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Debris flows can cause severe loss of human lives and damage to property, especially on densely populated hilly terrains. In the changing climate, the frequency of debris flows is on a rising trend. Therefore, it is important to forecast possible scenarios of debris flows under extreme weather conditions. Previous numerical studies often deal with one individual debris flow in one analysis. Yet a large number of debris flows can occur in a large storm. This paper presents a physically based model to predict likely debris flow clusters on Hong Kong Island with an area of approximately 80 km2 considering the influence of the changing climate. Firstly, a slope stability analysis is conducted, and unstable cells and landslide deposition areas are predicted. Then clusters of debris flows initiating from these landslides are simulated considering hillslope erosion. The models are validated with historical debris flows triggered by a rainstorm in 2008. Finally, debris flow clusters under three reference extreme rainstorms (i.e. 44%, 65% and 85% of the 24-h probable maximum precipitation, PMP) are predicted. With the increase of rainstorm magnitude, numerous debris flows can occur simultaneously and merge, posing much greater threat to society. The consequences of debris flows grow dramatically when the magnitude reaches a certain extent, i.e. 65% of the 24-h PMP. [ABSTRACT FROM AUTHOR]

• The climate change is identified by the ground measurement of HK over the 37 years. • The building energy needs can be influenced by the climate change. • The TMY is suggested to be updated every 10 years or less for the climate change. • 10 to 12 years of the latest data can be proper for TMY in the changing climate. The weather data is essential to simulation-based building energy studies. The weather data should render the features of the changing climate. The typical meteorological year (TMY) developments using the long-term climate data, however, may weaken the impact of the recent climate change and the corresponding building energy responses. This paper studies the changes of the climate data (by ground measurements) and their impacts on the simulation results of the subtropical Hong Kong over 37 years. The climate changes for solar radiation, temperature and wind speed were summarised, and their daily total, average, extreme, and/or deviation values were presented. The typical weather data developed by the ground measurements of different times and period lengths (within the 37 years) determined the cooling load of a representative building in the Hong Kong, and the outcomes were compared to that of the yearly data. The period (length) of the raw measurements and the update frequency of TMY were optimized for the building energy simulations in the changing climate. [ABSTRACT FROM AUTHOR]