Evaluation of the 3DVAR Operational Implementation of the Colombian Air Force for Aircraft Operations

A Case Study

Journal Article (2023)
Author(s)

Jhon Edinson Hinestroza Ramirez (Universidad EAFIT, Universidad Tecnológica del Chocó)

Juan Ernesto Soto Barbosa (Fuerza Aerea Colombiana)

Andrés Yarce Botero (Universidad EAFIT, TU Delft - Civil Engineering & Geosciences)

Danilo Andrés Suárez Higuita (Universidad EAFIT)

Santiago Lopez-Restrepo (Universidad EAFIT)

Lisseth Milena Cruz Ruiz (Universidad EAFIT)

Valeria Sólorzano Araque (Universidad EAFIT)

Andres Céspedes (Fuerza Aerea Colombiana)

Sara Lorduy Hernandez (Fuerza Aerea Colombiana)

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Research Group
Atmospheric Remote Sensing
DOI related publication
https://doi.org/10.3390/cli11070153 Final published version
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Publication Year
2023
Language
English
Research Group
Atmospheric Remote Sensing
Journal title
Climate
Issue number
7
Volume number
11
Article number
153
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341
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Abstract

This manuscript introduces an exploratory case study of the SIMFAC’s (Sistema de Información Meteorológica de la Fuerza Aérea Colombiana) operational implementation of the Weather Research and Forecasting (WRF) model with a 3DVAR (three-dimensional variational) data assimilation scheme that provides meteorological information for military, public, and private aviation. In particular, it investigates whether the assimilation scheme in SIMFAC’s implementation improves the prediction of the variables of interest compared to the implementation without data assimilation (CTRL). Consequently, this study compares SIMFAC’S 3DVAR-WRF operational implementation in Colombia with a CTRL with the same parameterization (without 3DVAR assimilation) against the ground and satellite observations in two operational forecast windows. The simulations are as long as an operational run, and the evaluation is performed using the root mean square error, the mean fractional bias, the percent bias, the correlation factor, and metrics based on contingency tables. It also evaluates the model’s results according to the regions of Colombia, accounting for the country’s topographical differences. The findings reveal that, in general, the operational forecast (3DVAR) is similar to the CTRL without data assimilation, indicating the need for further improvement of the 3DVAR-WRF implementation.