气候变化领域集成服务门户(CCPortal): Extreme rainfall events over Rio de Janeiro State, Brazil: Characterization using probability distribution functions and clustering analysis

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DOI	10.1016/j.atmosres.2020.105221
	Extreme rainfall events over Rio de Janeiro State, Brazil: Characterization using probability distribution functions and clustering analysis
	Lima A.O.; Lyra G.B.; Abreu M.C.; Oliveira-Júnior J.F.; Zeri M.; Cunha-Zeri G.
发表日期	2021
ISSN	0169-8095
卷号	247
英文摘要	Extreme rainfall events are likely to become more frequent according to recent scenarios of climate change. This issue is especially important over regions with complex topography, which enhances rainfall variability when associated with weather patterns. The state of Rio de Janeiro (SRJ), southeastern Brazil, is characterized by altitudes ranging from the mean sea level up to 2500 m.a.s.l, in mountain ranges and valleys covering significant parts of the region. Time series data of annual maximum daily rainfall were obtained from 110 stations with a data coverage of at least 20 years, from 1960 to 2010. The Probability Distribution Functions (PDFs) normal, log-normal, exponential, gamma, Gumbel, Weibull, and Generalized Extreme Value (GEV) were fitted to maximum rainfall series. Goodness-of-fit tests (Chi-squared - χ2 and Anderson-Darling) revealed that the Gumbel, GEV, and log-normal were found to be the best choices. However,the Gumbel and GEV PDFs were the best ranking by the χ2 and Anderson-Darling test, respectively. Extreme rainfall events with different recurrence intervals (5, 10, 25, 50 and 100 years) were calculated based on the Gumbel and GEV Cumulative Distribution Function (CDF). The differences between extreme values from Gumbell and GEV function increased as the shape parameter increases from zero, with higher probability and extreme value. Five regions with homogeneous patterns of extreme rainfall were identified using clustering analysis (Ward's method) and different recurrence intervals. Overall, the regions with higher values of extreme rainfall in all scenarios and CDFs were the ones close to the coast, within 40 km, and south of Serra dos Órgãos mountain range, located in the middle of the state. The mountain range separates the state in two halves, concentrating higher values of extreme rainfall in the lower part, where the city of Rio de Janeiro, the state's capital, is located. Scenarios for both CDF (GEV and Gumbel) indicated daily rainfall events up to 200 mm, with recurrence intervals of 50 to 100 years. In addition, the southernmost part of the state is subjected to rainfall extremes up to 260 mm in scenarios of 50 to 100 years of recurrence interval. This region, and the state's capital, are characterized by complex topography and a high fraction of population living in slums over hills, or lowlands near the ocean, increasing the vulnerability to events such as landslides and floods associated with extreme rainfall. © 2020 Elsevier B.V.
英文关键词	Climate extremes; Cluster analysis; Cumulative distribution function; Daily rainfall; Recurrence interval
来源期刊	Atmospheric Research
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/236923
作者单位	Programa de Pós-Graduação em Engenharia de Biossistemas, Departamento de Engenharia Agrícola e do Meio Ambiente, Escola de Engenharia, Universidade Federal Fluminense, 24.210-240, Niterói, Rio de Janeiro, Brazil; Departamento de Ciências Ambientais, Instituto de Florestas, Universidade Federal Rural do Rio de Janeiro, 23.890-000, Seropédica, Rio de Janeiro, Brazil; Instituto de Ciências Atmosféricas, Universidade Federal de Alagoas, Campus A.C. Simões, BR 104-Norte, Km 97, Tabuleiro dos Martins, 57.072-970, Maceió, Alagoas, Brazil; National Center for Monitoring and Early Warning of Natural Disasters (CEMADEN), São José dos Campos, SP 12247-016, Brazil; Center for Earth System Science (CCST), National Institute for Space Research (INPE), São José dos Campos, SP 12227-010, Brazil
推荐引用方式 GB/T 7714	Lima A.O.,Lyra G.B.,Abreu M.C.,et al. Extreme rainfall events over Rio de Janeiro State, Brazil: Characterization using probability distribution functions and clustering analysis[J],2021,247.
APA	Lima A.O.,Lyra G.B.,Abreu M.C.,Oliveira-Júnior J.F.,Zeri M.,&Cunha-Zeri G..(2021).Extreme rainfall events over Rio de Janeiro State, Brazil: Characterization using probability distribution functions and clustering analysis.Atmospheric Research,247.
MLA	Lima A.O.,et al."Extreme rainfall events over Rio de Janeiro State, Brazil: Characterization using probability distribution functions and clustering analysis".Atmospheric Research 247(2021).