Assimilação 3DVAR no WRF e a Previsão do Tempo no Sul do Brasil

• Ano de defesa: 2013
• Autor(a) principal: Beck, Vinicius Carvalho
• Orientador(a): Härter, Fabrício Pereira
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Pelotas
• Programa de Pós-Graduação: Programa de Pós-Graduação em Meteorologia
• Departamento: Meteorologia
• País: BR
• Palavras-chave em Português: Meteorologia; Assimilação de dados; 3DVAR; WRF; Mesoescala
• Palavras-chave em Inglês: Meteorology; Data assimilation; 3DVAR; WRF; Mesoscale
• Área do conhecimento CNPq: CNPQ::CIENCIAS EXATAS E DA TERRA::GEOCIENCIAS::METEOROLOGIA::METEOROLOGIA APLICADA
• Link de acesso: https://guaiaca.ufpel.edu.br/handle/123456789/2180

The procedure to combine mathematical models with noise data, in order to improve numerical weather forecasting by statistical methods, is an important and challenging meteorology research field, known as data assimilation. The 3DVAR approach, state of 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 stations and soundings in Southern Region of Brazil in the weather forecasts of the WRF model with data assimilation via 3DVAR method, analyzing in each processed case, if the forecasting reproduces the synoptic scenario observed, with better prediction then the WRF without data assimilation. The specific aim is to evaluate the assimilation procedure of two precipitation events occurred in the year 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, such as GFS, which provides initial and boundary conditions for regional models, such as WRF. The results show that the WRF with data assimilation procedure, reproduces satisfactorily the true synoptic scenario observed 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, with small improvement in prediction as compared with the WRF without assimilation. Additional experiments indicate that data assimilated from other sources, in addition to the INMET automatic weather stations and soundings stations, 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.