, and changes. The aim is to enhance our understanding of the dynamic drivers behind regional extremes in the context of climate change.

The frequencies and intensities of extreme events such as floods, tropical cyclones, heat waves, droughts etc. are increased in many regions across the globe and now of serious concern due to their socio-economic Impact. Hence understanding of the mechanism, pattern and characteristics of such events have been the focus of many recent studies. This session invites abstracts on observational and numerical modeling studies aimed to enhance the understanding of the spatial and temporal characteristics and predictability of the extreme events. This session also welcomes the submissions on model simulations and evaluations aimed to advance the understanding of the physics and dynamics associated with the extreme events. In particular, abstracts are encouraged on regional-scale analysis of the historical extreme events and their projections which would assist the policy makers to build more resilient societies to face the extreme event related disasters.

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'.

We invite contributions on all aspects of Meteorology and Climate for Renewable Energy (RE):
• Energy: wind, solar, hydro, tidal, wave, geothermal etc
• Spatial: microscale, mesoscale, synoptic and global
• Temporal: seconds, minutes, diurnal, seasonal, interannual, decadal and climatological
• Approach: measurement, modeling
The success of wind power has pushed turbines and research need into increasingly complex environments — mountainous terrain, forested areas, high in boundary layer and offshore. For solar power, new installation sites such as floating PV both rivers, water reservoirs for artificial snow, and “alpine PV farms” are gaining more attention. We need accurate measurements and short-term forecasts of cloud fields and aerosol effects. For weather-dependent renewables, the challenge of integrating shares into the power grid requires advances in understanding forecast uncertainty and spatio-temporal variability. Furthermore, meteorological conditions define how much power can be sent through the power grid and could help prevent curtailment or negative energy pricing.
Specifically, we invite contributions including but not limited to:
• Measurement techniques and analysis for e.g., wind, solar, hydro, and marine resources.
• Wind conditions (resource, extremes, turbulence) on all scales in complex environments (mountains, forests, coastal, offshore, urban).
• Wake effect models and measurements
• Forecast performance and uncertainty of RE at different time horizons
• Forecasts and detection of extreme and adverse weather events (wind ramps, droughts, heatwaves, storms, compound and consecutive)
• Detection and forecasting of dynamic line rating suitable conditions
• RE resource and atlas development (wind, solar, hydro, wave, thermal)
• Hydro-meteorological analyses of inflow variability, snowpack, precipitation extremes, and their implications for hydropower
• Tidal and wave resource assessment and predictability
• Impacts of renewable power plants or their large-scale integration on local, regional, and global scales
• Tools for strategic planning of RE in urban areas and smart energy systems.
• Climate Change Impact studies for renewables and weather-driven energy demand
• Interannual to decadal variability of renewable resources
• Typical Meteorological Years and probability of exceedance metrics
• AI and Machine Learning for weather and climate forecasting and applications to RE

Driven by atmospheric turbulence, and integrating surface processes to free atmospheric conditions, the Atmospheric Boundary Layer (ABL) plays a key role not only in weather and climate, but also in air quality and wind/solar energy. It is in this context that this session invites theoretical, numerical and observational studies ranging from fundamental aspects of atmospheric turbulence, to parameterizations of the boundary layer, and to renewable energy or air pollution applications. Below we propose a list of the topics included:

- Observational methods in the Atmospheric Boundary Layer
- Simulation and modelling of ABL: from turbulence to boundary layer schemes
- Stable Boundary Layers, gravity waves and intermittency
- Evening and morning transitions of the ABL
- Convective processes in the ABL
- Boundary Layer Clouds and turbulence-fog interactions
- Micro-Mesoscale interactions
- Micrometeorology in complex terrain
- Agricultural and Forest processes in the ABL
- Diffusion and transport of constituents in the ABL
- Turbulence and Air Quality applications
- Turbulence and Wind Energy applications
- Urban boundary layers

The session is addressed to experimentalists and modellers working on air-land interactions from local to regional scales. The programme is open to a wide range of new studies in micrometeorology and related atmospheric and remote sensing disciplines. It is also open to studies investigating how turbulent transport and surface-layer processes upscale from the atmospheric boundary layer to mesoscale dynamics and ultimately to large-scale circulation in weather and climate systems. The topics include the development of new devices, measurement techniques, experimental design, data analysis methods, as well as novel findings on surface layer theory and parametrization, including local and non-local processes. The theoretical parts encompass soil-vegetation-atmosphere transport, internal boundary-layer theories and flux footprint analyses. Of special interest are synergistic studies employing experimental data, parametrisations and models. This includes energy and trace gas fluxes (inert and reactive) as well as water, carbon dioxide and other GHG fluxes. Specific focus is given to outstanding problems in land surface boundary layer descriptions such as complex terrain, effects of horizontal heterogeneity on sub-meso-scale transport processes, energy balance closure, stable stratification and night time fluxes, dynamic interactions with atmosphere, plants (in canopy and above canopy) and soils.

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.

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.

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.

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.

The interactions between aerosols, climate, weather, and society are among the large uncertainties of current atmospheric research. Mineral dust is an important natural source of aerosol with significant implications on radiation, cloud microphysics, atmospheric chemistry, and the carbon cycle via the fertilization of marine and terrestrial ecosystems. Dust impacts snow and ice albedo and can accelerate glacier melt. In addition, properties of dust deposited in sediments and ice cores are important (paleo-)climate indicators.

This interdivisional session -- building bridges between the EGU divisions AS, CL, CR, SSP, BG and GM -- had its first edition in 2004 and it is open to contributions dealing with:

(1) measurements and theoretical concepts of all aspects of the dust cycle (emission, transport, deposition, size distribution, particle characteristics),
(2) numerical simulations of dust on global, regional, and local scales,
(3) meteorological conditions for dust storms,
(4) interactions of dust with clouds and radiation,
(5) influence of dust on atmospheric chemistry,
(6) fertilization of ecosystems through dust deposition,
(7) interactions with the biosphere, cryosphere, and hydrosphere,
(8) any study using dust as a (paleo-)climate indicator, including sediment archives in loess, ice cores, lake sediments, ocean sediments and dunes,
(9) impacts of dust on climate and climate change, and associated feedbacks and uncertainties,
(10) implications of dust for health, transport, energy systems, agriculture, infrastructure, etc., and early warning systems

We especially encourage the submission of papers that integrate different disciplines and/or address the modelling of past, present, and future climates.

We are delighted to announce that in the 23rd edition of the dust session, Dr Claudia Di Biagio (LISA) and Dr. Diego Villanueva (ETHZ) will provide solicited talks about their work on dust radiative properties and dust-driven droplet freezing.

Cloud feedbacks remain the dominant source of uncertainty in estimates of global and regional climate sensitivity. Advancing our understanding of the key processes governing cloud formation, evolution, and radiative effects is therefore essential for improving their representation in climate models and reducing uncertainties in future climate projections.
Cloud condensation nuclei (CCN), ice-nucleating particles (INPs), and secondary ice production (SIP) are central to cloud microphysical processes and radiative feedbacks, with far-reaching influences on weather and climate dynamics. This session focuses on the interactions between aerosols, CCN, INPs, and SIP, and their impacts on cloud properties, based on both laboratory and field studies.
Particular attention will be given to the Southern Ocean (SO), one of the cloudiest regions on Earth. Its pristine aerosol environment offers a natural laboratory for disentangling fundamental aerosol- cloud -radiation interactions in the relative absence of anthropogenic pollution, thereby providing critical insights into cloud microphysical processes.
We invite contributions that address pressing open questions on the coupling between gas-phase chemistry, aerosol nucleation and growth, cloud development, precipitation, and radiative impacts, with an emphasis on the Southern Hemisphere. Special focus will also be placed on advancing our understanding of SIP mechanisms, their influence on cloud evolution, and their representation in weather and climate models.
Topics of interest include:
• Laboratory studies on INPs and secondary ice production
• Aerosol, CCN, and INP sources and characteristics from field measurements (e.g., in-situ flight campaigns)
• Modeling of secondary ice production processes
• Advances in parameterizations of cloud formation and development in models (e.g., deep convective clouds, mixed-phase clouds, mesoscale convective systems)

Solicited Speaker: Prof. Dr. Mira Pöhlker, Leibniz Institute for Tropospheric Research (TROPOS), Germany.
Solicited Presentation: " The interplay of Clouds, Aerosols and Radiation above the Southern Ocean".

