Forecasting the weather, in particular severe and extreme weather, remains an important subject in meteorology. This session highlights recent research and advancements in forecasting methods, with a strong emphasis on AI-based methods and their integration into operational and impact-oriented forecasting systems. We welcome contributions that explore applications in nowcasting, mesoscale and convection permitting modelling, ensemble prediction, and seamless approaches that optimally integrate multiple forecast sources.

Topics may include:

• Data-driven forecasting, including ensemble methods, across global, regional and local scales
• Integration of data-driven models within data assimilation algorithms
• Operational workflows: implementation, monitoring, versioning of data and models, data, training, and inference pipelines
• AI-driven nowcasting methods and systems utilizing observational data and weather analysis
• Enhancement of mesoscale and convection-permitting models through AI techniques
• Application of novel remote sensing technologies in data assimilation processes
• Utilization of ensemble prediction techniques for improved forecasting
• Development of ensemble-based products for severe/extreme weather forecasting
• Seamless deterministic and probabilistic forecast prediction in data-driven, statistical, numerical and data-blending approaches
• Post-processing techniques, statistical methods in prediction
• Impact-oriented weather forecasting
• Presentation of results from relevant international research projects of EU, WMO, and EUMETNET etc.

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.

High-impact weather events, such as extreme rainfall, severe storms, damaging winds, landfalling atmospheric rivers, hurricanes/typhoons, heatwaves, and droughts, have significant impacts on our society and daily life. Data assimilation (including AI applications for data assimilation) and Research to Operations (R2O) play a crucial role in enhancing forecasts for high-impact weather events. This session will focus on recent research and advancements in atmospheric data assimilation, AI for data assimilation, and Research to Operations (R2O) aimed at improving forecasts for high-impact weather events, particularly those intended for operational and impact-oriented applications. We encourage submissions that explore various topics, such as advancements in data assimilation algorithms/techniques/systems, enhanced data preprocessing, assimilation of novel observation types, observational impact studies, synergies between artificial intelligence (machine learning) and data assimilation, Research to Operations (R2O) activities, the verification and validation of forecasts against theoretical frameworks and observational data, and other relevant studies.

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

For the last two decades Earth System Models (ESMs) have been applied to predict the future climate in ranges of decades to century timescales. More recently, advanced technology has been allowing the growth of computing power and the development of new techniques, like Machine Learning (ML). Enhanced computing capacity and techniques enable more complex modeling systems and larger ensembles. Complex modeling systems like ESMs are increasingly being used in weather and climate applications in a more seamless way in the last few years, setting the frame for a new generation of operational weather and climate prediction systems. This has brought more accurate and reliable forecasts, making weather and climate information more valuable for stakeholders and policymakers. However, in addition to errors within individual ESM components, complex inter-component interactions can lead to the growth of errors whose root causes are difficult to identify and correct. Despite the evolution of ESMs and the increase in the understanding of physical, dynamical and biogeochemical processes of the Earth System, the observational network does not provide enough information to constrain ESMs in ways that allow fully understanding and resolution of model errors. The efforts to assess, test, and enhance models have reduced major systematic errors, but some persist, and new ones have emerged. Therefore, there is a continued need to improve the representation of different processes in ESMs by identifying and correcting systematic errors.
This session invites contributions that help to increase understanding of the nature and cause of systematic errors in ESMs. Of particular interest are studies that consider:
-model errors across space and time scales; the use of hierarchies of models, including single column models and constrained ESM components;
-physics-dynamics and physics-physics cross-component coupling;
-initialized predictions;
-climatology of weather prediction models;
-data assimilation methodologies to identify systematic errors and constrain parameters;
-use of ML to identify systematic errors and/or to detect causal connections between seemingly disparate parameters; stochastic parameterization to represent uncertainty.
Verifying diagnostics and metrics to identify and characterize systematic errors and process understanding across different modeling communities (regional and global km-scale modeling) are also welcomed.

In recent years, machine learning (ML) and artificial intelligence (AI) have emerged as powerful tools for weather forecasting and detection of extreme weather and climate events. The application of data-driven algorithms across different temporal and spatial scales has shown great promise in predicting phenomena such as hurricanes, floods, heatwaves, and droughts and 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 timescales and for detecting and forecasting extreme weather and climate events. We encourage submissions that address the use of AI for meteorological forecasts, extended-range forecasts, sub-seasonal to seasonal climate forecasts, or longer-term climate projections, spanning local to global spatial scales. We also welcome studies that integrate ML with physical mechanisms, leading to AI-driven advancements that improve the representation of climate variables in numerical models or climate datasets.

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

This session invites contributions spanning all aspects of prediction, predictability, and applications on the Subseasonal-to-Seasonal (S2S) (i.e., 2 weeks to 2 months) lead time range. The session welcomes contributions on the following:

(a) Modes of variability (e.g. Madden Julian Oscillation (MJO) and others) impacting the S2S predictability;
(b) Tropical/extratropical wave dynamics and their effects on weather patterns;
(c) Teleconnections and combined influence of climate variability modes;
(d) The role of the atmosphere, ocean, land, and ice processes in S2S predictability;
(e) 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;
(f) Use of AI/ML methods for S2S prediction, data-driven models, post-processing, and attribution, including innovative techniques for improving forecast accuracy;
(g) Case studies of extreme or high-impact event prediction on the S2S timescale;
(h) Sector-specific applications, impact studies, and climate services on the S2S timescale, including 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;
(i) 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.

Weather is chaotic, with strong sensitivity to initial conditions tied to the intrinsic limit to predictability. The strong sensitivity also suggests effective control in which small modifications to the atmospheric conditions grow rapidly and result in big changes. Weather predictability has been studied extensively in the past decades, and the weather prediction skills have been improving consistently. Now with the accurate weather prediction, we are ready to study weather controllability, the other side of a coin. Control is achieved by effective accumulation and combination of modifications or interventions like an orbit control of spacecraft. This session welcomes presentations about understanding of weather sensitivity and predictability, theoretical developments of controllability beyond predictability, weather modification techniques, and other related topics toward weather controllability.

This session covers climate predictions from seasonal to multi-decadal timescales and their applications. Continuing to improve such predictions is of major importance to society. The session embraces advances in our understanding of the origins of seasonal to decadal predictability and of the limitations of such predictions. This includes advances in improving forecast skill and reliability and making the most of this information by developing and evaluating new applications and climate services.
The session welcomes contributions from dynamical models, machine-learning or other statistical methods and hybrid approaches. It will investigate predictions of various climate phenomena, including extremes, from global to regional scales, and from seasonal to multi-decadal timescales (including seamless predictions). Physical processes and sources relevant to long-term predictability (e.g. ocean, cryosphere, or land) as well as predicting large-scale atmospheric circulation anomalies associated with teleconnections will be discussed. Analysis of predictions in a multi-model framework, and ensemble forecast initialization and generation will be another focus of the session. We are also interested in approaches addressing initialization shocks and drifts. The session welcomes work on innovative methods of quality assessment and verification of climate predictions. We also invite contributions on the use of seasonal-to-decadal predictions for risk assessment, adaptation and further applications.

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.

This session will explore the role of moist convection in atmospheric dynamics, with a particular focus on precipitation and cloud formation processes. Key topics will include the fundamental mechanisms driving moist convection, such as latent heat release and vertical motion, and their direct influence on cloud development and precipitation patterns. The session will examine how moist convection affects large-scale atmospheric circulation patterns, including Hadley cells and jet streams, and contributes to the formation and intensification of weather systems like tropical cyclones, monsoons, and convective storms. Additionally, the session will delve into the relationship between moist convection and precipitation, with an emphasis on extreme weather events and their severity. Discussions will also cover the feedback mechanisms between moist convection and other atmospheric processes, such as radiation and surface conditions, highlighting the latest advancements in observational techniques and numerical modeling that enhance our understanding of these dynamics. Finally, the session will address the implications of climate change on moist convection and cloud formation, including potential shifts in regional climate patterns and the frequency of extreme weather events.

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. This year we particularly welcome early results from the recent 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.

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, a consequence of intricate ice particle nucleation, secondary ice production and growth processes, makes 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 (e.g. retrievals), which are useful to characterise cloud properties like extent, emissivity, or crystal size distributions, to clarify formation mechanisms, and to provide climatologies.

(2) Process-based, regional and global model simulations that employ observations for better representation of cold 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.

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. 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
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

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.
- 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.

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.

Precipitation, both liquid and solid, is a central element of the global water/energy cycle through its coupling with clouds, water vapor, atmospheric motions, ocean circulation, and land surface processes. Precipitation is also the primary source of freshwater, while it can have tremendous socio-economic impacts associated with extreme weather events such as hurricanes, floods, droughts, and landslides. Accurate and timely knowledge of precipitation characteristics at regional and 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: 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. Precipitation climatology 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. Precipitation Remote sensing of precipitation (spaceborne, airborne, ground-based, underwater, or shipborne sensors); 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. A special focus will be on international contributions to the exploitation of the international Global Precipitation Measurement (GPM) mission and preparations for new missions, such as Atmospheric Observing System (AOS), EUMETSAT Polar System-Second Generation (EPS-SG), and Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats (TROPICS), as well as new space-borne instrumentation (AMSR-3).

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, weather forecasting, climate modelling, avalanche hazard forecasting, and the remote sensing of snow. The characterization of snow thus demands synergetic 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. 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.

Extreme hydro-meteorological events drive many hydrologic and geomorphic hazards, such as floods, landslides and debris flows, which pose a significant threat to modern societies on a global scale. The continuous increase of population and urban settlements in hazard-prone areas in combination with evidence of changes in extreme weather events lead to a continuous increase in the risk associated with weather-induced hazards. To improve resilience and to design more effective mitigation strategies, we need to better understand the triggers of these hazards and the related aspects of vulnerability, risk, mitigation and societal response.
This session aims at gathering contributions dealing with various hydro-meteorological hazards that address the aspects of vulnerability analysis, risk estimation, impact assessment, mitigation policies and communication strategies. Specifically, we aim to collect contributions from academia, industry (e.g. insurance) and government agencies (e.g. civil protection) that will help identify the latest developments and ways forward for increasing the resilience of communities at local, regional and national scales, and proposals for improving the interaction between different entities and sciences.
Contributions focusing on, but not limited to, novel developments and findings on the following topics are particularly encouraged:
- Physical and social vulnerability analysis and impact assessment of hydro-meteorological hazards
- Advances in the estimation of socioeconomic risk from hydro-meteorological hazards
- Characteristics of weather and precipitation patterns leading to high-impact events
- Relationship between weather and precipitation patterns and socio-economic impacts
- Socio-hydrological studies of the interplay between hydro-meteorological hazards and societies
- Hazard mitigation procedures
- Strategies for increasing public awareness, preparedness, and self-protective response
- Impact-based forecast, warning systems, and rapid damage assessment.
- Insurance and reinsurance applications

Traditionally, hydrologists focus on the partitioning of precipitation water on the surface, into evaporation and runoff, with these fluxes being the input to their hydrological models. However, more than half of the evaporation globally comes back as precipitation on land, ignoring an important feedback of the water cycle if the previous focus applied. Land-use and water-use changes, as well as climate variability and change alter, not only, the partitioning of water but also the atmospheric input of water as precipitation, related with this feedback, 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.

Typically, studies in this session are applied studies using 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 sources of data for atmospheric hydrology and implications for inter-comparison and meta-analysis. For example, observations networks, isotopic studies, conceptual models, Budyko-based hydro climatological assessments, back-trajectories, reanalysis and fully coupled Earth system model simulations.

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 (YOPP, MOSAiC, (AC)3, ISLAS, EUREC4A 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.

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 and the global monsoon circulation to which they belong have profound impacts on water, energy, and food security. Monsoons cause severe floods and droughts as well as undergoing variability on subseasonal, interannual and decadal-to-multi-decadal time scales. In addition to their profound local effects, monsoon variability also causes global-scale impacts via teleconnections.

Monsoons are complex phenomena involving coupled atmosphere-ocean-land interactions and remain notoriously difficult to forecast at leads times ranging from numerical weather prediction (NWP) to long-term climate projections. A better understanding of monsoon physics and dynamics, 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, NWP modelling, S2S and decadal forecasting, and the latest CMIP6 findings to help inform the IPCC AR7. Applications of AI/ML to monsoon studies are also encouraged.

The Mei-yu season, typically occurring from mid-June to mid-July, on average, contributes to 32% of the annual precipitation over the Yangtze–Huai River Valley and represents one of the three heavy-rainfall periods in China. Research on Mei-yu frontal heavy rain has achieved a substantial number of results in international studies over the past few years. With the improvements and refinement of numerical forecasting, the forecasting accuracy for Mei-yu frontal rainstorms has also been continuously enhanced. This session will focus on the scientific field experiments and numerical simulation studies of Mei-yu frontal heavy rain, showcasing how field observations can provide deeper insights into the microphysical characteristics of clouds and precipitation associated with the Mei-yu front. It will also cover how to quantitatively assess the applicability of cloud microphysics schemes in regional models, as well as how to develop cloud microphysics parameterization schemes suitable for forecasting Mei-yu front precipitation. The session expects three topics as follows:
1. Observation experiment and monitoring technology of extreme precipitation;
2. Dynamical origin and multi-scale interactions of Mei-yu front systems;
3. Development of numerical model and new technology for the prediction and projection of extreme precipitation.

Large-scale atmospheric circulation is an essential component of the climate system. Understanding the drivers, variability and the dynamical processes of the large-scale circulation is important for improving future projection of global and regional circulation patterns under anthropogenic climate change, and for predicting the associated impacts on extreme weather and climate events.

This session highly encourages contributions covering the overturning circulation, jet streams, storm tracks, blocking, atmospheric rivers, and related topics.

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" leaving the place to nonlinear circulation features, such as atmospheric blocking.

Recent extreme weather and climate episodes, like the western European drought of winter 2023, summer flooding (e.g. in Germany and Switzerland in 2024), the recurrent and concurrent summer heatwaves or the unforeseen winter cold spells (e.g. in Scandinavia in winter 2023/24), highlight the need to further our understanding of jet streams and of the associated linear and non-linear, planetary and synoptic-scale Rossby wave dynamics in the atmosphere, and of their impacts on 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) The dynamics of propagating or quasi-stationary Rossby waves, of wave breaking, atmospheric blocking, or 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) Exploring the links 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 and/or blocking.
(3) Quantifying model representation of Rossby waves in climate and numerical weather prediction models, including wave propagation and breaking.
(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) Analyzing projected future changes in planetary or synoptic-scale Rossby waves, or in their future connection to weather and climate events.

This session investigates mid-latitude cyclones and storms on both hemispheres. We invite studies considering cyclones in all different stages of their life cycles, from initial generation to the final development, including studies to large- and synoptic-scale conditions influencing cyclones’ growth to a severe storm, their dissipation, and related socioeconomic impacts.
Papers are welcome, which focus also on the diagnostic of observed past and recent trends, long- and short-term natural variability, as well as on future storm development under changed climate conditions. This will include storm predictability studies on different time and spatial scales. The session also invites studies investigating storm related impacts: Papers are welcome dealing with vulnerability, diagnostics of sensitive social and infrastructural categories and affected areas of risk for property damages and loss. Which novel risk transfer mechanisms are currently developed or used? Which novel mechanisms (e.g., adapted re-insurance products) are already implemented or will be developed in order to adapt to future loss expectations under anthropogenic climate change?

Large-scale atmospheric dynamics and synoptic systems are a key driver of near-surface variables (e.g. air temperature, precipitation), their variability and their extremes such as heatwaves, floods, and droughts. Recent regional extreme weather events (e.g. floods and heatwave in Europe in September 2023) underline the 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). 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.

Atmospheric rivers (ARs) are narrow and transient filaments 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. 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
• 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 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.

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.

