Precipitation estimation from remotely sensed information using artificial neural networks

PERSIANN-CDR: Precipitation Estimation From Remotely Sensed Information Using Artificial Neural Networks-Climate Data Record.

PERSIANN-CDR is a daily quasi-global precipitation product that spans the period from 1983-01-01 to present. The data is produced quarterly, with a typical lag of three months. The product is developed by the Center for Hydrometeorology and Remote Sensing at the University of California, Irvine (UC-IRVINE/CHRS) using Gridded Satellite (GridSat-B1) IR data that are derived from merging ISCCP B1 IR data, along with GPCP version 2.2.

Data and Resources

Additional Info

Field Value
Maintainer NOAA NCDC
Last Updated April 12, 2022, 10:40 (UTC)
Created March 28, 2022, 10:11 (UTC)