Articles | Volume 9, issue 5
https://doi.org/10.5194/amt-9-2335-2016
https://doi.org/10.5194/amt-9-2335-2016
Research article
 | 
26 May 2016
Research article |  | 26 May 2016

An automated nowcasting model of significant instability events in the flight terminal area of Rio de Janeiro, Brazil

Gutemberg Borges França, Manoel Valdonel de Almeida, and Alessana C. Rosette

Data sets

Department of Atmospheric Science: the TEMP-coded data set UWYO (University of Wyoming) http://weather.uwyo.edu/upperair/sounding.html

Department of Atmospheric Science: the METAR-coded data set UWYO (University of Wyoming) http://weather.uwyo.edu/surface/meteorogram/

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Short summary
This paper presents a novel model, based on neural network techniques, to produce short-term and locally specific forecasts of significant instability for flights in the terminal area of Rio de Janeiro's airport, Brazil. Twelve years of data were used for neural network training/validation and test. The test showed that the proposed model can grab the physical content inside the data set, and its performance is encouraging for the first and second hours to nowcast significant instability events.