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WENAS GANDA KURNIA

Abstract

Rainfall prediction is an important aspect in improving weather and climate information. Rain becomes part of the hydrologic cycle are triggered by changes in weather parameters that synergy. Relations between parameters this as the basis for model creation based Global Circulation Model data is processed to estimate rainfall in an area. Kendari region (Season Zone 313) do not get the best method for predicting the monthly rainfall. The method used in this research is multiple linear regression predictor anomaly sea surface temperatures (SST), sea level pressure (SLP) and the zonal wind is processed by the time lag of 0 months to time lag 3 month. The model results are validated by looking at the coefficient correlation value and RMSE values show a good performance time lag 0 than the three other models in each month.


 


Keywords : rainfall, multiple regression, time lag

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