Clouds and aerosols play a key role in climate and weather-related processes over a wide range of spatial and temporal scales. An initial forcing due to changes in the aerosol concentration and composition may also be enhanced or dampened by feedback processes such as modified cloud dynamics, surface exchange or atmospheric circulation patterns. This session aims to link research activities in observations and modelling of radiative, dynamical and microphysical processes of clouds, aerosols, and their interactions. Studies addressing several aspects of the aerosol-cloud-radiation-precipitation system are encouraged. Contributions related to the EU projects CERTAINTY (Cloud-aERosol inTeractions & their impActs IN The earth sYstem) and CleanCloud (Clouds and climate transitioning to post-fossil aerosol regime) are also invited.

Topics covered in this session include, but are not limited to:
- Cloud and aerosol macro- and microphysical properties, precipitation formation mechanisms and their role in the
energy budget
- New constraints on aerosol, clouds or precipitation from EarthCARE
- Observational constraints on aerosol-cloud interactions
- Use of observational simulators to constrain aerosols, clouds and their radiative effects in models
- Explorations of cloud seeding or artificial cloud brightening techniques
- Experimental cloud and aerosol studies
- High-resolution modelling, including large-eddy simulation and cloud-resolving models
- Parameterization of cloud and aerosol microphysics/dynamics/radiation processes

The polar regions are experiencing rapid and profound environmental changes, with the Arctic warming at nearly four times the global average. Aerosol-cloud interactions remain one of the largest sources of uncertainty in climate models, particularly in these fragile and rapidly evolving environments. Mixed-phase clouds, biogeochemical processes in the ocean and sea ice, and atmospheric dynamics all contribute to complex feedbacks that modulate Earth's radiative balance, influence weather systems, and drive climate change.

This session, inspired by the goals of initiatives such as QuiESCENT (Quantifying the Indirect Effect: from Sources to Climate Effects of Natural and Transported aerosol in the Arctic), CATCH (Cryosphere and ATmospheric CHemistry), CIce2Clouds (Coupling of ocean-ice-atmosphere processes: from sea-Ice biogeochemistry to aerosols and Clouds), and BEPSII (Biogeochemical exchanges at Sea Ice Interfaces), aims to foster interdisciplinary collaboration by bringing together researchers studying aerosols, clouds, ocean–ice biogeochemistry, and their coupled interactions in both the Arctic and Antarctic. We seek to bridge disciplinary gaps—spanning aerosols and clouds, physics and chemistry, observations and modeling, and ocean–ice–atmosphere processes—to advance our understanding of polar climate systems.

We invite contributions that address the following key topics:
- Aerosol-cloud interactions: Their influence on cloud microphysics, radiative properties, and precipitation patterns in polar environments, including the contrasting effects of anthropogenic pollution and natural aerosols.
- Biogeochemical cycling: Marine and terrestrial sources of aerosols, including sea salt, mineral dust, biological particles, black carbon, and organic aerosols, and their feedbacks with atmospheric components.
- Boundary layer dynamics: The role of atmospheric and oceanic boundary layer processes in shaping aerosol and cloud properties, as well as their impact on boundary layer mixing and local pollution processing.
- Observational and modeling advances: Innovations in field campaigns, remote sensing, laboratory experiments, and modeling frameworks to improve the representation of polar aerosol–cloud–ocean–ice systems in climate models.
- Climate feedbacks and projections: Implications of polar aerosol–cloud interactions for climate model performance and global climate predictions, with a focus on reducing uncertainties in projections.

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

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

Along with the rapid economic development and accelerated urbanization process, many areas in the world are suffering from high levels of ozone and fine particle pollution. These air pollutants can affect weather and climate system through absorbing or scattering radiation. For example, ozone is a kind of greenhouse gases, while aerosols can not only directly affect solar radiation but serve as cloud ice nuclei or ice nuclei to modify microphysical processes of clouds and precipitation. On the other side, weather and climate are also closely linked to formation of air pollution. Monsoon climate, stagnant weather conditions and large-scale circulation patterns all play important roles in air pollution. Understanding how weather and climate interact with air pollution at present and in the future can help us in the field of air pollution prevention and mitigation of global warming.

This session aims to address the current challenges, methodological approaches and wider relevance of observing and modelling meteorology-atmospheric environment interactions around the world. We welcome contributions including, but not limited to, integrating multi-source data (such as, on-situ monitoring, remote sensing, etc.) with controlled experiments to identify the key processes, modelling of the interactions between climate change and air pollution as well as the future projections, assessment the impact of extreme weather on air pollution and future trends, and illustrating the development of cities and the effects of urban climate on regional air quality. Research that reveals the impact of air pollution on the environment, ecology and human health is also welcome.

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).

Remote sensing of clouds and aerosols is of central importance when studying processes and changes in the climate system. The new spaceborne generation of active sensors (e.g. EarthCare), passive multi-angular polarimeters (e.g. PACE/SPEX, PACE/HARP-2, 3MI, CO2M, MAP) together with single-viewing instruments (e.g. hyperspectral Sentinel 5P/5/4, OLCI and SLSTR on Sentinel 3) will take the characterisation of aerosols and clouds to a new level. This will significantly improve our understanding of physical and chemical processes in the atmosphere, particularly aerosol-cloud interactions, and climate and radiation studies. Nevertheless, there are still many challenges and unsolved problems in remote sensing algorithms and their applications.

The aim of this session is to discuss current developments, challenges and opportunities in the characterisation of aerosols and clouds, in the study of aerosol-cloud interactions and their long-term effects, using ground-based, airborne and spaceborne active and passive remote sensing systems. We invite submissions of theoretical, methodological and empirical studies to advance the field of aerosol/cloud remote sensing, and to improve our understanding of aerosol-cloud interactions and their effect on the climate.

Over the last years, more and more satellite data on tropospheric
composition have become available and are now being used in numerous
applications. In this session, we aim at bringing together reports on
new or improved data products and their validation, as well as studies
using satellite data for applications in tropospheric chemistry,
emission inversions and air quality. This includes both studies on trace
gases and aerosols.

We welcome presentations based on studies analysing data from current and future
satellite missions, including the geostationary GEMS and TEMPO platforms and the
recent S4, S5, IRS, IASI-NG and 3MI instruments. Topics also include the
inter-comparisons of different remote sensing measurements dedicated to
tropospheric chemistry sounding and/or analyses with ground-based
measurements and chemical transport models.

This session is organized for the second time at EGU General Assemblies and reflects the recent emerging trends of atmospheric monitoring: (i) realising multi-instrument synergy retrieval and (ii) bridging three branches of atmospheric research (modelling, in situ measurements, and remote sensing).

This session encourages discussions that explore the synergies of complimentary observations, such as synergies of passive imagery with active vertical profiling of the atmosphere, synergies of observations in different spectral ranges and at different time and/or spatial scales, and synergies of satellite observations with sub-orbital observations and chemical transport model simulations. Synergy is important because the quality of measurements cannot be radically improved once the instruments have been deployed, but algorithms can continuously evolve and notably improve results with data fusion and optimization of the joint sensitivity of multi-instrument datasets. The the session especially welcomes the ides and demonstrations of synergy methods and Interdisciplinary applications using novel observations from the , EPS-SG, MTG, PACE, Copernicus Sentinels, EarthCARE and other recent and forthcoming advanced satellite missions (e.g., CO2M) as well as field campaigns.

The session also invites presentations that demonstrate the benefits of collaboration amongst the three core fields of atmospheric aerosol studies outlined in the Models, In situ, and Remote sensing of Aerosols (MIRA) international working group, which was formed to facilitate collaborations and improve discussions amongst these fields of study and across regional boundaries. More information can be found at https://science.larc.nasa.gov/mira-wg/.

The radiation budget of the Earth is a key determinant for the genesis and evolution of climate on our planet and provides the primary energy source for life. Anthropogenic interference with climate occurs first of all through a perturbation of the Earth radiation balance. We invite observational and modelling papers on all aspects of radiation and energy flows in the climate system. A specific aim of this session is to bring together newly available information on the spatial and temporal variation of radiative and energy fluxes at the surface, within the atmosphere and at the top of atmosphere. This information may be obtained from direct measurements, satellite-derived products, climate modelling as well as process studies. Scales considered may range from local radiation and energy balance studies to continental and global scales. In addition, related studies on the spatial and temporal variation of cloud properties, albedo, water vapour and aerosols, which are essential for our understanding of radiative forcings, feedbacks, and related climate change, are encouraged. Studies focusing on the impact of radiative forcings on the various components of the climate system, such as on the hydrological cycle, on the cryosphere or on the biosphere and related carbon cycle, are also much appreciated.