The field of infrasonic research, the science of low-frequency acoustic waves, has expanded to include acoustic-gravity waves and developed into a broad interdisciplinary field encompassing several academic disciplines of geophysics as well as recent technical and basic scientific developments. The International Monitoring System (IMS) infrasound network for nuclear-test-ban verification and regional infrasound arrays deployed around the globe have demonstrated their capacity for detecting and locating various natural and anthropogenic disturbances. Infrasound and acoustic-gravity waves are capable of traveling up to thermospheric altitudes and over enormous ranges, where the wind and temperature structure controls their propagation. Recent studies have offered new insights on quantitative relationships between infrasonic observations and atmospheric dynamics, opening a new field for atmospheric remote sensing.

New studies using lidar, radar, microwave spectrometer, and mesospheric airglow observations complemented by satellite measurements help better determine the interaction between atmospheric layers and the influence of atmospheric waves on the mean flow. It is expected that further developing multi-instrument platforms will improve gravity wave parameterizations and enlarge the science community interested in operational infrasound monitoring. In a higher frequency range, the infrasound monitoring system also offers unique opportunities to provide, in near-real time, continuous relevant information about natural hazards with high societal impact, such as volcanic eruptions, surface earthquakes, meteoroids, and bright fireballs.

We invite contributions on recent studies characterizing infrasound sources or atmospheric phenomena using complementary technologies. We particularly encourage presentations utilizing acoustic waves to probe the atmosphere at both small and large scales. Results and advances in acoustic propagation modeling, signal processing and machine learning applications are also welcome. Another focus is on derived data products and services for civilian and scientific applications as well as on innovative instrumentation, which also encompasses sensors attached to moving or elevated platforms such as balloons. We also invite seismo-acoustic studies on the coupled Earth’s crust – ocean – atmosphere system and, in particular, on the ionospheric manifestations of physical processes in the ocean and in the solid Earth.

Extreme weather and climate conditions, such as recent events unprecedented in the observational record, have high-impact consequences globally. Some of these events would have been arguably nearly impossible without human-made climate change, and broke records by large margins. Furthermore, compounding hazards and cascading risks are becoming evident. Continuing warming does not only increase the frequency and intensity of events like these, or other until now unprecedented 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 events and their 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 ranging across spatial and temporal scales, and covering compound, cascading, and connected extremes as well as worst-case scenarios and storylines, with the ultimate goal to provide actionable climate information to increase preparedness to such extreme high-impact events.

We invite work addressing high impact extreme events via, but not limited to, observations, model experiments and intercomparisons, climate projections including large ensembles and unseen events, diverse storyline approaches such as event-based or dynamical storylines, 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 such impacts

The session is sponsored by the World Climate Research Programme lighthouse activity on Understanding High-Risk Events.

The climate system is changing rapidly, with some regions experiencing increases in extreme events beyond what is expected from climate model simulations. To improve the accuracy of climate predictions and projections, it is necessary to (1) identify and explain what factors and processes drive observed and predicted climate changes, (2) critically assess how key processes are represented in climate models, (3) understand and explain the predicted signals, which often result from the interaction of multiple drivers, and (4) use this knowledge to calibrate and further develop predictions to provide more reliable and thus useful information to society. In combination, these research activities contribute to building the capability for an integrated attribution and prediction of climate change - a key goal of the WCRP Lighthouse Activity on Explaining and Predicting Earth System Change (EPESC) and the Horizon-Europe project EXPECT.

Progress in integrated attribution and prediction will benefit from combining diverse data sources, such as Earth Observations, and various climate model experiments, including those at very high resolutions. This session invites contributions on advancing integrated attribution and prediction, with a particular focus on annual to decadal timescales, which involves explaining, predicting and constraining climate changes from regional to global scales. Relevant topics include, for example, studies attributing the drivers of specific climate phenomena and extremes such as the atmospheric circulation during the boreal summer and related surface extremes, evaluating climate responses to different forcings and internal variability, correcting biased climate responses e.g. using process-based constraints, providing calibrated prediction and projections of future climate based on these constraints, and methods that exploit a variety of data in combination with novel analysis techniques including Artificial Intelligence.

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 climate system exhibits complex variability across different timescales. Part of this complexity is influenced by the teleconnections, recurring patterns in the atmosphere and ocean that strongly shape the regional climate variability and climate change. However, given the large internal variability and strong external forcings involved, understanding the role of teleconnections in climate variability and change remains challenging. Statistical, dynamical and modelling approaches have provided many insights to date. More recently, the integration of these approaches has developed rapidly, and new data-driven approaches are becoming widespread. This session aims to bring together researchers using any combination of these approaches to explore climate variability, teleconnections across timescales from synoptic scale to long-term change, and in particular, how variability on different timescales is connected. The physical explainability and interpretability of statistical and modelling results as well as the accurate and appropriate use of statistics in physics-centred research are a focus of the session.
We invite contributions that address one or more of the following topics: disentangling variability in teleconnections and their influence on regional climate, dynamics and predictive potential of teleconnections, the influence of large-scale changes in driving future regional climate change, understanding model-observation discrepancies in climate variability and teleconnections.
Studies that employ innovative approaches to bridge statistical analysis and physical understanding are particularly encouraged, including but not limited to machine learning techniques, causal inference methods, storyline approaches, Bayesian methods, and novel diagnostics for teleconnections.

Mountains cover approximately one-quarter of the total land surface on the planet, and a significant fraction of the world’s population lives within, 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 is devoted to showcasing 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. Contributions connected with the TEAMx research programme (http://www.teamx-programme.org/) are encouraged.
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 welcomed are contributions that connect with and address the interdisciplinary objectives of the Elevation-Dependent Climate Change (EDCC) working group of the Mountain Research Initiative ( https://mountainresearchinitiative.org/our-activities/community-led-activities/active-working-groups/elevation-dependent-climate-change/).

Renewable energy has become new sources of electrical power. By their very nature, wind, solar, hydro, tidal, wave and other renewable forms of generation are dependent on weather and climate. Modelling and measurement for resource assessment, site selection, long-term and short term variability analysis and operational forecasting for horizons ranging from minutes to decades are of paramount importance.

The success of wind power means that wind turbines are increasingly put in sites with complex terrain, forests, or coastal and offshore regions that are difficult to model and measure. Major challenges for solar power are notably accurate measurements and the short-term prediction of the spatiotemporal evolution of the effects of cloud field and aerosols. Planning and meteorology challenges in Smart Cities are common for both. For both solar and wind power, the integration of large amounts of renewable energy into the grid is another critical research problem due to the uncertainties linked to their forecast and to patterns of their spatio-temporal variabilities.
We invite contributions on all aspects of weather dependent renewable power generation, including, but not limited to:
• Wind conditions (both resources, siting conditions and loads) on short and long time scales for wind power development, in different environments (e.g. mountains, forests, coastal, offshore or urban).
• Offshore wind development: interaction between atmosphere, sea and wind turbine/wind farms, for both bottom-fixed and floating wind, and its impact on marine environment
• Long term analysis of inter-annual variability of solar and wind resource
• Typical Meteorological Year and probability of exceedance for wind and solar power development
• Wind and solar resource and atlases
• Wake effect models and measurements, especially for large wind farms and offshore
• Performance and uncertainties of forecasts of renewable power at different time horizons and in different external conditions.
• Forecast of extreme wind events and wind ramps
• Local, regional and global impacts of renewable energy power plants or of large-scale integration.
• Dedicated wind measurement techniques (SODARS, LIDARS, UAVs, Satellite etc.)
• Dedicated solar measurement techniques from ground-based and space-borne remote sensing
• Tools for urban area renewable energy supply strategic planning and control
• AI and Machine Learning approaches for weather forecasting and its applications

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

Session aims to delve into the world of fog and dew, exploring the scientific processes governing their formation, interaction, and environmental impact. It will also showcase cutting-edge research across disciplines. The session will cover a wide range of topics, including the following
Fog Types and Processes
Classifications of fog, conditions that lead to fog formation and complex processes that govern fog life cycles, the influence of synoptic systems on fog formation.
Boundary Layer Processes include understanding how factors like temperature inversions, wind, near-surface processes like the Ramdas layer, and stability contribute to fog formation.
Turbulence and Aerosols Role of turbulence in mixing and its impact on fog. Additionally, role of aerosols on fog droplet formation and numerical studies on fog-turbulence and fog-aerosol interactions.
Detection and Forecasting
The advancements in satellite remote sensing techniques to detect and characterise fog.
Importance of observation networks and field experiments for fog study.
Capabilities and limitations of NWP models in forecasting fog. Advancements in high-resolution models and parameterisation schemes; specific studies like DNS or LES will be included.
Challenges and opportunities in incorporating real-time observations through data assimilation and potential of AI and ML techniques to improve fog forecasting.
Fog and Environmental Interactions
Examination of the relationship between fog/dew and air pollution, like fog as a sink for pollutants but aids formation of secondary pollutants through chemical reactions. Mitigation strategies to address the combined impacts of fog/dew and air pollution. Moreover, studies covering fog/dew chemistry will be covered under this topic.
Microphysical and Surface Processes: Fundamental physics governing fog and dew formation, radiative cooling, vapor pressure deficit, and surface properties that influence these processes. The role of land surface characteristics, such as soil moisture, vegetation cover, and heat fluxes in fog formation or dewfall. Moreover recent advancements in surface energy balance models.
Applications Fog and dew harvesting techniques, passive collection methods using specialised meshes. Significance of these techniques in water-scarce regions and discussions on their efficiency.
The session will deepen the understanding of fog and dew, paving the way for future advancements in research, forecasting, and potential applications.

The session invites experimentalists and modelers working on air-land interactions from local to regional scales, in vegetated and/or urban systems. The program is open to a wide range of innovative studies in micrometeorology and related atmospheric and remote sensing disciplines. The topics may include the development of new observational devices, measurement techniques, experimental designs, data analysis methods, as well as novel findings on surface layer theory and parametrization, including local and non-local processes. Theory-based contributions may encompass soil-vegetation-atmosphere transport, internal boundary-layer theories, and flux footprint analyses. Of particular interest are synergistic studies employing experimental data, parametrizations, and models addressing energy and trace gas fluxes (of inert and reactive species) as well as water, carbon dioxide and other GHG fluxes. We focus on addressing 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, coupling/decoupling, stable stratification and night time fluxes, dynamic interactions with atmosphere, and plants (in canopy and above canopy) and soils.

The deposition of reactive nitrogen to terrestrial ecosystems is a major threat to ecosystem integrity and biodiversity in Europe and other regions in the world. Yet, considerable uncertainties in the deposition estimates and underlying processes exist. These uncertainties also affect nature protection policies as well as emission regulation and mitigation strategies. This session welcomes studies investigating atmospheric deposition of reactive nitrogen species such as ammonia and oxidized nitrogen to terrestrial ecosystems. The session will greatly benefit from discussing different experimental approaches, using e.g. micrometeorological methods or deposition samplers, as well as process based and large-scale deposition modelling and the combinations thereof. Next to fundamental research on deposition processes and methods, studies creating the link to impacts and policy implications are especially encouraged, strengthening the connection between science output and societal application.

Ocean-atmosphere chemical flux exchanges have significant impacts on global biogeochemistry and climate. This session focuses on new research in the following areas: air-sea fluxes of greenhouse gases (e.g., CO2, CH4, N2O), atmospheric deposition of nutrients (e.g., nitrogen, phosphorus, iron) and its impact on ocean biological systems, the influence of ocean emissions of reactive gases and aerosols on atmospheric chemistry and climate (e.g., dimethyl-sulfide (DMS), marine organic compounds, halogenated species), and on the important biogeochemistry-climate feedback loops in the ocean-atmosphere system as well as future changes in these fluxes in response to anthropogenic and climate stressors. The session has long-standing links to the Surface Ocean Lower Atmosphere Study (SOLAS; https://www.solas-int.org/) and GESAMP Working Group 38 on atmospheric input of chemicals to the ocean (http://www.gesamp.org/work/groups/38). We welcome submissions from all remit areas of these programs, and from a range of analysis approaches: field measurements, remote sensing, laboratory studies, and atmospheric and oceanic numerical models.

This year we particularly welcome contributions on the following specialist themes:
(a) greenhouse gas emissions and cycling from coastal zones, with particular focus on the impacts of nutrient and pollutant transport across the land-ocean continuum (e.g. via riverine input, glacier meltwater runoff, submarine groundwater discharge), as well as benthic-pelagic coupling for greenhouse gas budgets in regional and global scales; and
(b) the role of the Sea-Surface Microlayer (SML) as a biofilm environment and direct air-sea- interface, and its influence on deposition and emission fluxes of gases, aerosols, and particulates between the ocean and atmosphere.

Covering 70% of the Earth's surface, the sea surface microlayer (SML) is recognized as a critical boundary between the ocean and atmosphere. Its unique position places the SML at the center of various global processes in biogeochemistry and climate science. This session welcomes recent advancements in understanding the SML's distinctive chemical, biological, and physical characteristics, with a focus on understanding the underlying mechanisms of processes. Particular emphasis is given to the SML's function in modulating air-sea exchanges of heat, freshwater, gases, particles, and biota, but also exchange processes between the SML and the underlying bulk water, which are crucial for a more comprehensive understanding.. The concept of the SML as a biogeochemical reactor is also a central theme in the session to highlight the roles of environmental interfaces in marine biogeochemistry. Of further interest is the accumulation of pollutants such as hydrocarbons, microplastics, soot and pharmaceuticals, but also pathogenic microorganisms and viruses. In this context, the formation of (bio)aerosols as well as deposition processes play a role. To advance future studies, new observational, experimental and genomic approaches to the study of SML are particularly welcome. This multidisciplinary session welcomes participants from all research fields interested in the SML and its impact on surrounding environments. The session aims to bring together insights and findings from field observations, laboratory experiments, and models. By exploring the interplay between physical, chemical, and microbiological processes at the ocean-atmosphere interface, we seek to further develop a holistic perspective and foster new collaborations across research disciplines.

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 and impacts relies on developments from multiple disciplines covering both experimental laboratory work, field studies and numerical modelling. In this general session all topics of Aerosol Chemistry and Physics are covered. Contributions from aerosol laboratory, field, remote sensing and model studies are all highly encouraged.

Alongside general contributions, this year we also propose a focus on the increasing uptake and use of tools under the banner of Data Science and AI. Adoption of machine learning can be found across all areas of science, including atmospheric aerosol research. We see increasing use of a range of tools, from computational image tools for improved detection and classification through to development of hybrid numerical models. However we must also recognize the importance of the broader data science ecosystem, from evolving regulations, standards and increased emphasis on data discoverability and provenance. With this in mind we welcome submissions that full under a broad range of atmospheric aerosol applications. This could include, but are not limited to:
- Improved classification of aerosol types from spectral, time-series through to image datasets
- Identification of new processes as a result of ML adoption
- Highlighting new challenges in adopting ML in aerosol research
- Improved understanding of process and parameter sensitivity
- Development of Digital Twins
- Development of hybrid process-ML based aerosol models
- Increased resolution and/or computational efficiency of numerical methods
- New ‘Machine Learning’ ready data repositories
- Use of foundation models and generative AI in atmospheric aerosol research

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 research efforts enhance our understanding of the origin and (trans)formation processes of (secondary) 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 and chamber 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.

Land plants are thought to impact Earth's radiation balance in a number of ways. Plant directly modify the surface albedo, and their aerosol emissions change the aerosol cloud interactions influencing the planetary albedo. In the marine realm photosynthetic organism mediate the emissions of different levels of aerosols, that intern influence the aerosol cloud interactions. The plant-aerosol-cloud interactions vary spatially and temporally on the present Earth. Early in Earth history there were no land plants. Later evolution land plant change both the surface cover and aerosol emissions. Later land plant ecosystems have changes have changed in response to evolution and/or changing continental plate configuration.

At present aerosol-cloud interactions represents the largest uncertainty in climate change assessments. In order to reduce this uncertainty this session aims to bring together researchers interested in accessing the climate relevance of land plants and marine algae in the climate of the past, present and future.

