An intercomparison of two passive microwave algorithms for snowfall detection over Europe

The proposed work aims to enhance the capabilities of the passive microwave measurements on board NOAA and MetOp satellites for snowfall identification. Two independent methods based on the same sensors (AMSU/MHS) were applied and qualitatively inter-compared during snowstorms over Europe by using the NIMROD radar network as ground truth. The first method developed at NOAA is a statistical algorithm that computes the probability of snowfall using a logistic regression and the principal components of the high frequency brightness temperature measurements at MHS or ATMS channel frequencies 89 GHz and above. The second approach for snowfall detection (183-WSLSF) developed by CNR-ISAC is a prototype based on the preexistent 183-WSL retrieval method. By considering as limit of snowfall formation the rainy clouds located from a few hundred meters to 5-6 km, the 183-WSLSF combines channel sensitivities from 90 and 190 GHz to identify snowfall areas in the precipitating cores.