Modeling of monthly rainfall analysis in Aceh Besar District with Indonesia’s Sea-Surface Temperatures as the primary component

Abstract

Abstract. There are various fields that crucially require information about rainfall, including agriculture. A major drop or rise in rainfall may significantly impact the agriculture in Indonesia. For this reason, research regarding on variables that effected rainfall are still being improved by applying variety of models in order to provide accurate and closely related to the original data on rainfall forecast. Precise and accurate rainfall forecast is essential to help extension workers and farmers to determine when to start planting their crops and to decide what kind of crops are suitable for a particular region. Data applied in this research are data on monthly Sea-Surface Temperature (SST) data which are limited by 10°N – 15°S and 90°E – 145°E with a 1° x 1° grid, as well as data on monthly rainfall in Aceh Besar district which were obtained by averaging the data from 10 rain post points in collaboration with the BMKG of Aceh Besar District between 2010 – 2019. Correlation analysis between Sea-Surface Temperature (SST) and rainfall resulted in correlation value that fulfill the requirement of “sufficient” to “high” in a number of regions for each month. The highest correlation value was recorded by 0.87 for the positive correlation in October, and it was recorded by -0.87 for the highest negative value of correlation in December. Under those circumstances, by utilizing the Principal Component Regression (PCR) method, a forecasting model is created for each of the region with the highest correlation which allows for the identification of the area that most impacted rainfall in district of Aceh Besar. Model validation obtained error value of 37.1 or roughly around 19.5%. The highest value difference was occurred in October 2014, measuring by the value difference of 96 mm. The results of monthly rainfall forecast in 2021 provide a pattern of rainfall that is similar with the observation data obtained in August to December. Research results indicate that sea-surface Temperature (SST) in regions of Indonesia can be utilized as the indicator in forecasting rainfall at a district level.