NH013
Data Science for Weather and Climate Extremes: Risks, Drivers, and Impacts
Session ID#: 252763
Session Description:
The growing severity of weather and climate extremes brings into focus the importance of using data and diverse expertise to explore their connected risks. This session aims to explore how data-driven methods can reveal hidden patterns behind destructive meteorological events—such as prolonged dry and wet spells, high-impact winds, fire outbreaks, and intense heat episodes—that often occur together or in sequence. We welcome studies that use observational records, empirical analysis, and AI-based tools to investigate real-world event chains and their effects on people, ecosystems, and infrastructure. Rather than focusing on simulation or forecasting, we emphasize grounded, data-centric insights into event triggers, compounding effects, and local-to-global consequences. Contributions that link physical processes with social or environmental outcomes are especially encouraged.
Index Terms:
4313 Extreme events [NATURAL HAZARDS]
4315 Monitoring, forecasting, prediction [NATURAL HAZARDS]
4321 Climate impact [NATURAL HAZARDS]
4328 Risk [NATURAL HAZARDS]
Primary Convener: Mukesh Kumar, University of California Merced, Merced, United States and Somnath Mandal
Conveners: Dr. Sridhara Nayak, PhD, Japan Meteorological Corporation Limited, Earth Science Center, Osaka, Japan, Somnath Mondal, Northeastern University, Civil & Environmental Engineering, Boston, MA, United States, Raju Attada, Indian Institute of Science Education and Research Mohali, Department of Earth and Environmental Sciences, Mohali, India and Somnath Mandal
Using Machine Learning to Understand the Environments of Lightning-Ignited Wildfires in Northern California and their Recent Changes (Invited) (1851079)
L. Ruby Leung1, Sally Sing-Chun Wang2, Yun Qian1 and Richard Grotjahn3, (1)Pacific Northwest National Laboratory, Richland, WA, United States, (2)Pacific Northwest National Laboratory, Richland, United States, (3)University of California Davis, Land, Air and Water Resources, Davis, United States
A Global Database of Glacier Break-offs: Spatio-Temporal Patterns and Implications for Hazard Assessment (1855003)
Ekaterina Bashkova1, Summer Rupper1, Simon Brewer1, Cameron Markovsky1, Richard R Forster1, Savanna Wolvin2, Courtenay Strong3 and Daniel H Shugar4, (1)University of Utah, School of Environment, Society, and Sustainability, Salt Lake City, United States, (2)University of Utah, Department of Atmospheric Sciences, Salt Lake City, UT, United States, (3)University of Utah, Department of Atmospheric Sciences, Salt Lake City, United States, (4)University of Calgary, Geosciences, Calgary, AB, Canada
Investigating Commonalities and Differences between Different Ignition Sources and Their Drivers: A Machine Learning-based Predictive Approach (1857224)
Yavar Pourmohamad, Boise State University, Civil Engineering, Boise, United States, John T Abatzoglou, University of California Merced, Management of Complex Systems, Merced, CA, United States and Moji Sadegh, Boise State University, Boise, United States
Discrepancies in Heat Metrics Across the United States (1891411)
Carly Frank, Purdue University, Department of Earth, Atmospheric, and Planetary Science, West Lafayette, IN, United States and Matthew Huber, Purdue University, Department of Earth, Atmospheric, and Planetary Sciences, West Lafayette, IN, United States
The application of climate projections to predictive failure modeling for electric infrastructure (1900325)
Revathi Muralidharan, Pacific Gas and Electric Company, San Francisco, CA, United States, Eric Kuhle, Pacific Gas and Electric Company, Climate Resilience, Oakland, United States and Olga Kavvada, Pacific Gas and Electric Company, San Francisco, United States
FireConformer: Fine-tuning Continuous Transformer based Weather Forecasting Model for Wildfire Forecasting (1904351)
Hira Saleem, University of New South Wales, Sydney, NSW, Australia, Flora Salim, University of New South Wales, Computer Science, Sydney, Australia and Cormac Purcell, University of New South Wales, Sydney, Australia
Unveiling the Physical Drivers of Short-Term Heat-Cold Compound Extremes with Explainable Machine Unlearning (1908187)
Changqi Sun, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, China, Yuntian Chen, Ningbo Institute of Digital Twin, Eastern Institute of Technology, Ningbo, China and Dongxiao Zhang, Eastern Institute of Technology, Ningbo, China
Assessing the disparities in air conditioning use for heat management across Southern California (1908348)
Diego Ramos Aguilera1, Yishi Wang2, Jiachen Zhang3 and Kelly Sanders2, (1)University of Southern California, Los Angeles, CA, United States, (2)University of Southern California, Civil and Environmental Engineering, Los Angeles, CA, United States, (3)University of Southern California, Department of Civil and Environmental Engineering, Los Angeles, United States
Natural variability was primarily responsible for the elevated January 2025 Los Angeles County fire weather risk (1929807)
Abhishekh Kumar Srivastava, University of California Davis, Land, Air and Water Resources, Davis, CA, United States, Mark Daniel Risser, Lawrence Berkeley National Laboratory, Earth and Environmental Sciences Area, Berkeley, CA, United States, Paul Aaron Ullrich, Lawrence Livermore National Laboratory, PCMDI, Livermore, United States and Paul Ullrich
