Documentation

Summary

This product, developed at Chalmers University of Technology (Sweden), provides probabilistic retrievals of precipitation over Africa by an artificial neural network. The network consists of a fully convolutional, quantile regression neural network, trained and evaluated using nearly four years of collocations of SEVIRI level 1.5 data and the GPM DPR and GMI Combined Precipitation L2B. The network infers the precipitation probability distribution for each pixel in SEVIRI image, using all thermal infrared channels and the satellite zenith angle. This enables retrievals independent of the time of day.

Paper

Amell, A., Hee, L., Pfreundschuh, S., Eriksson, P.: Probabilistic near real-time retrievals of Rain over Africa using deep learning. DOI: 10.22541/essoar.173867530.07619555/v1

Code

The code for executing Rain over Africa retrievals is available on GitHub.

We can also offer a full retrieval pipeline.