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沈王彬, 李昕, 秦正坤, 等. 2022. 基于EOF迭代的自动气象站气温观测资料修复方法[J]. 大气科学, 46(2): 406−418. doi: 10.3878/j.issn.1006-9895.2103.21021
引用本文: 沈王彬, 李昕, 秦正坤, 等. 2022. 基于EOF迭代的自动气象站气温观测资料修复方法[J]. 大气科学, 46(2): 406−418. doi: 10.3878/j.issn.1006-9895.2103.21021
SHEN Wangbin, LI Xin, QIN Zhengkun, et al. 2022. Restoration Method for Automatic Station Temperature Observation Data Based on EOF Iteration [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 46(2): 406−418. doi: 10.3878/j.issn.1006-9895.2103.21021
Citation: SHEN Wangbin, LI Xin, QIN Zhengkun, et al. 2022. Restoration Method for Automatic Station Temperature Observation Data Based on EOF Iteration [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 46(2): 406−418. doi: 10.3878/j.issn.1006-9895.2103.21021

基于EOF迭代的自动气象站气温观测资料修复方法

Restoration Method for Automatic Station Temperature Observation Data Based on EOF Iteration

  • 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00:00至7日23:00(北京时),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°C。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°C。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, a comprehensively automatic meteorological observation has been realized. However, the real application of this kind of observation always suffers from their low quality. A large number of error data seriously affects the practical application of observation. Therefore, it is a particularly important task to repair these abnormal observations. Using a total of 168 times of hourly surface temperature observations of automatic weather station during December 1–7, 2019, which is provided by the Jiangsu meteorological bureau, a restoration method based on the empirical orthogonal function method is proposed. The accuracy analysis of ideal restoration experiments shows that the new restoration method can well repair wrong observations with an error of about 0.48 degrees centigrade. The methods based on the Cressman interpolation, which rely on a single point observation information, are more vulnerable to small-scale signal interferences and introduce unnatural observation information, with the surface temperature repair error reaching up to 1.55 degrees centigrade. 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 the EOF analysis method and gradually eliminates the influence of wrong data through an iterative method to obtain better space-time continuity repair results with the surrounding observation data.

     

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