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@Article{PalhariniViRoQuPaSiAf:2020:AsExPr,
               author = "Palharini, Rayana Santos Araujo and Vila, Daniel Alejandro and 
                         Rodrigues, Daniele T{\^o}rres and Quispe, David Pareja and 
                         Palharini, Rodrigo Cassineli and Siqueira, Ricardo Almeida de and 
                         Afonso, Jo{\~a}o Maria de Sousa",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Universidade Federal 
                         do Piau{\'{\i}} (UFPI)} and {Instituto Nacional de Pesquisas 
                         Espaciais (INPE)} and {Universidad T{\'e}cnica Federico Santa 
                         Mar{\'{\i}}a} and {Instituto Nacional de Pesquisas Espaciais 
                         (INPE)} and {Instituto Nacional de Pesquisas Espaciais (INPE)}",
                title = "Assessment of the extreme precipitation by satellite estimates 
                         over South America",
              journal = "Remote Sensing",
                 year = "2020",
               volume = "12",
               number = "13",
                pages = "e2085",
                month = "July",
             keywords = "extreme precipitation, rainfall estimates, satellite.",
             abstract = "In developing countries, accurate rainfall estimation with 
                         adequate spatial distribution is limited due to sparse rain gauge 
                         networks. One way to solve this problem is the use of 
                         satellite-based precipitation products. These satellite products 
                         have significant spatial coverage of rainfall estimates and it is 
                         of fundamental importance to investigate their performance across 
                         spacetime scales and the factors that affect their uncertainties. 
                         In the open literature, some studies have already analyzed the 
                         ability of satellite-based rain estimation products to estimate 
                         average rainfall values. These investigations have found very 
                         close agreement between the estimates and observed data. However, 
                         further evaluation of the satellite precipitation products is 
                         necessary to improve their reliability to estimate extreme values. 
                         In this scenario, the main goal of this work is to evaluate the 
                         ability of satellite-based precipitation products to capture the 
                         characteristics of extreme precipitation over the tropical region 
                         of South America. The products evaluated in this investigation 
                         were 3B42 RT v7.0, 3B42 RT v7.0 uncalibrated, CMORPH V1.0 RAW, 
                         CMORPH V1.0 CRT, GSMAP-NRT-no gauge v6.0, GSMAP-NRT- gauge v6.0, 
                         CHIRP V2.0, CHIRPS V2.0, PERSIANN CDR v1 r1, CoSch and TAPEER v1.5 
                         from Frequent Rainfall Observations on GridS (FROGS) database. 
                         Some products considered in this investigation are adjusted with 
                         rain gauge values and others only with satellite information. In 
                         this study, these two sets of products were considered. In 
                         addition, gauge-based daily precipitation data, provided by 
                         Brazils National Institute for Space Research, were used as 
                         reference in the analyses. In order to compare gauge-based daily 
                         precipitation and satellite-based data for extreme values, 
                         statistical techniques were used to evaluate the performance the 
                         selected satellite products over the tropical region of South 
                         America. According to the results, the threshold for rain to be 
                         considered an extreme event in South America presented high 
                         variability, ranging from 20 to 150 mm/day, depending on the 
                         region and the percentile threshold chosen for analysis. In 
                         addition, the results showed that the ability of the satellite 
                         estimates to retrieve rainfall extremes depends on the 
                         geographical location and large-scale rainfall regimes.",
                  doi = "10.3390/rs12132085",
                  url = "http://dx.doi.org/10.3390/rs12132085",
                 issn = "2072-4292",
             language = "en",
           targetfile = "remotesensing-12-02085-v2.pdf",
        urlaccessdate = "26 jan. 2021"
}


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