Primary biological aerosol particles span a wide range of sizes from tens of nanometers to up to 100µm. Bioaerosols is a ‘catch all’ term to denote airborne microorganisms (airborne fungi, bacteria, pollen, virus and their constituents). Bioaerosols, or subsets of bioaerosols are sometimes known by other terms such as primary biological aerosol particles (PBAPs), aeroallergens or BioPM. While these particles make a small contribution to the total aerosol number they contribute significantly to the total mass, with biological aerosol accounting for 15-25% of the total aerosol mass burden. 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 detailed speciation suffer from poor time resolution and difficulties in producing atmospheric concentrations. As such, 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; the agricultural health security impacts of pathogenic species; and the efficacy of early warning capabilities for national security and defence.

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, technique validation, laboratory studies, indoor and outdoor ambient observations, the application and development of models, forecasting and nowcasting, exposure assessment and associated health impacts.

Cloud feedbacks are the dominant uncertainty in assessing global and regional climate sensitivity. As such, an improved understanding of the key processes involved in cloud formation, development, and radiative effects will support better representations of these processes in climate models and reduce uncertainty in future climate predictions.
Ice nucleating particles (INPs) and secondary ice production play crucial roles in cloud processes and radiative feedback, influencing weather patterns and climate dynamics. This session explores the intricate interplay between INPs, secondary ice production mechanisms, and their impacts on cloud properties from both observational and modeling perspectives.
We will discuss cutting-edge findings on the sources, distribution, and variability of INPs in different atmospheric conditions. Insights from observational studies, remote sensing techniques, and laboratory experiments will be integrated with advanced modeling approaches to elucidate the complex microphysical and radiative feedback mechanisms.
We then discuss the secondary ice production mechanism and highlight their influence on cloud formation, evolution, and precipitation processes. The session aims to foster discussions on improving our understanding of secondary ice production processes, their representation in climate models, and their implications for regional and global climate variability and change.
Topics covered in this session are:
- Laboratory studies related to ice nucleating particles or secondary ice production
- Ice nucleation processes and characterizing INP in the field
- Modelling of secondary ice production
- Improving parameterizations associated with cloud formation in models – deep convective clouds, mixed-phase clouds, mesoscale convective systems
- Arctic Amplification and the effect of polar clouds on the global climate system

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. Together with other light-absorbing particles, 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 of all aspects of the dust cycle (emission, transport, deposition, size distribution, particle characteristics) with in situ and remote sensing techniques,
(2) numerical simulations of dust on global, regional, and local scales,
(3) meteorological conditions for dust storms, dust transport and deposition,
(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 cryosphere, including also aerosols other than dust,
(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.

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

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
- 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-entry of reusable and discarded objects adds anthropogenic trace gases and aerosols to almost all layers of the atmosphere. The space sector is the only anthropogenic emission source to the middle-to-upper atmospheres where pollutants can persist for decades, leaving a lasting legacy of atmospheric pollution. These pollutants are becoming increasingly ubiquitous due to the recent exponential growth of the space sector, yet there are no regulatory controls targeting these emissions. Quantification of the complex and unique effects on the atmosphere is mired by many uncertainties and data gaps, such as in the chemical composition of exhaust from novel propellants, the resultant evolution during plume afterburning, the locations and trajectories of launches and re-entry, the radiative and chemical kinetic properties of the pollutants, and the physics and chemistry of controlled or uncontrolled re-entry, ablation, and breakup. Meanwhile a lack of openly-available modelling tools is compounded by a scarcity of real-world experiments and observations, and both historical and future impact estimates are hindered by a lack of commercial space activity data or well-supported growth projections. This session invites submissions from all EGU disciplines by representatives in and beyond academia to share planned, current, or ongoing research that provides new knowledge in this area, explores new open-source modelling techniques, or exposes methodological gaps that need to be resolved to inform policies and for a truer determination of the influence of space activity on the atmosphere. We are also interested in innovative methods adopted by researchers focusing on volcanic emissions, geoengineering, and meteors that could be applied to the space sector.

Aeroallergens 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.

In addition to their effects on human health, pollen and fungal spores negatively affect agriculture and forestry, contributing to reduced crop yields and forest health. Moreover, climate change exacerbates these issues, as rising temperatures and increased CO2 emissions disrupt plant life cycles. These changes lead to longer and more intense flowering seasons and shifts in the geographical distribution of certain species, which are both consequences and indicators of climate change.

Given the increasing concerns, there has been a paradigm shift in aeroallergen monitoring techniques. Traditional manual measurements are being replaced by automated in situ measurements, DNA sequencing-based methods, and remote sensing technologies. These advanced approaches do not only provide more accurate information about aeroallergens but also enhance model predictions and forecasts.

In this session, we invite contributions on the detection, analysis, and forecasting of aeroallergens as well as on studies dealing with their impact on climate, the environment and human health.

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
- Observational constraints on aerosol-cloud interactions
- Use of observational simulators to constrain aerosols, clouds and their radiative effects in models
- 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

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 analyses using the RAMIP dataset. We also welcome focused studies 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.

Weather and climate events, such as heat waves, drought, and tropical cyclones, exert high influences on air quality. Meanwhile, two or more weather events may occur simultaneously to form compound extremes, which may exhibit intensified impacts on human health and ecosystem relative to the individual event. This session seeks contributions regarding the mechanistic understanding of the nexus between extreme weather events and air quality, and associated impacts on human health and ecosystem. Abstracts on observations, modeling and projections are all welcomed.

There is a natural partitioning of scientific interest amongst three branches of aerosol research: modeling, in situ measurements, and remote sensing. The community sees enhanced measurement capabilities when these groups interact, and this strengthens the overall scientific impact on climate and air quality research. The Models, In situ, and Remote sensing of Aerosols (MIRA) international working group was formed to facilitate collaborations and improve discussions amongst these fields of study and across regional boundaries. MIRA emphasizes effort where these different aerosol subject areas overlap, and ideal MIRA topics seek collaboration from others. Indeed, many of us are already working across multiple aerosol disciplines, and our work benefits from synergetic access to different areas of expertise. We seek presentations that showcase multidisciplinary work and scientists who are interested in the MIRA concept. More information about MIRA can be found at https://science.larc.nasa.gov/mira-wg/.

Shipping has a significant impact on air quality through particulate matter and gaseous emissions, which serve as precursors to various, often toxic, aerosols. Concerns about human health have driven regulatory measures, such as the IMO-2020 sulphur cap, which has drastically reduced sulphur oxide emissions from ships since January 1st, 2020. While this regulation has been crucial in lowering harmful pollutants, it has also led to a significant reduction in sulphate aerosols, which play a critical role in cloud formation and cloud droplet lifetime. Recent studies suggest that this reduction may contribute to a net positive radiative forcing and climate warming, though the magnitude of this impact remains under debate.

As the shipping industry is poised to significantly lower its carbon footprint over the coming decades, the adoption of low-carbon fuels is expected to alter the landscape of ship emissions, introducing new or different side-pollutants. This demands a detailed understanding of the processes leading to their climate impacts. This session aims to bridge the gap between those focused on reducing shipping emissions and those researching their climate and air quality effects.

We invite contributions focused on ship emission observations and modelling, ship voyage analysis and optimization, assessments of aerosol emissions from maritime low-carbon fuels and research on modelling the radiative forcing, climate, and air quality impact of shipping. Our goal is to foster dialogue among diverse modelling approaches and encourage inter-comparison projects. This will enhance our understanding of the interaction between shipping and climate while providing a comprehensive review of the radiative impacts of anticipated technological advancements in this industry.

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 composition of the upper troposphere and stratosphere 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 modelling 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 introducing recent observations (both in situ and remote sensing) as well as models of various complexity, ranging from comprehensive chemistry climate models to idealized, conceptual models, and theoretical studies. This year, a special focus will be laid on processes in the coupling region of the upper troposphere and lower stratosphere (UTLS), and we especially welcome related contributions from joint research projects (e.g. TPChange).

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.

Aircraft condensation trails (contrails) are currently estimated to contribute a similar effective radiative forcing as all CO2 yet emitted from the aviation sector. They also constitute the ultimate short-lived forcer, with lifetimes estimated in hours and local radiative forcings on the order of several watts per meter squared. This has made them the subject of a recent explosion in interest from the scientific, aviation, and regulatory communities, including ongoing debate regarding potential measurement and regulation of contrail formation alongside aircraft CO2 emissions.

Although there have been several recent in-situ measurement campaigns and significant recent advances in the detection of contrails using remote sensing data, understanding their overall climate effects - as well as the development of effective strategies to mitigate said impacts - requires accurate models of contrail formation and evolution. This is a substantial challenge, given that contrails form at the scale of an aircraft engine exhaust but can spread to be tens or hundreds of kilometers wide. Furthermore there remains relatively little observational data to directly constrain contrails due to the difficulty of directly sampling contrail ice and the high degree of temporal and spatial variability in cruise altitude conditions.

With these concerns in mind, this session aims to bring together the growing community of contrail modellers who are seeking to advance our ability to represent and understand the full lifetime of a contrail and its long term impacts. This includes those who are working on: high-fidelity modelling of contrail formation in the exhaust plume; LES or RANS models of the exhaust plume and contrail; 0-, 1-, 2-, or 3-D models of long-term contrail behaviour; models of regional- and global-scale contrail evolution and climate responses, including potential cloud feedbacks; and studies using new datasets to evaluate the performance of existing contrail models. Particular attention will be given to research using open-source models and data.

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 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 and feedbacks 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.

The Earth Radiation Budget is the global annual mean difference between the incoming solar and reflected solar and emitted terrestrial radiation. It is a small number coming for the difference of two comparably large numbers (TSI and TOR), making its estimation particularly challenging. A positive Earth Energy Imbalance corresponds to the heat continuously accumulated in the Earth's climate system – mainly the oceans, and which will - with a time delay - cause the global warming of the surface and the atmosphere. From the analysis of in-situ observations– mainly based on ARGO, from 2006 to 2020 the mean EEI is 0.76 +/- 0.2 Wm-2, to be compared to a mean EEI of 0.48  0.1 Wm-2 from 1971 to 2020. The exact knowledge of the EEI and its trend is key for a predictive understanding of global warming and assessing the efficiency of global carbon reduction policies. Up to now, heat content measurements of the ocean, land, and atmosphere are used to determine its absolute value. While these in-situ measurements have a great potential, their sampling and trend uncertainty is - despite great improvements over the recent years - not perfect. To determine the EEI with higher accuracy and stability, independent measurement approaches are required. In this session we invite contributions on existing and new measurement concepts with an emphasis on space observations, but also welcome ground-based and in-situ measurements. We also invite modeling efforts that help to better determine the energy storage in the Earth's system and the terrestrial outgoing radiation.

Aerosols significantly influence the Earth’s climate system, atmospheric chemistry, and air quality, making their study crucial in polar, remote, marine, and high-altitude environments. These regions play a crucial role in comprehending the intricacies of global climate systems and atmospheric processes due to their unique atmospheric conditions. Understanding how aerosols grow, transform, and are eventually removed from the atmosphere is crucial for refining climate models. Despite their importance, aerosol properties, sources, and transformations in these regions are poorly understood due to limited observational data caused by logistical challenges, harsh conditions, and limited accessibility. This proposal highlights the need for field campaigns to address the data gap, focusing on recent expeditions to the Arctic, Antarctic, Himalayas, and other remote marine and high-altitude regions. The session will cover the following topics:
• Recent field campaign results that use ground, ship-based, and airborne measurements. This includes cutting-edge measurement techniques, such as UAVs, balloon-borne sensors, and real-time automated ground-based systems, newly established research infrastructures which enable high-resolution data collection in extreme environments.
• Use of field data in improving satellite retrievals and models simulating aerosol transport, atmospheric processes, and interactions with clouds and radiation.
• The physical and chemical composition of aerosols and their precursors, investigating the range of chemical species present in these regions and their roles in global atmospheric processes.
• The mechanisms driving aerosol generation, including the complex interactions between air-sea, air-snow interfaces, meteorology, and chemical processes that lead to emissions of trace gases and volatile organic compounds.
• By fostering collaboration and knowledge exchange, this session aims to advance the understanding of aerosol impacts in these fragile regions, contributing to efforts to mitigate climate change globally.

Remote sensing of clouds and aerosols is of central importance for studying climate system processes and changes. New generations of active sensors (EarthCare), passive multi-angular polarimeters (PACE/SPEX and PACE/HARP-2, 3MI, CO2M MAP etc.) and single viewing instruments (hyperspectral Sentinel 5P/5/4, OLCI and SLSTR on Sentinel 3), will bring aerosol and cloud characterization on a new level of possibilities. This will essentially boost our understanding of the physical/chemical processes in the atmosphere, specifically aerosol-cloud interactions. Nevertheless, till now, the number of challenges and unsolved problems remain in remote sensing algorithms and their applications.

This session is aimed at the discussion of current developments, challenges and opportunities in aerosol/cloud characterization and aerosol-cloud interaction studies, using active and passive remote sensing systems. We invite submissions of theoretical, methodological, and empirical studies to advance aerosol/cloud remote sensing and to understand better aerosol-cloud interactions and their effect on climate.

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, GOSAT-GW, and MethaneSAT 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, OCO-2/3, S5P, EMIT, Carbon Mapper, GHGSat, EMIT), upcoming and planned missions (e.g., CO2M, MicroCarb, Merlin, GOSAT-GW, MethaneSAT), 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.

A constellation of geostationary satellite ultraviolet-visible (UV-VIS) spectrometers with air quality related trace gas and aerosol observational capabilities will soon be in orbit forming a Geo-Ring. These include Geostationary Monitoring Spectrometer (GEMS) launched in January 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 to be launched in 2024 by European Space Agency over Europe. Both GEMS and UVN have operational continuity and for TEMPO, NOAA’s GeoXO atmospheric composition instrument (ACX) will be an operational follow-on. A very successful demonstration of tropospheric air quality observational capability by Ozone Monitoring Instrument (OMI) and Tropospheric Monitoring Instrument (TROPOMI) in Low Earth Orbit laid the foundation for similar instruments in geostationary orbit, expanding the observations from daily to hourly time scales. 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 TROPOMI 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 along with international collaborations.

Cities are hotspots for the emissions of air pollutants and greenhouse gases from traffic, industry, household heating and energy production. Air pollution impacts can be cumulative or episodic and may be exacerbated during heat waves, and greenhouse gases are often co-emitted with air pollutants. These relationships make cities both a major driver of climate change, and the locus of many harmful climate impacts. Urban air quality and the effect of policy measures are a challenge to monitor with traditional fixed stations or with models, because of the extreme variability in the cities’ geometry and emission patterns.

This session intends to bring together researchers of urban air quality and greenhouse gases. We invite submissions on topics related to urban air quality, heat stress, urban carbon budgets, and air pollution impacts including health. Topics may include sensor networks, personal monitoring, airborne observations, high spatial and temporal resolution model approaches, downscaling, source apportionment, isotopic source attribution methods, atmospheric processes, mechanisms for air quality deterioration, biogenic and anthropogenic precursors, allergens, community and personal exposure quantification, and air pollution effects.

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 on aerosols.

We welcome presentations based on studies analysing current and future
satellite missions, in particular Sentinel 5P, GEMS, and TEMPO,
inter-comparisons of different remote sensing measurements dedicated to
tropospheric chemistry sounding and/or analyses with ground based
measurements and chemical transport models.

The aim of this general session is to bring together the scientific community within air pollution modelling. The focus is ongoing research, new results and current problems related to the field of modelling the atmospheric transport and transformation of air pollutants and precursors on global, regional and local scales.

All presentations covering the research area of air pollution modelling are welcome, including recent model developments, applications and evaluations, physical and chemical parameterisations, process understanding, model testing, evaluation and uncertainty estimates, emissions, numerical methods, model systems and integration, forecasting, event-studies, scenarios, ensembles, assessment, machine learning, etc.

