Articles | Volume 9, issue 11
Atmos. Meas. Tech., 9, 5441–5460, 2016
https://doi.org/10.5194/amt-9-5441-2016
Atmos. Meas. Tech., 9, 5441–5460, 2016
https://doi.org/10.5194/amt-9-5441-2016

Research article 14 Nov 2016

Research article | 14 Nov 2016

The new Passive microwave Neural network Precipitation Retrieval (PNPR) algorithm for the cross-track scanning ATMS radiometer: description and verification study over Europe and Africa using GPM and TRMM spaceborne radars

Paolo Sanò et al.

Data sets

STORM-Precipitation Processing System (PPS) NASA https://storm-pps.gsfc.nasa.gov/

STORM-Precipitation Processing System (PPS) NASA ftp://pps.gsfc.nasa.gov/pub/

STORM-Precipitation Processing System (PPS) NASA ftp://arthurhou.pps.eosdis.nasa.gov

Comprehensive Large Array-data Stewardship System (CLASS), JPSS Advanced Technology Microwave Sounder Sensor Data Record (ATMS_SDR) NOAA http://www.nsof.class.noaa.gov/saa/products/search?sub_id=0&datatype_family=ATMS_SDR&submit.x=15&submit.y=8

Download
Short summary
The objective of this paper is to describe the development and evaluate the performance of a totally new version of the Passive microwave Neural network Precipitation Retrieval (PNPR v2), an algorithm based on a neural network approach, designed to retrieve the instantaneous surface precipitation rate using the cross-track ATMS radiometer measurements.