@Article{LimaLyAbOlZeCu:2021:ChUsPr,
               author = "Lima, Allana Oliveira and Lyra, Gustavo Bastos and Abreu, Marcel 
                         Carvalho and Oliveira J{\'u}nior, Jos{\'e} Francisco and Zeri, 
                         Marcelo and Cunha Zeri, Gisleine",
          affiliation = "{Universidade Federal Fluminense (UFF)} and {Universidade Federal 
                         Rural do Rio de Janeiro (UFRRJ)} and {Universidade Federal Rural 
                         do Rio de Janeiro (UFRRJ)} and {Universidade Federal de Alagoas 
                         (UFAL)} and {Centro Nacional de Monitoramento e Alertas de 
                         Desastres Naturais (CEMADEN)} and {Instituto Nacional de Pesquisas 
                         Espaciais (INPE)}",
                title = "Extreme rainfall events over Rio de Janeiro State, Brazil: 
                         Characterization using probability distribution functions and 
                         clustering analysis",
              journal = "Atmospheric Research",
                 year = "2021",
               volume = "247",
                pages = "e105221",
                month = "Jan",
             abstract = "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 
                         {\'O}rg{\~a}os 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.",
                  doi = "10.1016/j.atmosres.2020.105221",
                  url = "http://dx.doi.org/10.1016/j.atmosres.2020.105221",
                 issn = "0169-8095",
             language = "en",
        urlaccessdate = "27 abr. 2024"
}