Spatio-temporal variation of haze days and atmospheric circulation pattern in China (1961-2013)

摘要

Severe haze, which threatens human health and the economic development, occurs more and more frequently in China. For more than 60 days in 2013, severe haze covered nearly all the eastern and southern parts of China, in particular the Beijing-Hebei-Henan region, the Shanghai-Nanjing-Hangzhou region, and the Guangdong-Guangxi region. Based on observed haze data from 181 ground based meteorological stations and reanalysis data from NCEP for the period from 1961 to 2013, a statistical analysis on spatio-temporal changes in haze days and their relationship with meteorological parameters in China has been conducted. Due to high interests and quantitative details, Beijing, Nanjing, and Guangzhou are chosen to represent the typical haze-affected megacities located in the three identified regions. The research results reveal that the frequency of haze days has persistently increased in Nanjing and Guangzhou since 1961, while Beijing experienced an upward trend since 2000. An abrupt change point in the annual number of haze days in China is found for the year 2000, since then the frequency of haze days increased significantly. The analysis also shows that the probability of rainless days and windless days to occur before or at a haze day ranges between 80 and 90. Furthermore, the frequency of haze days shows a strong positive correlation with the frequency of windless days and rainless days. The time series of both meteorological indicators have shown steady increasing trends since 1961. Next to industrial emissions, windless days and rainless days can be attributed to be the major climate factors related to the worsening of the haze events in China. This relation is underlined by the atmospheric circulation pattern, which were dominated by a weaker than usual cold wave over China in December 2013. This pressure system led to warm-dry weather conditions and enabled inversions, and hence supported the formation of more than average haze days. (C) 2014 Elsevier Ltd and INQUA. All rights reserved.