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

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Source https://developers.google.com/earth-engine/datasets/catalog/NOAA_PERSIANN-CDR?hl=en#terms-of-use
Author NOAA NCDC
Maintainer NOAA NCDC
Last Updated April 12, 2022, 10:40 (UTC)
Created March 28, 2022, 10:11 (UTC)