Evaluation of lightning potential at antarctic peninsular using weather and research forecasting and thermodynamic indices

Abstract

It is needless to state that the economic effects of natural hazards are very severe. Thus, improving the accuracy of prediction of such events is imperative in this era of changing climate. Although the development of numerical prediction methods of such events is an active research field in Meteorology and Atmospheric Sciences, there is an apparent lack of studies in the area of lightning events which have substantial destructive effects on human life and properties. In this work, an attempt is made to identify the ability of the Advanced Research Weather Research and Forecast (WRF-ARW) model to efficiently simulate the Lightning Potential Index (LPI), a recently developed index for lightning predictions. A four-year data (2013-2017) is considered in this study at the selected location of study (Carlini’s base, Antarctica). Although lightning occurrences are not as extensively reported in the polar regions like Antarctica compared to the tropics, their inevitable presence can potentially harm local residents and research stations, motivating the development of the current model. The recently released WRF v4.0 was used in this study, where the model was nested in two-way, coarse grid resolution of 25 km by 25 km grids. The simulated LPI was validated using correlation and regression analysis with the Worldwide Lightning Location Network (WWLLN) data. The present study found that the LPI is fairly correlated to the observed yearly lightning flash counts (maximum correlation coefficient, R of 0.51) despite having some notable differences due to the weakness of both the WRF model and WWLLN data. Nonetheless, the qualitative predictions showed some meaningful results, including regions of high lightning propensity (coordinates of (-59.0, -62.5) and (-58.0, -62.0)) and seasons of high lightning occurrences (autumn and spring). This early scientific knowledge can potentially protect the local residents, research stations, and hardworking scientists. Thus, with considerable future improvements (addition of details about the complexity of the south pole, including strong katabatic winds and icy Antarctic clouds), the current model can be used to improve lightning forecast events in the future.