LATMOS-IPSL, Université Paris-Saclay, UVSQ, CNRS, 78280, Guyancourt, France *Météo-France, Avenue Coriolis, Toulouse Abstract-- Retrieval of rain from Passive Microwave from about 52,000 images to about 103,000 allowing us radiometers data has been a challenge ever since the to build a training database of 70,000 images for training launch of the first Defense Meteorological Satellite and 33,000 images for validation. Enormous progress has been years 2014 to 2018 and a few months from 2020 and made since the launch of the Tropical Rainfall 2021 are used but the whole year 2019 was kept separate Measuring Mission (TRMM) in 1997 but until for the performance assessment (test) and most results recently the data were processed pixel-by-pixel or presented hereafter are computed for that year. Deep large database is meant to dampen the effects of learning has obtained remarkable improvement in seasonal and interannual variability of rain. the computer vision field, and offers a whole new Second, DRAIN retrieves now a set of 99 quantiles way to tackle the rain retrieval problem. The Global instead of a simple averaged rain rate as in [1]. These Precipitation Measurement (GPM) Core satellite quantiles represent the probability that the rain rate is carries similarly to TRMM, a passive microwave below a certain threshold.