Abstract

<p>Lightning activity is predicted to increase with global warming, though estimates of lightning sensitivity to a change of temperature vary widely.  Since lightning is a small scale process, it must be represented by parameterizations in climate models. This paper uses large-scale meteorological parameters tied to thunderstorm generation to improve existing empirical models that simulate regional thunderstorm behavior. This study focuses on Tropical America, and uses the ERA5 higher resolution reanalysis data (ERA5) to develop our empirical model.  Thunderstorm data were taken from the World Wide Lightning Location Network (WWLLN) and processed using the clustering algorithm developed by Mezuman et al. (2014). The two meteorological parameters that correlated best with thunderstorm clusters in Tropical America were specific humidity (SH) and convective available potential energy (CAPE).  The resulting empirical model was run from 1979-2019 using ERA5 reanalysis data as input. This approach enables the observation of long-term trends in the behavior of thunderstorms in the regions, in the absence of a complete historical lightning record. To our surprise, Tropical American thunderstorms exhibited a negative trend over this period, with a ~8% decrease in thunderstorm clusters since the 1980s even with a rise of 1K in temperature over the same period. The regions of largest decreases in thunderstorm activity align well with estimates of deforestation.  We estimate that for every 1 Tg C lost due to deforestation, there is a 10% decrease in thunderstorm number.</p>

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