Source apportionment studies of air pollution aim to determine the sources of ambient particulate pollution, volatile organic compounds and other gases in the atmosphere. Receptor-oriented models (RMs) have become increasingly popular source apportionment methods among the research community and environmental protection agencies in the past two decades. RMs are designed to identify and quantify the measured mass of an atmospheric pollutant at a given site (the receptor site) to its potential emission sources by applying multivariate analysis to solve a mass balance equation. The results of RMs on atmospheric species are essential to policymakers for designing more effective air quality management strategies to reduce the health and environmental impacts of air pollution. This session aims to discuss case studies on the application of RMs as well as improvements and new methodologies on source apportionment of air pollution.

Despite the decline in the levels of many air pollutants due to the existing policies, air pollution remains associated with millions of premature deaths worldwide, including in Europe. A significant portion of the global urban population, including Europeans, has lived in areas with consistently unhealthy levels of particulate matter with an aerodynamic diameter smaller than 2.5 micrometers (PM2.5) and nitrogen dioxide.

Transportation plays a crucial role in the global distribution of food, materials, energy, and more. However, all transport sectors are substantial emitters of gaseous and particulate air pollutants. The influence of transport sectors on harmful ambient PM2.5 is not well understood, necessitating improved scientific understanding and evidence to justify policies and develop tools for policy implementation. This requires extensive emissions studies under real-world conditions, far beyond those used for the current emission standards. Additionally, emerging non-exhaust emissions (e.g. brake wear and tire microplastics) present new challenges.

The previous assumption that primary organic aerosol (POA) emissions are chemically inert has dramatically changed in the last decade. 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. Furthermore, it is now clear that large fractions of volatile organic compounds (VOCs), inorganic secondary aerosol precursors, as well as secondary aerosol formation from those have been neglected in most past emission studies and consequently are not explicitly included in the current emission inventories.

This session invites interdisciplinary contributions (experimental and/or theoretical) ranging from characterization of emissions related to various types of transport, including emerging non-exhaust emissions (e.g. microplastics), to their atmospheric transformations, and potential impacts on climate and health. Contributions will span from fundamental studies to real-world evaluation and mitigation of transport emissions, aiming for a better description of air quality in different regions, particularly in high-impact zones.

Air pollution remains a pressing global issue, prompting nations worldwide to implement various mitigation strategies, often targeting specific pollutants such as particulate matter. While these strategies are crafted with the best intentions, they sometimes yield unwanted effects, including alterations in atmospheric chemical compositions leading to phenomena like ozone increase or unforeseen climate impacts.

This session aims to shed light on the unintended consequences of air pollution mitigation strategies, focusing on the changes in chemical composition induced by these strategies. We invite contributions that delve into the observational data, modeling approaches, and projections of future changes to better understand the full spectrum of effects stemming from pollution control measures.

By fostering a discussion grounded in rigorous scientific analysis, we hope to pave the way for more holistic and effective strategies in the future, balancing the urgent need for pollution reduction with a deep understanding of potential unwanted effects.

We welcome submissions that employ a range of research methods including, but not limited to, observational studies and modeling to forecast future changes, encouraging a multidisciplinary approach to a complex issue.

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.

The weather and atmospheric composition (AC) are closely related. Still, Numerical Weather Prediction (NWP) from from the short-range to the seasonal range often only apply simplified presentations of aerosols, greenhouse gases and reactive gases, and NWP and AC forecasting is operated independently. However, 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.

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 NWP from short timescales to seasonal scales due to feedbacks between aerosols, chemistry and radiation and cloud physics,

b) Parameterization of weather-composition feedbacks in radiation and cloud physics,

c) Impact of the uncertainty of meteorological simulations on AC predictions,

d) Advancements in designing and developing operational coupled NWP-AC prediction systems,

e) Satellite retrievals of meteorological variables in the presence of aerosols,

f) Data assimilation developments for AC and NWP,

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 predication 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.

Agricultural activities are one of the major contributors to trace gases in the atmosphere. Besides the contribution to methane (CH₄), nitrous oxide (N₂O), ammonia (NH₃), ground-level ozone (O₃), and various volatile organic compounds (VOCs) are triggered by agricultural activities. These trace gases play significant roles in biogeochemical cycles, affecting air quality and interplaying with climate change. Understanding the dynamics of the source and sink processes of these trace gases—from agricultural soils, crops, and the impact of diverse management practices—is essential for developing effective strategies or practices to mitigate their environmental impact.
This session, " Agricultural Trace Gas Dynamics and Air Quality: Innovative Approaches and Emerging Insights," aims to showcase the latest research and technological advancements in measuring and modeling trace gas exchanges and concentrations within agricultural ecosystems.
The session will welcome the following topics, but not limited to, (1) the impact of different agricultural management practices, such as tillage, mineral/organic fertilization, irrigation, crop rotation, and livestock management, on trace gas concentrations, emissions and depositions from a range of agroecosystems across the globe; (2) cutting-edge methodologies, such as ecosystem-scale monitoring, automated chamber systems, remote sensing technologies, and novel analytical tools for detecting VOCs and other trace gases; (3) the use of state-of-the-art modeling techniques, including artificial intelligence and machine learning, to extrapolate and predict gas dynamics patterns under various environmental and management scenarios; (4) challenges and opportunities associated with reducing the environmental footprint of agriculture.
We seek to bring together researchers, policymakers, and industry practitioners, especially the early career researchers, to join and contribute their fresh perspectives and ideas to this important discussion. Expected outcomes include fostering new collaborations, identifying research gaps on agricultural trace gas management and the challenges of climate change and air quality, and developing actionable recommendations for sustainable agricultural practices that may improve soil health, air quality, and global food security.

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 in environments as different as the polar troposphere during the springtime ozone depletion events, the boundary layer over salt lakes, and volcanic plumes. There is strong evidence that halogens play a spatially even wider role in the marine boundary layer and free troposphere for ozone destruction, changes in the ratios of OH/HO2 and NO/NO2, destruction of methane, in the oxidation of mercury and in the formation of secondary aerosol. There are indications that both, oceanic sources as well as the chemistry of halogens and volatile organic compounds (VOCs) and oxygenated VOCs (OVOCs) in the tropics are linked with potential implications not only for the photochemistry but also the formation of secondary organic aerosol (SOA). More recently, marine emissions of active halogens have been linked to potential impacts on oxidants loading in coastal cities. Finally, bromine and iodine are also being proposed as proxies of past sea ice variability.

We invite contributions in the following areas dealing with tropospheric halogens on local, regional, and global scales:

- Model studies: Investigations of the chemical mechanisms leading to release, transformation and removal of reactive halogen species in the troposphere. Studies of consequences of the presence of reactive halogen species in the troposphere.

- 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 halogen species.

- Field experiments and satellite studies: Measurements of inorganic (X, XO, HOX, XONO2, ..., X = Cl, Br, I) and organic (CH3Br, CHBr3, CH3I, RX, ...) reactive halogen species and their fluxes in the troposphere with in situ and remote sensing techniques.

- Measurements and model studies of the abundance of (reactive) halogen species in volcanic plumes and transformation processes and mechanisms.

- All aspects of tropical tropospheric halogens and links to (O)VOCs: their chemistry, sources and sinks, and their impact on local, regional, and global scales.

Atmospheric radicals (OH, HO2, RO2, NO3, and halogen oxides) drive the oxidation of trace gases, promoting secondary pollution formation and influencing the climate. Understanding the sources (reactive species, e.g. HCHO, HONO, ClNO2 etc.) and fate (unimolecular and bimolecular chemical reactions, the later involving primary pollutants and CH4) of radicals is fundamental to tackle regional pollution and climate change. Measuring and modelling radicals is important but extremely challenging due to their low concentration, high reactivity and the complexity of reactions that they initiate.

This session invites results relating to radical measurements and modelling including:

1. The development of different techniques for radical detection and quantification, their precursors and intermediates species;

2. The adaption of instruments to different platforms (ground, mobile, shipborne, airborne, etc.);

3. Quality assurance (e.g. calibration procedures, inter-comparison of different techniques);

4. Model development (e.g. new chemical reactions/mechanisms, new model configuration, uncertainty analysis);

5. The implementation of radical measurements and modelling in the field and in chamber studies.

This session will concentrate on new scientific advances and technological progress concerning research in laboratory studies and with atmospheric simulation chambers like those in the European Infrastructure ACTRIS. Expected contributions comprise novel results in e.g. atmospheric chemical kinetics and modelling mechanisms, photophysical and photochemical processes, or aerosol formation and characterization. The focus of studies should be on new experimental developments, innovative enabling technologies and results of experiments that allow new knowledge for atmospheric science to be acquired.

The substantial uncertainty surrounding regional and global anthropogenic climate change is largely due to our limited understanding of molecular-scale processes that govern atmospheric systems. These processes critically influence cloud properties and their climate impacts by modulating particle formation and growth. The atomistic properties of individual aerosol particles, their interactions with surrounding vapor-phase molecules, and the transport processes within the particle phase occur on temporal and spatial scales that are accessible through only a few specialized techniques. Among these, molecular simulations—such as molecular dynamics and Monte Carlo methods—and single-molecule experiments stand out for their uniquely high spatial and temporal resolution. Depending on the system, a variety of approaches are used—ranging from classical and reactive force fields to ab initio methods, with recent advances in machine learning further enhancing their capabilities. These approaches effectively complement traditional experimental and modeling techniques, and their recent adoption in characterizing molecular-scale properties is driving the emergence of a new interdisciplinary field at the intersection of molecular modeling and aerosol science.

We invite contributions that apply single-particle or molecular-scale approaches to investigate aerosol properties—such as composition, structure, phase state, and shape—and processes critical to understanding the climate and health effects of aerosols. These processes may include new particle formation, cloud droplet and ice nucleation, and chemical reactions.

Wildfires emit vast amounts of trace gases and aerosols that significantly alter atmospheric composition, impact air quality, and influence climate dynamics. These emissions include photochemically reactive compounds that could modify tropospheric ozone levels, degrading air quality in both immediate and distant regions downwind. Furthermore, wildfire-generated aerosols affect solar radiation, modify cloud formation, and serve as sites for heterogeneous chemical reactions. Understanding the intricate chemistry within wildfire plumes—ranging from emission sources to long-range transport over continents—is crucial for improving predictions of air quality and assessing the broader environmental and health impacts. This session will focus on recent research exploring the chemical and physical processes occurring within wildfire plumes, considering both short- and long-range transport dynamics. Contributions that investigate the interaction of wildfire smoke with meteorological systems, the role of plumes in altering air quality across regions, and the potential for climate feedback are particularly encouraged. We welcome studies utilizing field measurements, satellite observations, and advanced computational models to improve our understanding of the impacts of wildfires on air quality, climate, and public health in the context of the increasing frequency and intensity of these events worldwide.

The Paris Agreement on Climate sets the international objective of reducing greenhouse gas (GHG) emissions to keep climate warming well below two degrees. However, quantifying past and present GHG emissions and sinks and predicting their future remains a substantial challenge. This challenge is primarily due to the high level of uncertainties in observing and modeling these GHG fluxes at regional to global scales. Thus, achieving climate and emission reduction targets requires a substantial improvement in our scientific ability to estimate the budgets and trends of these key major greenhouse gases (CO2, CH4 and N2O).

This session aims to bring together studies that seek to quantify past, present, and future global and regional budgets, trends and variability of major GHGs, as well as studies that contribute to understanding the key drivers and processes controlling their variations. We welcome contributions using a variety of approaches, such as emissions inventories, field and remotely sensed observations, terrestrial and ocean biogeochemical modeling, earth system modeling, and atmospheric inverse modeling. We encourage contributions integrating different datasets and approaches at multiple spatial (regional to global) and temporal scales (from past over the present and to the future) that provide new insights on processes influencing GHG budgets and trends in the past and future.

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) allow attribution of emissions to specific sources and / or (4) methods for upscaling measurements into inventories and creating policy relevant datasets.

Atmospheric measurements of greenhouse gases (GHGs) are routinely incorporated into atmospheric chemistry transport modelling systems to estimate sources and sinks at various temporal and spatial scales (the so called ‘top-down’ approach). Top-down approaches are important as they provide independent emission estimates that are consistent with the observed changes in the atmosphere. However, temporal variations in GHG mixing ratios alone only provide a weak constraint (if at all) on the sources. Information on the contribution from specific sources and processes is vital to aid effective and timely policy for mitigating emissions. The attribution of atmospheric GHG mixing ratio changes to anthropogenic or natural sources, and to source sectors, can be aided by the measurement and interpretation of isotope ratios of the GHG (e.g. stable isotopes of CH4, N2O or radio-carbon for CO2) or of gaseous tracers that are correlated with sources or sinks of the target pollutant (e.g. atmospheric potential oxygen - APO for CO2 or ethane for CH4).

This session invites contributions from the community working on the use of isotope ratios and other tracers in understanding the sources / sinks of GHGs to the atmosphere. This includes but is not limited to:
- Advances in analytics for GHG isotope ratios or tracers including developments in metrology, e.g. reference materials or methods, to improve sustainability of monitoring,
- Incorporation of isotope or trace gas measurements into models for improved understanding of the sources and/or sinks,
- Studies contributing data on GHG isotope ratio source signatures or tracer/target species emission factors.

Accurate and precise, long-term measurements of greenhouse gas (GHG) concentrations were an original cause for concern linking human activities to rapid, and so far, unceasing rise in global GHG concentrations. The resulting increases in global temperatures, sea-level, glacial retreat, and other negative impacts are clear. In response to this evidence, nations, states, and cities, industries and individuals have been accelerating GHG emission reduction and other mitigation efforts while working towards equitable development and environmental justice. Research advances have shown that GHG measurements and analyses are much more than merely harbingers of global warming. The urgency, complexity, and economic implications of the needed GHG emission reductions and other climate action demand strategic investment in science-based information for planning, implementing, and tracking emission reduction policies and actions. Several national and international efforts seek to enhance the capacity of nations, states, cities, and industries to target emissions reduction opportunities and track progress towards their goals. Success depends on the availability of measurements of atmospheric composition, GHG fluxes, and emission activity data in key GHG emission source regions and relies on a multi-tiered observing strategy involving satellite, aircraft, and surface-based measurements, as well as innovative data mining and analysis methods.

Since EGU18, this session has been a showcase for how scientific data and analyses are transformed into actionable information services and successful climate solutions for a wide range of user-communities. These methodologies must have the required temporal and granular details to target and track explicit emission activity where climate action is achievable.

We seek presentations from researchers, inventory compilers, government decision and policy makers, non-government and private sector service providers showing the use and impact of science-based methods of detecting, quantifying, and tracking GHG emissions, and, where possible, the resulting climate mitigation. These methods can involve direct-detection, inverse-modeling, and AI/ML data fusion/mining of statistical and observational activity data, as well as hybrid combinations of all these approaches.

With the atmosphere serving as an integrator for surface-atmosphere exchange processes across scales, monitoring and interpretation of atmospheric greenhouse gas (GHG) signals provides fundamental information on carbon, energy and water fluxes from natural and anthropogenic sources. Combining observations with modeling frameworks in process-based studies can reveal key mechanisms and drivers governing carbon-climate feedback processes, generating vital information to predicting their future evolution in a changing climate.
This session focuses on modeling frameworks (top-down and bottom-up) that investigate GHG exchange processes using observational platforms such as, localized surface networks (e.g. ICOS Atmosphere and Ecosystem, Fluxnet, NOAA,…), aircraft campaigns (e.g. MAGIC, COMET, ), active and passive remote-sensing missions (e.g., ECOSTRESS, OCO-2/3, TROPOMI, GOSAT).
We invite contributions on: 1) estimation of GHG budgets from global to local scales using inverse and direct methods (e.g. eddy-covariance fluxes, fossil fuel inventories, vegetation modeling); 2) examination of the role of errors (e.g. atmospheric transport, measurement errors) on estimated fluxes and associated GHG budgets; 3) innovative use of remote sensing (e.g. SIF), isotopes (e.g. 14CO2, 13CH4), & novel atmospheric tracers (e.g. NOx, carbonyl sulfide, APO) to improve attribution of carbon fluxes to specific processes, and 4) Observing System Simulation Experiments and Machine Learning approaches targeting the optimization of observing system constraints required to advance our understanding of the carbon cycle and carbon-climate feedbacks.

