5.2 Integrating Space-Borne Lightning Characteristics and Ground-Based Metrics for Assessing Thunderstorm Intensity

Wednesday, 25 January 2017: 8:45 AM
Conference Center: Tahoma 1 (Washington State Convention Center )
Christopher J. Schultz, NASA/MSFC, Huntsville, AL; and D. J. Cecil, L. D. Carey, P. M. Bitzer, and W. J. Koshak

With the impending deployment of GOES-R, the Geostationary Lightning Mapper (GLM) will provide hemispheric observations of lightning from geostationary orbit over most of the Western Hemisphere. This deployment delivers a new capability to continuously monitor thunderstorm intensity remotely from space; i.e., heritage low-Earth orbit lightning sensors have only provided brief overpasses of developing thunderstorms and hence have lacked the ability to thoroughly monitor and assess thunderstorm intensification.  Most of the work done using space-borne lightning datasets focuses on flash rates, and does not explore sub-flash properties which can also deliver crucial information on thunderstorm intensification. 

This study examines overpasses from the Tropical Rainfall Measuring Mission (TRMM) near Huntsville, AL between 2002 and 2014 that coincide with 89 tracked thunderstorms from a lightning jump algorithm database.  The goal of this study is to intercompare Lightning Imaging Sensor (LIS) and Precipitation Radar (PR) space-borne measurements with ground-based assets (e.g., lightning mapping array data, ground-based radar data, national lightning network data) in order to develop an integrated framework for assessing storm intensity, in preparation for GLM’s deployment in 2017.  The primary focus will be on comparison of lightning flash properties (events, groups, radiances, flash size) and storm intensity at the time of the overpass as viewed from ground-based radar in order to benchmark the rates/intensity of these properties in storms of varying size and morphology.  This work provides a first look into how algorithms for assessing storm intensity can utilize GLM properties beyond flash rates to build a physically-based assessment of storm intensity.

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