GSDR: A Global Sub-Daily Rainfall Dataset

作者：Elizabeth A. Lewis, Hayley Jane Fowler, Lisa V. Alexander, Robert Dunn, Fergus McClean, Renaud Barbero, Selma B. Guerreiro, Xiaofeng Li, Stephen Blenkinsop · 发表于：Journal of Climate · 年份：2019 · DOI：10.1175/jcli-d-18-0143.1 · 被引用次数：123 · 研究领域：Climate variability and models、Meteorological Phenomena and Simulations、Precipitation Measurement and Analysis

Abstract Extreme short-duration rainfall can cause devastating flooding that puts lives, infrastructure, and natural ecosystems at risk. It is therefore essential to understand how this type of extreme rainfall will change in a warmer world. A significant barrier to answering this question is the lack of sub-daily rainfall data available at the global scale. To this end, a global sub-daily rainfall dataset based on gauged observations has been collated. The dataset is highly variable in its spatial coverage, record length, completeness and, in its raw form, quality. This presents significant difficulties for many types of analyses. The dataset currently comprises 23 687 gauges with an average record length of 13 years. Apart from a few exceptions, the earliest records begin in the 1950s. The Global Sub-Daily Rainfall Dataset (GSDR) has wide applications, including improving our understanding of the nature and drivers of sub-daily rainfall extremes, improving and validating of high-resolution climate models, and developing a high-resolution gridded sub-daily rainfall dataset of indices.