This study examines the long-term variations of tropical cyclone(TC) frequency and intensity in the South China Sea(SCS) and the vicinity of Hong Kong from 1961 to 2010 based on the best track data of four main weathe...This study examines the long-term variations of tropical cyclone(TC) frequency and intensity in the South China Sea(SCS) and the vicinity of Hong Kong from 1961 to 2010 based on the best track data of four main weather agencies in the western North Pacific, namely the Hong Kong Observatory, China Meteorological Administration, Regional Specialized Meteorological Center Tokyo and Joint Typhoon Warning Center of the United States. To account for the discrepancy in the best track data between agencies, the maximum sustained wind speeds are standardized to the 10-minute average before data analysis. Moreover, a sensitivity assessment based on three different data scenarios is also conducted to study the uncertainty in trend analysis due to the discrepancy in the datasets from various agencies. The results show that, likely modulated by the El Ni?o Southern Oscillation and the Pacific Decadal Oscillation, there exist strong inter-annual and inter-decadal variations in the TC frequency in the SCS and the vicinity of Hong Kong.For the long-term trend, all dataset/scenario combinations depict a decrease in the TC frequency in the SCS and the vicinity of Hong Kong during the study period, but the trend is not statistically significant at 5% level for most of the datasets. As for the TC intensity, the discrepancy between weather agencies remains very substantial even when the difference in the wind speed averaging period is accounted for. The large differences in the available datasets do not allow for a reliable detection of the long-term trend of the TC intensity in the SCS. The study of the TC impacts on Hong Kong reveals that there is no significant trend on the TC-induced extreme rainfall in Hong Kong. The extreme high winds associated with TCs within 500 km range of Hong Kong have no significant trend at Waglan Island(offshore island) while those of the urban station at Kai Tak have a signifi-cant decreasing trend.展开更多
文摘This study examines the long-term variations of tropical cyclone(TC) frequency and intensity in the South China Sea(SCS) and the vicinity of Hong Kong from 1961 to 2010 based on the best track data of four main weather agencies in the western North Pacific, namely the Hong Kong Observatory, China Meteorological Administration, Regional Specialized Meteorological Center Tokyo and Joint Typhoon Warning Center of the United States. To account for the discrepancy in the best track data between agencies, the maximum sustained wind speeds are standardized to the 10-minute average before data analysis. Moreover, a sensitivity assessment based on three different data scenarios is also conducted to study the uncertainty in trend analysis due to the discrepancy in the datasets from various agencies. The results show that, likely modulated by the El Ni?o Southern Oscillation and the Pacific Decadal Oscillation, there exist strong inter-annual and inter-decadal variations in the TC frequency in the SCS and the vicinity of Hong Kong.For the long-term trend, all dataset/scenario combinations depict a decrease in the TC frequency in the SCS and the vicinity of Hong Kong during the study period, but the trend is not statistically significant at 5% level for most of the datasets. As for the TC intensity, the discrepancy between weather agencies remains very substantial even when the difference in the wind speed averaging period is accounted for. The large differences in the available datasets do not allow for a reliable detection of the long-term trend of the TC intensity in the SCS. The study of the TC impacts on Hong Kong reveals that there is no significant trend on the TC-induced extreme rainfall in Hong Kong. The extreme high winds associated with TCs within 500 km range of Hong Kong have no significant trend at Waglan Island(offshore island) while those of the urban station at Kai Tak have a signifi-cant decreasing trend.
