曼谷城市热量时空特征建模

Modeling Spatio-Temporal Characteristicsof Urban Heat in Bangkok Juan A. AceroVivek K. SinhSteven L. Rubinyi Urban, Disaster Risk Management, Resilience and Land Global DepartmentJune 2025 Policy Research Working Paper11158 Abstract in surrounding rural areas. The highest temperature differ-ences (>4°C) occur at night during this season, with over50% of BMA’s urban area and population experiencing sus-tained exposure to these elevated temperatures. In contrast,the smallest temperature differences occur in the hot anddry season, despite it being the hottest overall, due to lowsoil moisture limiting rural cooling. Under specific condi-tions, an urban cool island (Turban < Turban) may developduring the daytime. Compact urban areas exhibit the mostsignificant heating, although vegetated areas within BMAare also affected. These findings support the design of tar-geted mitigation strategies. Urban areas accumulate heat, developing distinct urbanclimates that differ from the regional climate, leading toelevated mean air temperatures within cities. In tropicalclimates, such as Bangkok, this urban heat can contributeto high levels of heat stress. This study analyzes the spatialand temporal variation of air temperature in the BangkokMetropolitan Administration (BMA) using dynamic cli-mate modeling (WRF, v4.2). The analysis focuses on threedistinct climatic periods: the cool and dry season (Novem-ber–February), the hot and dry season (March–May),and the wet monsoon season (June–October). Resultsindicate that during sunrise in the cool and dry season,urban temperatures can be up to 6.4°C higher than those The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about developmentissues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry thenames of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely thoseof the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank andits affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent. Modeling Spatio-Temporal Characteristics of Urban Heat in Bangkok∗ Juan A. Acero, Vivek K. Sinh, Steven L. Rubinyi Keywords:urban heat island, climate modeling, heat stress, Bangkok, land use JEL Classification Codes: Q54(Natural Disasters and Their Management);R14(Land Use Patterns);R11(Regional Economic Activity);O18(Urban Policy);Q51(Valuation of Environmental Effects) 1.Introduction Hot and humid conditions in tropical metropolitan areas like Bangkok frequently result in highlevels of heat stress. Populations in such cities already experience elevated temperatures, whichare further exacerbated by humidity, making them highly vulnerable to extreme heat eventslinked to climate change. As Bangkok’s population has increased over recent decades, urbansprawl has expanded, contributing to changes in the local climate (Varnakovida & Ko, 2023). Thereplacement of natural or rural surfaces with artificial impervious surfaces has a direct effect onurban climate, leading to the development of the Urban Heat Island (UHI) phenomenon—de-fined as a metropolitan area that is significantly warmer than its surrounding rural areas (Oke,1987; Oke T. R. et al., 2017; Tian et al., 2021). UHI is characterized not only by increased air tem-perature—particularly at night—but also by reduced humidity and lower mean wind speedscompared to rural surroundings. Due to the complexity of urban morphology and its interactionwith the regional climate, a wide range of microclimates can form within a single metropolitanarea (Oke T. R. et al., 2017; Stewart & Oke, 2012). In addition to its structural characteristics, urbanization introduces anthropogenic heat emissionsfrom sources such as air conditioning, transportation, and industrial activity, which further in-tensify the UHI effect ((Allegrini et al., 2015; Oke T. R. et al., 2017; Singh et al., 2022). These an-thropogenic heat (AH) fluxes from transport, buildings, and industry significantly affect the ur-ban energy balance and contribute to localized warming (Chow et al., 2014; Hii et al., 2014). How-ever, estimating these fluxes remains challenging, and empirical models are commonly used toapproximate emissions across sectors (Singh et al., 2020). Given rising global temperatures (Limsakul, 2020) and already high levels of heat stress in Bang-kok (Arifwidodo & Chandrasiri, 2020), quantifying the contribution of urban warming to regionalclimate dynamics is critical for effective climate adaptation (Webster & Mcelwee, 2009; WorldBank, 2009). Studies from East Asian cities, including Bangkok, have found that mortality in-creases by 2–6% for every 1°C rise in air temperature above 29°C—a threshold frequently ex-ceed