Improvement the largest lyapunov exponent for measurement of the winter monsoon prediction in Thailand

Abstract

Thailand is an agricultural country. So that, the water resources are important. The water management is very important for keep the water used in necessary time. The monsoon is causes a heavy rain. The monsoon prediction by the mathematical model is important. The accuracy of the forecasts by the predictability measurement method is very important. In this research, improvement the predictability measurement for the winter monsoon prediction in the Southeast Asia by the shallow water model. The data from The Bjerknes Centre for Climate Research (BCCR), University of Bergen, Norway. The global climate model is Bergen Climate Model (BCM) Version 2.0 (BCCR-BCM2.0) of the Intergovernmental Panel on Climate Change (IPCC) are used. The data for run the model on 19 December 2059 from the WCRP CMIP3 is the initial condition. The model is run for 7 days forecast. The Lyapunov exponent (LE) is the predictability measurement method for verify the efficiency of the model and improvement the largest Lyapunov exponent (LLE) by limit theorems for verify the efficiency of the model too. The results to show that the shallow water model can be prediction the winter monsoon for 4 days forecast is accuracy when compare with the BCCR-BCM2.0 model and measure the accuracy by LE. In addition, the improvement the LLE by limit theorems can be measure the accuracy of the winter monsoon for 4 days forecast to same as the LE. Therefore, the improvement the LLE by limit theorems can be measure the accuracy of the winter monsoon prediction in Thailand by the shallow water model are suitable.