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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Acknowledgements
This paper has benefited greatly from the expert technical editing of Juliet Way-Henthorne and an internal review by Will Turner. This research was supported by the U.S. Geological Survey’s Drivers of Drought program and Cooperative agreement G14 AC00042, SERVIR-AST grant: NNH15ZDA001N-SERVIR, the NASA Harvest Program grant Z60592017, and the NSF INFEWS/T1 project 2003169999: Understanding multi-scale resilience options for climate-vulnerable Africa. We gratefully acknowledge the support of the Defense Advanced Research Projects Agency (DARPA) World Modelers Program under Army Research Office (ARO) prime contract no. W911NF-18-C-0012. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the view of DARPA, ARO, or the US government.
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Funk, C. et al. (2020). Algorithm and Data Improvements for Version 2.1 of the Climate Hazards Center’s InfraRed Precipitation with Stations Data Set. In: Levizzani, V., Kidd, C., Kirschbaum, D.B., Kummerow, C.D., Nakamura, K., Turk, F.J. (eds) Satellite Precipitation Measurement. Advances in Global Change Research, vol 67. Springer, Cham. https://doi.org/10.1007/978-3-030-24568-9_23
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