The Unprecedented Freezing Disaster in January 2008 in Southern China and Its Possible Association with the Global Warming

The unprecedented disaster of low temperature and persistent rain, snow, and ice storms, causing widespread freezing in the Yangtze River Basin and southern China in January 2008, is not a local or regional event, but a part of the chain events of large-scale low temperature and snow storms in the same period in Asia. The severity and impacts of the southern China 2008 freezing disaster were the most significant among others. This disastrous event was characterized by three major features： （1） snowfall, freezing rain, and rainfall, the three forms of precipitation, coexisted with freezing rain being the dominant producer responsible for the disaster; （2） low temperature, rain and snow, and freezing rain exhibited extremely great intensity, with record-breaking measurements observed for eight meteorological variables based on the statistics made by China National Climate Center and the provincial meteorological services in the Yangtze River Basin and southern China; （3） the disastrous weathers persisted for an exceptionally long time period, unrecorded before in the meteorological observation history of China. The southern China 2008 freezing disaster may be resulted from multiple different factors that superimpose on and interlink with one another at the right time and place. Among them, the La Nina situation is a climate background that provided conducive conditions for the intrusions of cold air into southern China; the persistent anomaly of the atmospheric circulation in Eurasia is the direct cause for a succession of cold air incursions into southern China; and the northward transport of warm and moist airflows from the Bay of Bengal and South China Sea finally warranted the formation of the freezing rain and snow storms and their prolonged dominance in the southern areas of China. A preliminary discussion of a possible association of this disastrous event with the global warming is presented. This event may be viewed as a short-term regional perturbation to the global warming. There is not any possibility for this event to divert the long-term trend and the overall pattern of the global warming.

A primary-secondary background model with sliding window PCA algorithm

Rain and snow seriously degrade outdoor video quality.In this work,a primary-secondary background model for removal of rain and snow is built.First,we analyze video noise and use a sliding window sequence principal component analysis de-nosing algorithm to reduce white noise in the video.Next,we apply the Gaussian mixture model(GMM)to model the video and segment all foreground objects primarily.After that,we calculate von Mises distribution of the velocity vectors and ratio of the overlapped region with referring to the result of the primary segmentation and extract the interesting object.Finally,rain and snow streaks are inpainted using the background to improve the quality of the video data.Experiments show that the proposed method can effectively suppress noise and extract interesting targets.