Significant uncertainties remain in our understanding of Carbon Dioxide (CO2) and Methane (CH4) fluxes across land, ocean, and atmosphere on both regional and global scales. Remotely sensed CO2 and CH4 observations hold great potential for enhancing our understanding of the natural carbon cycle and monitoring anthropogenic emissions. Recent advances in remote sensing technologies for CO2 and CH4, spanning space, aircraft, and ground-based platforms, have delivered unprecedented accuracy and coverage. Moreover, upcoming next-generation platforms like CO2M, MicroCarb, Merlin, and TANGO promise to further enhance observational capabilities. When integrated with ground-based observation networks and modeling tools, these space-based observations can significantly improve our understanding of the carbon cycle at both local and global scales.

This session invites contributions on all aspects of remote sensing of CO2 and CH4, covering current missions (e.g., GOSAT/2/GW, OCO-2/3, S5P/S5, IASI-NG, Carbon Mapper, GHGSat), upcoming and planned missions (e.g., CO2M, MicroCarb, Merlin, TANGO), as well as ground-based (e.g., TCCON, COCCON), aircraft, and other remote sensing instruments. We welcome advances in retrieval techniques, instrumental concepts, and validation activities, with a particular emphasis on interpreting observations related to natural fluxes or anthropogenic emissions.

Methane is an important greenhouse gas that has contributed to ∼25% of the increase in radiative forcing experienced to date. Despite methane’s short atmospheric lifetime (~10 years), the global average methane mole fraction has increased three times faster than carbon dioxide since 1750. Rapid and severe reductions in methane emissions are required to lower peak warming, reduce the likelihood of overshooting warming limits and reduce reliance on net negative carbon dioxide emissions. In order to track mitigation efforts and ensure emission quantification required in legislation can be met, we must be able to accurately attribute and quantify emissions and are actively doing so through activities such as the UNEP International Methane Emissions Observatory (IMEO).

This session will highlight measurement studies at all scales and from ground-based to satellites, that focus on quantification and source attribution of methane emissions from human activities. We especially encourage submissions from both IMEO and non-IMEO funded work that focus on the following topics: (1) new technologies / methods to provide accurate and repeatable emissions measurements, (2) demonstration of affordable and reliable quantification methods for mitigation tracking, (3) attribution of emissions to specific sources and, (4) methods for upscaling measurements into inventories and creating policy relevant datasets.

Methane is a potent short-lived climate forcer, and rapid mitigation measures are crucial for meeting climate targets and limiting currently expected temperature overshoots. This session will explore these methane mitigation measures, spanning emissions reduction approaches, novel point-source oxidation technologies, and potential atmospheric methane removal approaches.
We invite contributions covering:
- Assessment of methane emission reduction approaches
- Novel and emerging methane mitigation approaches, including emissions destruction and atmospheric removal
- Measurement and verification of mitigation effectiveness
- The role of methane mitigation in future climate scenarios

Atmospheric radicals (such as OH, HO2, RO2, NO3, halogen atoms and halogen oxides) play a central role in the oxidation of trace gases, contributing to the formation of secondary pollutants and influencing Earth’s climate. A thorough understanding of radical sources, including precursor species like HCHO, HONO, organo-halogens, and ClNO2, as well as their chemical fate, such as the conversion of primary pollutants and methane (CH4) oxidation, is essential for addressing regional air quality issues and climate change. Reactive halogen species can have an important influence on the chemistry of the troposphere. For instance, chlorine atoms react faster with most hydrocarbons than OH does and inorganic bromine and iodine can catalytically destroy tropospheric ozone and oxidise mercury. These reactions have been shown to be important in environments as different as the polar troposphere during the springtime ozone depletion events, the boundary layer over salt lakes, and volcanic plumes. Although measuring and modeling radicals is critically important, it remains highly challenging due to their low concentrations, high reactivity, and the complex reaction networks they participate in.

This session welcomes contributions related to the measurement and modeling of radicals, including:
1. Development of novel techniques for detecting radicals, their precursors, and intermediate species;
2. Laboratory studies: determination of gas- and aqueous-phase rate constants, study of complex reaction systems involving halogens, Henry's law and uptake coefficients, UV/VIS spectra, and other properties of reactive species.
3. Adaptation of instruments for various platforms (e.g., ground-based, mobile, shipborne, airborne);
4. Quality assurance and control, such as calibration procedures and intercomparison of different methods;
5. Model development, including new chemical mechanisms, model configurations, and uncertainty analysis;
6. Applications of radical measurements and modeling in field campaigns and satellite-measurements including volcanic plumes as well as chamber studies.

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

The composition of the upper troposphere and the lower stratosphere (UTLS) plays a key role in the climate system. Our understanding of the interactions between dynamics, chemistry, and climate in this region is rapidly advancing thanks to both observational and modeling studies. In this session, we invite presentations on dynamical, transport, and chemical processes determining the variability and long-term trends in the composition of the UTLS, and related effects on radiation and dynamics. We particularly encourage contributions that introduce recent observations (both in situ and remote sensing) and models of various complexity ranging from comprehensive chemistry climate models to idealized and conceptual models.
This year, field campaigns of special focus include recent projects that explore atmospheric transport, composition, and chemical processes in the spring Arctic UTLS, like ASCCI 2025 and COLD SABRE 2023.

Volcanic aerosol clouds from major tropical eruptions cause periods of strong surface cooling in the historical climate record and are dominant influences within decadal surface temperature trends. Advancing our understanding of the influence of volcanoes on climate relies upon better knowledge of:

(i) the radiative forcings of past eruptions and the microphysical, chemical and dynamical processes which affect the evolution of stratospheric aerosol properties and

(ii) the response mechanisms governing post-eruption climate variability and their dependency on the climate state at the time of the eruption.

This can only be achieved by combining information from satellite and in-situ observations of recent eruptions, stratospheric aerosol and climate modelling activities, and reconstructions of past volcanic histories and post-eruption climate state from proxies.
In recent years the smoke from intense wildfires in North America and Australia has also been an important component of the stratospheric aerosol layer, the presence of organic aerosol and meteoric particles in background conditions now also firmly established.

This session seeks presentations from research aimed at better understanding the stratospheric aerosol layer, its volcanic perturbations and the associated impacts on climate through the post-industrial period (1750-present) and also those further back in the historical record.

Observational and model studies on the stratosphere and climate impacts from the 2022 eruption of Hunga Tonga are also especially welcomed.

We also welcome contributions to understand the societal impacts of volcanic eruptions and the human responses to them. Contributions addressing volcanic influences on atmospheric composition, such as changes in stratospheric water vapour, ozone and other trace gases are also encouraged.

The session aims to bring together research contributing to several current international co-ordinated activities: SPARC-SSiRC, CMIP7-VolMIP, CMIP7-PMIP, and PAGES-VICS.

The Earth's middle atmosphere, mesosphere, and lower thermosphere (MLT) region provide a great platform for studying ionospheric dynamics, disturbances, eddy mixing, atmospheric drag effects, and space debris tracking. The thermal structure of these regions is influenced by numerous energy sources such as solar radiation, chemical, and dynamical processes, as well as forces from both above (e.g., solar and magnetospheric inputs) and below (e.g., gravity waves and atmospheric tides). Solar atmospheric tides, related to global-scale variations of temperature, density, pressure, and wind waves, are responsible for coupling the lower and upper layers of the atmosphere and significantly impact their vertical profiles in the upper atmosphere. With evidence of climate change impacts on the middle and upper atmosphere, monitoring and understanding trends through observational data is critical. There has been a contraction of the stratosphere and a decrease in the density of the upper atmosphere, which could impact the accumulation of space debris. This session invites presentations on scientific work related to various experimental/observational techniques, numerical and empirical modeling, and theoretical analyses on the dynamics, chemistry, and coupling processes in the altitude range of ~ 20 km to 180 km of the middle atmosphere and MLT regions, including long-term climatic changes.

The session focuses on the variability of the tropospheric and stratospheric chemical composition on the timescales from diurnal to decadal. It discusses the processes driving this variability and attribution of changes to specific drivers. Special emphasis is put on the value of high-quality long-term measurement data sets both from scientific and societal perspective, including science-policy applications, and their sustainability. Supporting model simulations on different scales that utilize observational data will also be discussed. Contributions related to emerging constituents, new data sources and approached to atmospheric composition measurements (e.g. low cost sensor, emerging measurement techniques), measurement campaign that addresses specific processes and long-term projections of the atmospheric chemical composition are also welcome in the session.
Researchers are invited to present novel scientific results from mid- and long-term observational time series from various programmes and networks such as the Global Atmosphere Watch (GAW) Programme, European Monitoring, and Evaluation Programme (EMEP), Network for the Detection of Atmospheric Composition Change (NDACC), Southern Hemisphere Additional Ozonesondes (SHADOZ), Advanced Global Atmospheric Gases Experiment (AGAGE), National Oceanic and Atmospheric Administration (NOAA), regular airborne (e.g. CARIBIC, IAGOS, CONTRAIL) and other campaigns as well as satellite data and model simulations. Data relevant to tropospheric and stratospheric composition, in particular, related to climate change, ozone depletion, ecosystems and health impacts, and air quality as well as firn data on past atmospheric composition are welcome. We welcome contributions from multi-year modeling studies and inter-comparison exercises that address past and future tropospheric or stratospheric composition changes, carried out in the framework of international projects and initiatives.

