# Hailstorm Detection by Satellite Microwave Radiometers
## 5 Application Examples  
The performances of MWCC-Hail will be displayed by applying the model to several hailstorms characterized by different regime of severity. The aim of this section is showing the sensitivity of the detector to different hail conditions by prospecting its employing in reconstructing the hail patterns on the global scale. Accordingly, probability values lower than 0.36 are classified as no hail, values in the range 0.36-0.60 are associated to hail, and probabilities greater than 0.60 are associated to the super hail category.  
Thus, we propose a series of examples where the MWCC-Hail will be experimentally applied to all MHS-like radiometers currently flying on the GPM constellation. Although the well-known technical differences between the MHS-like radiometers and MHS (reference instrument) the present outcomes demonstrate the high skills of model in identifying hail clouds and discern hail size on the basis of likelihood values. These results have then stimulated new studies where the hail detection  
Figure 11: (**a**) March, (**b**) May, (**c**) June and (**d**) September scatter plots for the mean 2000–2011 maps of Figure 10.  
model described by Equation (4) will be recalibrated to fit better the instrumental characteristic of the MHS-like radiometers by improving the current retrievals.  
Figure 12 shows some of the hail events reported in Table 1. In all plates it can be seen the capability of model to identify the convective cores where the presence of hail is detected. All of these events were characterized by a hail-train clusters where the diameters significantly change.  
The retrievals show that the highest severity is registered over South Dakota where hail probability reaches 0.80 (super hail) in the smaller cores and 0.70 in the surroundings. The other cases can be classified from moderate to severe hailstorms due to the high values of hail probability reaching the maximum of 0.70 over Argentina and the lowest values (0.40-0.50) retrieved over Colorado-New Mexico. Noteworthy the event over Minnesota-North Dakota exhibiting two different hail regimes: probability values 0.50-0.60 over North Dakota typically associated to large hail and values around 0.40 over Minnesota which delineate smaller hail diameters.  
Figure 13 documents the first experiment where the MWCC-Hail is applied to the GPM constellation. Since not all satellites covers the same event we evaluate the performances of detection by using two separate hailstorms. Applying the MWCC-Hail to the GMI data on the heavy hailstorm over Naples on 5 September 2015 (Figure 13a) we can note as the severity of the event is fully captured by the model which identifies the intensity of each hail cluster. The borders of system are flagged by hail probability close to 0.50 while the main core of deep convection reaches values over than 0.90 which is associated to super hail as well documented by surface hail reports.  
Figure 12: Hail probability as calculated by the MWCC-Hail for hailstorms over (**a**) Argentina (Colonia) 13 Nov 2017 2136 UTC, (**b**) South Dakota (Charles) 21 Aug 2007 2341 UTC, (**c**) Colorado–New Mexico 9 May 2017 0337 UTC, and (**d**) Minnesota–North Dakota 10 Jun 2017 0237 UTC.  
On 10 July 2019 the Adriatic coast of Italy was hit by a long sequence of severe storms triggered from the early morning in the North-East part of Italy and dissolved during the night over Greece. The series of deep convections rapidly evolved in severe hailstorms is well-reconstructed by the MWCC-Hail when applied to MHS-like radiometers of the GPM constellation. The SSMIS caught the very large hail hitting the city of Milano Marittima (Figure 13b, hail probability: 0.80) while the ATMS identified the hail cloud over the city of Pescara (Figure 13c, hail probability: 0.60), and finally the MHS, used as a reference target, spotted the system traveling from Italy to Greece detecting a super hail cloud over Albania (Figure 13d).