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@Article{BrahmVilaMartOsgo:2019:CaDiEv,
               author = "Brahm, Manuel and Vila, Daniel and Martinez Saenz, Sofia and 
                         Osgood, Daniel",
          affiliation = "{The Earth Institute at Columbia University} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {The Earth Institute 
                         at Columbia University} and {The Earth Institute at Columbia 
                         University}",
                title = "Can disaster events reporting be used to drive remote sensing 
                         applications? A Latin America weather index insurance case study",
              journal = "Meteorological Applications",
                 year = "2019",
               volume = "26",
               number = "4",
                pages = "632--641",
                month = "Oct.",
             keywords = "disaster events, on the ground reporting, remote sensing 
                         applications, satellite rainfall, weather index insurance.",
             abstract = "A new data set was commissioned over Latin America with the goal 
                         of supporting decision-making in various socioeconomic activities 
                         and, in particular, for climate insurance products. The Historical 
                         Database for Gridded Daily Precipitation Dataset over Latin 
                         America (LatAmPrec), based on the combined scheme approach 
                         developed at the Centro de Previs{\~a}o de Tempo e Estudos 
                         Clim{\'a}ticos, Instituto Nacional de Pesquisas Espaciais 
                         (CPTEC/INPE), provides a new high-resolution, low-latency, 
                         gaugesatellite-based analysis of daily precipitation over Latin 
                         America for the period March 2000July 2017. In order to understand 
                         the strengths and limitations of the new data set for use in 
                         weather index insurance, the present study applies two different 
                         validation methodologies. The first focuses on capturing, through 
                         a cross-correlation process, the accuracy and improved 
                         characteristics of the new gauge-merged data set. Second, to gauge 
                         the skill of the data set in the context of insurance losses, the 
                         study uses a statistical approach, previously applied at a village 
                         level and here applied at regional levels, to assess how well the 
                         new data set predicts evidence of loss events. This is performed 
                         for both farmer interview data and national-level disaster data 
                         sets. The results from both validation methodologies show that 
                         LatAmPrec performs well when compared with other data sources and 
                         can satisfactorily capture the insurance-relevant losses on the 
                         ground. One main advantage of the new product is its high spatial 
                         resolution and low latency compared with other existing products 
                         used in the weather index insurance industry.",
                  doi = "10.1002/met.1790",
                  url = "http://dx.doi.org/10.1002/met.1790",
                 issn = "1350-4827",
             language = "en",
           targetfile = "brahm_can.pdf",
        urlaccessdate = "17 abr. 2021"
}


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