@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",
targetfile = "cechhini_hail.pdf",
urlaccessdate = "27 abr. 2024"
}