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

Sanò, Paolo; Panegrossi, Giulia; Casella, Daniele; Marra, Anna C.; Di Paola, Francesco; Dietrich, Stefano

doi:https://doi.org/10.5194/amt-9-5441-2016

Articles | Volume 9, issue 11

https://doi.org/10.5194/amt-9-5441-2016

© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

https://doi.org/10.5194/amt-9-5441-2016

© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Articles | Volume 9, issue 11

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, Giulia Panegrossi, Daniele Casella, Anna C. Marra, Francesco Di Paola, and Stefano Dietrich

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

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.