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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Prince of Songkla University
2023
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th-psu.2016-178512023-02-27T03:37:28Z Performance Assessment of Global Climate Models for Thailand and Southeast Asia Suchada Kamworapan Kritana Prueksakorn Faculty of Technology and Environment คณะเทคโนโลยีและสิ่งแวดล้อม Global climate models CMIP5 CMIP6 Temperature Precipitation Southeast Asia Thailand 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. Thesis (Ph.D., Earth System Science (International Program))--Prince of Songkla University, 2021 2023-02-27T03:37:28Z 2023-02-27T03:37:28Z 2021 Thesis http://kb.psu.ac.th/psukb/handle/2016/17851 en Attribution-NonCommercial-NoDerivs 3.0 Thailand http://creativecommons.org/licenses/by-nc-nd/3.0/th/ application/pdf Prince of Songkla University |
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Global climate models CMIP5 CMIP6 Temperature Precipitation Southeast Asia Thailand Suchada Kamworapan Performance Assessment of Global Climate Models for Thailand and Southeast Asia |
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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. |
author2 |
Kritana Prueksakorn |
author_facet |
Kritana Prueksakorn Suchada Kamworapan |
format |
Theses and Dissertations |
author |
Suchada Kamworapan |
author_sort |
Suchada Kamworapan |
title |
Performance Assessment of Global Climate Models for Thailand and Southeast Asia |
title_short |
Performance Assessment of Global Climate Models for Thailand and Southeast Asia |
title_full |
Performance Assessment of Global Climate Models for Thailand and Southeast Asia |
title_fullStr |
Performance Assessment of Global Climate Models for Thailand and Southeast Asia |
title_full_unstemmed |
Performance Assessment of Global Climate Models for Thailand and Southeast Asia |
title_sort |
performance assessment of global climate models for thailand and southeast asia |
publisher |
Prince of Songkla University |
publishDate |
2023 |
url |
http://kb.psu.ac.th/psukb/handle/2016/17851 |
_version_ |
1762854933822963712 |