Seasonal Predictability of Lightning over the Global Hotspot Regions

TL;DR

This study demonstrates that lightning occurrence over global hotspots can be predictably linked to global climate patterns like El Nino, enabling reliable seasonal forecasts for risk mitigation.

Contribution

It reveals the strong connection between global climate modes and seasonal lightning variability, providing a new approach for lightning prediction.

Findings

Lightning predictability is comparable to rainfall.

Global predictors like ENSO influence lightning variability.

Seasonal forecasting of lightning is feasible with current models.

Abstract

Skillful seasonal prediction of lightning is crucial over several global hotspot regions, as it causes severe damages to infrastructures and losses of human life. While major emphasis has been given for predicting rainfall, prediction of lightning in one season advance remained uncommon, owing to the nature of the problem, which is short-lived local phenomenon. Here we show that on the seasonal time scale, lightning over the major global hot-spot regions is strongly tied with slowly varying global predictors (e.g., El Nino and Southern Oscillation). Moreover, the sub-seasonal variance of lightning is highly correlated with global predictors, suggesting a seminal role played by the global climate mode in shaping the local land-atmosphere interactions, which eventually affects seasonal lightning variability. It is shown that the seasonal predictability of lightning over the hotspot is comparable to that of seasonal rainfall, which opens up an avenue for reliable seasonal forecasting of lightning for special awareness and preventive measures. Keywords: Lightning, Seasonal forecasting, SST, Global predictors