Climate Forecasts at the Centro de Lançamento de Alcântara Using the Climate Model RegCM4

Authors

  • Cleber Souza Corrêa Instituto de Aeronautica e Espaço
  • Gerson Luiz Camillo
  • Vinicius Milanez Couto
  • Gilberto Fisch
  • Felipe do Nascimento Correa
  • Fabricio Harter Faculdade de Meteorologia Universidade federal de Pelotas (UFPel)

Keywords:

Climate prediction, Centro de Lançamento de Alcântara, RegCM4 Climate Model.

Abstract

This study uses climate modeling (RegCM4 Climate Model) to provide a wind forecast average behavior at low levels, close to the surface. The model was used to generate an estimate of the average vertical wind profile lasting 5 months, from August to December 2015, attempting to observe intra-seasonal variations, with the presence of persistence in the wind field. The results of climate modeling of the wind profile near the surface have the great potential for great operational significance during launch campaigns at the Centro de Lançamento de Alcântara. Three average results were generated for the month of November 2015, while operating in São Lourenço. A dynamical downscaling nested with global models with RCP4.5 and RCP8.5, using 3 different global conditions initialization datasets. It used subsets with the models from the Met Office Hadley Centre (HadGEM2-ES), the Centre National de Recherches Météorologiques (CNRM-CM5), and the Commonwealth Scientific and Industrial Research Organization CSIRO-Mk3.6), making a downscaling with the RegCM4 Climate Model for the Centro de Lançamento de Alcântara region. The results are preliminary but show great potential. Since the RegCM4 Climate Model can show variations of high and low intensity, its temporal frequency in the average vertical wind profile and the duration of temporal variation are of the order of 3 – 5 days. The RegCM4 Climate Model had better results with the one from the Met Office Hadley Centre, HadGEM2-ES, when it was qualitatively compared with observational data (ERA Interim Model) of the campaign period and reanalysis data.

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Published

2017-02-28

Issue

Section

Original Papers