文章基本信息

标题：PPDIST, global 0.1 daily and 3-hourly precipitation probability distribution climatologies for 1979-2018
本地全文：下载
作者：Hylke E. Beck ; Seth Westra ; Jackson Tan 等
期刊名称：Scientific Data
电子版ISSN：2052-4463
出版年度：2020
卷号：7
期号：1
页码：1-12
DOI：10.1038/s41597-020-00631-x
语种：English
出版社：Nature Publishing Group
摘要：We introduce the Precipitation Probability DISTribution (PPDIST) dataset, a collection of global high-resolution (0.1掳) observation-based climatologies (1979鈥?018) 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鈥塵m 3鈥塰鈭? 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.