TY - JOUR
T1 - Toward Narrowing Uncertainty in Future Projections of Local Extreme Precipitation
AU - Marra, Francesco
AU - Armon, Moshe
AU - Adam, Ori
AU - Zoccatelli, Davide
AU - Gazal, Osama
AU - Garfinkel, Chaim I.
AU - Rostkier-Edelstein, Dorita
AU - Dayan, Uri
AU - Enzel, Yehouda
AU - Morin, Efrat
N1 - Publisher Copyright:
© 2021. American Geophysical Union. All Rights Reserved.
PY - 2021/3/16
Y1 - 2021/3/16
N2 - Projections of extreme precipitation based on modern climate models suffer from large uncertainties. Specifically, unresolved physics and natural variability limit the ability of climate models to provide actionable information on impacts and risks at the regional, watershed and city scales relevant for practical applications. Here, we show that the interaction of precipitating systems with local features can constrain the statistical description of extreme precipitation. These observational constraints can be used to project local extremes of low yearly exceedance probability (e.g., 100-year events) using synoptic-scale information from climate models, which is generally represented more accurately than the local scales, and without requiring climate models to explicitly resolve extremes. The novel approach, demonstrated here over the south-eastern Mediterranean, offers a path for improving the predictability of local statistics of extremes in a changing climate, independent of pending improvements in climate models at regional and local scales.
AB - Projections of extreme precipitation based on modern climate models suffer from large uncertainties. Specifically, unresolved physics and natural variability limit the ability of climate models to provide actionable information on impacts and risks at the regional, watershed and city scales relevant for practical applications. Here, we show that the interaction of precipitating systems with local features can constrain the statistical description of extreme precipitation. These observational constraints can be used to project local extremes of low yearly exceedance probability (e.g., 100-year events) using synoptic-scale information from climate models, which is generally represented more accurately than the local scales, and without requiring climate models to explicitly resolve extremes. The novel approach, demonstrated here over the south-eastern Mediterranean, offers a path for improving the predictability of local statistics of extremes in a changing climate, independent of pending improvements in climate models at regional and local scales.
KW - climate change
KW - extreme precipitation
KW - global climate model projection
KW - impact studies
KW - south-eastern Mediterranean
UR - http://www.scopus.com/inward/record.url?scp=85102485908&partnerID=8YFLogxK
U2 - 10.1029/2020GL091823
DO - 10.1029/2020GL091823
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AN - SCOPUS:85102485908
SN - 0094-8276
VL - 48
JO - Geophysical Research Letters
JF - Geophysical Research Letters
IS - 5
M1 - e2020GL091823
ER -