Evaluation of CMIP6 GCMs for simulations of temperature over Thailand and nearby areas in the early 21st century

• Main Authors: Suchada Kamworapan, Pham Thi Bich Thao, Shabbir H. Gheewala, Sittichai Pimonsree, Kritana Prueksakorn
• Other Authors: University of Phayao
• Format: Article
• Published: 2022
• Subjects: Multidisciplinary
• Online Access: https://repository.li.mahidol.ac.th/handle/123456789/79287
• Institution: Mahidol University

This study evaluates the performance of 13 global climate models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) for simulating the temperature over Thailand during 2000–2014, for land-only, sea-only, and both land and sea. Both observation and reanalysis datasets are employed to compare with the GCMs, evaluated by five performance metrics including mean annual temperature, mean bias errors, mean seasonal cycle amplitude, correlation coefficient, and root mean square error. GCMs are ranked by relative error of all performance metrics. Results show that the temperatures from most GCM simulations are below the mean reference data (i.e., average of ground-based and reanalysis datasets), with north to south gradient in the range from 19 °C to 33 °C. In addition, all the GCM biases range from -0.07 °C to 2.78 °C and show severity of the temperature changes in spatial pattern ranging from -5 °C to 15 °C. The correlations of most GCMs range from 0.70 to 0.95, while the magnitudes of error are less than 2 °C. Study cases point out that the 13-MODEL ENSEMBLE, CESM2, and CNRM-CM6-1 perform better than the other models in simulating the temperature over Thailand for land-only and sea-only, and both land and sea cases, respectively, while MIROC6 performs the worst for all study cases in this study area. From the designed methodology, CNRM-CM6-1 has the best performance and is the most appropriate choice to simulate the temperature for the overall Thailand area.