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Uncertainties in Future U.S. Extreme Precipitation From Downscaled Climate Projections
Author(s) -
LopezCantu Tania,
Prein Andreas F.,
Samaras Constantine
Publication year - 2020
Publication title -
geophysical research letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.007
H-Index - 273
eISSN - 1944-8007
pISSN - 0094-8276
DOI - 10.1029/2019gl086797
Subject(s) - climate change , precipitation , climate extremes , environmental science , resilience (materials science) , climatology , scale (ratio) , data set , magnitude (astronomy) , climate model , meteorology , statistics , geography , mathematics , geology , cartography , oceanography , physics , astronomy , thermodynamics
Impacts modelers and stakeholders use publicly available data sets of downscaled climate projections to assess and design infrastructure for changes in future rainfall extremes. If differences across data sets exist, infrastructure resilience decisions could change depending on which single data set is used. We assess changes in U.S. rainfall extremes from 2044–2099 compared with 1951–2005 based on 227 projections under RCP4.5 and RCP8.5 from five widely used data sets. We show there are large differences in the change magnitude and its spatial structure between data sets. At the continental scale, the data sets show different increases, with high‐end extremes (e.g. 100‐year event) generally increasing more (between 10% and 50%) than low‐end extremes (e.g. 5‐year). These differences largely contribute to the overall uncertainty for small average recurrence intervals (ARIs) extremes (2‐ to 10‐year), while uncertainties due to short record length dominate large ARIs (25‐ to 100‐year). The results indicate that robust infrastructure planning should consider these uncertainties to enable resilient infrastructure under climate change.