# Hailstorm Detection by Satellite Microwave Radiometers
## 2 Data Selection
### The MicroWave Cloud Classification (MWCC) Method  
To better isolate the hail signature the MicroWave Cloud Classification method (hereafter MWCC) [7; 9] was applied. The MWCC originally developed for MHS and now adapted to the ATMS and Special Sensor Microwave Imager/Sounder (SSMIS), exploits the properties of the high frequency channels to classify the cloud type (stratiform/convective) by estimating the cloud top altitude and the phase of hydrometeors. The concept of the MWCC algorithm is based on the probing capability of the MHS channels on the basis of their different weighting function distributions. The MWCC method infers the variation of the nominal signal as observed in clear sky conditions by the spectral channels in the water vapor absorption band at 183.31 GHz. The basic concept is that different stages of cloud formation impacts differently on the channel frequencies at 183.31 GHz. Therefore, the effects of clouds on the MHS water vapor channels can be assessed and capitalized for classifying cloud types according to core-associated scattering. Figure 2 introduces the conceptual scheme of the MWCC. An idealized convection tower (Figure 2a) progressively grows and impacts on the MHS weighting functions (Figure 2b) as a direct effect of its development phase ([6; 41]). Thus, the vertical evolution of convection gradually affects the radiation field around the 183.31 GHz frequencies by \"perturbing\" their nominal signal at different levels in the atmosphere. Generally, clouds peaking in the low and middle atmosphere affect channels at 190 GHz and 186 GHz. Deep convection strongly scatters the incoming radiation by affecting the highest weighting function of the channel at 184 GHz that peaks around 8 km. This signal perturbation depends on the channel characteristics, such as the nominal frequency and the weighting functions, and on the cloud structure in terms of its vertical development and microphysical composition. It is computed and compared with the unperturbed radiation field for deriving cloud information. Thus, the vertical evolution of clouds can be derived by evaluating their penetration in the atmosphere on the basis of the signal depression quantified as a percentage variation of the clear sky radiation field (unperturbed background, TB\({}^{\rm max}\)). Figure 2: Conceptual scheme of the MicroWave Cloud Classification (MWCC) algorithm. (**a**) Artist image describing the impact (\(TB_{i}^{\rm bar}\)) of convection development on each water vapor channel as a function of the height of the peak of the weighting functions; (**b**) channel weighting functions. The MWCC thresholds were statistically calculated from several satellite observations. Radiative transfer simulations were used to support satellite observations in calculating the algorithm offset for reducing the absorption of water vapor which can obscure the signal especially for low level clouds. The signal variation for each frequency is quantified by the variational normalized index  
\[TB_{i}^{var}=ABS\left[\left(\frac{TB_{i}}{TB_{i}^{max}}\right)\times 100-100 \right]i=184,\ 186,\ 190 \tag{1}\]  
measuring the absolute value of the net deviation from the unperturbed background radiation and varying between 0 (unperturbed) and 1 (max perturbation). Hence, all \(TB_{i}^{var}\) indices are merged in a cascade test which routinely calculates the total perturbation (P\({}_{\text{MWCC}}\)) induced by clouds. The algorithm identifies two main cloud types (stratiform and convective) on the basis of the disturbance due to the penetration of cloud tops into the MHS weighting functions. According to the scattering features observed in the stratiform and convective domain the MWCC method classifies further three sub-classes for each cloud type. Figure 3 shows the TB150 (<150 K in the core) map of an intense hailstorm over South Dakota (Vivian). The MWCC retrieval scheme identifies a wide region of deep convections (CO1, red), which includes the main core of the hailstorm.