Carbon dioxide, methane and nitrous oxide emissions are the primary greenhouse gases (GHGs) driving climate change and severely impacting the environment. It is essential to first control and reduce these emissions, and then implement novel engineering techniques such as carbon dioxide, methane capture, destruct and sequestration to further decrease their atmospheric levels. This session aims to connect science-based measurements, engineering approaches, industrial measurement-based studies and policy to provide an environment for exploring the potentials for reducing, destructing and storing emissions and atmospheric greenhouse gases abundances. Measurement-based emission quantification methods are key due to the EU Methane regulation and OGMP2.0 (level 5 = site level) for emission reduction regulation. Top-down and bottom-up emission quantification reconciliation is core of efforts for framing the emissions rates in well order; i.e. measurements, monitoring, reporting and verification.

Measurement-based methods are crucial for gaining a better understanding of emission sources, which can inform policymakers and engineers in developing relevant policies and engineering solutions to address both anthropogenic and natural emissions. While greenhouse gas emission sources are known, accurately quantifying their emissions remains a challenge. For this session abstracts are invited from studies focusing on campaign planning strategies, challenges, measurement-based studies, emission reduction cases, engineering techniques for capturing or storing emissions, the impact of legislation on emission reduction, flux-inversion modelling, integrations between methods and the relationship between GHG emissions and health.

This session welcomes contributions that utilize multi-scale observational data to enhance emission estimates, with a specific focus on methodologies, case studies, and implications for climate change mitigation. Researchers from academia and industry, policymakers, and practitioners are encouraged to share their findings and insights on the use of advanced automated and non-automated observational techniques to improve our understanding, management and engineering of GHG emissions from onshore and offshore sources.

Atmospheric mercury (Hg) presents significant analytical challenges due to its ultra-trace concentrations, complex behavior and diverse sources. This session addresses critical advancements in the determination of atmospheric mercury, with a focus on speciation, isotopic fingerprinting, and modeling. Accurate mercury speciation is essential for understanding the distinct roles of elemental, particulate-bound, and reactive gaseous mercury in atmospheric chemistry and deposition processes. New advanced techniques are needed for precise Hg speciation, enabling researchers to distinguish between different forms of mercury and their respective environmental impacts. Isotopic fingerprinting of mercury provides valuable insights into the sources and transformation processes of mercury in the atmosphere. Utilizing cutting-edge methods, like multi-collector inductively coupled plasma mass spectrometry, mercury emissions can be tracked to their origins and understand the isotopic fractionation that occurs during atmospheric transport and deposition. This approach enhances our ability to identify anthropogenic and natural sources of mercury and track its movement through the environment. Integrating speciation and isotopic data into atmospheric models is a key focus of this session. Environmental models aim to improve predictions of mercury distribution and its environmental impacts, offering a comprehensive understanding of mercury in the atmosphere. By combining detailed chemical and isotopic information with advanced modeling techniques, the fate and transport of mercury in the environment can be better predicted, thus informing policy decisions and mitigation strategies. Accordingly, this session aims to provide a comprehensive overview of current methodologies, challenges, and future directions in atmospheric mercury research. The aim is to address the complex analytical challenges of mercury determination and contribute to the development of more effective strategies for managing mercury pollution on a global scale. Participants will gain insights into the latest advancements in mercury speciation, isotopic fingerprinting, and modeling, as well as the practical applications of these techniques in environmental monitoring and assessment.

Molecular hydrogen is gaining global attention as an alternative to fossil fuels, with the potential to significantly reduce carbon dioxide emissions, other greenhouse gases, and air pollutants. Although hydrogen itself is not a greenhouse gas, its chemical oxidation can affect greenhouse gases like methane, ozone, and stratospheric water vapor. The uncertainties on the climate impact of hydrogen are large, because the overall budget of atmospheric hydrogen is less understood. Sources of hydrogen in the atmosphere include both direct emissions and oxidation by volatile organic compounds in the atmosphere. Hydrogen is removed by consumption of bacteria in soils and by oxidation of OH in the atmosphere.
This session invites contributions aimed at enhancing our understanding of the hydrogen budget and the potential impacts of increased hydrogen use. Areas of interest include: utilizing observations of hydrogen sources and sinks; quantifying the indirect climate effects of hydrogen emissions on methane, ozone, stratospheric water vapor, and aerosols; measuring and quantifying hydrogen leakages; and exploring scenarios of future hydrogen economies, including the associated co-benefits of reducing fossil fuel emissions for both the climate and environment.

Given the critical role of hydrogen (H₂) in the global energy transition to mitigate climate change, understanding its biogeochemical cycle becomes crucial. H2 emissions from leakages, venting, and incomplete combustion can alter atmospheric chemistry and affect Earth’s radiative balance. Despite recent advances, our knowledge of the H₂ biogeochemical cycle remains limited. This session will feature cutting-edge research on the global H₂ cycle, spanning experimental and theoretical approaches of H₂ biogeochemistry, as well as top-down and bottom-up assessments of H₂ sources and sinks. We invite contributions that examine the H₂ budget across various spatial and temporal scales and also encourage studies that assess the social, environmental, and climatic implications of increased H₂ usage.

The polar climate system is strongly affected by interactions between the atmosphere and the cryosphere. Processes that exchange heat, moisture and momentum between land ice, sea ice and the atmosphere, such as katabatic winds, blowing snow, ice melt, polynya formation and sea ice transport, play an important role in local-to-global processes. Atmosphere-ice interactions are also triggered by synoptic weather phenomena such as cold air outbreaks, polar lows, atmospheric rivers, Foehn winds and heatwaves. 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 and impact on the land ice and sea ice through interactions with radiation,
Presentations including new observational (ground and satellite-based) and modelling 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 welcomed.

This session is intended to provide an interdisciplinary forum to bring together researchers working in the areas of high-latitude meteorology, atmospheric chemistry, air quality, biogeochemistry, boundary layer physics, cloud microphysics, surface radiative processes, oceanography, sea ice and climate.

The emphasis is on the role of boundary layer processes that mediate exchange of heat, momentum and mass between the Earth's surface (snow, sea-ice, ocean and land) and the atmosphere 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 in the polar regions and their teleconnections with mid-latitude weather and climate.

It is expected that the recent implementation of long-term and new measurements from pan-Arctic networks and recent field campaigns (e.g. MOSAiC, ALPACA, ARTofMELT, POLAR CHANGEand modeling efforts, e.g. within CRiceS and PolarRES, will help diagnose large-scale and local processes as well as the coupling between local and large-scale dynamics and their impacts on climate, health and ecosystems.

We encourage submissions such as (but not limited to):
(1) External controls on the boundary layer such as clouds, radiation and long-range transport processes
(2) Results from field programs, and routine observatories, insights from laboratory studies, and advances in modeling and reanalysis,
(3) Use of data from pan-Arctic and Antarctic observing networks,
(4) Surface processes involving snow, sea-ice, ocean, land/atmosphere chemical and isotope exchanges, and natural aerosol sources
(5) Studies on atmospheric chemistry (aerosols and trace gases) and air pollution during polar winter
(6) The role of boundary layers in polar climate change and implications of climate change for surface exchange processes, especially in the context of reduced sea ice, wetter snow packs, increased glacial discharge and physical and chemical changes associated with an increasing fraction of first year ice and increasing open water.
(7) Surface energy budget of the coupled system, including contributions of ABL-dependent turbulent fluxes, clouds and radiative fluxes, precipitation and factors controlling snow/ice albedo.
(8) Sea ice dynamics and thermodynamics, e.g. wind driven sea-ice drift, snow on ice;
(9) Upper ocean mixing processes.
(10) Sea ice biogeochemistry and interactions at interfaces with sea ice.

Polar regions are experiencing rapid environmental changes that have profound impacts on global climate. Aerosols, clouds, and biogeochemical processes within the sea ice and ocean in these regions play a critical role in regulating the Earth’s energy balance, influencing weather patterns, and driving feedback mechanisms that affect global climate dynamics. This session aims to bring together researchers investigating the complex interactions between aerosols, clouds, and sea ice/ocean biogeochemistry in the Arctic and Antarctic.

We invite contributions that explore sources, transport, and transformation of aerosols; the formation, properties, and impacts of polar clouds; the impact of atmospheric physics and boundary layer dynamics on aerosols and clouds; and the biogeochemical processes in sea ice and ocean that influence and are influenced by these atmospheric components.

Key topics of interest include, but are not limited to:
- Aerosol-cloud interactions and their influence on cloud microphysics, radiative properties, and precipitation in polar environments
- The impact of natural and anthropogenic aerosols, including sea salt, mineral dust, biological particles, black carbon, and organic aerosols, on polar climate and ecosystem processes
- The influence of atmospheric physics and boundary layer dynamics on polar aerosol and cloud properties
- Sea ice and ocean biogeochemical cycling in polar regions, including the roles of marine and terrestrial sources, and the feedbacks between aerosols, clouds, and surface processes
- Advances in observational and modeling techniques to improve our understanding of aerosol and cloud dynamics in polar regions
- The implications of polar aerosol-cloud interactions for global climate models and predictions

By fostering interdisciplinary dialogue, this session aims to advance our understanding of the interconnectedness of aerosols, clouds, and biogeochemistry in polar regions and their broader climate implications. We welcome submissions from researchers at all career stages and encourage collaboration across disciplines to address these critical scientific challenges. Studies utilizing field observations (especially from observations from recent field campaigns, such as MOSAiC and ARTofMELT in the Arctic and MISO in the Southern Ocean), remote sensing, laboratory experiments, and numerical modeling (on a process, regional or climate level) are invited.

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.

Understanding the scale-dependent interactions of the atmosphere and the mountain cryosphere are critical for estimating the response of snow and ice to ongoing climate change. A lack of observational data and/or process understanding in high mountain regions creates substantial uncertainties with respect to future cryospheric change and how it may react to climatic variability, climatic extremes and long-term warming. Atmospheric dynamics in mountain regions are complex and further complicated by a rapidly changing cryosphere which may not be appropriately represented in atmospheric models used to estimate the mountain surface energy balance and mass changes of snow and ice.

This session aims to address the current challenges, methodological approaches and wider relevance of observing and modelling cryosphere-atmosphere interactions at varying scales in mountain environments around the world. We welcome contributions including, but not limited to, the characterisation and quantification of glacier/snow boundary layer exchanges, observations and modelling of katabatic winds and turbulent structures over the mountain cryosphere, the role of glaciers in valley circulation systems, the cryosphere and elevation-dependent warming, advances in atmospheric modelling and/or meteorological downscaling over high elevation snow and ice or the representation of glacier meteorology in numerical weather models or models of glacier energy/mass. We particularly welcome submissions related to the modulating role of cryospheric boundary layers in the face of ongoing climate changes in mountain regions.

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.

Fire is the main terrestrial ecosystem disturbance globally and a critical Earth system process. Fire research is rapidly expanding across disciplines, highlighting the need to advance our understanding of how fire interacts with land, atmosphere and society. This need is growing as fire activity increases in many world regions. This session invites contributions that investigate the role of fire within the Earth system across any spatiotemporal scale, using statistical (including AI) and process-based models, field and laboratory observations, proxy records, remote sensing, and data-model fusion techniques. We strongly encourage abstracts on fire's interactions with: (1) weather, climate, atmospheric chemistry, and circulation, (2) land physical properties, (3) vegetation composition and structure and biogeochemical cycle, (4) cryosphere elements and processes (such as permafrost, sea ice), and (5) human health, land management, conservation, and livelihoods. Moreover, we welcome submissions that address: (6) spatiotemporal changes in fire in the past, present, and future, 7) fire products and models, and their validation, error/bias assessment and correction, as well as (8) analytical tools designed to enhance situational awareness for fire practitioners and to improve fire early warning systems.

The dynamics of the atmosphere in the extratropics is characterized by the coexistence of multiple fundamental processes spanning a variety of spatio-temporal scales. The interactions between the atmosphere and the oceans are central to several of these, while the interaction with sea-ice also plays a major role in high latitudes. The thermal contrast between the ocean and land surface, the different thermal inertia of the ocean and the atmosphere, and the moisture and heat exchange between the two are important for the general circulation of the atmosphere and oceans, and indicate that both a thermodynamic and a dynamic perspective are needed for understanding this topic. For example the oceanic anomalies, through air-sea interactions, affect the atmospheric dynamics already at the weather scales, and the atmosphere can quickly transfer anomalies towards remote areas, as in the case of diabatic heating along frontal zones. Atmospheric rivers originating over oceanic surfaces affect the formation of synoptic systems in the mid-latitudes and trigger climate extremes. Careful understanding of these mechanisms is crucial, especially regarding the assessment and predictability of extreme events, and the capability to discern the impacts of anthropogenic climate change on the variability of the climate system.
We welcome all contributions on the interactions between the oceanic and atmospheric circulation. These include investigations of atmosphere – ocean dynamics and thermodynamics at hemispheric and regional scales, including the role of sea-ice, and both weather and climate timescales. We also encourage submissions that address and compare different methodologies, e.g. detection of dominant patterns or weather regimes, dimensionality reduction involving traditional techniques such as PCA and EOFs, or new methods such as random forest or other AI-based algorithms. Model intercomparisons, and evaluations of past and future climate projections, are also welcome.

The ocean surface layer mediates the transfer of matter, energy, momentum, heat, and trace gases between the ocean, atmosphere and sea ice, and thus plays a central role in the dynamics of the climate system. This session will focus on the ocean surface layer globally, from the coasts – including the marginal sea ice zone – to the pelagic ocean, and its interactions with the overlaying low atmosphere. We will discuss in particular recent advances in the understanding of (sub-)mesoscale and internal-wave dynamics, ocean surface-interior interactions, ice-ocean interactions, particle and tracer dispersion as well as boundary-layer turbulence and surface-wave effects. We also encourage studies focusing on the coupling of physical, biological, and biogeochemical processes. Of special interest will be contributions describing the impact of ocean surface-layer processes on air-sea fluxes and atmosphere-ocean feedbacks. These include the parameterization of air-sea interactions, the impact of tropical cyclones, and the role of extreme events. Our session welcomes observational (from in-situ to remote sensing), theoretical and numerical investigations focusing on the ocean surface layer and its interactions with the atmosphere and sea ice, regardless of the temporal and spatial scales considered.

Atmospheric science research provokes and reacts to policy and the historical connection between these subjects persists to the present. Air quality and climate hazards induce risks to exposed populations that impact public health, equity, and resilience often through compounding exposures that motivates policy. Action designed to improve air quality and reduce climate change impacts can improve health and address environmental injustices when it is supported through atmospheric science research. This session calls for research seeking to understand how mitigations and adaptations to air pollution and climate change could influence atmospheric chemistry and dynamics in the present and future and how these actions could affect health and equity. We welcome abstracts that leverage remote-sensing, statistical and earth-system modeling, ground-based observation, machine-learning approaches, and policy analysis techniques to investigate the efficacy of policies in ameliorating poor air quality, climate change, health impacts, and environmental injustices. Additionally, we seek novel research that identifies areas of policy need through advances in atmospheric science research.

