Performance Assessment of Global Climate Models for Thailand and Southeast Asia
Southeast Asia is a region vulnerable to climate variability that increases the frequency and intensity of natural disasters. Thailand, one of the Southeast Asia countries, is also highly affected by these natural disasters. Global climate models (GCMs) are developed to simulate the past and present...
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| Format: | Theses and Dissertations |
| Language: | English |
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Prince of Songkla University
2023
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| Online Access: | http://kb.psu.ac.th/psukb/handle/2016/17851 |
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| Institution: | Prince of Songkhla University |
| Language: | English |
| Summary: | Southeast Asia is a region vulnerable to climate variability that increases the frequency and intensity of natural disasters. Thailand, one of the Southeast Asia countries, is also highly affected by these natural disasters. Global climate models (GCMs) are developed to simulate the past and present climatic characteristics and predict the climate in the future. However, there are a variety of GCMs developed by many climate institutes around the world and their GCMs have different performances due to different parameterizations. Therefore, the aim of this study is to find the best GCMs in CMIP5 and CMIP6 that work over Southeast Asia and Thailand, respectively. In Southeast Asia, temperature and precipitation simulated by 40 CMIP5 GCMs are evaluated for the short-term period (1960 - 1999) and the long-term period (1901 - 1999). Simulation results are compared with ground-based and reanalysis data using ten statistical metrics. The results show that CNRM-CN5-2 has the best performance with the lowest total error, followed by CNRM-CM5, BNU-ESM, CESM-CAM5, and CCSM4, respectively. In Thailand, the temperatures simulated by 13 CMIP6-GCMs are evaluated for the near-to-current term period (2000 - 2014). The simulation results are compared with the ground-based and reanalysis data using five statistical metrics. The results show that CNRM-CM6-1, CNRM-CM6-1-HR and CNRM-ESM2-1 perform better than the other models in temperature simulation over Thailand. In particular, CNRM-ESM2-1 perform best for all study cases, while MIROC6 perform worst for all study cases in this study area. |
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