Algorithm and data improvements for version 2.1 of the Climate Hazards center’s InfraRed Precipitation with Stations Data Set
To support global drought early warning, the Climate Hazards Center (CHC) at the University of California, Santa Barbara developed the Climate Hazards center InfraRed Precipitation with Stations (CHIRPS) dataset, in collaboration with the US Geological Survey and NASA SERVIR. Specifically designed to support early warning applications, CHIRPS has high a spatial resolution (0.05°), a long period of record (1981 to the near present), and relatively low latencies. Here we will describe a brief formal analysis of distributional bias in CHIRPS2.0. This analysis reveals, as expected, that CHIRPS2.0 means are very similar to observed station data. However, a closer look suggests that low precipitation values are underestimated and high values are over-estimated in the CHIRPS2.0. We describe a potential correction for this below.
Citation Information
Publication Year | 2020 |
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Title | Algorithm and data improvements for version 2.1 of the Climate Hazards center’s InfraRed Precipitation with Stations Data Set |
DOI | 10.1007/978-3-030-24568-9_23 |
Authors | Chris Funk, P. Peterson, Martin Landsfeld, Frank Davenport, A Becker, U Schneider, Diego Pedreros, Amy McNally, Kristi Arsenault, Laura Harrison, S. Shukla |
Publication Type | Book Chapter |
Publication Subtype | Book Chapter |
Index ID | 70208914 |
Record Source | USGS Publications Warehouse |
USGS Organization | Earth Resources Observation and Science (EROS) Center |