TY - JOUR
T1 - Nonstationary extreme precipitation in Brazil
AU - Cortez, Bianca Nespoli
AU - Pires, Gabrielle Ferreira
AU - Avila-Diaz, Alvaro
AU - Fonseca, Humberto Paiva
AU - Oliveira, Lais Rosa
N1 - Funding Information:
This work was supported by Coordenação de Aperfeiçoamento de Pessoal de Nível Superior— Brasil (CAPES) [Finance Code 001]; and Conselho Nacional de Desenvolvimento Científico e Tecnológico - Brasil - (CNPq) [Process 171021/2018-5]. The authors thank the graduate programme in Applied Meteorology at the Federal University of Viçosa. This study was supported by The National Council for Scientific and Technological Development (CNPq) and the Coordination of Training of Higher Education Personnel (CAPES). AAD also acknowledges the financial support received from the CNPq post-doctoral programme. The authors are thankful for the downscaled climate simulations generated by CPTEC/INPE and made available on the PROJETA platform, and we appreciate the NEX-GDDP dataset, prepared by the Climate Analytics Group and NASA Ames Research Center using the NASA Earth Exchange, and distributed by the NASA Center for Climate Simulation (NCCS).
Funding Information:
The authors thank the graduate programme in Applied Meteorology at the Federal University of Viçosa. This study was supported by The National Council for Scientific and Technological Development (CNPq) and the Coordination of Training of Higher Education Personnel (CAPES). AAD also acknowledges the financial support received from the CNPq post-doctoral programme. The authors are thankful for the downscaled climate simulations generated by CPTEC/INPE and made available on the PROJETA platform, and we appreciate the NEX-GDDP dataset, prepared by the Climate Analytics Group and NASA Ames Research Center using the NASA Earth Exchange, and distributed by the NASA Center for Climate Simulation (NCCS).
Publisher Copyright:
© 2022 IAHS.
PY - 2022
Y1 - 2022
N2 - This study provides the first estimates of the frequency distribution of observational and future maximum daily precipitation considering nonstationarity for the entire Brazilian territory. We assess observational data from 1980 to 2015 and projected data from 2020 to 2099 for two climate change scenarios and four downscaled climate models. We modelled extreme precipitation according to the extreme values theory and calculated the precipitation intensity associated with the return periods of 5, 10, 25, 50, and 100 years in nonstationary conditions. The results indicate that nonstationarity is identified in 17.5% of the study area during 1980–2015. The analysis of future climate projections indicated an increase in the return levels of extreme precipitation compared to the historical period in at least 90% of the national territory. It shows that engineering design must urgently consider the nonstationarity of extreme precipitation under the risk of increasingly unsafe infrastructure.
AB - This study provides the first estimates of the frequency distribution of observational and future maximum daily precipitation considering nonstationarity for the entire Brazilian territory. We assess observational data from 1980 to 2015 and projected data from 2020 to 2099 for two climate change scenarios and four downscaled climate models. We modelled extreme precipitation according to the extreme values theory and calculated the precipitation intensity associated with the return periods of 5, 10, 25, 50, and 100 years in nonstationary conditions. The results indicate that nonstationarity is identified in 17.5% of the study area during 1980–2015. The analysis of future climate projections indicated an increase in the return levels of extreme precipitation compared to the historical period in at least 90% of the national territory. It shows that engineering design must urgently consider the nonstationarity of extreme precipitation under the risk of increasingly unsafe infrastructure.
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U2 - 10.1080/02626667.2022.2075267
DO - 10.1080/02626667.2022.2075267
M3 - Article
AN - SCOPUS:85133643241
SN - 0262-6667
VL - 67
SP - 1372
EP - 1383
JO - Hydrological Sciences Journal
JF - Hydrological Sciences Journal
IS - 9
ER -
