@Article{DelgadoMABRLGN:2008:BaRaEs,
               author = "Delgado, G. and Machado, Luiz A. T. and Angelis, Carlos Frederico 
                         de and Bottino, Marcus J. and Redano, A and Lorente, J. and 
                         Gimeno, L. and Nieto, R.",
          affiliation = "Univ Barcelona, Dept Astron \& Meteorol, E-08028 Barcelona, Spain 
                         and {Instituto Nacional de Pesquisas Espaciais (INPE)} and 
                         {Instituto Nacional de Pesquisas Espaciais (INPE)} and {} and Univ 
                         Barcelona, Dept Astron \& Meteorol, E-08028 Barcelona, Spain and 
                         {} and Univ Lisbon, CGUL, IDL, P-1699 Lisbon, Portugal and Univ 
                         Lisbon, CGUL, IDL, P-1699 Lisbon, Portugal",
                title = "Basis for a Rainfall Estimation Technique Using IR VIS Cloud 
                         Classification and Parameters over the Life Cycle of Mesoscale 
                         Convective Systems",
              journal = "Journal of Applied Meteorology and Climatology",
                 year = "2008",
               volume = "47",
               number = "5",
                pages = "1500--1517",
                month = "May",
             keywords = "ARTIFICIAL NEURAL-NETWORK, PASSIVE MICROWAVE, PRECIPITATION 
                         ESTIMATION, SATELLITE IMAGERY, METEOSAT IMAGERY, INFRARED DATA, 
                         RESOLUTION, ALGORITHM, RADIANCES, AREA.",
             abstract = "This paper discusses the basis for a new rainfall estimation 
                         method using geostationary infrared and visible data. The 
                         precipitation radar on board the Tropical Rainfall Measuring 
                         Mission satellite is used to train the algorithm presented (which 
                         is the basis of the estimation method) and the further 
                         intercomparison. The algorithm uses daily Geostationary 
                         Operational Environmental Satellite infrared-visible (IR-VIS) 
                         cloud classifications together with radiative and evolution 
                         properties of clouds over the life cycle of mesoscale convective 
                         systems (MCSs) in different brightness temperature (T-b) ranges. 
                         Despite recognition of the importance of the relationship between 
                         the life cycle of MCSs and the rainfall rate they produce, this 
                         relationship has not previously been quantified precisely. An 
                         empirical relationship is found between the characteristics that 
                         describe the MCSs' life cycle and the magnitude of rainfall rate 
                         they produce. Numerous earlier studies focus on this subject using 
                         cloud-patch or pixel-based techniques; this work combines the two 
                         techniques. The algorithm performs reasonably well in the case of 
                         convective systems and also for stratiform clouds, although it 
                         tends to overestimate rainfall rates. Despite only using satellite 
                         information to initialize the algorithm, satisfactory results were 
                         obtained relative to the hydroestimator technique, which in 
                         addition to the IR information uses extra satellite data such as 
                         moisture and orographic corrections. This shows that the use of 
                         IR-VIS cloud classification and MCS properties provides a robust 
                         basis for creating a future estimation method incorporating 
                         humidity Eta field outputs for a moisture correction, digital 
                         elevation models combined with low-level moisture advection for an 
                         orographic correction, and a nighttime cloud classification.",
                  doi = "10.1175/2007JAMC1684.1",
                  url = "http://dx.doi.org/10.1175/2007JAMC1684.1",
                 issn = "1558-8432 and 1558-8424",
                label = "lattes: 5139331351519474 3 DelgadoMABRLGN:2008:BaRaEs",
             language = "en",
           targetfile = "machado_basis.pdf",
        urlaccessdate = "27 abr. 2024"
}