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Title: The CHRS Data Portal, an easily accessible public repository for PERSIANN global satellite precipitation data

Journal Article · · Scientific Data
 [1];  [2];  [2]; ORCiD logo [2];  [2];  [2];  [2];  [2];  [2];  [2];  [3];  [4];  [2]
  1. Univ. of California, Irvine, CA (United States); Nong Lam Univ., Ho Chi Minh City (Vietnam); DOE/OSTI
  2. Univ. of California, Irvine, CA (United States)
  3. NOAA Center for Satellite Applications and Research (STAR), MD (United States)
  4. US Army Corps of Engineers, Washington, DC (United States). International Center for Integrated Water Resources Management (ICIWaRM), Inst. for Water Resources

The Center for Hydrometeorology and Remote Sensing (CHRS) has created the CHRS Data Portal to facilitate easy access to the three open data licensed satellite-based precipitation datasets generated by our Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) system: PERSIANN, PERSIANN-Cloud Classification System (CCS), and PERSIANN-Climate Data Record (CDR). These datasets have the potential for widespread use by various researchers, professionals including engineers, city planners, and so forth, as well as the community at large. Researchers at CHRS created the CHRS Data Portal with an emphasis on simplicity and the intention of fostering synergistic relationships with scientists and experts from around the world. The following paper presents an outline of the hosted datasets and features available on the CHRS Data Portal, an examination of the necessity of easily accessible public data, a comprehensive overview of the PERSIANN algorithms and datasets, and a walk-through of the procedure to access and obtain the data.

Research Organization:
Univ. of California, Oakland, CA (United States)
Sponsoring Organization:
USDOE Office of International Affairs (IA); US Army Corps of Engineers; United Nations Educational, Scientific and Cultural Organization (UNESCO); National Oceanic and Atmospheric Administration (NOAA); US Army Research Office (ARO); National Science Foundation (NSF); California Energy Commission
Grant/Contract Number:
IA0000018
OSTI ID:
1613790
Journal Information:
Scientific Data, Journal Name: Scientific Data Journal Issue: 1 Vol. 6; ISSN 2052-4463
Publisher:
Nature Publishing GroupCopyright Statement
Country of Publication:
United States
Language:
English

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Cited By (5)

Precipitation Biases in CMIP5 Models over the South Asian Region journal July 2019
Precipitation Biases in CMIP5 Models over the South Asian Region journal July 2019
Conditional Generative Adversarial Networks (cGANs) for Near Real-Time Precipitation Estimation from Multispectral GOES-16 Satellite Imageries—PERSIANN-cGAN journal September 2019
Satellite Remote Sensing of Precipitation and the Terrestrial Water Cycle in a Changing Climate journal October 2019
FROGS: a daily 1°  ×  1° gridded precipitation database of rain gauge, satellite and reanalysis products journal January 2019