双月刊

ISSN 1006-9895

CN 11-1768/O4

基于EOF的自动气象站气温观测资料修复方法
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作者单位:

1.南京信息工程大学大气科学学院;2.南京气象科技创新研究院/江苏省气象科学研究所;3.南京信息工程大学 大气科学学院 资料同化研究与应用联合中心

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基金项目:

国家自然科学基金


Restoration method for automatic station temperature observation data based on EOF
Author:
Affiliation:

Joint Center of data assimilation research and applications, school of atmospheric science,Nanjing University of Information Science & technology

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    摘要:

    全国目前已经建成了近7万个自动气象观测站点,然而自动气象站观测资料一直存在资料质量较低的问题,大量错误资料的存在极大影响了其在气象研究中的应用,因此对错误观测的数据进行准确的修复是一项重要工作。本文利用2019年12月1日00时至7日23时,共168个时次的地面自动站温度观测资料,在利用EOF(Empirical Orthogonal Function)质量控制方法识别异常观测资料的基础上,提出了一种基于迭代EOF分析方法的错误资料修复方法。通过理想修复试验的精度分析表明,新修复方法能够很好地修复错误的地面自动站观测气温,修复方法的误差约为0.48℃。而基于Cressman插值等这一类依赖单点观测信息进行修复的方法更容易受到小尺度信号干扰而引入非自然观测信息,对地面温度的修复误差可以达到1.55℃。实际的修复结果分析也证明新修复方法充分利用了EOF分析方法的时空分离作用和模态正交性特点,通过迭代方法逐步消除错误资料的影响,从而获得了与周边观测资料有更好时空连续性的修复结果。

    Abstract:

    With the construction of about 70,000 automatic weather stations across China, comprehensively automatic meteorological observation has been realized. However, the real application of this kind of observations always surfers from their low quality. Large number of error data seriously affect the practical application of observation. Therefore, it is a particularly important work to repair those abnormal observations. Using a total of 168 times of hourly surface temperature observations of automatic weather station during December 1-7, 2019 provided by Jiangsu meteorological bureau, a restoration method based on the Empirical Orthogonal Function method is proposed. The accuracy analysis of the ideal restoration experiments shows that the new restoration method can well repair the wrong observations, and the error of the restoration method is about 0.48 ℃. The methods based on Cressman interpolation, which rely on single point observation information, are more vulnerable to small-scale signal interference and introduce unnatural observation information, and the surface temperature repair error can reach 1.55 ℃. The analysis of the actual repair results also proves that the new repair method makes full use of the time-space separation and modal orthogonality of EOF analysis method, and gradually eliminates the influence of wrong data through iterative method, so as to obtain better space-time continuity repair results with the surrounding observation data.

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历史
  • 收稿日期:2021-01-31
  • 最后修改日期:2021-03-24
  • 录用日期:2021-05-24
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