BIAS CORRECTION FOR DROUGHT PREDICTION OVER SUMATERA USING ECMWF MODEL

Frequently forest fire occurred over Sumatra Island require us to provide seasonal forest fire prediction. With this prediction, hopefully, we can manage and anticipate forest fire which will held. This study utilizes the prediction of seasonal rainfall from the ECMWF model for drought prediction using the SPI drought index. However, before the ECMWF output is used for prediction, the bias is corrected first. The results of this study indicate that with the bias correction the output can produce better predictions. The strong drought event is generally related to the el-Niño event. The eastern and southern parts of Sumatra are drier and the chance of getting forest fires is greater in August, September, and October which are drier than other months. This condition occurred due to the monsoonal wind.