PPDIST, global 0.1° daily and 3-hourly precipitation probability distribution climatologies for 1979–2018

Hylke E. Beck, Seth Westra, Jackson Tan, Florian Pappenberger, George J. Huffman, Tim R. McVicar, Gaby J. Gründemann, Noemi Vergopolan, Hayley J. Fowler, Elizabeth Lewis, Koen Verbist, Eric F. Wood

Research output: Contribution to journalArticlepeer-review

11 Scopus citations

Abstract

We introduce the Precipitation Probability DISTribution (PPDIST) dataset, a collection of global high-resolution (0.1°) observation-based climatologies (1979–2018) of the occurrence and peak intensity of precipitation (P) at daily and 3-hourly time-scales. The climatologies were produced using neural networks trained with daily P observations from 93,138 gauges and hourly P observations (resampled to 3-hourly) from 11,881 gauges worldwide. Mean validation coefficient of determination (R2) values ranged from 0.76 to 0.80 for the daily P occurrence indices, and from 0.44 to 0.84 for the daily peak P intensity indices. The neural networks performed significantly better than current state-of-the-art reanalysis (ERA5) and satellite (IMERG) products for all P indices. Using a 0.1 mm 3 h−1 threshold, P was estimated to occur 12.2%, 7.4%, and 14.3% of the time, on average, over the global, land, and ocean domains, respectively. The highest P intensities were found over parts of Central America, India, and Southeast Asia, along the western equatorial coast of Africa, and in the intertropical convergence zone. The PPDIST dataset is available via www.gloh2o.org/ppdist.
Original languageEnglish (US)
JournalScientific data
Volume7
Issue number1
DOIs
StatePublished - Dec 1 2020
Externally publishedYes

Bibliographical note

Generated from Scopus record by KAUST IRTS on 2023-02-14

Fingerprint

Dive into the research topics of 'PPDIST, global 0.1° daily and 3-hourly precipitation probability distribution climatologies for 1979–2018'. Together they form a unique fingerprint.

Cite this