Urban areas are major contributors to climate change and are especially vulnerable to its effects. Over the coming decades, millions of urban residents are expected to face rising sea levels, more intense storms, inland flooding, and extreme temperature variations. These challenges will strain urban infrastructure, reducing access to essential services and lowering the quality of life. Most critical economic and social infrastructure is located in cities, making them highly exposed to climate risks. However, many cities are not yet equipped to respond effectively due to outdated policies, limited resources, and low public awareness.
Citizen science offers a valuable way to address these challenges by enhancing our understanding of urban climate, health, and air quality. Through the active involvement of citizens and stakeholders, communities can collect critical data on air quality and other environmental factors. This participatory approach not only improves our knowledge of climate risks but also strengthens adaptation strategies for urban areas. Simple, low-cost tools can be used by citizens to gather atmospheric data, while stakeholders provide insights into local vulnerabilities. Additionally, unconventional data sources, such as crowdsourced observations and urban cellular networks, can offer important information on climate impacts and response strategies.
By engaging citizens in these efforts, we foster a sense of responsibility for the environment and build stronger support for adaptation initiatives. Citizen participation in data collection provides hands-on experience with the real effects of climate change, leading to greater awareness and climate-friendly behaviors. This is essential for meeting climate mitigation goals, along with technological and societal actions. Citizen science projects that monitor climate variables, health impacts, and air quality in urban settings, as well as those that develop digital tools to enhance public knowledge, play a critical role in combating misinformation and advancing climate adaptation.
This session encourages contributions that explore participatory science, crowdsourced data collection, and best practices for involving citizens in Europe’s climate adaptation strategies.

Atmospheric hazards can cause significant socio-economic damages and therefore it is of paramount importance that their impacts and historical variability are well understood by those in the insurance and financial sectors. These groups are expected to deal with climate risk on multiple timescales, for example through enhanced risk assessments.

As the climate continues to change, an understanding of changes to frequency, severity, exposure, and vulnerability are all required for a multitude of different perils. Furthermore, attention needs to be paid to emerging risks, and also to global regions that may be more vulnerable in the future. This understanding will aid planning and potential operational changes for those in the private sector.

This session will explore studies on historical impacts, modelling of hazards, understanding of variability, risks from climate change, and quantifications of exposure and vulnerability. Submissions are encouraged from both academic studies, and research projects from within the insurance and financial sectors. In particular, submissions are encouraged that focus on:

- Quantification of historical variability in hazards around the globe
- High resolution modelling of impactful perils
- Studies on compound or correlated risks
- Assessments of future changes or trends in either hazard, exposure, or vulnerability with climate change
- Techniques for assessing hazards in climate models
- Use of large ensembles for modelling risks
- Studies on emerging hazards such as drought/wildfire

Join us for the third edition of the Lagrangian session, where researchers across disciplines showcase their work using Lagrangian tools and techniques on turbulent to planetary scales. In this session, you can expect to hear about the latest developments in Lagrangian techniques, learn about a wide range of topics and applications, and expand your professional network.

We invite presentations on topics including – but not limited to – the following:
- Large-scale circulation studies using direct Lagrangian modeling and/or age and chemical tracers (jets, gyres, overturning circulations);
- Exchanges between reservoirs and mixing studies (e.g. transport barriers and Lagrangian Coherent Structures in the stratosphere and in the ocean, stratosphere-troposphere exchange);
- Tracking long-range anthropogenic and natural influence (e.g. effects of recent volcanic eruptions and wildfire smoke plumes on the composition, chemistry, and dynamics of the atmosphere, transport of pollutants, dusts, aerosols, plastics, and fluid parcels in general, etc);
- Inverse modeling techniques for the assessment and constraint of emission sources (e.g. backtracking, including diffusion and buoyancy);
- Model and tool development, computational advances.

Statistical post-processing techniques for weather, climate, and hydrological forecasts are powerful approaches to compensate for effects of errors in model structure or initial conditions, and to calibrate inaccurately dispersed ensembles. These techniques are now an integral part of many forecasting suites and are used in many end-user applications such as wind energy production or flood warning systems. Many of these techniques are flourishing in the statistical, meteorological, climatological, hydrological, and engineering communities. The methods range in complexity from simple bias correction up to very sophisticated machine learning and/or distribution-adjusting techniques that take into account correlations among the prognostic variables.

At the same time, a lot of efforts are put in combining multiple forecasting sources in order to get reliable and seamless forecasts on time ranges from minutes to weeks. Such blending techniques are currently developed in many meteorological centers. These forecasting systems are indispensable for societal decision making, for instance to help better prepare for adverse weather. Thus, there is a need for objective statistical framework for "forecast verification'', i.e. qualitative and quantitative assessment of forecast performance.

In this session, we invite presentations dealing with both theoretical developments in statistical post-processing and evaluation of their performances in different practical applications oriented toward environmental predictions, and new developments dealing with the problem of combining or blending different types of forecasts in order to improve reliability from very short to long time scales.

The Earth's climate system is characterized by the intricate interplay of atmospheric and oceanic processes evolving at various timescales, exhibiting complex behaviors and nonlinear interactions. Gaining a deeper insight into the underlying dynamics of this system is crucial for understanding the physical origins of weather and climate variability, as well as for predicting climate trends and extreme events. However, this task poses significant challenges, as traditional theoretical approaches alone often fall short in capturing the full extent of these complexities. To address these challenges, data-driven methods have increasingly become indispensable tools in the study of oceanic and atmospheric dynamics.

Over the past few decades, the application of data-driven approaches has led to substantial advancements in our understanding of climate systems. Linear techniques such as normal modes, wave analysis, and Fourier methods, have long been employed to extract relevant spatiotemporal features and identify key climate modes. Furthermore, empirical dynamical methods, such as Linear Inverse Models (LIMs), have proven invaluable for the study and prediction of climate phenomena like the El Niño-Southern Oscillation (ENSO).

In recent years, the advent of non-linear data-driven methodologies has opened new avenues in the field. Techniques such as transfer operators, including Koopman mode decomposition, and various machine learning approaches have significantly broadened the scope of what can be achieved in the analysis and forecasting of climate dynamics. These methods offer potential to uncover complex patterns, improve climate predictability, and develop more accurate reduced-order models that capture the essence of the underlying dynamical processes, holding great potential for enhancing our understanding of complex atmospheric and oceanic climate processes.

This session aims to bring together researchers at the forefront of applying data-driven methods to study oceanic and atmospheric dynamical systems. We invite contributions that explore the application of these methodologies in various aspects of climate science, including (but not limited to) the following topics:

- Climate Predictability and Forecasting

- Spatiotemporal Feature Extraction

- Climate Mode Identification

- Climate Network Analysis

- Exploration of Climate Attractors

- Development of Reduced-order Models

- Extreme Event Analysis

Proper characterization of uncertainty remains a major research and operational challenge in Environmental Sciences and is inherent to many aspects of modelling impacting model structure development; parameter estimation; an adequate representation of the data (inputs data and data used to evaluate the models); initial and boundary conditions; and hypothesis testing. To address this challenge, methods that have proved to be very helpful include a) uncertainty analysis (UA) that seek to identify, quantify and reduce the different sources of uncertainty, as well as propagating them through a system/model, and b) the closely-related methods for sensitivity analysis (SA) that evaluate the role and significance of uncertain factors (in the functioning of systems/models).

This session invites contributions that discuss advances, both in theory and/or application, in methods for SA/UA applicable to all Earth and Environmental Systems Models (EESMs), which embraces all areas of hydrology, such as classical hydrology, subsurface hydrology and soil science.

Topics of interest include (but are not limited to):
1) Novel methods for effective characterization of sensitivity and uncertainty
2) Analyses of over-parameterised models enabled by AI/ML techniques
3) Single- versus multi-criteria SA/UA
4) Novel methods for spatial and temporal evaluation/analysis of models
5) The role of information and error on SA/UA (e.g., input/output data error, model structure error, parametric error, regionalization error in environments with no data etc.)
6) The role of SA in evaluating model consistency and reliability
7) Novel approaches and benchmarking efforts for parameter estimation
8) Improving the computational efficiency of SA/UA (efficient sampling, surrogate modelling, model identification and selection, model diagnostics, parallel computing, model pre-emption, model ensembles, etc.)
9) Methods for detecting and characterizing model inadequacy

Across our planet, microorganisms - including bacteria, archaea, viruses, microalgae, and fungi - play vital roles in nutrient cycling and ecological balance. Airborne microbial cells that were emitted from marine and terrestrial surfaces are transported and redistributed in the atmosphere on various temporal and spatial scales.
While extensive research has been dedicated to understand microbial communities in the cryo-, litho-, hydro-, and phyllo-spheres, studies on atmospheric microorganisms have been limited to describing their abundance, diversity, and potential climatic and sanitary implications. However, the atmosphere hosts living cells that take part in and are affected by biological, chemical, and physical processes while airborne, contributing to the intricate web of life on our planet.
The continuous exchange of microorganisms between surface habitats and the air makes the atmosphere an important, highly dynamic component of the microbial life cycle that effects biogeochemical cycles and chemical composition.
Thus, to gain a more complete understanding of the planet’s microbiome, it is important to identify atmospheric chemical, physical and biological factors that shape and modulate airborne microbial populations, diversity, and functioning. Such factors include, e.g., emission/deposition and transport processes, exposure to stress factors (e.g., oxidative or osmotic stress) and other intrinsic biological traits of airborne microorganisms which may contribute to their survival and activity.
This session will provide an interdisciplinary platform for atmospheric scientists, biogeoscientists, microbial ecologists and other researchers which are concerned with (i) the transport processes of living microorganisms, (ii) microbial processes in the atmosphere and their feedbacks on the Earth surface (water, soil, vegetation, ice), and (iii) atmospheric factors, processes and conditions that affect atmospheric microbial diversity, concentrations, survival, and functioning. We particularly encourage contributions that lead to a more comprehensive characterization of the microbiome and its interactions with the atmosphere and Earth’ surfaces.

Transportation systems are particularly vulnerable to weather conditions, with impacts that can range from minor delays to severe disruptions, compromising both safety and efficiency. As climate variability intensifies, the need to understand and predict these weather-related effects becomes increasingly urgent. The session "Transportation Meteorology: From Insights to Impacts, From Forecasting to Solutions" will delve into the vital role meteorology plays in transportation, offering an in-depth examination of the latest advancements in weather observations and forecasting specific to transportation, and their practical applications in developing resilient strategies to address these challenges.
This session encompasses a wide array of topics, including the effects of extreme weather events on various modes of transportation—such as road, rail, air, and maritime—the integration of meteorological monitoring and early warning systems into transportation networks to enhance decision-making, and innovative methods to strengthen infrastructure resilience. Additionally, the session also explores how advancements in transportation meteorology can contribute to the transformation toward more sustainable and climate-resilient transportation systems, supporting the global push for greener, more efficient infrastructure. Contributions in the form of case studies, research findings, and technological innovations are encouraged, as they showcase successful implementations and share valuable lessons learned.

The proposed session, "Innovative Weather Driven Event Management for Society," explores how weather influences the planning and execution of various scientific and societal events, from large public gatherings to specialized community activities. The focus will be on integrating advanced weather forecasting technologies into event management to improve decision-making.

Key areas of discussion will include:
- Developing real-time, weather-responsive strategies.
- Assessing the impact of severe weather on event safety and execution.
- Utilizing AI, machine learning, and data fusion to predict and manage weather-related risks.

The past years have seen a renaissance in applications of meteoric cosmogenic 10Be and the 10Be(meteoric)/9Be(stable) ratio in the terrestrial, oceanic, and helio-magneto-atmospheric realms. Terrestrial applications include quantifying soil residence times, dating of landforms such as moraines and sedimentary sections, soil mixing and transport, catchment-wide erosion, weathering and denudation rates as well as subglacial erosion. Marine applications include reconstructions of cosmogenic production rates, ocean water circulation, trace metal input and global paleo-weathering. Many of these applications rely on knowing the meteoric 10Be depositional flux, which is provided by marine and ice core/lake archives. Conversely, 10Be concentrations and the 10Be/9Be ratio are used to reconstruct changes in the meteoric 10Be depositional flux related to helio- and geomagnetic modulation of the cosmic ray flux. For a better quantitative understanding of these records, modelling-based approaches encompass atmospheric production and delivery models that include aerosol chemistry and transport models and state-of-the-art physics-based 10Be production functions.

This session invites a broad range of contributions surrounding meteoric 10Be, with the aim to bring together colleagues from these different communities to stimulate discussion and foster collaboration. The contributions may include, but are not limited to, the “model side” (e.g. construction of atmospheric production/delivery models, their downscaling, and inter-model comparison as well as comparison to observational data, systematics/laws of meteoric 10Be production and depositional flux, effects of geo- and heliomagnetic variations), and the “observational side”. This may include studies relying on either knowing the depositional flux, such as meteoric 10Be/9Be in terrestrial weathering and denudation, dating of landforms, or reconstructing the depositional flux from geomagnetic field observations or from terrestrial and marine archives, as well as oceanic applications.

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. 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 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).

Moreover, any contributions to the civil or scientific use of IMS data are welcome. 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 about climate change, ocean processes, solid earth structure, and atmospheric circulation. This session furthermore invites studies on the enhancement of small-scale seismic velocity and regional seismic travel-time models as well as the modeling of acoustic wave propagation, ATM of radionuclides, and contributions regarding the data fusion of various technologies. Finally, contributions are encouraged on the application of machine learning in event detection, localization, discrimination, and monitoring.

The modeling of the Earth Climate System has undergone outstanding advances to the point of resolving atmospheric and oceanic processes on kilometer-scale, thanks to the development of high-performance computing systems. Models resolving km-scale processes (or storm-and-eddy-resolving models) on a global scale are also able to resolve the interaction between the large and small-scale processes, as evidenced by atmosphere- and ocean-only simulations. More importantly, this added value comes at the expense of avoiding the use of parameterizations that interrupts the interaction between scales, i.e., convective parameterization in the atmosphere or mesoscale eddy parameterization in the ocean. These advantages are the bases for the development of global-coupled storm-and-eddy-resolving models, and even at their first steps, such simulations can offer new insights into the importance of capturing the air-sea interface and their associated small-scale processes in the representation of the climate system.
The objective of this session is to have an overview of the added values of global simulations using storm-resolving atmosphere-only configuration, eddy-resolving ocean-only models, and to identify which added values stay after coupling both components, i.e., mechanisms not distorted by the misrepresentation of sub-grid scale processes in the atmosphere and ocean. In addition to highlighting the importance of the already resolved processes in shaping the climate system in global storm-and-eddy-resolving models, this session is also dedicated to presenting the current challenges in global storm-and-eddy-resolving models (identification of biases and possible solutions) by pointing to the role of the sub-grid scale processes in shaping processes on the large scale.
We call for studies contributing to highlighting the advantages and challenges of using global storm-and-eddy-resolving models in ocean-only, atmosphere-only, and coupled configurations, such as the ones proposed by NextGEMS, EERIE, DestinE, and WarmWorld, as well as studies coming from independent institutions around the world

In weather prediction and climate modelling, numerical models of the Earth System are used extensively. For both the atmosphere and ocean components such models consist of a fluid dynamics solver (dynamical core) coupled to physical parameterizations to represent processes that occur below the grid scale (physics). Over time these models have become capable of sophisticated simulations. Research and development are constantly being undertaken to improve the accuracy, efficiency, and scalability of the dynamical core, the physics, and their coupling.

This session encompasses the development, testing, and application of novel numerical techniques for Earth system models, including 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.

Projections of future climate rely on 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 simple conceptual models, which offer qualitative process understanding and allow for a broad range of theoretical approaches. Simple climate models are also widely used as physics-based emulators of computationally expensive ESMs, forming the basis of many probabilistic assessments in the IPCC 6th Assessment Report.

Between these two approaches, a persistent “gap between simulation and understanding” (Held 2005, see also Balaji et al. 2022) challenges our ability to transfer insight from simple 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, striving to understand the differences and similarities across its various levels of complexity for increased confidence in climate projections.

In this session, we invite contributions from all subfields of climate science that showcase how modeling approaches of different complexity advance our process understanding, and/or highlight inconsistencies in the model hierarchy. We also welcome studies exploring a single modeling approach, as we aim to foster exchange between researchers working on different rungs of the model hierarchy. Contributions may employ dynamical systems models, physics-based low-order models, explainable machine learning, Earth System Models of Intermediate Complexity (EMICs), simplified or idealized setups of ESMs (radiative-convective equilibrium, single-column models, aquaplanets, slab-ocean models, idealized geography, etc.), and full ESMs.

