The study of the effects of change in meteorological factors on rainfall pattern change in Hong Kong

Abstract

A study of the effect of change in meteorological factors on rainfall pattern in Hong Kong has been carried out because the formation of rainfall is controlled by other meteorological factors. Especially the extreme rainfall events seem to occur more frequently in recent years. In order to prepare for upcoming hazards, it is necessary to study the relationships between rainfall pattern and other meteorological factors in depth. The objectives of the study were to identify and examine the possible changes of rainfall pattern of Hong Kong on yearly, monthly and seasonal basis in 50 years (1961-2010), secondly to find out the relationship between meteorological factors and rainfall and finally to analyse the possible factors on the variation in rainfall pattern in the study period. Data has been obtained from the Hong Kong Observatory, Japan Meteorological Agency and International Pacific Research Centre. The data is presented in the form of spreadsheet in excel and SPSS. The characteristics of rainfall data have been studied by adopting trend analysis and the data have also been correlated with various meteorological parameters in the analysis of correlation and linear regression. It is concluded that for the rainfall pattern change the amount and intensity of rainfall has been increasing in 1961-2010, the trends are especially significant in the cases of summer. Meanwhile the length of rainy season also has an increasing trend. For the relationships between rainfall pattern parameters and meteorological parameters, the surface temperature of Hong Kong, SOI and Monsoon Index are relatively significant parameters to have relationship with rainfall pattern. But most of the significant correlations are mainly shown in seasonal and monthly data. In fact the effects of other possible factors like greenhouse effect would complicate the mechanism of rainfall pattern. The efficiency of direct correlation between different parameters may be lower than expected.