High-Resolution Lightning Detection and Possible Relationship with Rainfall Events over the Central Mediterranean Area

Guido Paliaga,Carlo Donadio,Marina Bernardi,Francesco Faccini

doi:10.3390/rs11131601

Abstract

Lightning activity is usually associated with precipitations events and represents a possible indicator of climate change, even contributing to its increase with the production of NOx gases. The study of lightning activity on long temporal periods is crucial for fields related to atmospheric phenomena from intense rain-related hazard processes to long-term climate changes. This study focuses on 19 years of lightning-activity data, recorded from Italian Lightning Detection Network SIRF, part of the European network EUCLID (European Cooperation for Lightning Detection). Preliminary analysis was dedicated to the spatial and temporal assessment of lightning through detection in the Central Mediterranean area, focusing on yearly and monthly data. Temporal and spatial features have been analyzed, measuring clustering through the application of global Moran’s I statistics and spatial local autocorrelation; a Mann–Kendall trend test was performed on monthly series aggregating the original data on a 5 × 5 km cell. A local statistically significant trend emerged from the analysis, suggesting possible linkage between surface warming and lightning activity.

Highlights

In recent years, research interest in lightning has increased thanks to improved monitoring technology, which makes a huge amount of high-precision data available on an increasing temporal range
We use the term “lightning” to generically indicate atmospheric discharges correlated to convective activity, while we use the term “flash” to indicate the more specific process of a discharge forming from a stepped-leader–return-stroke process
Where: n is the number of geographic entities, that is, the number of cells; xi is the spatial feature at the location I, that is, the count of stroke per cell; X is the xi mean value; Wij is the spatial weight between features i and j; Calculations were done using inverse distance for the weight matrix with a Euclidian metric; results were tested at 99% confidence level, as the null hypothesis was the random spatial distribution of strokes

Summary

Introduction

Research interest in lightning has increased thanks to improved monitoring technology, which makes a huge amount of high-precision data available on an increasing temporal range. Cloud–ground lightning causes damage to buildings, infrastructures, and facilities, wildfires, and even casualties [1]. Thousands of deaths and injuries are caused by lightning every year, and occurrence is more frequent in developing countries where, on average, 150–200 casualties are registered per year. Lightning causes many losses even in industrialized western countries: in the United States, about 100 people die of a lightning stroke every year [13]. We use the term “lightning” to generically indicate atmospheric discharges correlated to convective activity, while we use the term “flash” to indicate the more specific process of a discharge forming from a stepped-leader–return-stroke process (for cloud-to-ground events). For cloud-to-cloud discharges we generically use the term “cloud-cloud events”, without distinction between cloud-to-cloud, intracloud, or cloud-to-air processes

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Conclusion