Multi-sensor Approach for Satellite Hail Advection (MASHA): a new technique to support the nowcasting of hailstorms

The Multi-sensor Approach for Satellite Hail Advection (MASHA) is a new multi-instrument technique conceived for real-time tracking of hail-bearing clouds. MASHA can identify hail clouds from satellite measurements and monitor the evolution of hail-bearing systems every 5 min, combining the strength of the MicroWave Cloud Classification-Hail (MWCC-H) method to detect hail through the whole GPM sensor constellation (Laviola et al., 2020a-b) with the high temporal rate of the Meteosat Rapid Scan Service (MSG-RSS). This opens the way to operational applications of MASHA method by offering an unprecedented support to the nowcasting of hailstorms and to regional numerical weather predictions.Recent applications experimented the ingestion in the MASHA scheme of lightning strikes and radar hail indices. This new configuration of the final products significantly refines the reconstruction of hail maps when the GPM constellation overpasses are missing. The result is a near-real time, more consistent and high-resolution hail map described by a proper Hail Severity Index (HSI). Recent applications demonstrate the ability of the MASHA technique to identify severe flash flood events in mountain catchments. These results draw new perspectives to optimally investigate hydro-meteorological events over mountain areas where more traditional methodologies might underestimate the severity of events. Thus, the MASHA scheme provides a useful tool in support to nowcasting systems of hailstorms and severe weather over complex areas.ReferencesLaviola S., V. Levizzani, R. R. Ferraro, and J. Beauchamp: Hailstorm Detection by Satellite Microwave Radiometers. Remote Sens. 2020a, 12(4), 621; https://doi.org/10.3390/rs12040621.Laviola S., G. Monte, V. Levizzani, R. R. Ferraro, and J. Beauchamp: A new method for hail detection from the GPM constellation. A prospective for a global hailstorm climatology. Remote Sens. 2020b, 12(21), 3553; https://doi.org/10.3390/rs12213553.