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

被引:0
|
作者
Chea, Kimhong [1 ,2 ]
Manomaiphiboon, Kasemsan [1 ,2 ]
Aman, Nishit [1 ,2 ]
Thepa, Sirichai [3 ]
Junpen, Agapol [1 ,2 ]
Devkota, Bikash [1 ,2 ]
机构
[1] King Mongkuts Univ Technol Thonburi, Joint Grad Sch Energy & Environm, Bangkok 10140, Thailand
[2] Minist Higher Educ Sci Res & Innovat, Ctr Excellence Energy Technol & Environm, Bangkok 10400, Thailand
[3] King Mongkuts Univ Technol Thonburi, Sch Energy Environm & Mat, Bangkok 10140, Thailand
来源
SCIENCEASIA | 2021年 / 47卷 / 05期
关键词
urban climate; heat index; extreme condition; Nino3; 4; dipole mode index; HEAT INDEX; TEMPERATURE; RAINFALL;
D O I
10.2306/scienceasia1513-1874.2021.067
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Characterizion of ambient thermal comfort using a standard heat index (HI) was performed for Bangkok, Chiang Mai, Phnom Penh, and Vientiane, with data covering 37 and 17 years for the first two and last two cities, respectively. HI was lower during the night and the early morning but high in the afternoon in both the dry and the wet seasons. Its diurnality showed a tendency to be more influenced by temperature than by relative humidity. The daily maximum heat index (DMHI) was the highest in April-May due to both warm and humid conditions, but was the lowest in December-January due to cool dry air. Among the five considered risk DMHI levels, "extreme caution" occurred the most often for the majority of the months, and "danger" occurrence tended to increase in April-June. Low-latitude cities (i.e., Bangkok and Phnom Penh) showed less pronounced diurnality and seasonality due to their proximity to the Equator and large water bodies. Increasing trends in seasonal DMHI average were found in Bangkok, Chiang Mai, and Vientiane; while decreasing trends in Phnom Penh were found in both seasons. The trends in seasonal DMHI extremes were consistent with those of the seasonal DMHI average in terms of direction (except Bangkok). Polynomial regression modeling, developed for trend factor attribution, suggests more influence of humidity than of temperature for most trends. Partial correlation analysis indicates seasonal DMHI average to be more associated with El Nino-Southern Oscillation than with the Indian Ocean Dipole.
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页码:618 / +
页数:17
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