Molecular hydrogen (H₂) is gaining global attention as a key component of the transition to sustainable energy systems, with the potential to significantly reduce greenhouse gas emissions and air pollutants. However, the biogeochemical cycle of H₂ and its impacts on atmospheric chemistry and climate present critical knowledge gaps. While hydrogen itself is not a greenhouse gas, its chemical oxidation can influence methane, ozone, and stratospheric water vapor, with potential effects on the Earth’s radiative balance.

This session aims at advancing our understanding of the hydrogen budget and the implications of increased hydrogen use. Topics of interest include:
- Quantifying hydrogen emissions from direct sources, including leakages, venting, and incomplete combustion, as well as oxidation by volatile organic compounds.
- Investigating the removal of hydrogen by soil bacteria and by reaction with OH in the atmosphere.
- Assessing the indirect climate effects of hydrogen emissions on methane, ozone, and stratospheric water vapor.
- Utilizing observations and modeling to refine estimates of hydrogen sources and sinks across various spatial and temporal scales.
- Exploring scenarios of future hydrogen economies, including their potential to reduce fossil fuel emissions and the associated environmental and climatic co-benefits.

We welcome studies that employ experimental, observational, and theoretical approaches to hydrogen biogeochemistry and atmospheric processes, contributing to a more comprehensive understanding of H₂ in the context of the global energy transition.

Urban air pollution comprises a complex mixture of pollutants, including particulates, trace gases, and volatile organic compounds, primarily from anthropogenic activities. The composition has been changing due to shifts from petroleum and diesel vehicles to those powered by compressed natural gas (CNG) and liquefied petroleum gas (LPG), which produce 95% less NOx than diesel and 65% less than petrol. Many nations are now focusing on electric vehicles (EVs), altering emission profiles and air pollutant chemistry through atmospheric transformation, photochemical reactions, and aging processes. These atmospheric pollutants create various health impacts, with studies linking air pollution to increased respiratory conditions.

This session at the European Geosciences Union (EGU) invites submissions on observational and modeling studies of emerging air pollution emissions and chemistry, including their climate and health impacts.

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.

Atmospheric composition and air quality are at the core of global environmental change, with profound implications for public health, ecosystems, and policy. Fine particulate matter, ozone, and reactive trace gases increasingly interact with wildfires, heatwaves, urbanization, and climate variability, creating complex exposure patterns and disproportionate risks for vulnerable groups.
New frontiers in satellite monitoring—from Low Earth Orbit to geostationary platforms—combined with chemical transport models and artificial intelligence, now allow unprecedented accuracy in characterizing pollution sources, dynamics, and health outcomes. At the same time, integrative frameworks linking atmospheric science, epidemiology, and socio-economic analysis are essential for informing effective adaptation and mitigation strategies.
This interdisciplinary session invites studies that advance understanding of atmospheric composition, air quality, and health through innovative observations, modeling, and AI applications. We especially encourage contributions that explore climate–air quality–health interactions, quantify health and economic burdens, develop early-warning systems, and provide policy-relevant insights. The session aims to foster cross-disciplinary collaboration to support evidence-based decision-making for cleaner air and healthier societies.

The transport sector, which includes road traffic, shipping, and aviation, is a significant contributor to global warming and has detrimental effects on air quality. The combustion of fossil fuels results in the emission of gases and particles that alter the chemical composition of the atmosphere. These gases can act as direct greenhouse gases, such as CO2, or undergo complex reactions, forming secondary species. The emitted particles interact with radiation and affect clouds. Emissions from aviation can also lead to the formation of contrails, which affect natural cloud formation processes. While some of these non-CO2 effects contribute to global warming others to cooling.
Due to the significant increase in demand, the contribution of aviation to climate change is expected to grow. Additionally, emissions from road traffic and shipping may also increase depending on changes in mobility and technological advancements. Therefore, it is crucial to develop and implement measures and methods to reduce the anthropogenic climate footprint, including the share of different transport modes. Possible methods to reduce the environmental impact of transport include alternative fuels, such as electricity or hydrogen, and technological advancements, such as after-exhaust treatment systems. Besides these rather technical measures, also operational measures are possible, such as optimized routes.
However, the assessment of the effects of such measures and methods with numerical atmospheric models relies heavily on state-of-the-art emission inventories. It is crucial to provide information on the uncertainties in the emission data to ensure a dependable assessment of air quality and climate effects. This information also contributes to the uncertainties in the representation of physical, chemical, and dynamic processes in atmospheric models.
The objective of this session is to bring together the community involved in the development of transport emissions inventories with the community involved in the use of these inventories. On one hand, the aim is to establish a shared understanding of the different requirements and uncertainties related to emission inventories. On the other hand, particular attention will be given to the latest research on the non-CO2 and air quality effects of transport emissions. Contributions can range from measurement campaigns to modelling results and implementing strategies for reducing the environmental impact of transport.

Over the last twenty years, a significant portion of the global urban population, including Europeans, has lived in areas with consistently unhealthy levels of particulate matter (PM10, PM2.5, ultrafine particles). Despite the reduction of many air pollutants due to earlier policies, air pollution remains associated with millions of premature deaths worldwide, including in Europe.
Transportation plays a crucial role in the global distribution of food, materials, energy, and more. However, all transport sectors are substantial emitters of air pollutants. The influence of transport sectors on harmful ambient PM is not well understood, necessitating increased scientific understanding and evidence to justify policies and develop tools for policy implementation. Addressing key questions requires extensive emissions studies under real-world conditions, far beyond current emission standard protocols. Additionally, emerging sources like non-exhaust emissions and microplastics present new challenges.
The previously simple view of chemically inert primary organic aerosol (POA) has dramatically changed in the last decade. It is now clear that large fractions of volatile organic compounds (VOCs) have been neglected in most past emission studies and are not explicitly included in current emission inventories. Evidence shows that both gases and particles continuously react in the atmosphere, creating complex chemical mixtures that are just beginning to be analyzed with new analytical tools.

This session invites interdisciplinary contributions, both experimental and theoretical, ranging from real-world emissions related to various transport sectors, including new sources like non-exhaust emissions and microplastics, to their chemical transformations in the air and potential impacts on climate and health. Contributions are expected from fundamental studies to the evaluation and mitigation of these pollution sources, aiming for a better description of air quality in different regions, particularly in high-impact zones.

A constellation of geostationary satellite ultraviolet-visible (UV-VIS) spectrometers with air quality related trace gas and aerosol observational capabilities is in orbit forming a Geo-Ring in the Northern Hemisphere. These include Geostationary Monitoring Spectrometer (GEMS) launched in February 2020 by Korean Aerospace Research Institute over Asia, Tropospheric Emissions: Monitoring of Pollution (TEMPO) launched in April 2023 by NASA over North America, and Sentinel-4 ultraviolet visible near infrared (UVN) instrument launched in July 2025 by European Space Agency over Europe. A very successful demonstration of GEMS and TEMPO trace gas and aerosol products in air quality monitoring and forecasting is paving the way for the newly launched Sentinel-4 UVN instrument. We are soliciting papers on global hourly observations of different pollutants from Geo-Ring, consistency of products with state-of-the-art calibration and validation including Low Earth Orbiting satellite sensors as a transfer standard for Level 1B radiances, usage of trace gas and aerosol data in models, inverse modeling to derive emissions, long-range transport of pollutants, and related topics involving international collaboration to minimize data gaps in the Global South.

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.

