Development of untypical meteorological year in the hot and humid climate of Indonesia: An application for thermal stress assessment

Abstract

Urban open spaces, which are crucial for outdoor activities, are increasingly vulnerable to deviations in thermal comfort due to extreme/untypical climates. The use of typical meteorological year (TMY) datasets for designing built environments has limitations in accounting for climate deviations caused by extreme/untypical climates. Therefore, there is a need to develop new datasets that more accurately represent atypical climates and can be used for adaptive strategies under these atypical conditions. This study aims to develop the untypical meteorological year (UTMY) dataset consisting of minimum untypical meteorological year (UTMY-N) and maximum untypical meteorological year (UTMY-M) datasets which is applied for thermal stress assessment, through a case study in the hot and humid climate of Indonesia. Finkelstein-Schafer statistics with weighting applied to more climate variables, including global horizontal irradiance (GHI), temperature, dew point temperature, and wind speed were used to select extreme/untypical years. The large weighting of the GHI and temperature variables influenced the selection of extreme/untypical years that represent extremes for these variables compared with other variables in the UTMY dataset. The average annual temperature in the UTMY-M dataset across 106 sites is 0.2 °C to 1.0 °C higher than that in the TMY dataset, while the UTMY-N dataset is 0.4 °C to 1.8 °C lower. Compared with the TMY dataset, monthly and annual thermal stress calculations using the universal thermal climate index (UTCI) derived from the UTMY dataset are more effective in assessing the farthest thermal stress deviations (the upper maximum and lower minimum limits) under untypical climate conditions in each climate zone.