双月刊

ISSN 1006-9895

CN 11-1768/O4

中国地基GNSS/MET水汽产品质量控制及与再分析产品的对比评估
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国家气象信息中心

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国家气象信息中心结余资金项目, 国家重点基础研究发展计划


Ground-based GNSS/MET Water Vapor Data: Quality control Method of and Comparative Analysis with Reanalysis Datasets
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National Meteorological Information Centre

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    摘要:

    本文研究并提出中国地基全球导航卫星系统(GNSS)水汽产品的综合质量控制(CQC)算法。CQC算法由质量检查和综合决策两个环节组成。质量检查环节主要对待检观测数据与其参考数据的差异进行分析,包括界限值检查、考察时间一致性的临近点检查和低通滤波检查,考察空间一致性的邻近站检查、距平值检查和峰谷值检查,以及基于背景场的粗大误差检查等7个模块。每个检查标记出超过阈值的观测数据,随后利用综合决策算法对数据的标记情况进行综合评分,最终给出数据的质量控制码。基于质量控制后的数据,评估了中国第一代全球大气再分析产品(CRA)、ERA-Interim和ERA5等五套再分析数据在中国地区的水汽模拟效果。结果表明几套再分析资料模拟的大气可降水量(PWV)在冬季整体略高于观测,夏季则明显低于观测。在空间上,中国南方地区和西部地区模拟的PWV低于观测,这种情况在夏半年更加明显。相对于观测,CRA的平均偏差(O-B)为0.633mm,均方根误差为3.650mm。CRA相对于观测的误差略高于ERA5,但略低于ERA-Interim,明显优于JRA55和NCEP2结果。

    Abstract:

    This paper proposes a comprehensive quality control (CQC) algorithm for the Chinese ground-based navigation satellite system (GNSS) water vapor products. The CQC algorithm consists of two sections: quality checks and comprehensive decision-making algorithm. The quality checks consist of 7 parts: limit check to eliminate errors that exceed reasonable limits, buddy check and low-pass filter check for better time consistency, neighboring station check, anomaly check and peak-valley value check for better spatial consistency, and background check to mark out data deviate from background field for assimilation application. After each check, the data that exceeds the threshold is marked, and then the comprehensive decision-making algorithm is used to score the marked data, and finally flag (correct, suspicious, or error) the data. Based on the quality-controlled observation data, the precipitable water vapor simulation of five sets of reanalysis data, including China"s first-generation global atmosphere reanalysis (CRA) product, were evaluated. The results show that the simulated total water vapor of all the reanalysis data in winter is slightly higher than the observation in winter and significantly lower than the observation in summer. Spatially, the simulated water vapor content in southern and western China is lower than the observation and this situation is more obvious in the summer half of the year. Relative to the observation, the average bias (B-O) of CRA is -0.633mm, and the root mean square error is 3.650mm. The deviation of CRA relative to observation is slightly lower than ERA-Interim but slightly higher than ERA5, which is significantly better than JRA55 and NCEP2 results.

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  • 收稿日期:2021-08-01
  • 最后修改日期:2021-10-12
  • 录用日期:2021-12-21
  • 在线发布日期: 2022-01-05
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