Extreme precipitation can cause flooding, result in substantial damages and have detrimental effects on ecosystems(1,2). Climate adaptation must therefore account for the greatest precipitation amounts that may be expected over a certain time span(3). The recurrence of extreme-to-heavy precipitation is notoriously hard to predict, yet cost-benefit estimates of mitigation and successful climate adaptation will need reliable information about percentiles for daily precipitation. Here we present a new and simple formula that relates wet-day mean precipitation to heavy precipitation, providing a method for predicting and downscaling daily precipitation statistics. We examined 32,857 daily rain-gauge records from around the world and the evaluation of the method demonstrated that wet-day precipitation percentiles can be predicted with high accuracy. Evaluations against independent data demonstrated high skill in both space and time, indicating a highly robust methodology.
Benestad, RE; Nychka, D; Mearns, LO
Spatially and temporally consistent prediction of heavy precipitation from mean values
Nature Climate Change