Author(s)

Surasit Punyawansiri^*, Bancha Kwanyuen

Department of Irrigation Engineering, Faculty of Engineering, Kasetsart University, Nakhon Pathom, Thailand.

The study evaluates the effect of climate change on temperature, which is one of the most important variables in water resources management and irrigation scheduling. Climate prediction is necessary in the agricultural and hydrological analysis. This study proposed an approach to the application of the Long Ashton Research Station Weather Generator (LARS-WG) in Coupled Model Inter-comparison Project Phase 5 (CMIP5) under EC-Earth and MPI-ESM-MR. The first step is model calibration, where the observed dataset is analyzed statistically. In the second stage, the synthetic data and observed data are checked for Kolmogorov-Smirnov and the means and standard deviations. In order to evaluate the response of temperature under future warmer climate trends, the approach was assessed using data series. These parameters consisted of the minimum and maximum temperature at the Phitsanulok Meteorological Station (WMO Index 48378) and RCP4.5 climate change scenario for the base period as well as for 2021-2040 (the near future), 2041-2060 (the medium future) and 2061-2080 (the far future). The results of the numerical applications indicated that the linkage between the observed data spatially downscaled from LARS-WG simulations with the historical one of the locations during the baseline period had a very good accuracy. It was also found that the future climate change of temperature contributed to higher change. The mean of minimum temperature in the baseline year was 23.13°C while the mean of minimum temperature in the projection period for 2021-2040, 2041-2060 and 2061-2080 is expected to be 24.09 (+4.18%), 24.49 (+5.94%) and 24.82 (+7.36%)°C, and 24.12 (+4.32%), 24.82 (+7.36%) and 25.08 (+8.48%)°C for the EC-Earth and MPI-ESM-MR, respectively. While, the mean of maximum temperature in the baseline year was 33.41°C, the maximum temperatures are projected to increase at 34.47 (+3.19%), 34.88 (+4.43%) and 35.21 (+5.40%)°C, and 34.53 (+3.36%), 35.19 (+5.34%) and 35.30 (+5.67%)°C, respectively. Furthermore, the future local surface temperatures from the MPI-ESM-MR project tended to be higher than EC-Earth. In conclusion, the study results indicate that in coming three time periods, the minimum and maximum temperature increase is expected in Phitsanulok province, Thailand.

LARS-WG, CMIP5, Climate Change, Downscaling, Temperature

Punyawansiri, S. and Kwanyuen, B. (2020) Forecasting the Future Temperature Using a Downscaling Method by LARS-WG Stochastic Weather Generator at the Local Site of Phitsanulok Province, Thailand. Atmospheric and Climate Sciences, 10, 538-552. doi: 10.4236/acs.2020.104028.