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

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          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.

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          Most cited references57

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          Representing Twentieth-Century Space–Time Climate Variability. Part I: Development of a 1961–90 Mean Monthly Terrestrial Climatology

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            Evaluation of PERSIANN System Satellite–Based Estimates of Tropical Rainfall

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                Author and article information

                Journal
                Sci Data
                Sci Data
                Scientific Data
                Nature Publishing Group
                2052-4463
                08 December 2015
                2015
                : 2
                : 150066
                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
                Author notes
                [a ] C.F. (email: cfunk@ 123456usgs.gov
                []

                C.F. designed the CHIRPS algorithm and analyzed the hydrologic simulations. P.P. wrote, and runs, the CHIRPS estimation procedures and provided the CHIRPS validations. M.L. processed and quality controlled the input station data. D.P. assisted with validation and quality control. J.V. helped conceive and design the CHIRPS product. S.S. ran the hydrologic simulations and assessed the daily CHIRPS. G.H. assisted with validation and quality control. J.R. helped conceive and design the CHIRPS product. L.H. assisted with validation and quality control and assessed the daily CHIRPS. A.H. helped with the diagnostic climate analyses. J.M. helped design the CHIRPS algorithm.

                Article
                sdata201566
                10.1038/sdata.2015.66
                4672685
                26646728
                43652668-fb3e-4b1c-aed7-2c9993ff850a
                Copyright © 2015, Macmillan Publishers Limited

                This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0 Metadata associated with this Data Descriptor is available at http://www.nature.com/sdata/ and is released under the CC0 waiver to maximize reuse.

                History
                : 23 July 2015
                : 13 October 2015
                Categories
                Data Descriptor

                climate-change impacts,hydrology,environmental sciences,attribution,atmospheric dynamics

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