Evaluation of WRF-Downscaled CMIP5 Climate Simulations for Precipitation and Temperature over Thailand (1976–2005): Implications for Adaptation and Sustainable Development

Chakrit Chotamonsak (), Duangnapha Lapyai, Atsamon Limsakul, Kritanai Torsri, Punnathorn Thanadolmethaphorn and Supachai Nakapan
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Chakrit Chotamonsak: Department of Geography, Faculty of Social Sciences, Chiang Mai University, Chiang Mai 50200, Thailand
Duangnapha Lapyai: Office of Research Administration, Chiang Mai University, Chiang Mai 50200, Thailand
Atsamon Limsakul: Climate Change and Environmental Research Center, Pathum Thani 12120, Thailand
Kritanai Torsri: Hydro-Informatics Institute, Ministry of Higher Education, Science, Research, and Innovation, Bangkok 10900, Thailand
Punnathorn Thanadolmethaphorn: Office of Strategy Management, Office of University, Chiang Mai University, Chiang Mai 50200, Thailand
Supachai Nakapan: Department of Physics and Materials Science, Faculty of Science, Chiang Mai University, Chiang Mai 50200, Thailand

Sustainability, 2025, vol. 17, issue 21, 1-32

Abstract: Dynamical downscaling is an essential approach for bridging the gap between coarse-resolution global climate models and regional details required for climate impact assessment and sustainable development planning. Thailand, a climate-sensitive country in Southeast Asia, requires robust climate information to support its adaptation and resilience strategies. This study evaluated the Weather Research and Forecasting (WRF) model in dynamically downscaling selected Coupled Model Intercomparison Project Phase 5 (CMIP5) simulations over Thailand during the baseline period of 1976–2005. A two-way nested WRF configuration was employed, with domains covering Southeast Asia (36 km) and Thailand (12 km) in the model. Model outputs were compared with gridded observations from the Climatic Research Unit (CRU TS), and spatial variations were analyzed across six administrative regions in Thailand. The WRF successfully reproduces broad climatological patterns, including the precipitation contrast between mountainous and lowland areas and the north–south gradient of temperature. Seasonal cycles of rainfall and temperature are generally well represented, although systematic biases remain, specifically the overestimation of orographic rainfall and a cold bias in high-elevation regions. The 12 km WRF simulations demonstrated improved special and temporal agreement with the CRU TS dataset, showing a national-scale wet bias (MBE = +17.14 mm/month), especially during the summer monsoon (+65.22 mm/month). Temperature simulations exhibited seasonal derivations, with a warm bias in the pre-monsoon season and a cold bias during the cool season, resulting in annual cold biases in both maximum (−1.25 C) and minimum (−0.80 C) temperatures. Despite systematic biases, WRF-CMIP5 downscaled framework provides enhanced regional climate information and valuable insights to support national-to-local climate change adaptation, resilience planning, and sustainable development strategies in Thailand and the broader Southeast Asian region.

Keywords: WRF model; dynamical downscaling; CMIP5; precipitation; temperature; Thailand; regional climate modeling; model evaluation; climate change adaptation; sustainable development; climate resilience (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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