Abstract

The integration of satellite-borne and ground-based global lightning location networks offers a better perspective to study lightning processes and their evolutionary characteristics within thunderstorm clouds, thereby bolstering the predictive capabilities for severe weather phenomena. Currently, the satellite-borne network is in the preliminary testing phase with a single satellite. The geographic locations of single-satellite detection events primarily rely on synchronous information from coincident ground-based network events; this method is called synchronous locating (SCL). However, variations in detection-frequency bands and system capabilities prevent this method from accurately locating more than a mere 10% of events. To address this limitation, this paper introduces a cluster-analysis-based strategy, utilizing the observations from the Worldwide Lightning Location Network (WWLLN), termed the cluster analysis locating (CAL) method. The CAL method’s performance, influenced by the density-based spatial clustering of applications with noise (DBSCAN), the K-means, and the mean shift algorithms, is examined. Subsequently, an advanced version, mean shift denoised (MSDN)-CAL, is proposed, demonstrating marked improvements in location accuracy and reliability over the other CAL methods. The satellite-borne wideband electromagnetic pulse detector (WEMPD), orbiting at an altitude of approximately 500 km with a 97.5° inclination, captured 1061 strong electromagnetic pulses (EMPs). Among these, trans-ionospheric single pulses (TISPs) and trans-ionospheric pulse pairs (TIPPs) constituted 21.30% and 78.70%, respectively. Using the MSDN-CAL method successfully determines the geographic locations for 81.15% (861 out of 1061) of the events. This success rate represents an approximate eightfold enhancement over the SCL method. The arithmetic mean, geometric mean, and standard deviation of the two-dimensional range deviation of the locating results between the MSDN-CAL method versus the WWLLN-SCL (or the Guangdong-Hong Kong-Macao Lightning Location System (GHMLLS)-SCL) method are 51.06 (176.26) km, 16.17 (92.53) km, and 100.95 (174.79) km, respectively. Furthermore, it has been possible to estimate the occurrence altitudes for 81.92% (684 out of 835) of the TIPP events. The altitude deviations, as determined by comparing them with the GHMLLS-SCL method’s locating results, exhibit an arithmetic mean of 2.08 km, a geometric mean of 1.30 km, and a standard deviation of 2.26 km. The outcomes of this research establish a foundation for deeper investigation into the origins of various event types, their seasonal variations, and their geographical distribution patterns. Moreover, they pave the way for utilizing a single satellite to measure global surface reflectance, thus contributing valuable data for meteorological and atmospheric studies.

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