%0 Journal Article
%4 sid.inpe.br/mtc-m21c/2020/11.23.11.55
%2 sid.inpe.br/mtc-m21c/2020/11.23.11.55.23
%@doi 10.1175/WAF-D-20-0017.1
%@issn 0882-8156
%F self-archiving-INPE-MCTIC-GOV-BR
%T Cloud-resolving model applied to nowcasting: An evaluation of radar data assimilation and microphysics parameterization
%D 2020
%8 Dec.
%9 journal article
%A Vendrasco, Éder Paulo,
%A Machado, Luiz Augusto Toledo,
%A Ribeiro, B. Z.,
%A Freitas, E. D.,
%A Negri, Renato Galante,
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation University at Albany
%@affiliation Universidade de São Paulo (USP)
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@electronicmailaddress
%@electronicmailaddress luiz.machado@inpe.br
%B Weather and Forecasting
%V 35
%N 6
%P 2345-2365
%X This research explores the benefits of radar data assimilation for short-range weather forecasts in southeastern Brazil using the Weather Research and Forecasting (WRF) Models three-dimensional variational data assimilation (3DVAR) system. Different data assimilation options are explored, including the cycling frequency, the number of outer loops, and the use of null-echo assimilation. Initially, four microphysics parameterizations are evaluated (Thompson, Morrison, WSM6, and WDM6). The Thompson parameterization produces the best results, while the other parameterizations generally overestimate the precipitation forecast, especially WDSM6. Additionally, the Thompson scheme tends to overestimate snow, while the Morrison scheme overestimates graupel. Regarding the data assimilation options, the results deteriorate and more spurious convection occurs when using a higher cycling frequency (i.e., 30 min instead of 60 min). The use of two outer loops produces worse precipitation forecasts than the use of one outer loop, and the null-echo assimilation is shown to be an effective way to suppress spurious convection. However, in some cases, the null-echo assimilation also removes convective clouds that are not observed by the radar and/or are still not producing rain, but have the potential to grow into an intense convective cloud with heavy rainfall. Finally, a cloud convective mask was implemented using ancillary satellite data to prevent null-echo assimilation from removing potential convective clouds. The mask was demonstrated to be beneficial in some circumstances, but it needs to be carefully evaluated in more cases to have a more robust conclusion regarding its use.
%@language en
%3 vendrasco_cloud.pdf