10.2
Using Total Lightning Data to Improve Real-Time Tropical Cyclone Intensity and Genesis Forecasts

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Wednesday, 7 January 2015: 1:45 PM
225AB (Phoenix Convention Center - West and North Buildings)
Andrea B. Schumacher, CIRA/Colorado State Univ., Fort Collins, CO; and M. DeMaria and R. T. DeMaria

A recent study by DeMaria et al. (2012) has shown that lightning information has the potential to improve short-term prediction of tropical cyclone (TC) rapid intensity change. The lightning dataset used in that study, the World Wide Lightning Location Network (WWLLN), primarily detects cloud-to-ground (CG) strikes. However, research suggests that total lightning measurements may provide more useful information concerning convective evolution and hence intensity and structure changes in TCs. Unfortunately, the limited spatial and temporal availability of total lightning data has made it difficult to use in studies of TC evolution to date.

With the impending launch of GOES-R, a new capability for total lightning detection will become available via the onboard Geostationary Lightning Mapper (GLM). The GOES-R GLM will map total lightning activity continuously over the Americas and adjacent ocean regions. In preparation for this new dataset, this study seeks to expand upon the work in DeMaria et al. 2012 and explore the potential for using total lightning data to improve real-time TC intensity and genesis forecasts. As a first step, total lightning data from a relatively new ground-based total lightning network, the Earth Networks Total Lightning Network (ENTLN), will be obtained for cases where TCs are sufficiently close to the detection network and compared with WWLLN data. Then, a calibration procedure developed for the WWLLN data, which involves a comparison with a TRMM-based climatology, will also be performed using the ENTLN data to determine the spatial variability in the detection efficiency. Preliminary results from the comparison and calibration will be presented and plans for incorporating total lightning data into statistical algorithms for TC rapid intensity and genesis will be discussed.

Disclaimer: The views, opinions, and findings contained in this article are those of the authors and should not be construed as an official National Oceanic and Atmospheric Administration (NOAA) or U.S. Government position, policy, or decision.