Abstract
A new method for detecting hailstorms by using all the MHS-like (MHS, Microwave Humidity Sounder) satellite radiometers currently in orbit is presented. A probability-based model originally designed for AMSU-B/MHS-based (AMSU-B, Advanced Microwave Sounding Unit-B) radiometers has been fitted to the observations of all microwave radiometers onboard the satellites of the Global Precipitation Measurements (GPM) constellation. All MHS-like frequency channels in the 150–170 GHz frequency range were adjusted on the MHS channel 2 (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. The application of the hail detection model to the entire GPM constellation 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.
Highlights
Hail detection is an open issue from the remote sensing point of view both from the ground and from space
The potential offered by the Global Precipitation Measurement (GPM) constellation (GPM-C) for monitoring precipitation and severe storms is unprecedented [3,4]
The nearly global climatology of hail developed in this study has shown that the majority of hailstorms develops over South America and the central United States
Summary
Hail detection is an open issue from the remote sensing point of view both from the ground and from space. Spencer et al [6] first correlated the signature from several severe storms over the US to the TB depression at 37 GHz mainly due to the scattering from large falling hail These pioneering studies opened the way to the retrieval of cloud properties using the signal of high-frequency microwave (MW) channels as a proxy to identify convective clouds and detect hail cores [10]. Similar results were found by Ferraro et al [19], who applied a threshold algorithm based on Advanced Microwave Sounding Unit (AMSU)-based data to derive hail occurrences and generate a global climatology of hailstorms over land This investigation demonstrates the sensitivity of frequencies higher than 85 GHz while sampling a wide range of hail diameters. SSeeccttiioonn 44 sshhoowwss aa gglloobbaall ssccaallee aapppplliiccaattiioonn ffoorr ssttuuddyyiinngg tthhee sseeaassoonnaalliittyy ooff hhaaiill ppaatttteerrnnss. We consider three key variables as a source of main displacement between the MHS-like and the MHS radiometers: (1) the sampling frequency, (2) the scan mechanism, and (3) the spatial resolution in terms of the instantaneous field of view (IFOV)
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