@Article{PalhariniViRoPaMaPe:2021:ReAn,
               author = "Palharini, Rayana Santos Ara{\'u}jo and Vila, Daniel Alejandro 
                         and Rodrigues, Daniele Torres and Palharini, Rodrigo Cassinelli 
                         and Mattos, Enrique Vieira and Pedra, George Ulguim",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Universidade Federal 
                         do Piau{\'{\i}} (UFPI)} and {Universidad T{\'e}cnica Federico 
                         Santa Mar{\'{\i}}a (USM)} and {Universidade Federal de 
                         Itajub{\'a} (UNIFEI)} and {Instituto Nacional de Pesquisas 
                         Espaciais (INPE)}",
                title = "Assessment of extreme rainfall estimates from satellite-based: 
                         regional analysis",
              journal = "Remote Sensing Applications: Society and Environment",
                 year = "2021",
               volume = "23",
                pages = "e100603",
                month = "Aug.",
             keywords = "Brazil, Extreme rainfall, FROGS dataset, Satellite estimates.",
             abstract = "Excessive rain may cause several problems for society. 
                         Understanding the behaviour of extreme rainfall and quantifying it 
                         in an assertive manner is important for whole society. The purpose 
                         of this work is to evaluate the ability of satellite precipitation 
                         products to detect the extreme rainfall over different regions of 
                         Brazil. The products evaluated in this investigation were from 
                         Frequent Rainfall Observations on GridS (FROGS) database. The 
                         results show that, each region of Brazil is characterized by 
                         extremes of rain with different intensities. The regions that 
                         presented the highest values are south and north regions of Brazil 
                         with values around 125.0 mm/day. In both regions, the GSMAP 
                         product (with rain gauges adjustments) have better performance, as 
                         shown in the metrics for the south and north regions where bias = 
                         \−1.20 mm/day and \−6.49 mm/day; r = 0.65 and 0.50; 
                         std = 10.15 mm/day and 10.63 mm/day; rmse = 9.58 mm/day and 13.16 
                         mm/day respectively. On the other hand, the regions with the 
                         lowest intensities are the northeastern region, inland and coast, 
                         presented frequent extreme values of approximately 35.0 mm/day. At 
                         these regions, both versions of product 3B42RT v7.0 demonstrated a 
                         better performance, as demonstrated in the metrics for inland and 
                         coast northeastern regions, bias = 2.82 mm/day and \−2.94 
                         mm/day; r = 0.18 and 0.30; std = 8.53 mm/day and 6.97 mm/day; rmse 
                         = 14.75 mm/day and 7.03 mm/day, respectively. It is worth 
                         mentioning that the precipitation values found in this work do not 
                         necessarily cause disasters or generate impacts in the analyzed 
                         regions, they were considered extreme from a statistical point of 
                         view, considering the analyzed database.",
                  doi = "10.1016/j.rsase.2021.100603",
                  url = "http://dx.doi.org/10.1016/j.rsase.2021.100603",
                 issn = "2352-9385",
             language = "en",
           targetfile = "palharini_assessment_2021.pdf",
        urlaccessdate = "21 maio 2024"
}