Although the Tibetan Plateau is widely thought as a potential dust source to the atmosphere over East Asia,little is known about the temporal changes of Tibetan dust activities and Tibetan dust source strength.In this study,we address these two issues by analyzing dust storm frequencies and aerosol index through remote sensing data and by means of numerical simulation.The findings indicate that monthly dust profiles over the Tibetan Plateau vary significantly with time.Near the surface,dust concentration increases from October,reaches its maximum in February March,and then decreases.In the middle to upper troposphere,dust concentration increases from January,reaches its maximum in May June,and decreases thereafter.Although Tibetan dust sources are important contributors to dust in the atmosphere over the Tibetan Plateau,their contribution to dust in the troposphere over eastern China is weaker.The contribution of Tibetan dust sources to dust in the atmosphere over the Tibetan Plateau decreases sharply with height,from 69% at the surface,40% in the lower troposphere,and 5% in the middle troposphere.Furthermore,the contribution shows seasonal changes,with dust sources at the surface at approximately 80% between November and May and 45% between June and September;in the middle and upper troposphere,dust sources are between 21% from February to March and less than 5% in the other months.Overall,dust aerosols originating from the Tibetan Plateau contribute to less than 10% of dust in East Asia. 相似文献
Spatial clustering is widely used in many fields such as WSN (Wireless Sensor Networks), web clustering, remote sensing and so on for discovery groups and to identify interesting distributions in the underlying database. By discussing the relationships between the optimal clustering and the initial seeds, a clustering validity index and the principle of seeking initial seeds were proposed, and on this principle we recommend an initial seed-seeking strategy: SSPG (Single-Shortest-Path Graph). With SSPG strategy used in clustering algorithms, we find that the result of clustering is optimized with more probability. At the end of the paper, according to the combinational theory of optimization, a method is proposed to obtain optimal reference k value of cluster number, and is proven to be efficient. 相似文献
Natural Resources Research - Depletion of shallow mineral resources caused by deep mining has become an inevitable trend, and deep mining can increase safety accidents and geological hazards.... 相似文献