In recent years, microplastics and nanoplastics have become recognised as ubiquitous atmospheric pollutants. However, many open questions remain regarding emissions, transport and deposition of microplastics and nanoplastics, along with atmospheric processes that determined their fate. In this session we welcome contributions from observational, laboratory and modelling studies that advance the field of airborne microplastics and nanoplastics research, including:

- Sampling and analysis of airborne micro- and nanoplastics
- Atmospheric microplastics and nanoplastics and their interactions with different environmental compartments (oceans, land and the cryosphere)
- Contributions of soils, roads and other terrestrial sources to the atmospheric micro- and nanoplastic burden
- Ocean-atmosphere exchange of microplastics and nanoplastics
- Microplastics and nanoplastics in the cryosphere
- Interactions between micro- and nanoplastics and other sources of aerosol
- Interactions between microplastics, nanoplastics, radiation and clouds
- Airborne microplastics as vectors for chemical and pathogen transport
- Indoor, outdoor, urban, rural and remote microplastics and nanoplastics (measurements, observations, modelling)
- Toxicological and exposure studies related to airborne micro- and nanoplastics
- Degradation of macro-, micro- and nanoplastics in real and simulated atmospheric conditions
- Airborne sources and sinks of micro- and nanoplastics (measurements and modelling)

Rocket launches and re-entries of reusable and discarded objects adds familiar and exotic anthropogenic trace gases and aerosols to all layers of the atmosphere. The space sector is the only anthropogenic source released directly to the middle and upper layers of the atmosphere. Once emitted to these layers, pollutants persist for years, leaving a long legacy of atmospheric pollution. These pollutants are increasingly ubiquitous due to recent exponential space sector growth, yet there are no regulatory controls targeting these emissions. Quantification of the complex and unique effects on the atmosphere is hindered by many uncertainties and data gaps, such as the chemical composition of exhaust from novel propellants, the resultant evolution during plume afterburning, the locations and trajectories of ablative re-entry, the radiative and chemical kinetic properties of the pollutants, and the physical and chemical evolution of controlled and uncontrolled re-entry. Lack of openly-available modelling tools is compounded by a scarcity of real-world experiments and observations, and future scenarios are hindered by a lack of commercial space activity data or well-supported growth projections. This session invites submissions across all geophysical and related disciplines in and beyond academia to share planned, current, or ongoing research that provides new knowledge in this area, explores and devises new open-source modelling techniques, or exposes methodological gaps that need to be resolved to inform sustainability initiatives and global regulation. We are also interested in innovative methods adopted by researchers in other domains that could be applied to advance understanding of environmental harm from the space sector. These include related topics such as geoengineering, space weather, space engineering, upper atmosphere circulation and chemistry, and meteors.

The urgency, complexity, and economic implications of greenhouse gas (GHG) emission reductions demand strategic investments in science-based information for planning, implementing, and tracking emission reduction policies and actions. An increasing number of applications succeed by combining activity-based emissions data with atmospheric GHG measurements and analyses – this hybrid approach can yield additional insights and practical information to support mitigation efforts at different scales. Inspired by this potential, the Integrated Global Greenhouse Gas Information System (IG3IS) of the World Meteorological Organization works to identify and document good practice guidelines for informing decisions, while promoting scientific advances and facilitating two-way linkages between practitioners and stakeholders in the policy realm, tailoring research actions to meet policy needs.
Since EGU18, this session continues to showcase how scientific data and analyses can be transformed into actionable information services and successful climate solutions for a wide range of user-communities. Actionable information results from data with the required spatial and temporal granularity and compositional details able to explicitly target, attribute and track GHG emissions and reductions where climate action is achievable.
This session seeks contributions from researchers, inventory compilers, government decision and policy makers, non-government and private sector service providers that show the use and impact of science-based methods for detecting, quantifying, tracking GHG emissions and the resulting climate mitigation. We especially welcome presentations of work guided by IG3IS good practice research guidelines at urban and national scale and for specific economic sectors. The scope of the session spans measurements of all GHGs and from all tiers of observation.

Biogenic and anthropogenic emissions, which undergo complex physical and chemical transformations in the atmosphere, affect air quality and climate change. To understand these processes, we need knowledge of the fundamental mechanisms that underpin them. This session welcomes contributions from laboratory investigations, simulation chamber experiments, field studies, and computational and theoretical work that provide new insights into atmospheric processes, from single-reaction kinetics through chemical mechanisms in the gas and particle phases, to single particle physical chemistry that determines aerosol climate forcing. Contributions employing quantum chemistry, molecular dynamics simulations, or theoretical modeling of fundamental aerosol processes are encouraged. We also welcome studies that demonstrate new experimental approaches, make use of research infrastructures such as ACTRIS, ICOS, and IAGOS for process studies, or introduce innovative techniques that facilitate the acquisition of new knowledge in atmospheric science.

The weather and atmospheric composition (AC) are closely related. AC forecasts rely on the correct prediction of the meteorological situation, in particular for the simulation of transport, wet deposition and surface fluxes. Numerical Weather Prediction (NWP) from the short-range to the seasonal range has started using prognostic presentations of aerosols, greenhouse gases and reactive gases in radiation and cloud physics schemes to improve the forecast accuracy. Recognizing the scientific and operational benefits of combining NWP and AC forecasting and data assimilation, integrated AC-NWP systems for global, regional, and local applications have been developed. Most recently machine-learning-based approaches for forecasting the weather and AC have emerged.

We invite contributions on all aspects of forecasting and data assimilation of aerosols, reactive gases, greenhouse gases, and weather or stratospheric dynamics across different time scales. Our focus is on the scientific, computational, and societal advantages of such integrated approaches. Specifically, but not exclusively, we invite papers addressing the following topics:

a) Improved weather predictions due to simulated feedback between aerosols and chemistry in radiation and cloud physics,

b) Improved AC prediction by improved representation of the meteorological variability,

c) Advancements in operational NWP-AC prediction systems, in particular using data-driven machine learning methods,

f) Data assimilation developments for AC and NWP systems,

g) Forecasting of stratospheric composition and dynamics after large volcanic eruptions such as the Hunga-Tonga,

h) Combined impact of environmental hazards on society, such as air pollution and high-impact weather, wildfires, dust storms and the underlying meteorological factors,

i) Evaluation, validation, and applications of NWP-AC prediction systems.

This Session is organized in cooperation with the Copernicus Atmosphere Monitoring Service (CAMS) and the Global Air Quality Forecasting and Information Systems (GAFIS) initiative of the WMO Global Atmosphere Watch (GAW) Program.

Understanding the sources and variability of atmospheric composition, including ambient particulate matter, volatile organic compounds, greenhouse gases, and complementary chemical and isotopic tracers, is central to addressing air quality and climate challenges. Reliable observational data and robust source apportionment methods are both essential for attributing emissions, detecting changes over time, and supporting effective environmental and climate policy.
This session brings together data-driven approaches for analysing atmospheric composition, combining recent advances in source apportionment methodologies with developments in atmospheric measurements. Contributions addressing receptor-oriented models, multivariate analysis techniques, and novel or improved approaches for source attribution of air pollutants and greenhouse gases are welcomed, alongside studies that focus on measurement quality, calibration, uncertainty quantification, and harmonisation across observational platforms and monitoring networks.
The session encourages case studies, methodological developments, and intercomparison exercises that include high-quality in situ, mobile, airborne, and emerging measurement platforms (e.g. low-cost sensors, UAVs, mobile laboratories), receptor modelling, satellite observations, and supporting model simulations. Of particular interest are studies that improve the consistency, interpretability, and comparability of observational datasets across temporal and spatial scales, new methodologies on source apportionment of air pollution, application of receptor models and studies that strengthen the link between atmospheric composition measurements, emissions attribution, and science–policy applications. By fostering dialogue between observational and modelling communities, the session aims to advance a more integrated understanding of atmospheric composition relevant to both air quality management and climate mitigation.

The session welcomes contributions on aerosol observations and their interactions with clouds, solar radiation, and climate, with a focus on both ground-based and satellite-based measurements. It aims to highlight recent advances in aerosol measurement techniques, harmonization efforts, and calibration/validation studies, especially those supporting long-term consistency and comparability across networks.
Key topics include the observation of aerosol optical properties, results from field campaigns, radiative transfer in cloud-free and cloudy atmospheres—including 3D modeling aspects—and the validation of satellite aerosol products using ground-based networks. Studies on aerosol impacts on solar radiation and energy production and aerosol assimilation into models, are also encouraged.
Particular emphasis is given to contributions from the Harmonia COST Action (AEutopean network of 150 scientists), which supports global harmonization of aerosol measurements, and the ACTRIS community, including the Calibration of Aerosol Remote Sensing (CARS) group. However, the session is open to all researchers working on aerosol measurements, modeling, and satellite product validation.
Overall, the session aims to promote collaboration and knowledge exchange to improve the quality and increase the use of aerosol data for climate, atmospheric, and solar energy applications.

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.

This session focuses on volatile organic compounds (VOCs) at the biosphere-atmosphere interface, encompassing innovative analytical methods, laboratory and field studies, and emission modelling approaches.

We invite contributions on plant and other biogenic VOC emissions sources (e.g., from soil, litter, and freshwater) under environmental changes and welcome contributions on methodological advances in sampling and analysis techniques, and modelling frameworks that bridge experimental observations with atmospheric processes.

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.

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).

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.

