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@InProceedings{CecchiniHeSiMaFiHo:2018:ThCoAp,
               author = "Cecchini, Micael Amore and Heymsfield, Andrew and Silva Dias, 
                         Maria A. F. and Machado, Luiz Augusto Toledo and Field, paul and 
                         Honeyager, Ryan",
          affiliation = "{Universidade de S{\~a}o Paulo (USP)} and {National Center for 
                         Atmospheric Research} and {Universidade de S{\~a}o Paulo (USP)} 
                         and {Instituto Nacional de Pesquisas Espaciais (INPE)} and {United 
                         Kingdom Met Office} and NOAA",
                title = "Hail size distribution parameterization: theoretical 
                         considerations and application to radar retrievals",
                 year = "2018",
         organization = "AGU Fall Meeting",
             abstract = "Hail formation is one of the characteristic processes occurring 
                         within intense convective clouds and is usually associated with 
                         heavy rainfall and lightning activity. Hailfall can produce 
                         appreciable damage to buildings and automobiles. Therefore, 
                         understanding hail characteristics and the underlying physical 
                         mechanisms of development is of crucial importance to better 
                         represent them in models and to support society in general. A 
                         recent study has found that hail particle size distributions can 
                         be parameterized with an exponential function (Field et al., 
                         2018), where the parameters are constrained from the hail water 
                         content alone. This parameterization is used, together with 
                         T-Matrix simulations, to propose a relation between the hail size 
                         and the respective backscatter cross-sectional area. The T-Matrix 
                         simulations are based on digital 3D scans of collected hail 
                         particles, so their shape is realistically reproduced. We propose 
                         that the new relation can be used to estimate the reflectivity of 
                         a hail volume, which can be applied to radar retrievals to better 
                         estimate hail characteristics and potentially improve nowcasting 
                         techniques.",
  conference-location = "Washington, D. C.",
      conference-year = "10-14 dec.",
             language = "en",
        urlaccessdate = "30 nov. 2020"
}


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