Processes and phenomena of interest include, but are not limited to:
* Earth system response to forcing scenarios (policy-relevant, extreme, counterfactual)
* Tipping points and abrupt transitions (e.g. Dansgaard-Oeschger events)
* Coupled modes of climate variability (e.g. ENSO, AMV, MJO)
* Emergent and transient phenomena (e.g. cloud organization)
* Extreme weather events

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 user-driven climate information and new climate services and products. In fact, the "user's dilemma" is no longer that there is a lack of downscaled data, but rather how to select amongst the available datasets and to assess their credibility. In this context, model evaluation and verification is growing in relevance and advances in the field will likely require close collaboration between various disciplines.

Furthermore, epistemologists have started to revisit current practices of climate model validation. This new thread of discussion encourages to clarify the issue of added value of downscaling, i.e. the value gained through adding another level of complexity to the uncertainty cascade. For example, the ‘adequacy-for-purpose view’ may offer a more holistic approach to the evaluation of downscaling models (and atmospheric models, in general) as it considers, for example, user perspectives next to a model’s representational accuracy.

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 enrich our discussion about novel challenges faced by the evaluation of increasingly complex simulation models.

Contributions to this session may address, but are not limited to:

- newly available downscaling products,
- applications relying on downscaled data,
- downscaling method development, including the potential for 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 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.

Understanding the exchange of CO2 and other greenhouse gases (GHGs) between land, atmosphere, and ocean is crucial for mitigating climate change and supporting climate agreements. However, significant uncertainties remain due to challenges in integrating experimental, observational, and theoretical research across scales. Data-driven machine learning (ML) approaches have become popular for studying different components of the carbon cycle, but current artificial intelligence (AI) systems rarely provide a comprehensive view of the entire Earth system. This session aims to connect diverse research communities to discuss AI-driven research on the carbon cycle.

We encourage submissions on all aspects of the carbon cycle, including the atmosphere, biosphere, ocean, and human impacts. ML can enhance top-down and bottom-up approaches for quantifying land and ocean fluxes, constraining carbon budgets and carbon stocks, and mapping CO2 and CH4 through atmospheric tracer transport. This is crucial for tasks such as partitioning land fluxes into photosynthesis and respiration, estimating carbon stocks in soils and biomass, etc. This session particularly targets works that integrate diverse data sources that are not traditionally combined, such as remote sensing data with eddy covariance flux measurements.

Recent advances in numerical weather prediction have shown the effectiveness of deep neural networks, particularly transformers. Emerging "Foundation Models" integrate diverse data streams to address multiple tasks within a single AI system. Classical algorithms like random forests, Gaussian processes, and gradient-boosting trees remain useful due to their efficiency and ease of use. Uncertainty quantification and explainable AI enhance ML methods by revealing key variables.

In summary, this session welcomes all submissions that leverage machine learning for carbon cycle research, including but not limited to:
- Machine learning for integrating remote sensing data with in-situ observations.
- Hybrid modeling for enhanced inference of parameters and responses of key processes in the carbon cycle.
- Mapping of stocks, fluxes, and other carbon-related quantities.
- Emulators to speed up conventional models, such as atmospheric tracer transport models for GHGs.
- ML methodologies for improving uncertainty quantification, prediction accuracy, explainability, or sample efficiency.
- Model-data integration to better understand CO2 and CH4 fluxes.

Earth, its weather and climate constitute a complex system whose monitoring and modelling has undergone remarkable progress in recent years. In particular, enhanced spaceborne observations and the integration Machine/Deep Learning (ML/DL) techniques are key drivers of innovation in Earth System Observation and Prediction (ESOP) for Weather and Climate.

ML/DL techniques revolutionized numerous fields and have proven advantageous in various applications. These techniques garnered significant attention and adoption within the ESOP community due to their ability to enhance our understanding and prediction capabilities of the Earth's complex dynamics. One prominent area where ML/DL techniques have proven invaluable is in the development of high fidelity digital models of the Earth on a global scale. These models serve as comprehensive monitoring, simulation, and prediction systems that enable us to analyse and forecast the intricate interactions between natural phenomena and human activities.

ML/DL solutions also showcased promising advancements in weather forecasting and climate prediction. Algorithms can be trained to identify instances where physical models may exhibit inaccuracies and subsequently learn to correct their predictions accordingly. Moreover, AI-based models have the potential to create hybrid forecast models that combine the strengths of traditional, physics-based NWP/Climate prediction methodologies with the capabilities of ML/DL, ultimately enhancing the accuracy and reliability of predictions.As such, the application of ML/DL for ESOP and the hybrid usage in combination with established numerical prediction and assimilation methods are thematic areas of particular interest in this session.

Inspired by the successful 4-days long ESA-ECMWF ML4ESOP workshop, this sprint session invites new ML4ESOP explorers to present their latest innovation in ESOP. Focus is on the exploration of new data sources and benchmarks for weather and climate modelling, the adaptation of large-scale data-driven Earth system models, as well as novel demonstrations of their applicability to weather and climate observation and prediction.
This session invites all experts from diverse fields to discuss how recent advances innovate on established ESOP approaches, to address current challenges, and to identify opportunities for future work.

Uncrewed Aircraft Systems (UAS) are an emerging technology, significantly expanding observational capabilities in atmospheric and climate related sciences. This expansion is enabled by the increased availability and deployment of UAS. The rapid development of these platforms in recent years, combined with advances in miniaturised sensors, has led to a growing dataset that supports various aspects of atmospheric research in different environmental domains with linkages to hydrology, ecology, volcanology or geochemistry as well as applied sciences such as wind energy or transport of pollutants and aerosol particles.
This session invites abstracts discussing scientific contributions in atmospheric and climate sciences using various platforms, including fixed-wing UAS, multicopters, and tethered balloon/kite systems (TBS) etc. The topics could include presentations on the development of novel platforms and instrumentation, recent measurement efforts leveraging UAS systems, deployment of UAS to enhance the weather and climate prediction and monitoring networks, data analysis and synthesis from past UAS field campaigns, and other scientific interpretations of UAS-based datasets to improve process understanding, numerical model prediction, data assimilation and parameterisation development.

Air pollution remains a critical global challenge, impacting vulnerable communities the most. In low- and middle-income countries (LMICs), weak policies and fragmented institutions further hinder effective air quality (AQ) management. Furthermore, AQ monitoring is often hampered by the lack of comprehensive measurement infrastructure. Limited computational resources also restrict data analysis and modeling. Addressing these challenges requires strong local and international collaboration to improve AQ management. Accessible and affordable AQ sensors (popularly known as low-cost sensor systems, LCS) are key tools for building local capacity and addressing these challenges in LMICs.
This session will showcase best practices in using LCS for AQ monitoring. We will explore case studies where LCS enhance remote sensing, improve forecasting and modeling, and support public health and community monitoring initiatives, particularly, but not limited, to resource-limited settings. This session promotes practical sensor applications that enhance data capabilities and foster strong local and international collaboration. It will also explore strategies for sustainable practices that empower communities and ensure equitable partnerships.
We welcome, but not limit, contributions that aim at:
- Proposing innovative solutions to address QA/QC in sensors.
- Characterizing sensor uncertainty and evaluating sensor performance across various locations and/or climatic conditions.
- Addressing calibration and maintenance challenges to ensure long-term accuracy and reliability of sensors.
- Enhancing local technical skills and computational resources to manage, integrate, and analyze large volumes of data.
- Highlighting the integration of sensor data with other data sources such as satellite imagery, models, and higher-end measurements.
- Designing effective sensor networks to optimize coverage and data reliability.
- Tackling technical and logistical challenges in sensor use within financially and technically constrained environments.
- Assessing the role of sensors in public health and personal exposure studies.
- Evaluating the role of policy and regulation in promoting and overseeing the effective use of sensors.
- Fostering citizen involvement in AQ monitoring to enhance community engagement and data collection.
- Building frameworks for enduring local and international partnerships that support comprehensive AQ initiatives.

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

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

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

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

This session 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.

Differential Optical Absorption Spectroscopy (DOAS) was originally developed to retrieve column densities of atmospheric trace gases. Nowadays, DOAS systems exist in a large setup variety with different operating modes being capable of retrieving the vertical and the horizontal distribution of atmospheric trace gas concentrations and aerosol extinction with high accuracy. While MAX-DOAS instruments utilise scattered sunlight, there are also active DOAS applications hosting their own light source, further improving the accuracy at the cost of setup simplicity.

Spectral imaging techniques can vastly enhance the spatio-temporal information content of atmospheric trace gas measurements, often by a trade-off between spectral and spatio-temporal resolution. They are particularly useful to observe stronger spatial gradients of trace gas column densities in the atmosphere, which can, for instance, largely improve the retrieval of mass fluxes at point sources, such as power plants, volcanoes, or vehicles. The increased spatio-temporal resolution of imaging techniques also adds information on the context of the atmospheric measurements (e.g., cloudiness, horizon line, wind conditions).

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.

To assure consistency between different DOAS and imaging instruments, intercomparison measurements were carried out during the CINDI3 campaign (Cabauw, Netherlands) in spring 2024. Contributions from this recent campaign are particularly welcome.

No single sensor provides comprehensive information about a targeted object in a complex environment, and there is always a need to inject the missing information from complementary observations, modeling or other sources of knowledge. In addition, once the instruments have been deployed, the quality of measurements cannot be radically improved, while the processing algorithms remain under constant improvement and the final product can be notably improved by fusion of information and optimizing the use of joint sensitivity of multi-instrument datasets. Therefore, the need and value of the synergy processing becomes especially evident in the light of the continuous rapid increase in the number and diversity of the available diverse remote sensing observations.

This session encourages the discussion of the approaches exploring the synergies of complimentary observations such as: synergy of passive imagery with active vertical profiling of the atmosphere, synergies of observations in different spectral ranges, at different time and/or spatial scales, as well as, synergies of satellite observations with sub-orbital observations and chemical transport model simulations. The session particularly solicits the presentations demonstrating the novel synergy methods for using observations from the Copernicus Sentinels, EarthCARE, MTG, EPS-SG, PACE and other recent and forthcoming advanced satellite missions as well as field campaigns.

Instrumentation and its development play a key role in advancing research, providing state-of-the-art tools to address open scientific questions. Over the last several decades, atmospheric environmental monitoring has benefited from novel spectroscopic measurement techniques that arose from breakthroughs in photonic technologies from the UV to THz spectral regions. These advances open new research avenues for observation of spatial and long-term trends in the concentration and optical properties of atmospheric constituents, and for studying atmospheric processes in laboratories and atmospheric simulation chambers. These advances are vital for expanding our insight into atmospheric composition and processes, and ultimately their impacts on air quality and global climate change.
The upcoming session of "Advanced Spectroscopic Measurement Techniques and Applications for Atmospheric Science" focuses on the latest developments and advances in a broad range of spectroscopic instrumentation and technologies, and their use in a variety of atmospheric applications. It aims to be a platform for sharing information on the state-of-the-art and emerging developments for atmospheric sensing. This interdis¬ciplinary forum aims to foster discussion among experimentalists, atmospheric scientists, and development engineers. It is also an opportunity for R&D and analytical equipment companies to evaluate the capabilities of new instrumentation and techniques.
Topics for presentation include developments, demonstrations and applications of novel spectroscopic methods and instruments dedicated to measuring atmospheric aerosols, isotopologues, greenhouse gases and other trace gases, as well as associated atmospheric meteorological parameters such as temperature, wind speed, humidity, etc. Studies of vertical concentration profiles and flux measurements are all welcome when the instrumentation is a focus of the work. Spectroscopic methods could include high sensitivity and selectivity spectroscopy (such as dual-comb spectroscopy, cavity-enhanced absorption/Raman spectroscopies, photoacoustic & photothermal spectroscopy and other spectroscopic methods), low-cost optical sensors, heterodyne radiometry and imaging spectroscopy. Applications include laboratory demonstration, ground and airborne platforms (UAV/drone, balloon, aircraft) observations, smog chamber studies. Approaches using new spectral data analysis tools (including machine learning) are encouraged.

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.

Satellite measurements of our Earth from space are essential to our study of global
climate and weather patterns. Teasing out complexities in our Earth system requires a
framework of calibrated and curated remote sensors that can operate in space over
decadal periods. These instruments cover a variety of spectral, spatial, angular,
polarized, and coherent regimes and target specific Earth phenomena in the
atmosphere, surface, or oceans.

A comprehensive remote sensor calibration is required in order to
retrieve decadal and actionable climate trends with high accuracy and confidence.
Instrument teams follow an exhaustive pre-launch, on-orbit, vicarious, and cross-
calibration plan. Validating these efforts against radiative transfer simulations,
measurement trends over pseudo-invariant Earth targets, and dedicated field
campaigns with ground-network, airborne, or satellite-based intercomparisons help to
enhance and extend the original pre-launch characterization.

New and planned progressive missions with multi-angle polarimetry and/or multi-
instrument synergy are changing the way we understand our Earth system and how we
measure our observables. This session welcomes new research in pre-launch, on-orbit,
vicarious, and cross calibration activities on data from recently launched missions such
as PACE and EarthCARE and recent field campaigns, such as PACE-PAX, ARCSIX,
and ORCESTRA. Expected on-orbit performance studies for upcoming missions with
multi-angle polarimetry and/or multi-instrument synergy, such as 3MI, MAIA, and CO2M,
are highly encouraged as well.

Geodesy contributes to atmospheric science by providing some of the essential climate variables of the Global Climate Observing System. In particular, 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 over 20 years+ of cooperation between the geodetic community and the national meteorological services. Improving the skill of NWP models, e.g., to forecast extreme precipitation, requires GNSS products with a higher spatio-temporal resolution and shorter turnaround. Homogeneously reprocessed GNSS data have high potential for monitoring water vapor climatic trends and variability. With shorter orbit repeat periods, SAR measurements are a new source of information to improve NWP models. Using NWP data within RT GNSS data analysis can initialize PPP algorithms, thus reducing convergence times and improving positioning. GNSS signals can also be used for L-band remote sensing when Earth-surface reflected signals are considered. GNSS-R contributes to environmental monitoring with estimates of soil moisture, snow depth, ocean wind speed, sea ice concentration and can potentially be used to retrieve near-surface water vapor.
We welcome, but not limit, contributions on:
• Estimates of the neutral atmosphere using ground- and space-based geodetic data and their use in weather forecasting and climate monitoring
• Retrieval and comparison of tropospheric parameters from multi-GNSS, VLBI, DORIS and multi-sensor observations
• Now-casting, forecasting, and climate research using RT and reprocessed 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 thereof in NWP
• Homogenization of long-term GNSS and VLBI tropospheric products
• Delay properties of GNSS signals for propagation experiments
• Exploitation of NWP data in GNSS data processing
• Techniques for soil moisture retrieval from GNSS data and for ground-atmosphere boundary interactions
• Detection and characterization of sea level, snow depth and sea ice changes, using GNSS-R
• Investigating the atmospheric water cycle using satellite gravimetry

The visualization and user-friendly exploration of information from scientific data is one of the main tasks of good scientific practice. But steady increases in temporal and spatial resolutions of modeling and remote sensing approaches lead to ever-increasing data complexity and volumes. On the other hand, earth system science data are getting increasingly important as decision support for stakeholders and other end users far beyond the scientific domains.

This poses major challenges for the entire process chain, from data storage to web-based visualization. For example, (1) the data has to be enriched with metadata and made available via appropriate and efficient services; (2) visualization and exploration tools must then access the often decentralized tools via interfaces that are as standardized as possible; (3) the presentation of the essential information must be coordinated in co-design with the potential end users. This challenge is reflected by the active development of tools, interfaces and libraries for modern earth system science data visualization and exploration.

In this session, we hence aim to establish a transdisciplinary community of scientists, software-developers and other experts in the field of data visualization in order to give a state-of-the-art overview of tools, interfaces and best-practices. In particular, we look for contributions in the following fields:

- Developments of open source visualization and exploration techniques for earth system science data
- Co-designed visualization solutions enabling transdisciplinary research and decision support for non-scientific stakeholders and end-users
- Tools and best-practices for visualizing complex, high-dimensional and high frequency data
- Services and interfaces for the distribution and presentation of metadata enriched earth system science data
- Data visualization and exploration solutions for decentralized research data infrastructures

All contributions should emphasize the usage of community-driven interfaces and open source solutions and finally contribute to the FAIRification of products from earth system sciences.

