Hail detection from high-frequency radiometers on the GPM constellation. A new prospect for a global hailstorm climatology

<p>Hail detection is an open issue from the remote sensing point of view both from the ground and from space. Hail is extremely difficult to observe using passive and active sensing due to signal attenuation and the relatively scarce knowledge of the cloud structure in hailstorms. Several approaches have been recently proposed mainly using radar data from the ground in connection with observations in the visible and infrared from geostationary satellites. High frequency MWs aboard to airborne and satellite were also used to infer hail patterns. The potential of the 90–190 GHz frequency range when employed in the classification of cloud types and in the detection of signals from different hail sizes was recently proved by Laviola et al. 2020 and Ferraro et al. (2020) extending previous approaches to these frequencies that are now available on several platforms. MW high frequencies offer the advantage of very high sensitivity to the scattering signature from different ice particles with diameters from a few millimeters to 10s of centimeters. Thus, we are able to classify the region of convective clouds where different hail sizes are generated by identifying severity areas characterized by small ice aggregates potentially forming hail, large hail and super hail. In this work, a probability-based model originally designed for AMSU-B/MHS (Laviola et al, 2020) has been fitted to the observations of all MHS-like radiometers onboard the satellites of the GPM constellation. All MHS-like frequency channels in the 150-170 GHz frequency range were adjusted on the MHS channel at 157 GHz in order to account for the instrumental differences and tune the original model on the MHS-like technical characteristics. The novelty of this approach offers the potential of retrieving a uniform and homogeneous hail dataset on the global scale. Currently running on 10 MHS-like radiometers orbiting on the GPM constellation, the application of the hail detection model demonstrates the high potential of this generalized model to map the evolution of hail-bearing systems at very high temporal rate. The results on the global scale also demonstrate the high performances of the hail model in detecting the differences of hailstorm structure across the two hemispheres by means of a thorough reconstruction of the seasonality of the events particularly in South America where the largest hailstones are typically observed.</p>