12Lightning Creating a Combined Lightning Product for Operational Use in the Multi-Radar/Multi-Sensor System

The Multi-Radar/Multi-Sensor System (MRMS) system combines a wide array of meteorological data, including from radar, surface and upper air observations, numerical weather prediction models, and satellite and ground based observing platforms. These synthesized data assist with decision-making around hazardous weather conditions in multiple applications and sectors. At present, the MRMS includes lightning data from a single ground-based detection network. In order to better meet lightning awareness goals for aviation over the contiguous United States, an updated combined lightning product is being developed to present a more complete picture of lightning occurrence. The new product fuses data from the satellite-borne GOES-East Geostationary Lightning Mapper (GLM) with lightning detections from the ground-based National Lightning Detection Network (NLDN) and Earth Networks Total Lightning Network (ENTLN), taking advantage of their diverse observing technologies that preferentially capture different elements of the lightning flash process.

The first step toward effective combination of lightning data requires geolocation to a unifying grid. While ground-based detections of lightning radio emissions are geolocated with relative ease and accuracy, GLM data suffer from parallax, or an apparent shift in the location of detected lightning as a result of the instrument viewing angle. Parallax correction to determine accurate ground-referenced GLM lightning locations requires knowledge of the emission height of detected light, often assumed to be the tops of clouds. A standard optimal cloud-top height ellipsoid is used for speed in real-time applications, though other cloud-top height models exist for GLM parallax correction, including the Virts & Koshak (2020) monthly optimal emitter height data and GOES-R Series Advanced Baseline Imager cloud-top height retrievals. A new local adaptive parallax correction method for GLM data will be demonstrated, as part of which detections from the ENTLN and NLDN are used to make a more informed selection of the cloud-top height model used to determine the ground-referenced location of GLM lightning detections. Once geolocated and combined, the resultant data deliver more widespread and complete information about lightning occurrence than any individual network or instrument, including lightning flash location, number of connections to ground, frequency, density, polarity, extent, and duration. This work will also explore methods of condensing relevant information from the varying datasets into an effective display that better informs about lightning hazards and assists with convective interpretation.