NH036-03
Hail Storm Risk Assessment Using Space-Borne Remote Sensing Observations and Reanalyses
Tuesday, 15 December 2020: 20:45
Virtual
Kristopher M Bedka1, Daniel Cecil2, Sarah D Bang3, Christopher J Schultz4, Jordan R Bell2, Heinz-Jurgen Punge5, Geoffrey Saville6, Konstantin V Khlopenkov7, Kyle Frederick Itterly8, Benjamin R Scarino9, John William Cooney10, Douglas Spangenberg8, Timothy Larson11, Paola Veronica Salio12 and Luciano Vidal13, (1)NASA Langley Research Center, Hampton, VA, United States, (2)NASA Marshall Space Flight Center, Huntsville, AL, United States, (3)University of Utah, Salt Lake City, UT, United States, (4)NASA Marshall Space Flght Ctr, Huntsville, AL, United States, (5)Karlsruhe Institute of Technology, Karlsruhe, Germany, (6)Willis Towers Watson, London, United Kingdom, (7)Sci Systems & Applications Inc, Hampton, VA, United States, (8)Science Systems and Applications, Inc. Hampton, Hampton, VA, United States, (9)Science Systems and Applications, Inc., Hampton, VA, United States, (10)NPP/USRA Post-Doc at NASA Langley Research Center, Hampton, VA, United States, (11)Science Systems and Applications, Inc. Hampton, Hampton, United States, (12)University of Buenos Aires, Atmospheric and Oceanic Sciences, Buenos Aires, Argentina, (13)Servicio Meteorológico Nacional, Buenos Aires, Argentina
Abstract:
Hail is the costliest severe weather hazard for the insurance industry, generating ~70% of severe convective storm losses due to damage to assets such as homes, businesses, agriculture, and infrastructure. Most insurance companies do not reserve enough capital to cover catastrophes, so they acquire reinsurance. The reinsurance industry uses catastrophe models (CatModels) to statistically estimate risk to an insurer’s portfolio. Hail CatModels are developed with climatologies that define hailstorm frequency and severity. Hail-prone areas can be defined using hail reports from trained spotters, the media, and the general public. Hail climatologies are difficult to derive because hail covers small areas and there are neither hail reporting mechanisms (e.g. website or mobile app) nor radar networks in most places outside the US and Europe.
Hail is generated within storms by strong updrafts that exhibit unique signatures in NASA and other agency satellite observations. Geostationary (GEO) visible and infrared imagery has been collected for ~15-25 years across the world and GEO-based methods have been developed at NASA Langley (LaRC) to detect hailstorm updrafts. Hail can also be inferred with passive microwave imagery collected by low-Earth-orbiting sensors such as the GPM GMI and TRMM TMI over the last 20+ years using methods developed at NASA Marshall (MSFC).
This presentation will describe a framework for developing hail climatologies and CatModels based on NASA satellite data and capabilities. This is a collaboration between LaRC and MSFC, WTW, and partners in Brazil, Argentina, and South Africa. South America and South Africa are developing insurance markets of interest to WTW clients, similar to other regions routinely impacted by hail that do not have comprehensive hail reporting. GEO metrics of storm intensity, environmental conditions based on reanalyses, spotter hail reports and radar MESH observations are intercompared to quantify the detectability of hailstorms. We are also maturing methods using land surface imaging satellite data (e.g. Landsat, Sentinel 1/2) to identify hail damage to agriculture. Project datasets will be made available via online GIS-enabled tools developed at the LaRC Atmospheric Science Data Center (ASDC).
