Impact of WRF-3Dvar data assimilation on the prediction of rainfall over southern Brazil
numerical weather forecasting by statistical methods, is an important and challenging
meteorology research field, known as data assimilation. The 3DVAR approach, state of the art in
data assimilation technique, is applied in this study. The aim of present development is to
evaluate the results of the data assimilation from INMET automatic weather stations and
atmospheric soundings in the weather forecast produced by WRF model. The region of interest is
the South of Brazil. The specific aim is to evaluate the assimilation procedure of two precipitation
events occurred in 2012. This study is especially important, because the INMET automatic
weather stations data are not transmitted by GTS. Therefore, these data were not assimilated by
prediction systems generated by global models, suchas GFS, which provides initial and boundary
conditions for regional models, such as WRF. The results showed that the WRF with data
assimilation procedure, reproduces satisfactorily the true synoptic scenario given by GFS model in
the two cases evaluated, and produces better forecasts then WRF without data assimilation. The
thermodynamic analysis showed that the WRF with data assimilation producing vertical profiles
of air temperature and dew point temperature very close to the observed profiles. Additional
experiments indicate that data assimilated from other sources, in addition to the INMET
automatic weather stations and atmospheric soundings, as well as the increases of horizontal
resolution in the integration of the WRF with inclusion of subset, provide significant
improvements in weather forecasting fields.
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