Patterns and Trends of Wildfire Ignitions, Burned Area and Their Drivers in the Western United States (1935475)
Amirhossein Montazeri, Boise State University, Boise, ID, United States, John T Abatzoglou, University of California Merced, Sierra Nevada Research Institute, Merced, United States, Jeffrey Prestemon, USDA Forest Service, Southern Research Station, Research Triangle Park, United States, Zachary Holden, US Department of Agriculture, Rocky Mountain Research Station, Missoula, United States, Karen Short, US Forest Service Missoula, Missoula, MT, United States, Ata Akbari Asanjan, Universities Space Research Association Moffett Field, Greenbelt, United States and Moji Sadegh, Boise State University, Boise, United States
Using Deep Learning to Constrain Coastal Subsidence with InSAR (1951048)
Rebecca Bussard, Pennsylvania State University, Department of Geosciences, University Park, United States, Christelle Wauthier, The Pennsylvania State University, Department of Geosciences, University Park, United States, Rachel Housego, Pennsylvania State University Main Campus, Department of Geosciences, University Park, United States and Anastasia Piliouras, Pennsylvania State University Main Campus, College of Earth and Mineral Sciences, University Park, PA, United States
River discharge and short-term forecasts of fire risk in Amazon Forests (1951622)
Andrea D de Almeida Castanho1, Douglas C Morton2, Manoela Machado1, Michael Thomas Coe1 and Marcia Macedo1,3, (1)Woodwell Climate Research Center, Falmouth, United States, (2)NASA Goddard Space Flight Center, Greenbelt, United States, (3)Columbia University, Department of Ecology, Evolution, and Environmental Biology and Columbia Climate School, New York, United States
Extreme Humid-Heat Disentangling, Stickiness, and Responses to Local Sea Surface Temperatures in Future Climates of the Arabian Peninsula (1959295)
Daniel Bose, Montana State University, Bozeman, MT, United States and Cascade Tuholske, Montana State University, Department of Earth Sciences, Geospatial Core Facility, Bozeman, United States
Multi-Decadal Assessment of Hydrometeorological Droughts across Ravi River Basin (1960849)
Saadia Hina, Government College University Faisalabad, Department of Environmental Sciences, Faisalabad, Pakistan, Mashal Fatima, Government College University Faisalabad, Faisalabad, Pakistan, Ammara Habib, Urban Sector Policy and Management Services Unit (Pvt.) Limited, Lahore, Pakistan and Adnan Arshad, Lanzhou University, College of Pastoral Agriculture Science and Technology, Lanzhou, China
How Interpretable Machine Learning Advances Our Understanding of Climate Extremes and Their Impacts on Ecosystems and Infrastructure (1960854)
Wenli Zhao1, Biqing Zhu2, Kevin W Bowman3, Jianing Fang1, Guo Yu Qiu4 and Pierre Gentine1, (1)Columbia University, Department of Earth and Environmental Engineering, New York, United States, (2)ETH Swiss Federal Institute of Technology Zurich, Institute of Biogeochemistry and Pollutant Dynamics, Zurich, Switzerland, (3)Jet Propulsion Laboratory, California Institute of Technology, Pasadena, United States, (4)Peking University Shenzhen Graduate School, School of Environment and Energy, Shenzhen, China
Operationalizing AI Weather Forecasts of Monsoon Onset for Farmers in India (1969673)
Katie Kowal1, Colin Aitken2, Rajat Masiwal3, Adam Marchakitus3, Mayank Gupta4, William R Boos5, Amir Jina6, Michael Kremer7 and Pedram Hassanzadeh8, (1)University of Chicago, Data Science Institute, Chicago, United States, (2)University of Chicago, Development Innovation Lab, Chicago, United States, (3)University of Chicago, Department of the Geophysical Sciences, Chicago, United States, (4)University of Chicago, Delhi, India, (5)University of California Berkeley, Department of Earth and Planetary Science, Berkeley, CA, United States, (6)University of Chicago, Harris School of Public Policy, Chicago, United States, (7)University of Chicago, Department of Economics, Development Innovation Lab, Chicago, United States, (8)The University of Chicago, Department of the Geophysical Sciences, Chicago, United States
Vulnerability of U.S. Power Generation to Extreme Weather: A Data-Driven Analysis (1971493)
Yi Lu1, Tao Sun2 and Ram Rajagopal2, (1)Stanford University, Civil and Environmental Engineering, Stanford, CA, United States, (2)Stanford University, Civil and Environmental Engineering, Stanford, United States
Rapid Disaster Response and Damage Estimation with Social Media and Pretrained Large Language Models: Insights from Multiple Hurricanes (1986603)
Bing Zhou1, Lei Zou2, Mingzheng Yang3, Binbin Lin4, Debayan Mandal2, Joynal Abedin2, Heng Cai2, Hao Tian2, Andrew George Klein5 and Shuiwang Ji4, (1)Organization Not Listed, Washington, DC, United States, (2)Texas A&M University, Department of Geography, College Station, United States, (3)Texas A&M University College Station, Department of Geography, College Station, United States, (4)Texas A&M University, College Station, United States, (5)Texas A & M University, Department of Geography, College Station, TX, United States
