Statistical Downscaling for Rainfall Forecasts Using Modified Constructed Analog Method in Thailand

Abstract

The simulations of rainfall from historical data were created in this study by using statistical downscaling. Statistical downscaling techniques are based on a relationship between the variables that are solved by the General Circulation Models (GCMs) and the observed predictions. The Modified Constructed Analog Method (MCAM) is a technique in downscaling estimation, suitable for rainfall simulation accuracy using weather forecasting. In this research, the MCAM was used to calculate the Euclidean distance to obtain the number of analog days. Afterwards, a linear combination of 30 analog days is created with simulated rainfall data which are determined by the corresponding 5 days from the adjusted weights of the appropriate forecast day. This method is used to forecast the daily rainfall and was received from the Thai Meteorological Department (TMD) from the period during 1979 to 2010 at thirty stations. The experiment involved the use of rainfall forecast data that was combined with the historical data during the rainy season in 2010. The result showed that the MCAM gave the correlation value of 0.8 resulting in a reduced percentage error of 13.66%. The MCAM gave the value of 1094.10 mm which was the closest value to the observed precipitation of 1119.53 mm.