Algorithm and data improvements for version 2.1 of the Climate Hazards center’s InfraRed Precipitation with Stations Data Set

Chris Funk; P. Peterson; Martin Landsfeld; Frank Davenport; A Becker; U Schneider; Diego Pedreros; Amy McNally; Kristi Arsenault; Laura Harrison; S. Shukla

doi:10.1007/978-3-030-24568-9_23

USGS · 70208914

Algorithm and data improvements for version 2.1 of the Climate Hazards center’s InfraRed Precipitation with Stations Data Set

Chris Funk·P. Peterson·Martin Landsfeld·Frank Davenport·A Becker·U Schneider·Diego Pedreros·Amy McNally·Kristi Arsenault·Laura Harrison·S. Shukla

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Abstract

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.

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BibTeX RIS

Chris Funk, P. Peterson, Martin Landsfeld, Frank Davenport, A Becker, U Schneider, Diego Pedreros, Amy McNally, Kristi Arsenault, Laura Harrison, S. Shukla. 2020-04-11. Algorithm and data improvements for version 2.1 of the Climate Hazards center’s InfraRed Precipitation with Stations Data Set. https://doi.org/10.1007/978-3-030-24568-9_23

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