PPDIST

PPDIST — Glob­al maps OF the pre­cip­i­ta­tion prob­a­bil­i­ty distribution

The Prob­a­bil­i­ty DIS­Tri­b­u­tion (PPDIST) dataset rep­re­sents a col­lec­tion of glob­al high-res­o­lu­tion (0.1°) obser­va­tion-based cli­ma­tolo­gies (1979–2018) of the occur­rence and peak inten­si­ty of pre­cip­i­ta­tion at dai­ly and 3‑hourly time scales.

The cli­ma­tolo­gies were pro­duced using neur­al net­work ensem­bles and take advan­tage of the strengths of all three main pre­cip­i­ta­tion data sources — satel­lites, reanaly­ses, and gauges — to obtain reli­able esti­mates for the entire globe. For more infor­ma­tion, see the fol­low­ing open-access paper: 

• Beck, H. E., Wes­tra, S., Tan, J., Pap­pen­berg­er, F., Huff­man, G. J., McVicar, T. R., Grün­de­mann, G. J., Ver­gopolan, N., Fowler, H. J., Lewis, E., Ver­bist, K., and Wood, E. F.: PPDIST, glob­al 0.1° dai­ly and 3‑hourly pre­cip­i­ta­tion prob­a­bil­i­ty dis­tri­b­u­tion cli­ma­tolo­gies for 1979–2018, Sci­en­tif­ic Data 7, 302 (2020).

Down­load

The lat­est ver­sion of the PPDIST dataset can be down­loaded here. If the dataset forms a key com­po­nent of your research, we kind­ly ask that you give us the oppor­tu­ni­ty to com­ment on your results pri­or to pub­li­ca­tion. Please see the above-men­tioned paper for details on the dataset. By using the dataset in any pub­li­ca­tion you agree to cite the above-men­tioned paper. 

Acknowl­edge­ments

The PPDIST dataset was devel­oped by Hylke Beck (Prince­ton Uni­ver­si­ty) in col­lab­o­ra­tion with Eric Wood, Seth Wes­tra, Jack­son Tan, Flo­ri­an Pap­pen­berg­er, George Huff­man, Tim McVicar, Gaby Grün­de­mann, Noe­mi Ver­gopolan, Hay­ley Fowler, Eliz­a­beth Lewis, and Koen Ver­bist. The Water Cen­ter for Arid and Semi-Arid Zones in Latin Amer­i­ca and the Caribbean (CAZA­LAC) and the Cen­tro de Cien­cia del Cli­ma y la Resilien­cia (CR) 2 (FON­DAP 15110009) are thanked for shar­ing the Mex­i­can and Chilean gauge data, respec­tive­ly. We also acknowl­edge the gauge data providers in the Latin Amer­i­can Cli­mate Assess­ment and Dataset (LACA&D) project: IDEAM (Colom­bia), INAMEH (Venezuela), INAMHI (Ecuador), SENAMHI (Peru), SENAMHI (Bolivia), and DMC (Chile). We fur­ther wish to thank Ali Ali­jan­ian and Piyush Jain for pro­vid­ing addi­tion­al gauge data. We grate­ful­ly acknowl­edge the devel­op­ers of the pre­dic­tor datasets for pro­duc­ing and mak­ing avail­able their datasets. Hylke Beck was sup­port­ed in part by the U.S. Army Corps of Engi­neers’ Inter­na­tion­al Cen­ter for Inte­grat­ed Water Resources Man­age­ment (ICI­WaRM).