采用主要部件的分析和二阶段的簇分析的一个自动化过程被开发分类在 Urumqi 上占优势的摘要的气象学的条件，在世界上的最重重地弄脏的城市之一。代表不同循环模式和空气团特征的六簇用表面被分类 -- 并且上面气象学的变量在加热期间，从 2001 ～ 2008 的时期，和在摘要的簇和空气质量之间的关系被评估。当 Urumqi 在极其冷的、强壮的反气旋或在移居的气旋的前面时，最重的空气污染事件发生了，与轻风，湿表面空气，和相对干燥的上面的空气。中等污染被看 Urumqi 是否与相对更温暖的、更干燥的空气在 pre-cold/cold 是有更低的温度和轻风或中等反气旋的正面的段落。当 Urumqi 在移居的反气旋或在有中等的风的弱反气旋的前面，大多数温暖时，弄干空气，或在 cold/post-cold 正面的段落与相对强烈在北方的气流和猛冲，相对好的空气质量能被看见。这些结果建议在 Urumqi 的那空气污染是很仔细与摘要的气象学的条件有关，它在人的病态上为这里而且为天气和污染的微分影响的分析的城市的空气质量问题的不仅预言和控制提供一个重要基础。
An automated procedure employing principal-component analysis and a two-stage cluster analysis was developed to classify the synoptic meteorological conditions prevailing over Urumqi, one of the most heavily polluted cities in the world. Six clusters representing different circulation patterns and air-mass characteristics were classified using surface- and upper-meteorological variables during the heating period from 2001 to 2008, and the relationships between synoptic clusters and air quality were evaluated. The heaviest air-pollution episodes occurred when Urumqi was in either an extremely cold, strong anticyclone or at the front of a migrating cyclone, both with light winds, wet surface air, and relatively dry upper air. Moderate pollution was seen when Urumqi was in the pre-cold/cold frontal passages with lower temperatures and light winds or moderate anticyclone with relatively warmer, drier air. When Urumqi was at the front of a migrating anticyclone or in a weak anticyclone with moderate winds and most warm, dry air, or in the cold/post-cold frontal passages with relatively strongly northerly airflows and precipitation, relatively good air quality could be seen. These results suggest that air pollution in Urumqi is very closely related to the synoptic meteorological conditions, which provides an important basis for not only the prediction and control of urban air-quality problems here but also for the analysis of the differential impacts of weather and pollution on human morbidity.
Atmospheric and Oceanic Science Letters
Acknowledgements. This work was partially supported by the Knowledge Innovation Program of the Chinese Academy of Sciences （Grant No. KZCXl-YW-06-01）.
synoptic climatology, automated meteorological classification, air-pollution index （API）, Urumqi
Corresponding author： WANG Yue-Si, email@example.com