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The lat­est ver­sion is V1.2 (released Novem­ber 28, 2016)

Mul­ti-Source Weight­ed-Ensem­ble Pre­cip­i­ta­tion (MSWEP) ret­ro­spec­tive is a new ful­ly glob­al pre­cip­i­ta­tion dataset (1979–2015) with a high 3-hourly tem­po­ral and 0.25° spa­tial res­o­lu­tion (Beck et al., 2016). The dataset is unique in that it takes advan­tage of a wide range of data sources, includ­ing gauges, satel­lites, and atmos­pher­ic reanaly­sis mod­els, to obtain the best pos­si­ble pre­cip­i­ta­tion esti­mates at glob­al scale.

MSWEP has been val­i­dat­ed at glob­al scale using hydro­log­i­cal mod­el­ing for approx­i­mate­ly 9000 catch­ments and using inde­pen­dent pre­cip­i­ta­tion data from 125 FLUXNET sta­tions. The dataset was found to per­form favor­ably com­pared to pop­u­lar gauge-adjust­ed pre­cip­i­ta­tion datasets such as CPC Uni­fied, TMPA 3B42, GPCP-1DD, and WFDEI-CRU. MSWEP was select­ed as the main pre­cip­i­ta­tion forc­ing for the state-of-the-art evap­o­ra­tion mod­el GLEAM and for Tier-2 of the EU-FP7 project eartH­2Ob­serve. For more infor­ma­tion about MSWEP, see the fol­low­ing open-access paper:

The lat­est MSWEP tech­ni­cal doc­u­men­ta­tion, includ­ing the ver­sion his­to­ry and exam­ples on how to read the data with MAT­LAB and Python, can be viewed here.

Down­load

By using MSWEP in any pub­li­ca­tion you agree to cite Beck et al. (2016). Please read the tech­ni­cal doc­u­men­ta­tion care­ful­ly before attempt­ing to use the data. The ocean esti­mates pro­vid­ed since V1.2 are exper­i­men­tal and should be used at your own risk. The MSWEP mean annu­al pre­cip­i­ta­tion map is avail­able here. The map of CHP­clim bias cor­rec­tion fac­tors is avail­able here. Enter your name and email address to receive the FTP address for down­load­ing the data.

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Acknowl­edge­ments

princeton-university-logoMSWEP may not be used for com­mer­cial or busi­ness appli­ca­tions. MSWEP is being devel­oped by Hylke Beck (Prince­ton Uni­ver­si­ty, Prince­ton, USA) in col­lab­o­ra­tion with Albert van Dijk (ANU, Can­ber­ra, Aus­tralia), Ad de Roo (JRC, Ispra, Italy), Vin­cen­zo Lev­iz­zani (CNR-ISAC, Bolog­na, Italy), Jaap Schellekens (Deltares, Delft, The Nether­lands), Diego Miralles (VU Uni­ver­si­ty Ams­ter­dam, The Nether­lands), and Brecht Martens (Ghent Uni­ver­si­ty, Bel­gium). We grate­ful­ly acknowl­edge the pre­cip­i­ta­tion dataset devel­op­ers for pro­duc­ing and mak­ing their datasets avail­able. The Glob­al Runoff Data Cen­tre (GRDC) and the U.S. Geo­log­i­cal Sur­vey (USGS) are thanked for pro­vid­ing most of the observed stream­flow data.  We would also like to thank the FLUXNET com­mu­ni­ty for pro­vid­ing the pre­cip­i­ta­tion data. This research received fund­ing from the Euro­pean Union Sev­en­th Frame­work Pro­gram­me (FP7/2007–2013) under grant agree­ment no. 603608, “Glob­al Earth Obser­va­tion for inte­grat­ed water resource assess­ment”: eartH­2Ob­serve. By using MSWEP in any pub­li­ca­tion you agree to cite Beck et al. (2016).