Almost a decade ago, the FAIR data guiding principles were introduced to the broader research community. These principles proposed a framework to increase the reusability of data in and across domains during and after the completion of e.g. research projects. In subdomains of the Earth System Sciences (ESS), like atmospheric sciences or partly geosciences, data reuse across institutions and geographical borders was already well-established, supported by community-specific and cross-domain standards like netCDF-CF, geospatial standards (e.g.OGC). Further, authoritative data producers such as CMIPs were already using Persistent Identifiers and corresponding handle systems for data published in their repositories – so it was often thought and communicated this data is “FAIR by design”.

However, fully implementing FAIR principles, particularly machine-actionability—the core idea behind FAIR—has proven challenging. Despite progress in awareness, standard-compliant data sharing, and the automation of data provenance, the ESS community continues to struggle to reach a community-wide consensus on the design, adoption, interpretation and implementation of the FAIR principles.

In this session, we invite contributions from all fields in Earth System Sciences that provide insights, case studies, and innovative approaches to advancing the adoption of the FAIR data principles. We aim to foster a collaborative dialogue on the progress our community has made, the challenges that lie ahead, and the strategies needed to achieve widespread acceptance and implementation of these principles, ultimately enhancing the future of data management and reuse.

We invite contributions focusing on, but not necessarily limited to,
- Challenges and solutions in interpreting and implementing the FAIR principles in different sub-domains of the ESS
- FAIR onboarding strategies for research communities
- Case studies of successful FAIR data implementation (or partial implementation) in ESS at infrastructure and research project level
- Methods and approaches to gauge the impact of FAIR data implementation in ESS
- Considerations on how AI might help to implement FAIR
- Future direction for FAIR data in ESS

Pangeo (pangeo.io) is a global community of researchers and developers that tackle big geoscience data challenges in a collaborative manner using laptop to HPC and Cloud infrastructure. This session's aim is:
to motivate researchers who are using or developing in the Pangeo ecosystem to share their endeavours with a broader community that can benefit from these new tools.
to contribute to the Pangeo community in terms of potential new applications for the Pangeo ecosystem, containing the following core packages: Xarray, Iris, Dask, Jupyter, Zarr, Kerchunk and Intake.

We warmly welcome contributions that detail various Cloud computing initiatives within the domains of Earth Observation and Earth System Modelling, including but not limited to:
- Cloud federations, scalability and interoperability initiatives across different domains, multi-provenance data, security, privacy and green and sustainable computing.
- Cloud applications, infrastructure and platforms (IaaS, PaaS SaaS and XaaS).
- Cloud-native AI/ML frameworks and tools for processing data.
- Operational systems on the cloud.
- Cloud computing and HPC convergence and workload unification for EO data processing.

Also, presentations using at least one of Pangeo’s core packages in any of the following domains:
- Atmosphere, Ocean and Land Models
- Satellite Observations
- Machine Learning
- And other related applications

We welcome any contributions in the above themes presented as science-based in other EGU sessions, but more focused on research, data management, software and/or infrastructure aspects. For instance, you can showcase your implementation through live executable notebooks.

Recent Earth System Sciences (ESS) datasets, such as those resulting from very high resolution numerical modelling, have increased both in terms of precision and size. These datasets are central to the advancement of ESS for the benefit of all stakeholders, public policymaking on climate change and to the performance of modern applications such as Machine Learning (ML) and forecasting.

The storage and shareability of ESS datasets have become an important discussion point in the scientific community. It is apparent that datasets produced by state-of-the-art applications are becoming so large that even current high-capacity data centres and infrastructures are incapable of storing, let alone ensuring the usability and processability of such datasets. The needs of ongoing and upcoming community activities, such as various digital twin centred projects or the 7th Phase of the Coupled Model Intercomparison Project (CMIP7) already stretch the abilities of current infrastructures. With future investment in hardware being limited, a viable way forward is to explore the possibilities of data reduction and compression with the needs of stakeholders in mind. Therefore, the use of data compression has grown in interest to 1) make the data weight more manageable, 2) speed up data transfer times and resource needs and 3) without reducing the quality of scientific analyses.

Concurrently, replicability is another major concern for ESS and downstream applications. Being able to reproduce the most recent ML and forecasting results and analyses thereof has become mandatory to develop new methods and integrated workflows for operational settings. On the other hand, the data accuracy needed to produce reliable downstream products has not yet been thoroughly investigated. Therefore, research on data reduction and prediction interpretability helps to 1) understand the relationship between the datasets and the resulting prediction and 2) increase the stability of prediction.

This session discusses the latest advances in both data compression and reduction for ESS datasets, focusing on:
1) Approaches and techniques to enhance shareability of high-volume ESS datasets: data compression (lossless and lossy) or reduction approaches.
2) Understanding the effects of reduction and replicability: feature selection, feature fusion, sensitivity to data, active learning.
3) Analyses of the effect of reduced/compressed data on numerical weather prediction and/or machine learning methods.

Natural organic matter (NOM) is the largest reservoir of reduced organic carbon on Earth, affecting C-N-P storage, metals availability, microbial activity, and the retention of organic contaminants, thereby modulating global biogeochemical cycles and processes. In seawater, NOM primarily exists in dissolved form as dissolved organic carbon (DOC), accounting approximately 662 Pg C, a value approximately equal to the atmospheric CO2 (750 Pg C). In terrestrial and atmospheric ecosystems, NOM accounts for around 1500 Pg C and 16 Tg C, respectively. Compositionally, NOM is a complex and heterogeneous mixture of thousands of organic substances with varying molecular sizes, physical and chemical properties, as well as a range of functional groups, including aromatic, aliphatic, phenolic and quinone structures. Currently <10% of NOM has been chemically characterized at the molecular level (as the sum lipids; amino acids and sugars) while, a plethora of molecular formulas in NOM isolated from various environmental compartments have been revealed from mass spectrometric techniques.
This session invites researchers with diverse expertise in spectroscopy (NMR, fluorescence, XPS) and mass spectrometry (Py-GC–MS; IR-MS, FTICR-MS; LC-MS-MS, FTMS; HR-MS) to present new findings and approaches on the composition and transformation of NOM including contaminants using the aforementioned techniques in the terrestrial, aquatic and atmospheric environment. We particularly welcome contributions that:
i) Introduce new methodologies and applications for HR-MS, FT-IRMS, and especially NMR—the latter, despite its potential, remains underexplored in environmental studies.
ii) Present innovative technologies for field study of NOM or monitoring of organic contaminants in the environment.
iii) Develop new practices for exploring, processing and storing biogeochemical data generated from spectroscopic and mass spectrometric techniques

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

Python is one of the fastest growing programming languages and has moved to the forefront in the earth system sciences (ESS), due to its usability, the applicability to a range of different data sources and, last but not least, the development of a considerable number of ESS-friendly and ESS-specific packages.

This interactive Python course is aimed at ESS researchers who are interested in adding a new programming language to their repertoire. Except for some understanding of fundamental programming concepts (e.g. loops, conditions, functions etc.), this course presumes no previous knowledge of and experience in Python programming.

The goal of this course is to give the participants an introduction to the Python fundamentals and an overview of a selection of the most widely-used packages in ESS. The applicability of those packages ranges from (simple to advanced) number crunching (e.g. Numpy), to data analysis (e.g. Xarray, Pandas) to data visualization (e.g. Matplotlib).

The course will be grouped into different sections, based on topics discussed, packages introduced and field of application. Furthermore, each section will have an introduction to the main concepts e.g. fundamentals of a specific package and an interactive problem-set part.

This course welcomes active participation in terms of both on-site/virtual discussion and coding. To achieve this goal, the i) course curriculum and material will be provided in the form of Jupyter Notebooks ii) where the participants will have the opportunity to code up the iii) solutions to multiple problem sets and iv) have a pre-written working solution readily available. In these interactive sections of the course, participants are invited to try out the newly acquired skills and code up potentially different working solutions.

We very much encourage everyone who is interested in career development, data analysis and learning a new programming to join our course.

Julia offers a fresh approach to scientific computing, high-performance computing and data crunching. Recently designed from the ground up, Julia avoids many of the weak points of older, widely used programming languages in science such as Python, Matlab, and R. Julia is an interactive scripting language, yet it executes with similar speed as C(++) and Fortran. Its qualities make it an appealing tool for the geoscientist.

Julia has been gaining traction in the geosciences over the last years in applications ranging from high-performance simulations, data processing, geostatistics, machine learning, differentiable programming to scientific modelling. The Julia package ecosystem necessary for geosciences has substantially matured, which makes it readily usable for research.

This course provides a hands-on introduction to get you started with Julia as well as a showcase of geodata visualisation and ocean, atmosphere and ice simulations.

The hands-on introduction will cover:
- learn about the Julia language and what sets it apart from others
- write simple Julia code to get you started with scientific programming (arrays, loops, input/output, etc.)
- installing Julia packages and management of package environments (similar, e.g., to virtual-environments in Python)

The show-case will feature a selection of:
- Visualisation of Geo-Data using the plotting library Makie.jl and various geodata libraries
- Global ocean modelling with Oceananigans.jl on CPUs and GPUs
- Interactive atmospheric modelling with SpeedyWeather.jl
- Ice flow modelling and data integration and sensitivity analysis using automatic differentiation on GPUs with FastIce.jl

Ideally, participants should install Julia on their laptops to allow a smooth start into the course. We will provide detailed documentation for this installation. However, we will also provide a JupyterHub, albeit connectivity to it maybe spotty depending on Wi-Fi reception.

Visualisation of scientific data is an integral part of scientific understanding and communication. Scientists have to make decisions about the most effective way to communicate their results every day. How do we best visualise the data to understand it ourselves? How do we best visualise our results to communicate with others? Common pitfalls can be overcrowding, overcomplicated or suboptimal plot types, or inaccessible colour schemes. Scientists may also get overwhelmed by the graphics requirements of different publishers, for presentations, posters, etc. This short course is designed to help scientists improve their data visualisation skills so that the research outputs would be more accessible within their own scientific community and reach a wider audience.
Topics discussed include:
- golden rules of DataViz;
- choosing the most appropriate plot type and designing a good DataViz;
- graphical elements, fonts and layout;
- colour schemes, accessibility and inclusiveness;
- creativity vs simplicity – finding the right balance;
- figures for scientific journals (graphical requirements, rights and permissions);
- tools for effective data visualisation.
This course is co-organized by the Young Hydrologic Society (YHS), enabling networking and skill enhancement of early career researchers worldwide. Our goal is to help you make your figures more accessible to a wider audience, informative and beautiful. If you feel your graphs could be improved, we welcome you to join this short course.

Science’s “open era” is here (to stay?). Data and software repositories make it possible to share and collectively develop tools and resources. Diamond open-access publishing and pre-print servers are breaking barriers to knowledge exchange. Free virtual meetings make science more accessible to those interested in listening, or speaking.

The benefits for the community are clear—better communication and more collaboration foster scientific advancement. It is therefore surprising that the vast majority of data-, tool-, and knowledge-sharing initiatives rely on the community and the community alone, without financial support from funding bodies and more often than not lacking the recognition they deserve.

We aim to bring together individuals and teams who have, in any way, served the wider geoscience community through knowledge, data, or tool creation and/or distribution. Such efforts include—but are not limited to—online learning platforms, transdisciplinary databases, open-access software and publishing.

Ultimately, this session seeks to:
1. Be a space for sharing, advertising, discussing, and recognising the value of existing resources and initiatives
2. Discuss the challenges faced by those behind them (i.e., lack of funding and institutional support) and possible strategies to eliminate these
3. Inspire new efforts, initiatives, and projects

All science has uncertainty. Global challenges such as the Covid-19 pandemic and climate change illustrate that an effective dialogue between science and society requires clear communication of uncertainty. Responsible science communication conveys the challenges of managing uncertainty that is inherent in data, models and predictions, facilitating the society to understand the contexts where uncertainty emerges and enabling active participation in discussions. This session invites presentations by individuals and teams on communicating scientific uncertainty to non-expert audiences, addressing topics such as:

(1) Innovative and practical tools (e.g. from social or statistical research) for communicating uncertainty
(2) Pitfalls, challenges and solutions to communicating uncertainty with non-experts
(3) Communicating uncertainty in risk and crisis situations (e.g., natural hazards, climate change, public health crises)

Examples of research fitting into the categories above include a) new, creative ways to visualize different aspects of uncertainty, b) new frameworks to communicate the level of confidence associated with research, c) testing the effectiveness of existing tools and frameworks, such as the categories of “confidence” used in expert reports (e.g., IPCC), or d) research addressing the challenges of communicating high-uncertainty high-impact events.

This session encourages you to share your work and join a community of practice to inform and advance the effective communication of uncertainty in earth and space science.

In this short course we will address the increasing role of artificial intelligence (AI) in geoscientific research, guiding participants through the various stages of the research process where AI tools can be effectively implemented, however with responsibility. We will explore freely available AI tools that can be used for data analysis, model development, and research publication. Additionally, the course aims to provoke reflections on the ethical implications of AI use, addressing concerns such as data bias, transparency, and the potential for misuse. Participants will engage in interactive discussions to explore what constitutes responsible and acceptable use of AI in geoscientific research, aiming to establish a set of best practices for integrating AI into scientific workflows.

Following the success of previous years, this session will explore reasons for the under-representation of different groups (gender identities, sexual orientations, racial and cultural backgrounds, abilities, religions, nationality or geography, socioeconomic status, ages, career stages, etc.) by welcoming debate among scientists, decision-makers and policy analysts in the geosciences.

The session will focus on both obstacles that contribute to under-representation and on best practices and innovative ideas to remove those obstacles. Contributions are solicited on the following topics:

- Role models to inspire and further motivate others (life experience and/or their contributions to promote equality)
- Imbalanced representation, preferably supported by data, for awards, medals, grants, high-level positions, invited talks and papers
- Perceived and real barriers to inclusion (personally, institutionally, culturally)
- Recommendations for new and innovative strategies to identify and overcome barriers
- COVID-related data, discussions and initiatives
- Gender Equality Plans (GEP) in European host institutions: the good, the bad, and the ugly
- Best practices and strategies to move beyond barriers, including:
• successful mentoring programmes;
• networks that work;
• specific funding schemes;
• examples of host institutions initiatives;

This session is co-organised with the support of the European Research Council (ERC).

Persistent issues of bullying, harassment, and other exclusionary behaviours remain prevalent in research and academic settings, disproportionately impacting underrepresented groups. Bystander intervention offers a proactive approach that enables individuals to safely counteract these instances of exclusionary behaviours and support those who are targeted. This Short Course is facilitated by ADVANCEGeo and is designed to equip participants with the skills to be effective active bystanders. Workshop participants will be trained to: (i) discern various types of hostile behaviours such as bullying, microaggressions, and sexual harassment, (ii) identify the institutional structures and practices in research and academia that support their prevalence, and (iii) respond in a manner that's both safe and constructive.

Taking time off (e.g. while being on vacation) in academia poses several challenges, often due to the pressures of maintaining productivity in a highly competitive environment. Academic work is typically characterized by flexible but demanding schedules, making it difficult to fully disconnect during time off. Researchers often face the expectation of continuous output, leading to guilt or anxiety when taking breaks. Additionally, academic timelines are shaped by grant deadlines, publication schedules, and teaching commitments, limiting the optimal timing for vacations. These factors can result in burnout and reduced well-being, highlighting the need for a healthier life-work balance in academia.
In this short course, geoscientists from different career stages will talk about their experiences in taking time off. We will also focus on how the academic system can improve to allow scientists to take time off, considering that the academic world involves collaborating with scientists from different cultures, each with varying vacation times and public holidays. There will be room for questions and an open part for exchange and discussion.