Clouds play an important role in the Polar climate due to their interaction with radiation and their role in the hydrological cycle linking poleward water vapour transport with precipitation. Cloud and precipitation properties depend on the atmospheric dynamics and moisture sources and transport, as well as on aerosol particles, which can act as cloud condensation and ice nuclei. These processes are complex and are not well represented in the models. While measurements of cloud and precipitation microphysical properties in the Arctic and Southern Ocean/Antarctic regions are challenging, they are highly needed to evaluate and improve cloud processes representation in the models used for polar and global climate and cryosphere projections.

This session aims at bringing together researchers using observational and/or modeling approaches (at various scales) to improve our understanding of polar tropospheric clouds, precipitation, and related mechanisms and impacts. Contributions are invited on various relevant processes including (but not limited to):
- Drivers of cloud/precipitation microphysics at high latitudes,
- Sources of cloud nuclei both at local and long range,
- Linkages of polar clouds/precipitation to the moisture sources and transport, including extreme transport events (e.g., atmospheric rivers, moisture intrusions),
- Relationship of moisture/cloud/precipitation processes to the atmospheric dynamics, ranging from synoptic and meso-scale processes to teleconnections and climate indices,
- Interactions between clouds and radiation, including impacts on the surface energy balance,
- Impacts that the clouds/precipitation in the Polar Regions have on the polar and global climate system, surface mass and energy balance, sea ice and ecosystems.

Papers including new methodologies specific to polar regions are encouraged, such as (i) improving polar cloud/precipitation parameterizations in atmospheric models, moisture transport events detection and attribution methods specifically in the high latitudes, and (ii) advancing observations of polar clouds and precipitation.

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.

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 interactions among the climate systems, ecosystems, and atmospheric chemistry are central to understanding Earth system dynamics in the Anthropocene. Climate regulates ecosystem structure and function through changes in temperature, precipitation, and extreme events, while ecosystems alter climate via biogeochemical (e.g., the carbon cycle) and biogeophysical (e.g., vegetation-induced albedo change) processes. For this climate–ecosystem coupling, atmospheric chemistry serves as a crucial bridge. Specifically, ecosystem emissions (e.g., wildfire plumes, biogenic emissions) affect cloud condensation nuclei and surface radiation balance, thereby influencing climate from regional to global scales. Meanwhile, air pollutants (e.g., ozone, aerosols) affect plant physiology (e.g., photosynthesis, stomatal conductance) and land-atmosphere energy and water exchanges, further modifying the climate system. Deliberate manipulation of atmospheric aerosols could be employed as a climate intervention strategy (e.g., solar geoengineering). Yet, current research faces two major limitations: (1) difficulties in observing multi-scale nonlinear processes, and (2) inadequate parameterizations in coupled models.
This session will bring together progress in observations, modeling, and applications to advance understanding of climate-ecosystems-atmospheric chemistry interactions. Topics include, but are not limited to:
• Observations: Integrating multi-source data (e.g., field measurements, remote sensing, flux networks, atmospheric monitoring) with controlled experiments (e.g., FACE, warming experiments) to identify key interactions;
• Modeling: Improving the multi-scale representations in Earth system models, developing high-resolution regional coupled models, and optimizing parameterizations of key processes such as biogenic emissions and biogeochemical feedbacks;
• Applications: Assessing how interactions between atmospheric aerosols/pollutants and ecosystems influence climate change mitigation and carbon neutrality goals, and quantifying the strength of the ecosystem-climate feedbacks to air quality under different scenarios, and evaluating the effectiveness and risks of aerosol/cloud-based geoengineering.
By addressing these topics, the session aims to advance understanding of coupled climate–ecosystem–chemistry processes, enhance predictive capability, and provide a stronger scientific foundation for climate adaptation and sustainable development.

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

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

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

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

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

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.

This session invites contributions focused on the understanding, modeling, and prediction of extreme events in weather, climate, and broader geophysical systems, from both theoretical and applied perspectives. We aim to bring together researchers from the traditional geophysical sciences with those working in mathematical, statistical, and dynamical systems approaches, fostering an interdisciplinary dialogue and discussions.
By highlighting the complementary nature of physical intuition and mathematical formalism, this session seeks to advance our understanding of the processes that give rise to extremes, improve predictive capabilities, and assess the extremes' societal and environmental impacts.
Topics of interest include, but are not limited to:
- Variability and projected changes in extremes under climate change
- Representation and performance of climate models in simulating extreme events
- Attribution of extreme events
- Emergent constraints on extreme behavior
- Predictability of extremes across meteorological to climate timescales
- Connections between extremes in dynamical systems and observed geophysical extremes
- Theoretical and applied studies of extremes in nonlinear and chaotic systems
- Downscaling techniques for extreme events
- Linking the physical dynamics of extreme events to their impacts on society and ecosystems.
We particularly encourage submissions that bridge disciplines, propose novel methodologies, or offer new insights into the mechanisms and consequences of extreme geophysical phenomena. We encourage submissions from the "Transdiscipinary Newtork to bridge Climate Science and Impacts on Society" (FutureMED) and the "Seasonal-to-decadal climate predictability in the Mediterranean: process understanding and services" (MEDUSSE) COST action communities.

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.

Rapid urbanization and climate change are intensifying urban heat stress, flooding, and environmental degradation, increasing risks to human health, infrastructure, ecosystems, and long-term sustainability. Interacting heat islands and extreme precipitation create compound hazards that require integrative approaches across climatology, hydrology, ecology, and urban planning. Green and blue infrastructure (trees, parks, vegetated surfaces, and water bodies) offers nature-based solutions through cooling, stormwater retention, and air quality and carbon benefits, yet their effectiveness is constrained by extreme urban climates, resource limits, and socio-economic factors.
This session brings together research that advances the characterization, modeling, and mitigation of urban heat and flood risks through quantitative, data-driven, and geospatial approaches. We welcome contributions leveraging remote sensing, in-situ observations, numerical and process-based models, spatial statistics, machine learning, as well as the integration of multi-source datasets (satellite, airborne, ground-based, and socio-economic). Particular emphasis is placed on understanding heat–flood interactions, evaluating green adaptation strategies across scales, and assessing their impacts on microclimate, hydrology, energy demand, biodiversity, and human well-being.
Topics of interest include geospatial and AI-based methods to monitor, model, and predict urban heat dynamics, quantitative assessments of urban heat island mitigation and cooling demand, modeling of flood attenuation and runoff reduction through green infrastructure, integrated analyses linking heat with air quality, health, energy use, and social vulnerability, and strategies to optimize the costs and benefits of urban ecosystems under climate stress. By bridging geospatial analyses, modelling frameworks, and urban environmental science, this session aims to deepen understanding of urban climate processes and support the design of resilient, sustainable, and climate-adaptive cities.

The recent revolution of data-driven forecasting systems based on artificial intelligence (AI) has opened new research possibilities in weather forecasting, climate science, and various other areas. At the same time, many open questions remain–such as how to properly evaluate the model outputs in terms of generalizability under climate change, whether models extrapolate to unseen extremes, and to what extent they are consistent with physical principles. This session focuses on new scientific approaches emerging from this AI revolution, limitations of current models, and strategies to overcome them. We encourage submissions that explore a wide range of topics, including evaluations of outputs and comparisons to numerical models, technical advancements in initial condition optimization or model fine-tuning, novel techniques from explainable AI, and other relevant studies. Bringing together experts from AI, climate sciences, statistics, and applied math will foster interdisciplinary collaborations and guide scientific progress in this quickly evolving field of research.

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.

This session explores forecasting in geosciences using statistical methods. Ranging from linear regression to the most advanced machine learning (ML) or artificial intelligence (AI) algorithms, the session welcomes all contributions developing and/or using these tools for various applications such as AI-based numerical weather prediction and nowcasting, time series forecasting in geosciences, forecast blending, statistical post-processing, and downscaling.
This session also welcomes contributions advancing the assessment of AI-based forecasts. Aiming at a proper and in-depth assessment of the strengths and weaknesses of AI-based models, the session will report on benchmarking activities, new verification methodologies, diagnostics of forecast realism, and progress in the interpretability of AI-based models.

This session is designed to foster interdisciplinary discussions among geoscientists from meteorology, climate, hydrology, and other related communities, promoting the use of statistical methods in forecasting, verification, and beyond.

In recent years, machine learning (ML) and artificial intelligence (AI) have emerged as powerful weather forecasting tools, including for weather and climate extremes and related events. Data-driven algorithms applied across different temporal and spatial scales have shown great promise in predicting phenomena such as hurricanes, floods, heatwaves, and droughts, while also improving the accuracy and timeliness of climate projections.

