Urban heat island analysis for Bangkok: multi-scale temporal variation, associated factors, directional dependence, and cool island condition

Abstract

This study analyzed urban heat island characteristics in Bangkok, observed during a period of 10 years (2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015) with emphasis on the dry season when the urban heat island is intensified in both daytime and nighttime as compared to the wet season. December-January was found to be the months of peak urban heat island intensity (UHII) in terms of average. The intensity is relatively large at night due to the faster cooling rate during the early evening at the rural site whose thermal admittance of land surface is lower than the urban site. UHII is slightly larger during the weekdays than the weekend, suggesting certain degree of influence of anthropogenic heat emitted in the urban area. UHII is negatively correlated with most of rain, cloud, relative humidity, and wind speed variables. The assessment of polar plots shows UHII dependence on wind direction. The statistical regression models relating UHII to selected meteorological variables are capable of explaining the variability of the original data by 82% for daytime UHII and 66% for nighttime. Southwesterly wind direction and persistence were found to be important in modulating UHII, and both appear in the final regression models. The presence of dry-season cool island events was also investigated, and it was found that they are generally induced by the high intensity of urban-alone/urban-rural rain, cloud, relative humidity, or urban wind speed (or combined). Overall, the findings from the study provide enhanced perspectives, which can support urban policy and planning related to weather for the study area.

Ambient thermal comfort analysis for four major cities in Thailand, Cambodia, and Laos: Variability, trend, factor attribution, and large-scale climatic influence

“…( 4) HI was affected by geographical location with less pronounced diurnality and seasonality in the low-latitude cities (i.e., Bangkok and Phnom Penh) due to their proximity to the Equator and to large water bodies. (5) In both dry and wet seasons, increasing trends in seasonal DMHI average were found in all cities (except Phnom Penh), and increasing trends in seasonal DMHI extreme were found in Chiang Mai and Vientiane. These suggest concern and severity.…”

“…The area background of each weather station within a 2-km radius was visually inspected using recent satellite images from Google Earth (Fig. S3) [5,23]. Both BK and PP lie in a low-level plain at low latitudes (11°-14°).…”

“…Prolonged exposure to heat strain may have several negative effects, e.g., fatigue and irritability, heat cramps and exhaustion, and even heat stroke [4]. A large or well-developed city is generally associated with urban heat islands, a phenomenon with outdoor temperature in its center (i.e., urban core) being larger than that in its surroundings due to modified land cover and built-up materials, emitting anthropogenic heat [5,6]. Such factors could also modify surface moisture and then humidity [6].…”

Evolution of Urban Haze in Greater Bangkok and Association with Local Meteorological and Synoptic Characteristics during Two Recent Haze Episodes

“…where u * is the frictional velocity, θ * is the temperature scale, k is the von Karman constant (0.4), g is the acceleration due to gravity, z 0 is the roughness length, z u is the single measurement height of wind (here, 50 m or 100 m separately), U(z u ) is the hourly wind speed, z θ v1 and z θ v2 are the two measurement heights of temperature (here, 2 m and 50 m, respectively), θ v1 and θ v2 are the virtual potential temperature at those two heights, T v1 and T v2 are the virtual temperatures at those two heights, respectively, and Ψ M and Ψ H are the Businger stability correction functions for wind and temperature, respectively. As in Kamma et al (2020) [51], the surrounding area of the M6 tower within a 2 km radius was assessed using Google Earth (https://www.google.com/earth/) (Google, Mountain View, CA, USA) and visually examined, finding ponds and paddy fields being dominant with built-up areas present in its northeast quadrant. Using the classification by Stewart and Oke (2012) [52], the approximate local climate zone is "sparsely built" with terrain roughness (or Davenport) class 5, whose roughness length (z 0 ) equals 0.25.…”

Integration of phase change material into fiber cement roof for reduction of heat accumulation in buildings

“…Energy consumption in the building sector continually rises over the past decade, due to the rapid growth of urbanization, the population growth, more time spent indoors, and more requirement for the living indoors quality, etc. [1]. Building energy consumption currently accounts for a significant part of the total global energy consumption.…”