| 自动气象站运行效能统计 |
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| 引用本文： | 李雁,梁海河,孟昭林,裴翀,石城.自动气象站运行效能统计[J].应用气象学报,2009,20(4):504-509. |
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| 作者姓名： | 李雁 梁海河 孟昭林 裴翀 石城 |
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| 作者单位： | 中国气象局气象探测中心, 北京 100101 |
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| 摘 要： | 利用中国气象局气象探测中心综合气象观测系统运行监控平台中对自动气象站的监控情况, 将监控平台上2100余套国家级自动气象站的运行效能分华北、东北、华东、中南、西南、西北6个区域从数据到报率、可用性和可靠性3方面进行统计, 并从数据报文格式错误和数据要素错误两方面对影响自动站效能的因素进行分析。结果表明:2007年9-10月全国国家级自动站的数据到报率、可用性和可靠性保持在80%以上, 且三者的变化趋势基本一致; 东北区域自动站的运行效能最高, 而西南区域的运行效能最低; 数据到报率是数据可用性和可靠性的前提条件, 在数据到报率一定的情况下, 数据报文格式错误较数据要素质量错误更多地影响数据可用性和可靠性; 第1行格式错误较第2行格式错误对自动站效能的影响程度更大, 相对于其他观测要素, 地温要素是影响自动站效能高低的主要因子; 在地温要素中, 不同层次地温对自动站效能影响也存在一定差异, 320 cm地温影响程度最大, 而5 cm地温影响程度最小, 基本呈现出越往地下深处地温要素对效能影响程度越大的趋势。
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| 关 键 词： | 综合气象观测系统运行监控平台 自动气象站 运行效能 |
| 收稿时间： | 2008-04-22 |
The Statistic of Automatic Weather Station's Efficiency |
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| Li Yan,Liang Haihe,Meng Zhaolin,Pei Chong and Shi Cheng.The Statistic of Automatic Weather Station's Efficiency[J].Quarterly Journal of Applied Meteorology,2009,20(4):504-509. |
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| Authors: | Li Yan Liang Haihe Meng Zhaolin Pei Chong and Shi Cheng |
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| Affiliation: | CMA Meteorological Observation Center, Beijing 100081 |
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| Abstract: | Over 2100 state automatic weather stations (AWS) can be monitored by the Atmospheric Observing System Operations and Monitoring (ASOM) platform of CMA Meteorological Observation Center at present. They are divided into six groups by areas, which are north, northeast, east, south central, southwest, northwest China. The efficiencies of the AWS are statically analyzed in the respect of data arrival rate, equipment availability and reliability. Influencing factors on the data format errors of datagram and the qualities of data element errors are also analyzed. The results indicate that the data arrival rate, equipment availability and the reliability of all the 2100 state AWS maintain over 80%, with a generally consistent trend. The AWS operation efficiencies of the northeast region are the highest and those of the southwest are the lowest. The data arrival rate is the precondition of the equipment availability and reliability. With the data arrival rate fixed, the format error of datagram has more influence on the equipment availability and reliability comparing to the data elements errors. The 1st line data format errors have more influence on AWS operation efficiencies than the 2nd line data format errors. The ground temperature is the main elements affecting AWS operation efficiencies. Among the ground temperature factors, the different levels of ground temperature have different impacts on AWS efficiencies; 320 cm ground temperature has the most significant influence, while the 5 cm ground temperature's influence is relatively lower. It shows a trend that deeper layers of the geothermal elements have greater influences on AWS efficiencies. |
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