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自动站小时气温数据的质量控制系统研究
引用本文:张志富,任芝花,张强,邹凤玲,杨燕茹.自动站小时气温数据的质量控制系统研究[J].气象与环境学报,2013,29(4):64-70.
作者姓名:张志富  任芝花  张强  邹凤玲  杨燕茹
作者单位:国家气象信息中心,北京 100081
基金项目:国家重点基础研究发展计划项目(973计划),公益性行业(气象)科研专项,国家气象局气象关键技术集成与应用项目,国家气象局气象新技术推广项目,中国气象局基建项目"全国自动站实时资料质量控制与综合评估系统建设"共同资助
摘    要:逐小时自动站数据对于气象灾害预警、决策服务及预报预测等十分重要。以国家级自动站小时观测气温数据为基础,分析研究了小时气温数据的疑误形式,针对各种疑误数据,利用国家级台站建站以来的日最高、日最低以及4时次(北京时02点、08点、14点、20点)定时观测气温数据,研制形成了适用于中国自动站(区域站和国家站)逐小时气温数据质量控制系统,并将此系统应用到2006-2010年中国27000多自动站小时气温观测数据中。结果表明:区域站的正确率、可疑率、错误率分别为99.43 %、2.24 ‰和3.45 ‰,国家站则分别为99.82 %、1.27 ‰和0.49 ‰;区域站和国家站数据的可疑率相当,但国家站错误率明显比区域站低一个量级。通过历史数据质量控制结果的分析,证明自动站气温质量控制系统设计合理,可以判断出错误和可疑数据,具有可用性。

关 键 词:小时气温数据  质量控制  区域自动站  国家级自动站  

Analysis of quality control procedures for hourly air temperature data from automatic weather stations in China
ZHANG Zhi-fu , REN Zhi-hua , ZHANG Qiang , ZOU Feng-ling , YANG Yan-ru.Analysis of quality control procedures for hourly air temperature data from automatic weather stations in China[J].Journal of Meteorology and Environment,2013,29(4):64-70.
Authors:ZHANG Zhi-fu  REN Zhi-hua  ZHANG Qiang  ZOU Feng-ling  YANG Yan-ru
Affiliation:National Meteorological Information Center, Beijing 100081, China
Abstract:The hourly meteorological data from the automatic weather stations(AWS) is very vital to meteorologi- cal disaster warning, decision-making service and forecast and so on. Based on the hourly temperature data from the national AWS,the questionable and wrong hourly air temperature data were analyzed. According to the daily maximum/minimum air temperature in four limes ( 02 : 00,08 : 00,14: 00,20 : 00 Beijing time ) from the national AWS ,a quality control procedure of hourly air temperature data was developed for the temperature of AWS in Chi- na. The quality control procedure could be used for the regional and national AWS. It had been evaluated by the hourly air temperature data about 27000 weather stations from 2006 to 2010 in China. The results show that the ac- curate rates, questionable rates and wrong rates of hourly air temperature in the regional AWS are 99. 43‰, 2. 24‰ and 3.45‰, and the corresponding rates in the national AWS are 99.82‰, 1.27‰ and 0. 49‰, respective- ly. Both questionable rates are similar, while there is a magnitude difference for both wrong rates. According to the analysis of quality control of long time series air temperature data, it suggests that the design of the procedure is reasonable, and it could check the questionable data and wrong data. Thus, it could be used in the meteorological operation.
Keywords:Hourly air temperature data  Quality control  Regional automatic weather station  National automatic weather station
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