This session seeks contributions exploring the development and application of ML or ML-enhanced algorithms for forecasting weather and climate at multiple spatial and temporal scales and for detecting and anticipating extreme weather and climate events. We welcome studies that address the use of AI for short-and medium-range meteorological forecasts, extended-range forecasts, sub-seasonal to seasonal climate forecasts, or longer-term climate projections, spanning local to global spatial scales.

We particularly encourage submissions that connect extremes to their societal and environmental impacts, such as impacts on infrastructure, ecosystems, health, or energy systems.Contributions that integrate ML with physical mechanisms to advance the representation of climate variables in numerical models or climate datasets are also highly encouraged.

By bringing together experts from AI, data science, meteorology, climate science, and impact modelling, this session aims to foster interdisciplinary collaborations that push the boundaries of forecasting and understanding extreme weather and climate events, as well as their impacts. We encourage submissions from early-career scientists, established researchers, and industry professionals alike.

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

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

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

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

The session focuses on the latest developments in spectroscopic and optical instrumentation and technologies from the UV to THz spectral regions and their use in atmospheric applications. These applications include observation of spatial and temporal changes in the concentrations and optical properties of atmospheric constituents, as well as the study of atmospheric processes in laboratories, atmospheric simulation chambers, and field deployments.

As the scattering and absorption of radiation by atmospheric particles are central to Earth’s radiation balance, this session facilitates an exchange of insights between the measurement and modeling communities. Accurately quantifying these radiative effects remains a challenge. Specifically, uncertainties in morphology and the computational cost of modeling complex particles necessitate novel and efficient approaches.

The session aims to be a forum for sharing information on the state-of-the-art and emerging developments in atmospheric sensing measurements and modeling. We welcome contributions from atmospheric scientists, engineers, and industry. Topics include developments and applications of novel spectroscopic methods (such as frequency comb, cavity-enhanced, and photoacoustic spectroscopies) dedicated to measuring aerosols, isotopologues, and trace gases, as well as advances in the measurement and modeling of atmospheric particle optics. Approaches using ground and airborne platforms, simulation chambers, and new data analysis tools (including deep learning) are also encouraged.

Recent advances in high-performance computing have enabled climate models to resolve processes at smaller scales, leading to a new generation of simulations that can explicitly capture km-scale atmospheric and oceanic dynamics like storms and eddies. Traditional low-resolution climate models rely on the use of eddy parameterizations in the ocean, and convective parameterizations in the atmosphere that can partially interrupt the coupling between small and large scale dynamics. Global storm- and eddy- resolving models, by largely removing the need for such parameterizations, allow us to probe the rectified effect of small-scale processes on the large-scale climate system. This new modeling frontier offers unprecedented opportunities to uncover the importance of small-scale processes in the ocean, atmosphere, and at the air-sea interface in Earth’s climate.

In this session, we welcome submissions on the added value of high-resolution ocean, atmosphere, or coupled modeling, and the importance of small-scale processes in shaping the Earth’s climate. This includes studies at global to regional scales and over all timescales, from multidecadal variability to extreme events. We also welcome contributions addressing current limitations and challenges in km-scale modeling, such as persistent model biases, computational costs, and the complexities of initializing and validating models. Studies using models from coordinated projects such as NextGEMS, EERIE, DestinE and WarmWorld, and other similar efforts are encouraged.

This session is the result of the merge of former sessions "Remote sensing of atmospheric composition: MAX-DOAS, spectral imaging and other techniques" and "The use of uncrewed aircraft systems (UAS) for atmospheric and climate research".

Shortened description of MAX-DOAS, spectral imaging and other techniques:

This session aims to present research activities and instrument developments in the field of atmospheric remote sensing, particularly emphasising Multi-AXis (MAX-) DOAS and (hyper-) spectral imaging techniques which use scattered sunlight as a light source. Contributions from other passive and active DOAS applications are also welcome.

MAX-DOAS and spectral trace gas imaging techniques provide an essential link between in-situ measurements of trace gas concentrations or reported point source emissions and column-integrated measurements from satellites. They play a key role in satellite validation and are found to be a valuable addition to global measurement networks.

Shortened description of the use of uncrewed aircraft systems (UAS):

Uncrewed Aircraft Systems (UAS) are revolutionizing atmospheric and climate sciences by significantly expanding observational capabilities. Driven by rapid platform development and sensor miniaturization, these systems now provide critical datasets linking hydrology and ecology with applied fields like wind energy and pollutant transport.

This session invites abstracts on scientific contributions utilizing fixed-wing UAS, multicopters, and tethered balloon systems. We welcome presentations on novel instrumentation, recent measurement efforts, and the use of UAS datasets to improve numerical modeling, data assimilation, and weather prediction. Contributions highlighting recent field campaigns are especially encouraged to foster a deeper understanding of atmospheric processes.

Air pollution remains a critical global challenge, disproportionately impacting vulnerable communities in low- and middle-income countries. Weak policies, fragmented institutions, limited financial and computational resources, and lack of comprehensive monitoring infrastructure hinder effective air quality (AQ) management. Accessible and affordable AQ sensors (low-cost sensor systems, LCS) offer a promising solution by enabling dense spatial networks, rapid deployment, citizen engagement, and integration with other data sources. Yet, persistent challenges remain around data quality, calibration, standardisation, integration with regulatory frameworks, long-term sustainability, and equitable access. Addressing these issues requires strong local capacity-building and international collaboration.
This session will showcase best practices in using LCS for AQ monitoring. We will explore case studies where LCS enhance air quality monitoring products (integrating satellite with air sensor information), verify air quality forecasting systems, and support public health and community monitoring initiatives, particularly, but not limited, to resource-limited settings. This session promotes cutting-edge research, case studies, and best practices for using air sensors in air quality monitoring. These aspects will help to enhance air quality monitoring capabilities and foster strong local and international collaboration. It will also explore strategies for sustainable practices that empower communities and ensure equitable partnerships.

This session invites contributions on the latest developments and results in lidar remote sensing of the atmosphere, covering • new lidar techniques as well as applications of lidar data for model verification and assimilation, • ground-based, airborne, and space-borne lidar systems, • unique research systems as well as networks of instruments, • lidar observations of aerosols and clouds, thermodynamic parameters and wind, and trace-gases. Atmospheric lidar technologies have shown significant progress in recent years. While, some years ago, there were only a few research systems, mostly quite complex and difficult to operate on a longer-term basis because a team of experts was continuously required for their operation, advancements in laser transmitter and receiver technologies have resulted in much more rugged systems nowadays, many of which are already operated routinely in networks and several even being fully automated and commercially available. Consequently, also more and more data sets with very high resolution in range and time are becoming available for atmospheric science, which makes it attractive to consider lidar data not only for case studies but also for extended model comparison statistics and data assimilation. Here, ceilometers provide not only information on the cloud bottom height but also profiles of aerosol and cloud backscatter signals. Scanning Doppler lidars extend the data to horizontal and vertical wind profiles. Raman lidars and high-spectral resolution lidars provide more details than ceilometers and measure particle extinction and backscatter coefficients at multiple wavelengths. Other Raman lidars measure water vapor mixing ratio and temperature profiles. Differential absorption lidars give profiles of absolute humidity or other trace gases (like ozone, NOx, SO2, CO2, methane etc.). Depolarization lidars provide information on the shapes of aerosol and cloud particles. In addition to instruments on the ground, lidars are operated from airborne platforms in different altitudes. Even the first space-borne missions are now in orbit while more are currently in preparation. All these aspects of lidar remote sensing in the atmosphere will be part of this session.

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.

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

Climate modeling is pushing the frontier towards increasingly complex, high-resolution earth system models (ESMs). At the same time, nonlinearities and emergent phenomena in the climate system are often studied by means of conceptual models, which offer qualitative understanding and permit theoretical approaches. Recent advancements in statistical and physical emulators, from reduced-complexity models to machine learning techniques, are enabling rapid and computationally efficient assessments of climate trajectories, impacts and risks.

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

A diverse and well-integrated model ecosystem is also an indispensable prerequisite for the timely assessment of climate risks and effective decision-making. This places renewed emphasis on the concept of fit-for-purpose modeling, which is intrinsically linked to the climate model spectrum through the need to understand what levels of complexity are required and sufficient for a given scientific question or application. The climate community is increasingly interested in making models useful also beyond the academic domain (Mansfield et al., 2023).

In this session, we bring together contributions from all subfields of climate science that showcase how different modeling approaches advance our understanding of the Earth system, highlight inconsistencies in the model spectrum, and/or enable applications in climate impact projections. The key goal is to foster exchange between researchers working on different rungs of the model complexity ladder, focusing on process understanding. Contributions may employ dynamical systems models, physics-based low-order models, explainable machine learning, fast climate models and Earth System Models of Intermediate Complexity (EMICs), simplified or idealized setups of ESMs, CMIP models, and km-scale models. Processes and phenomena of interest include the Earth system response to transient forcing, tipping behavior, climate variability and extremes, and predictability.

