Data assimilation for nowcasting in the terminal area of Rio de Janeiro




Data assimilation, WRF, 3D-Var, Surface data, Profile data


The process of data assimilation, in which meteorological observations and weather forecasts are merged to provide an analysis field, has been largely studied by the scientific community and operational centers. The 3D-Variational (3D-Var) approach available in the Weather Research and Forecast (WRF) computer model is evaluated for data assimilation for the Terminal Control Area of Rio de Janeiro (TCA-RJ). The basic goal of any variational data assimilation system is to produce an optimal estimate of the atmospheric state at analysis time. The analysis field is estimated from a first guess (previous forecast) and an observation field, weighted by the error matrices. The WRF is designed for nowcasting (forecasts up to 6h) for the TCA-RJ through assimilation cycles using surface, sounding, and wind profile data. The preliminary results show the model sensibility for each observation type and encourage the use of this technique operationally for the support of the air traffic management controlled by the Brazilian Air Force.


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Author Biographies

Vinícius Albuquerque de Almeida, Universidade Federal do Rio de Janeiro, Rio de Janeiro, RJ

Graduated in Meteorology from the Federal University of Rio de Janeiro (2013), master's degree in Meteorology from the Federal University of Rio de Janeiro (2016) and ongoing doctorate in Civil Engineering from the Federal University of Rio de Janeiro

Gutemberg Borges França, Universidade Federal do Rio de Janeiro, Rio de Janeiro, RJ

Graduated in Physics from the Federal University of Mato Grosso do Sul (1985), master's degree in System Analysis and Applications from the National Institute for Space Research (1988) and doctorate in Remote Sensing of the Atmosphere from the University of Dundee (Scotland, 1994). Head of the Laboratory for Applied Meteorology (2004-present). He has experience in the fields of applied meteorology, acting mainly on the following topics: aviation meteorology, remote sensing of the atmosphere and the ocean, machine learning

Haroldo Campos Velho, Instituto Nacional de Pesquisas Espaciais, São Paulo, SP

Graduated in Chemical Engineering from the Pontifica Universidade Católica do Rio Grande do Sul (1983), M.Sc. (1988) on Nuclear Engineering and D.Sc.(1992) on Mechanical Engineering from the Universidade  Federal do Rio Grande do Sul. Currently, he is a senior researcher from the National Institute of Space Research (INPE, Brazil)


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How to Cite

Almeida, V. A. de, França, G. B., & Velho, H. C. (2020). Data assimilation for nowcasting in the terminal area of Rio de Janeiro. Ciência E Natura, 42, e40.