With several seasons of Geostationary Lightning Mapper (GLM), this work revisits incorporating lightning observations into operational tropical cyclone rapid intensification guidance. GLM provides freely available, real-time lightning data over the… Click to show full abstract
With several seasons of Geostationary Lightning Mapper (GLM), this work revisits incorporating lightning observations into operational tropical cyclone rapid intensification guidance. GLM provides freely available, real-time lightning data over the central and eastern North Pacific and North Atlantic oceans. A long-term lightning data set is needed to use GLM in a statistical–dynamical operational application to capture the relationship between lightning and the rare occurrence of rapid intensification. This work uses the World Wide Lightning Location Network (WWLLN) data set from 2005 to 2017 to develop lightning-based predictors for rapid intensification guidance models. The models mimic the operational Statistical Hurricane Intensity Prediction Scheme Rapid Intensification Index and Rapid Intensification Prediction Aid frameworks. The frameworks are averaged to form a consensus as a means to isolate the impact of the lightning predictors. Two configurations for lightning predictors are assessed: a spatial configuration with 0- to 100-km inner-core and 200- to 300-km rainband area for the preceding 6 h predictors and a temporal configuration with an inner-core only for the preceding 0 to 1 h, 0 to 6 h, and 6 to 12 h. When tested on the 2018 to 2021 seasons, the temporal configuration adds skill primarily to the 12–48 h forecasts when compared to the no-lightning version and Rapid Intensification Operational Consensus. When WWLLN is replaced with GLM, minor changes to the prediction are observed suggesting that this approach is suitable for operational applications and provides a new baseline for tropical cyclone lightning-based rapid intensification aids.
               
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