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.

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

In the past years, the analysis of compound events has emerged as an essential step to enhance our knowledge of and response to multi-hazard high-impact events that occur simultaneously or sequentially, causing interconnected or aggravated impacts. Compound events involve two (or more) events happening together. These can be independent events (in which the outcome of one event has no effect on the probability of the other), or dependent events (when the outcome of one event affects the probability of another). Compound weather, climate or hydrological events refer to combinations of multiple drivers or hazards that may lead to large impacts and disasters. These events can be related to extreme conditions (e.g. storms, heatwaves, floods and droughts), or to combinations of events that are not themselves extremes but lead to an extreme event or significant impact when combined.
In this Short Course, we will introduce compound events, their types (preconditioned, multivariate, temporally compounding, and spatially compounding events), and the methods used to detect and characterize them. We will highlight the advantages and limitations of statistical methods (regression, multivariate statistics, and classification), empirical approaches based on large datasets, high-dimension approaches such as copulas, and complex network-based techniques that help to identify non-trivial spatio-temporal patterns of extreme events.
The Short Course will focus on sharing experience from a wide range of applications worldwide, state-of-the-art methodological approaches, open access code and datasets, and will allow participants to discuss their own challenges in detecting, characterizing and assessing the risk of compound events in diverse contexts (climate, atmospheric, hydrologic, ocean and natural hazards sciences).

Are you unsure about how to bring order in the extensive program of the General Assembly? Are you wondering how to tackle this week of science? Are you curious about what EGU and the General Assembly have to offer? Then this is the short course for you!

During this course, we will provide you with tips and tricks on how to handle this large conference and how to make the most out of your week at this year's General Assembly. We'll explain the EGU structure, the difference between EGU and the General Assembly, we will dive into the program groups and we will introduce some key persons that help the Union function.

This is a useful short course for first-time attendees, those who have previously only joined us online, and those who haven’t been to Vienna for a while!

The Meteorological Archival and Retrieval System (MARS) is the world’s largest meteorological archive and ECMWF's main data repository. It stores operational weather analyses and forecasts, reanalyses, observations and research experiments that support a wide range of Earth system science applications.
This short course provides a practical introduction of MARS archive to the new users of the archive. Participants will learn how to explore the MARS data catalogue to identify datasets relevant to their research. The session will demonstrate how to construct and run MARS requests to download data efficiently.
Through step by step examples, attendees will gain a clear understanding of the archive’s structure and the main concepts behind exploring the data and retrieving the data they need for their research.

This short course will train you how to use robust Machine Learning methods to do statistical downscaling of coarse climate model scenarios. A sample dataset will be used: daily surface temperature from one Global Climate Model of the CMIP6 database (historical and future climate time periods), along with a high resolution reanalysis.
Introduction on climate statistical downscaling
Methodology: classical and Machine-Learning based
Steps to perform downscaling
Sample datasets
Results
All material will be made available online, and a sample Jupyter Notebook will be provided.

In April 2023, EPOS, the European Plate Observing System launched the EPOS Data Portal (https://www.ics-c.epos-eu.org/), which provides access to multidisciplinary data, data products, services and software from solid Earth science domain. Currently, ten thematic communities provide input to the EPOS Data Portal through services (APIs): Anthropogenic Hazards, Geological Information and Modelling, Geomagnetic Observations, GNSS Data and Products, Multi-Scale Laboratories, Near Fault Observatories, Satellite Data, Seismology, Tsunami and Volcano Observations.
The EPOS Data Portal enables search and discovery of assets thanks to metadata and visualisation in map, table or graph views, including download of the assets, with the objective to enable multi-, inter- transdisciplinary research by following FAIR principles.
This short course will introduce the EPOS ecosystem and demonstration of integrated virtual research environment where users can stage their data and run Jupyter Notebooks, either from existing examples or their own. We see this interactive coding and development environment as a gate towards faster scientific progress and enabling open science.
It is expected that participants have scientific background in one or more scientific domains listed above. The training especially targets young researchers and all those who need to combine multi-, inter- and transdisciplinary data in their research. The use of the EPOS Platform will simplify data search for Early Career Scientists and potentially help them in accelerating their career development. Feedback from participants will be collected and used for further improvements of the EPOS system.

Earth System Sciences (ESS) datasets, particularly those generated by high-resolution numerical models, are continuing to increase in terms of resolution and size. These datasets are essential for advancing ESS, supporting critical activities such as climate change policymaking, weather forecasting in the face of increasingly frequent natural disasters, and modern applications like machine learning.

The storage, usability, transfer and shareability of such datasets have become a pressing concern within the scientific community. State-of-the-art applications now produce outputs so large that even the most advanced data centres and infrastructures struggle not only to store them but also to ensure their usability and processability, including by downstream machine learning. Ongoing and upcoming community initiatives, such as digital twins and the 7th Phase of the Coupled Model Intercomparison Project (CMIP7), are already pushing infrastructures to their limits. With future investment in hardware likely to remain constrained, a critical and viable way forward is to explore (lossy) data compression & reduction that balance efficiency with the needs of diverse stakeholders. Therefore, the interest in compression has grown as a means to 1) make the data volumes more manageable, 2) reduce transfer times and computational costs, while 3) preserving the quality required for downstream scientific analyses.

Nevertheless, many ESS researchers remain cautious about lossy compression, concerned that critical information or features may be lost for specific downstream applications. Identifying these use-case-specific requirements and ensuring they are preserved during compression are essential steps toward building trust so that compression can become widely adopted across the community.

This short course is designed as a practical introduction to compressing ESS datasets using various compression frameworks and to share tips on preserving important data properties throughout the compression process. After completing the hands-on exercises, using either your own or provided data, time will be set aside for debate and discussion to address questions about lossy compression and to exchange wishes and concerns regarding this family of methods. A short document summarising the discussion will be produced and made freely available afterwards.

To learn more about recent advances in data compression, please also join the ESSI2.2 oral and poster sessions.

Why this short course
Earth and environmental sciences thrive on data diversity: from ocean temperatures to biodiversity records, from climate indicators to geological observations. Yet, this very diversity can also be a barrier: different datasets are described with different standards, stored in different formats, and are difficult to connect across research infrastructures. The ENVRI-Hub provides a set of tools to overcome these challenges. It offers researchers a unified framework to discover, access, and reuse complex and multidisciplinary data.

This short course will give researchers a practical introduction to how ENVRI-Hub workflows can directly support their own projects, to build more reproducible and impactful science.

What researchers will learn
By joining this short course, researchers will:
- Get a clear picture of why Essential Variables matter in Earth and environmental sciences and how variable harmonisation improves scientific collaboration;
- Explore datasets through different pathways, including LLM-based search;
- Draft a mini workflow using curated Jupyter notebooks to map and query essential variables and visualise results;
- Share ideas with peers on how ENVRI-Hub workflows could advance their own research projects.

Interactive format
This 1h45min researcher-focused applied training session will blend live demonstrations, guided practice with curated tools, and participation discussions.

The interactive outline will engage participants by offering them an opportunity to:
- Navigate the ENVRI-Hub services and datasets: knowing what’s available and what fits their needs;
- Understand how to integrate ENVRI-Hub analytical tools into their research workflows: from data discovery and annotation to analysis and sharing;
- Present research use cases by reflecting on common challenges and benefits across domains

Who should join
This short course is tailored for:
- Researchers in Earth and environmental sciences, project coordinators, and data scientists looking to improve their data workflows;
- Anyone interested in applying interoperable approaches to interdisciplinary research;
- Anyone with basic familiarity with Python/Jupyter.

Data assimilation (DA) is widely used in the study of the atmosphere, the ocean, the land surface, hydrological processes, etc. The powerful technique combines prior information from numerical model simulations with observations to provide a better estimate of the state of the system than either the data or the model alone. This short course will introduce participants to the basics of data assimilation, including the theory and its applications to various disciplines of geoscience. An interactive hands-on example of building a data assimilation system based on a simple numerical model will be given. This will prepare participants to build a data assimilation system for their own numerical models at a later stage after the course.
In summary, the short course introduces the following topics:

(1) DA theory, including basic concepts and selected methodologies.
(2) Examples of DA applications in various geoscience fields.
(3) Hands-on exercise in applying data assimilation to an example numerical model using open-source software.

This short course is aimed at people who are interested in data assimilation but do not necessarily have experience in data assimilation, in particular early career scientists (BSc, MSc, PhD students and postdocs) and people who are new to data assimilation.