Heat Illness Related Meteorology over Chiangmai Using Automatic Weather Station Observed Data

Abstract

This research is a part of study of heat illness vulnerability. Understanding heat characteristic, especially in tropical area, would decrease loss from heat deceases and also support tourism in tropical countries. The aim of this research is to apply the meteorological sensor dataset in Chiangmai (a famous city in northern Thailand), which is under the control of Thai Meteorological Department, from 2015-2017 to investigate heat index characteristic. Two elements, temperature and relative humidity, were used to calculate heat index following Steadman’s equation. Analyzed heat index would be arranged by its intensity and then applied on heat illness warning. The study demonstrated that heat index warning from Automatic Weather Station data analysis could get along with the maximum temperature historical statistics data which observed by weather stations. Local people and visitors in Chiangmai mostly suffer from heat in between March and June. The greatest vulnerability to heat illness in Chiangmai was in April and May. This extreme-heat period is consistent with the report from Department of Decease Control Thailand, an amount of heat illness patients is very high in April and May. Moreover, the results show that even if the air temperature is getting low in after summer season but heat index is still high through the year. So, people still need to be aware of heat deceases and always concern about environmental heat when doing outdoor activities. In the future, AWS data from every station over Thailand would be used to develop a real-time Heat Illness Alert System.