Exploring Lightning and Convective Processes Using the Ground-Radar Multiplatform Precipitation Feature Database

The Multiplatform Precipitation Feature (MPF) database synthesizes coincident spaceborne and ground-based lightning and radar data in a framework of storm-based features, fusing broader spaceborne detection capabilities with process-based, storm-level analysis practices. The MPF database was designed to extend the scale and scope of investigations into the complex connections between precipitation, updrafts, and lightning. The NASA International Space Station Lightning Imaging Sensor (ISS LIS) serves as the source of lightning information for the database. The first iteration of the MPF database leveraged the NASA Global Precipitation Measurement (GPM) mission spaceborne Dual-frequency Precipitation Radar (DPR) to define features, along with contributions of microphysics data and vertical wind retrievals from the GPM Validation Network (VN) of ground-based radar data. The dependency on coincident ISS and GPM satellite overpasses of radars in a dual-Doppler configuration significantly limited the size of the initial database of features, referred to as VNMPFs, but established the database infrastructure and feasibility.

We present here a second iteration of the MPF database that omits the GPM DPR and VN, instead incorporating data directly from selected proximal installations of the operational Next Generation Radar (NEXRAD) network that facilitate vertical wind retrievals via dual-Doppler analysis. These features based exclusively on ground-based polarimetric Doppler radar are hereafter referred to as Ground-Radar MPFs (GRMPFs). Removing the restriction of a coincident GPM overpass appreciably increases the size of the GRMPF database while incorporating more detailed information from higher-resolution radar data and retrievals. This expansion allows for unprecedented broad, robust statistical analyses of the electrical, kinematic, and microphysical characteristics of deep convective processes. These results highlight the potential for advancements in lightning meteorology made possible by combining multiple perspectives from global lightning measurements and ground-based radar data.