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Assessing the potential of a long-term climate forecast for Cuba using the WRF model
* 1 , 2 , 1 , 1
1  Instituto de Meteorología. Cuba
2  Centro de Investigación Científica y de Educación Superior de Ensenada CICESE. México
Academic Editor: Anthony Lupo (registering DOI)

Seasonal climatic prediction studies are a matter of wide debate all over the world. Cuba, a mainly agricultural nation, should greatly benefit from the knowledge with months in advance of the precipitation regime, which would allow a proper management of water resources. In this work, a series of 6 experiments was made with mesoscale model WRF (Weather Research and Forecasting Model) that produced a 15 months forecast each of monthly cumulative precipitation starting at two dates for three years with different meteorological characteristics, one dry year (2004), one year that started dry and turned rainy (2005) and one year signaled by the occurrence of several tropical storms (2008). ERA-Interim reanalysis data were used for initial and border conditions and runs started one month before the beginnings of the rainy and the dry seasons respectively. In a general sense, the experience of using WRF indicates that it is a valid resource for seasonal forecast, since results obtained are in the same range as those reported by literature for similar cases. Several limitations were revealed by the results, such as that forecasts underestimate the monthly cumulative precipitation figures, tropical storms entering through the borders may follow courses different from the real ones inside the working domain, storms that developed inside the domain were not reproduced by WRF and differences in initial conditions led to significantly different forecasts for corresponding time steps (non linearity). It is recommended to carry on ensemble forecast experiments changing model parameterizations and initial conditions.

Keywords: seasonal climatic prediction; seasonal models, dinamic downscaling
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