文章基本信息

标题：Advancing early warning capabilities with CHIRPS-compatible NCEP GEFS precipitation forecasts
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作者：Laura Harrison ; Martin Landsfeld ; Greg Husak 等
期刊名称：Scientific Data
电子版ISSN：2052-4463
出版年度：2022
卷号：9
期号：1
页码：1-13
DOI：10.1038/s41597-022-01468-2
语种：English
出版社：Nature Publishing Group
摘要：CHIRPS-GEFS is an operational data set that provides daily bias-corrected forecasts for next 1-day to ~15-day precipitation totals and anomalies at a quasi-global 50-deg N to 50-deg S extent and 0 .05-degree resolution . These are based on National Centers for Environmental Prediction (NCEP) Global Ensemble Forecast System version 12 (GEFS v12) precipitation forecasts . CHIRPS-GEFS forecasts are compatible with Climate Hazards center InfraRed Precipitation with Stations (CHIRPS) data, which is actively used for drought monitoring, early warning, and near real-time impact assessments . A rank- based quantile matching procedure is used to transform GEFS v12 “reforecast” and “real-time” forecast ensemble means to CHIRPS spatial-temporal characteristics . Matching distributions to CHIRPS makes forecasts better refect local climatology at fner spatial resolution and reduces moderate-to-large forecast errors . As shown in this study, having a CHIRPS-compatible version of the latest generation of NCEP GEFS forecasts enables rapid assessment of current forecasts and local historical context . CHIRPS-GEFS efectively bridges the gap between observations and weather predictions, increasing the value of both by connecting monitoring resources (CHIRPS) with interoperable forecasts .