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| 云迹风反演中高密度示踪云选取技术的研究 | |
| 引用本文： | 杨文凯,白洁,严卫,刘健文.云迹风反演中高密度示踪云选取技术的研究[J].气象,2007,33(4):35-39. |
| 作者姓名： | 杨文凯 白洁 严卫 刘健文 |
| 作者单位： | 1. 中国人民解放军理工大学气象学院,南京,211101;北京航空气象研究所 2. 北京航空气象研究所 3. 中国人民解放军理工大学气象学院,南京,211101 |
| 摘 要： | 云迹风反演中的一项很重要的工作是选取随风移动、变化缓慢的云，即示踪云。文中设计了一种示踪云选取算法，以改善云迹风的质量和密度分布。该算法的特色是反演风的位置并不固定在反演网格的中心位置，而是通过梯度分析的方法使反演风的位置得到优化，再经过积雨云检测和灰度分布均匀程度检验，剔除不适合用来反演的目标物。对用该方法选取的示踪云进行云迹风反演，然后对反演出的云迹风进行环流分析，并与探空风进行比较。结果表明，反演出的云迹风质量好，密度很高，清晰地反映出天气系统的风场结构。 |
| 关 键 词： | 云迹风 示踪云选取 梯度分析 均匀程度检验 |
| 收稿时间： | 2006/4/29 0:00:00 |
| 修稿时间： | 2006-04-292007-01-04 |
A Study of Selecting High Density Tracers in Deriving Winds from Geostationary Meteorological Satellite Data |
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| Yang Wenkai,Bai Jie,Yan Wei and Liu Jianwen.A Study of Selecting High Density Tracers in Deriving Winds from Geostationary Meteorological Satellite Data[J].Meteorological Monthly,2007,33(4):35-39. | |
| Authors: | Yang Wenkai Bai Jie Yan Wei and Liu Jianwen |
| Institution: | 1. Institute of Meteorology, PLA University of Science and Technology, Nanjing 211101 ; 2. Beijing Aviation Meteorology Research Institute |
| Abstract: | An important step in deriving winds from geostationary meteorological satellite data is selecting the clouds which move slowly and go with the wind, which is called tracers. A new scheme of tracer selection is developed to improve the quality and the density of cloud motion winds. The scheme has a novel feature that the extraction location of the tracer is not fixed at the center location of the grid, but first optimized at the location where the gradient is maximum in the grid domain, and then by cumulonimbus and uniformity test, the final tracers can be decided. Then cloud motion winds are derived from these tracers and after a circumfluence analysis on the cloud motion winds, the cloud motion winds are compared with the rawinsonde winds. The result shows that the cloud motion winds have well quality and higher density, and the wind structure of weather system can be seen clearly from them. |
| Keywords: | cloud motion wind tracer selection gradient analysis uniformity test |
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