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@Article{GonçalvesCosAngRodSou:2012:ReGORe,
               author = "Gon{\c{c}}alves, Weber Andrade and Costa, Simone Marilene Sievert 
                         da and Angelis, Carlos Frederico de and Rodrigues, Jurandir 
                         Ventura and Souza, Rodrigo Augusto Ferreira",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)} and {Instituto Nacional de Pesquisas 
                         Espaciais (INPE)} and {Universidade Estadual do Amazonas}",
                title = "Regionalization of the GOES-10 retrieval algorithm for tropical 
                         South America",
              journal = "International Journal of Remote Sensing",
                 year = "2012",
               volume = "33",
               number = "17",
                pages = "5366 - 5378",
             keywords = "sounder, profiles.",
             abstract = "Meteorological satellites provide a unique opportunity to obtain 
                         thermodynamic profiles in regions of the globe that do not have a 
                         dense meteorological upper air stations network, as in South 
                         America. The geostationary satellite GOES-10 made the inference of 
                         temperature and mixing ratio profiles every hour with a special 
                         resolution of 10 km over South America from July 2007 to February 
                         2009. The GOES-10 retrieval algorithm for thermodynamic profiles 
                         was developed by the CIMMS in the United States, so some 
                         adjustments for its application in South America could be done. 
                         Among these adjustments is the construction of a new covariance 
                         matrix. In this context, the scientific focus of this research was 
                         to construct a new covariance matrix adapted to meteorological 
                         conditions of South America. In addition, a validation of the 
                         algorithm results by the use of the original and the new 
                         covariance matrices was performed. The variables validated were 
                         the air temperature and mixing ratio vertical profiles and the 
                         values of total precipitable water. The dataset used was a total 
                         of 1095 radiosonde observations located in South America tropical 
                         region at 00:00 and 12:00 UTC, as well as thermodynamic profiles 
                         from 12h forecasts of the CPTEC Global Model, used as first guess, 
                         and upwelling radiances of 18 infrared channels from GOES-10 
                         satellite for the period from July to November 2007. In general, 
                         the results indicated that with the regionalization of the 
                         covariance matrix the algorithm performed better retrievals than 
                         when it used the original matrix. The greatest improvements were 
                         found in the mixing ratio profiles and in the values of total 
                         precipitable water. These results could be associated to the 
                         presence of the Amazon Rainforest that incorporated a greater 
                         amount of moisture in the new covariance matrix than the previous 
                         matrix had.",
                  doi = "10.1080/01431161.2012.657367",
                  url = "http://dx.doi.org/10.1080/01431161.2012.657367",
                 issn = "0143-1161",
             language = "en",
        urlaccessdate = "24 jan. 2021"
}


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