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Funk C, Peterson P, Landsfeld M, et al. The climate hazards infrared precipitation with stations--a new environmental record for monitoring extremes. Sci Data. 2015;2:150066doi: 10.1038/sdata.2015.66.
Funk, C., Peterson, P., Landsfeld, M., Pedreros, D., Verdin, J., Shukla, S., Husak, G., Rowland, J., Harrison, L., Hoell, A., & Michaelsen, J. (2015). The climate hazards infrared precipitation with stations--a new environmental record for monitoring extremes. Scientific data, 2150066. https://doi.org/10.1038/sdata.2015.66
Funk, Chris, et al. "The climate hazards infrared precipitation with stations--a new environmental record for monitoring extremes." Scientific data vol. 2 (2015): 150066. doi: https://doi.org/10.1038/sdata.2015.66
Funk C, Peterson P, Landsfeld M, Pedreros D, Verdin J, Shukla S, Husak G, Rowland J, Harrison L, Hoell A, Michaelsen J. The climate hazards infrared precipitation with stations--a new environmental record for monitoring extremes. Sci Data. 2015 Dec 08;2:150066. doi: 10.1038/sdata.2015.66. PMID: 26646728; PMCID: PMC4672685.
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Sci Data. 2015 Dec 08;2:150066. doi: 10.1038/sdata.2015.66.

The climate hazards infrared precipitation with stations--a new environmental record for monitoring extremes.

Scientific data

Chris Funk, Pete Peterson, Martin Landsfeld, Diego Pedreros, James Verdin, Shraddhanand Shukla, Gregory Husak, James Rowland, Laura Harrison, Andrew Hoell, Joel Michaelsen

Affiliations

  1. US Geological Survey, Center for Earth Resources Observation and Science, 47914 252nd St., Sioux Falls, South Dakota 57198, USA.
  2. UC Santa Barbara Climate Hazards Group, Santa Barbara, California 93106, USA.
  3. National Oceanic and Atmospheric Administration Earth Systems Research Laboratory, Boulder, Colarodo 80305, USA.

PMID: 26646728 PMCID: PMC4672685 DOI: 10.1038/sdata.2015.66

Abstract

The Climate Hazards group Infrared Precipitation with Stations (CHIRPS) dataset builds on previous approaches to 'smart' interpolation techniques and high resolution, long period of record precipitation estimates based on infrared Cold Cloud Duration (CCD) observations. The algorithm i) is built around a 0.05° climatology that incorporates satellite information to represent sparsely gauged locations, ii) incorporates daily, pentadal, and monthly 1981-present 0.05° CCD-based precipitation estimates, iii) blends station data to produce a preliminary information product with a latency of about 2 days and a final product with an average latency of about 3 weeks, and iv) uses a novel blending procedure incorporating the spatial correlation structure of CCD-estimates to assign interpolation weights. We present the CHIRPS algorithm, global and regional validation results, and show how CHIRPS can be used to quantify the hydrologic impacts of decreasing precipitation and rising air temperatures in the Greater Horn of Africa. Using the Variable Infiltration Capacity model, we show that CHIRPS can support effective hydrologic forecasts and trend analyses in southeastern Ethiopia.

References

  1. Sci Data. 2015;2:150050 - PubMed
  2. Sci Adv. 2015 Oct 09;1(9):e1500682 - PubMed

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