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

Abstract

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.

Data Assimilation Using WRFDA Over the Terminal Area of Rio de Janeiro

“…This results are in accordance to the results in the experiments commonly carried out by University Corporation for Atmospheric Research (UCAR) and the National Center for Atmospheric Research (NCAR), where numerical experiments are described for 1D systems and also to the results presented in Almeida et al (2020b). From the cited UCAR-NCAR experiments, they conclude that the data assimilation process reduces the added noise in the prior forecast and makes the posterior field closer to the "actual dynamics", that is, closer to the true state of the system.…”

“…The present article is part of a sequence of studies related to nowcasting that have been executed by the Applied Meteorological Laboratory at the Federal University of Rio de Janeiro, following Almeida (2009), Silva et al (2016), França, Almeida, and Rossete (2016), França et al (2018), Paulucci et al (2019, and Almeida et al (2020aAlmeida et al ( , 2020b. All these studies encompass researches based on artificial intelligence and methods of limited-area numerical weather forecasts.…”

Visibility and Ceiling Nowcasting Using Artificial Intelligence Techniques for Aviation Applications

“…They are based on the principle that it is possible to learn from a set of training data and consequently be able to correctly classify new standards [22]. This research is part of a sequence of short-term prediction studies based on machine learning algorithms that have been carried out by the Applied Meteorology Laboratory at the Federal University of Rio de Janeiro and can be found in the work of [13,[15][16][17][18]23,24]. So, in the present study, the WEKA (Waikato Environment for Knowledge Analysis) software package (version 3.8.4) [25] developed by the University of Waikato in New Zealand was used, with and without the Auto-WEKA subsystem [26,27].…”