AS - Atmospheric Sciences (Primary)
HS - Hydrological Sciences

Extreme Events: Observations and Modeling

* Dr Sridhara Nayak (Japan Meteorological Corporation)
Dr Pawan Kumar Chaubey (Nanyang Technological University, Singapore)
Dr Mohan Kumar Das (National Oceanographic and Maritime Institute (NOAMI))
Prof Tetsuya Takemi (Kyoto University)
Dr Takashi Unuma (Meteorological Research Institute)

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

Extreme Events;Climate Change;Modeling Studies

60

AS - Atmospheric Sciences (Primary)

Application of Regional and Global Cloud-resolving Model Simulations for Studying Cloud and Precipitation Processes in Climate

* Prof Chien-Ming Wu (National Taiwan University)
Prof Xiaowen Li (Morgan State University)
Prof Pay-Liam Lin (National Central University)
Prof Masaki Satoh (The University of Tokyo)

Cloud-system-related problems are at the heart of global and regional climate simulations for understanding climate change and feedback. However, the representation of cloud systems in General Circulation Models (GCMs) and Regional Climate Models (RCMs) remains one of the major challenges for climate simulations. While GCMs require convection and cloud parameterizations, Cloud-Resolving Models (CRMs) and high-resolution regional models explicitly resolve convection and mesoscale organization with horizontal resolutions from O(km) to O(100m) or less, where cloud microphysical processes and cloud-radiation interactions directly respond to the cloud-scale dynamics. Examples of solicited studies by this session include applying CRM simulations to improve subgrid-scale process parameterizations in RCMs and GCMs, replacing cloud-related parameterizations in GCMs, and understanding interactions of cloud systems with large-scale circulations as convective aggregations. CRMs are also powerful in studying the interaction between clouds, precipitation, dynamics, and radiation processes. Fine-resolution Large-scale Eddy Simulations (LES), including studies on cloud and related physical processes such as convective thermal, radiation, and turbulence, are also welcome. This session also encourages modeling studies of cloud particle phases, size distributions and number concentrations as important parameters in radiative transfer, latent heat, and surface precipitation. These properties have variabilities depending on cloud schemes, cloud definition, coupling between cloud microphysics and related parameterizations in the models, so their feedback to radiation, precipitation, mesoscale and general circulations have large uncertainties. In these aspects, we need to understand the current limitations on observations and modeling of clouds/precipitation and related physical processes. Moreover, we must identify these challenges efficiently for better weather and climate predictions. This session addresses the above issues and encourages/facilitates collaborations between CRM, LES, GCM, and RCM studies.

cloud/precipitation;physical processes;cloud-resolving models

BG - Biogeosciences (Primary)
HS - Hydrological Sciences

Dissolved Organic Matter Across the Land-to-ocean Continuum Under Global Change

* Dr Hongyan Bao (Xiamen University)
Prof ALEX CHOW (The Chinese University of Hong Kong)
Dr Qinglong Fu (China University of Geosciences (Wuhan))
Dr Manabu Fujii (Institute of Science Tokyo)
Prof Junjian Wang (Southern University of Science and Technology)

biogeochemistry, linking terrestrial, freshwater, estuarine, and marine systems through the land-to-ocean continuum. DOM regulates carbon and nutrient cycling, light penetration and availability, and ecosystem metabolism, making it central to water quality and climate feedbacks. In today’s rapidly changing world—marked by intensive anthropogenic activities, land-use shifts, and climate variability—the need to understand DOM sources, transformations, biogeochemical roles, and environmental effects has become more urgent than ever.
This session welcomes studies investigating DOM sources (both natural and anthropogenic origins), characterization, fluxes and the diverse biogeochemical processes that shape its composition, reactivity, and ecological impacts. Topics may include microbial transformation, photodegradation, sorption–desorption, sediment–water and groundwater–surface water exchanges, and other processes that regulate DOM biogeochemistry along the land-to-ocean continuum.
We also encourage contributions that present methodological and technological advances, such as high-resolution molecular characterization, isotopic tracing, remote sensing, and modeling. By integrating perspectives from hydrology, biogeochemistry, microbiology, and environmental sciences, this session aims to advance our understanding of DOM cycling and provide new insights into how aquatic carbon dynamics respond to global change.

dissolved organic matter;global change;land-to-ocean contiuum

12

BG - Biogeosciences (Primary)
IG - Interdisciplinary Geosciences

Soil Organic Carbon Dynamics – Bridging Observations, Experiments, and Models Across Scales

* Dr Umakant Mishra (University of California Santa Cruz)
Prof Pil Joo Kim (Gyeongsang National University)
Prof Zhangcai Qin (Sun Yat-sen University)

Soil organic carbon (SOC) determines soil health and ecosystem functioning. SOC levels regulate soil fertility, water retention, nutrient cycling, and a wide range of ecosystem services. Yet, SOC levels are highly dynamic, responding to changes in land use, management practices, and environmental conditions. While it is well established that agricultural and ecological management can either increase or decrease SOC, the cascading effects of these changes on soil properties, biogeochemical processes, and ecosystem resilience remain incompletely understood.
In order to address these knowledge gaps, researchers use field experiments, laboratory incubations, remote sensing technologies, microbial and soil omics, and advanced modeling frameworks. Despite progress, significant uncertainties persist in linking these multiple lines of evidence and in scaling insights from plot-level studies to regional and global Earth system contexts. Addressing these knowledge gaps is essential for improving predictive understanding of SOC dynamics under changing environmental conditions and for developing actionable strategies that sustain soil productivity, enhance carbon sequestration, and secure ecosystem health. Our session invites contributions that (1) highlight innovative land management practices that enhance SOC levels while improving soil function, (2) integrate multi-source datasets into geospatial, statistical, and process-based models, and (3) advance data–model integration techniques to reduce uncertainties in SOC storage, turnover, and feedbacks under diverse land-use and climate regimes.
By bringing together experimentalists, observational scientists, modelers, and data integration specialists, this session will foster cross-disciplinary dialogue and synthesis. Contributions will collectively help illuminate how SOC responds to land use change, weather variability, and management interventions, and how these responses can be leveraged to promote soil security and sustainable agroecosystems.

soil organic carbon;observations;modeling

15