NH032-0002
Developing Hydroclimate Risk Quantification with High Resolution Global Climate Modeling

Tuesday, 15 December 2020
Poster
Sarah B Kapnick1, Thomas L Delworth2, William Cooke1, Derek Lemoine3, Surabhi C. Biyani4, Sarah Weidman5, Feiyu Lu6,7, Mitchell Bushuk7, Matt Harrison1, Nathaniel Johnson7, Liwei Jia7, Colleen McHugh8, Hiroyuki Murakami7, Anthony John Rosati1, Kai-Chih Tseng6, Andrew Thorne Wittenberg9, Xiaosong Yang7, Liping Zhang7 and Fanrong Jenny Zeng7,10, (1)Geophysical Fluid Dynamics Laboratory, Princeton, NJ, United States, (2)NOAA/GFDL, Princeton, NJ, United States, (3)University of Arizona, Tucson, AZ, United States, (4)University of Washington Seattle Campus, Atmospheric Sciences, Earth and Space Sciences, Seattle, WA, United States, (5)Massachusetts Institute of Technology, Cambridge, MA, United States, (6)Princeton University, Princeton, NJ, United States, (7)NOAA/Geophysical Fluid Dynamics Laboratory, Princeton, NJ, United States, (8)Science Applications International Corporation, Reston, VA, United States, (9)NOAA GFDL, Princeton, NJ, United States, (10)GFDL, NJ, United States
Abstract:
Extreme weather events regularly cause physical and financial damages. Developing data for extreme weather risk quantification across timescales is critical to both allocate resources to reduce risk exposure and estimate the evolution of risk over time. This information can be utilized for infrastructure decisions and the development of financial products and services to transfer or hedge weather and climate risk. Here, we present a framework for risk analysis using GFDL SPEAR (Seamless System for Prediction and Earth System Research) run at global 50 km atmospheric/land resolution. We highlight how this seamless system, used for both seasonal prediction and climate projections through 2100 can be used to quantify hydroclimate risk and develop risk products within a single framework. Needs for developing methodology and data adoption will be explored.
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