Open AccessUtilization of ECMWF Seasonal Rainfall Forecast System (SEAS5) for forest fire prediction over Sumatera Island, Indonesia
Author(s) -
Furqon Alfahmi,
A Khaerima,
A W Byantoro
Publication year - 2021
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/893/1/012042
Subject(s) - environmental science , precipitation , seasonality , climatology , index (typography) , physical geography , geography , meteorology , ecology , geology , world wide web , computer science , biology
As part of the lungs of the world, the forest which covers Sumatra Island has a significant impact on the world oxygen production and the absorption of carbon dioxide. Drought over Sumatra Island often causes forest fires that can damage the function of forests as the world's lungs. Prediction of the seasonality of forest fires is needed to prevent and overcome forest fires that will occur next month. This study utilized seasonal rainfall predictions to predict the incidence of forest fires based on the drought index obtained. The result showed that ECMWF SEAS5 had good performance to predict rainfall over Sumatera Island for the first until the fourth months (lead time of 0 - 3). The Negative Standardized Precipitation Index (SPI) coincided with the increasing number of the hotspots. Furthermore, a linear equation has been applied to the calculated number of hotspots based on SPI from ECMWF.