Assessment of 3DVAR assimilation on the Yakecan subtropical cyclone

Authors

DOI:

https://doi.org/10.5902/2179460X74269

Keywords:

Cyclone, Subtropical, Yakecan, Assimilation

Abstract

In the present work, the impact of the assimilation of AMSU-A satellite data, performed through the three-dimensional variational system of the WRF weather forecast model, is evaluated. The Yakecan cyclone, system that have caused socioeconomic damage in southern Brazil on May 17th 2022, was emulated. Extratropical systems are quite common in the region, however systems such as the Yakecan, which have hibrid characteristics are specially interesting for research purposes. The simulations performed by the WRF model capture the propagation and development of the system. However, the initial condition generated by variational technique showed a more accurate positioning of the system than the simulation without data assimilation. This difference is fundamental for weather forecasting in southern Brazil, since the correct positioning of the system defines whether the consequences of the cyclone affect densely populated areas on the coast of the country or are limited to the adjacent ocean.

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Author Biographies

Fabrício Pereira Härter, Universidade Federal de Pelotas

graduado em Meteorologia pela Universidade Federal de Pelotas (1995), mestre em Meteorologia pelo Instituto Nacional de Pesquisas Espaciais (1999) e doutor em Computação Aplicada pelo Instituto Nacional de Pesquisas Espaciais (2004) com pós-doutorado pela University of Waterloo (2006). Trabalhou com previsão de tempo voltada para meios de comunicação e agricultura, foi auxiliar de pesquisa num projeto sobre estimativas de precipitação por satélite, participou do Programa Antártico Brasileiro e prestou consultoria a Organização Meteorológica Mundial, junto ao Instituto Nacional de Meteorologia. Tem como linha de pesquisa prioritária assimilação de dados meteorológicos (redes neurais, filtragem de Kalman e métodos variacionais) e inicialização de modelos numéricos. Foi Vice-Diretor da Faculdade de Meteorologia e Chefe Adjunto do Centro de Pesquisas e Previsões Meteorológicas (CPPMet). Atualmente é professor Associado da Universidade Federal de Pelotas (UFPel), membro permanente do Programa de Pós-Graduação em Modelagem Matemática, membro do Núcleo Docente Estruturante do colegiado do Curso de Graduação em Meteorologia, do Conselho Departamental da Faculdade de Meteorologia, representante da Faculdade de Meteorologia no Conselho Universitário da UFPEL (CONSUN), representante Adjunto do CONSUN no Conselho de Ensino Pesquisa e Extensão (COCEPE) e Diretor da Faculdade de Meteorologia no segundo mandato.

Leonardo Calvetti, Universidade Federal de Pelotas

Possui graduação em Meteorologia pela Universidade Federal de Pelotas (1998), mestrado(2002) e doutorado (2011) em Meteorologia pela Universidade de São Paulo. Atuou como meteorologista pesquisador no Simepar até janeiro de 2016. Atualmente é professor da Faculdade de Meteorologia da UFPel atuando nas áreas de radar meteorológico, nowcasting, mesoescala, hidrometeorologia e previsão numérica de tempo.

Elcio Hideiti Shiguemori, Instituto de Estudos Avançados (IEAv)

É Pesquisador do Instituto de Estudos Avançados (IEAv) do Departamento de Ciência e Tecnologia Aeroespacial (DCTA). Doutor em computação aplicada pelo Instituto Nacional de Pesquisas Espaciais (INPE) (2007). Mestre em Computação Aplicada pelo INPE (2002), possui graduação em Engenharia da Computação (1998) e em Ciências da Computação pela UBC (1999). É docente no programa de Pós-Graduação em Computação Aplicada do INPE e docente no programa de Pós-graduação PG-CTE do ITA. É professor na Universidade Paulista (UNIP) e coordenador do curso de Engenharia da Computação. Tem experiência na área de Computação, atuando principalmente nos seguintes temas: Inteligência Artificial, Aprendizagem de Máquina, Ciência dos Dados, Navegação Aérea Autônoma, Processamento de Imagens e Visão Computacional.

Felipe Copceski Rossatto, Universidade Federal de Pelotas

Possui graduação em Matemática pela Universidade Regional Integrada do Alto Uruguai e das Missões (2019). Mestrado em Modelagem Matemática (2021-2023). Tem experiência na área de Matemática, com ênfase em Matemática.

References

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Published

2023-12-01

How to Cite

Härter, F. P., Calvetti, L., Shiguemori, E. H., & Rossatto, F. C. (2023). Assessment of 3DVAR assimilation on the Yakecan subtropical cyclone. Ciência E Natura, 45(esp. 3), e74269. https://doi.org/10.5902/2179460X74269

Issue

Vol. 45 No. esp. 3 (2023): ENMC/ECTM/MCSul/SEMENGO

Section

Special Edition

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