AGU26 call for abstract: OS31 - Prediction and Predictability of Coastal Flooding Risks on Subseasonal-to-Interannual Timescales

[Matt Newman]

We would like to encourage everyone to submit an abstract to session OS031 - Prediction and Predictability of Coastal Flooding Risks on Subseasonal-to-Interannual Timescales - at the upcoming AGU 2026 Fall Meeting in San Francisco.

Session description:

As coastal communities worldwide face growing exposure to flooding risks, providing prediction products across subseasonal-to-interannual timescales becomes more urgent. Meeting this demand requires advancing understanding of how local processes, including tides, storm surge, riverine flooding, and coastally-trapped waves, interact with large-scale climate drivers and rising seas to govern predictability. It also requires bridging the divide from large-scale climate model output to the sub-kilometer scales needed for community-level planning. This session seeks to identify research gaps limiting operational extended-range coastal flood prediction and explore approaches to meeting stakeholder needs. Papers are invited on the prediction and predictability of coastal flooding risks for lead times ranging from two weeks to two years, including contributions on probabilistic forecasting approaches in numerical and statistical models, methods to identify processes and/or phenomena providing high potential skill, new downscaling and postprocessing techniques including machine learning, and end-user perspectives on information uptake and translation needed for planning.

Submit your abstract here; the submission deadline is August 5.

Conveners

Matthew Newman

NOAA Physical Sciences Laboratory

William Sweet

NOAA National Ocean Service

Matthew Widlansky

University of Hawai‘i at Mānoa

Laura McGee

University of Colorado CIRES and NOAA Physical Sciences Laboratory

Cross-Listed

NH - Natural Hazards

GC - Global Environmental Change

Co-organized

Natural Hazards

_________

Matt Newman

Research Physical Scientist

NOAA Physical Sciences Laboratory

Atmosphere-Ocean Processes and Predictability Division

matt....@noaa.gov

(303) 497-6233