›› 2014, Vol. 23 ›› Issue (9): 99401-099401.doi: 10.1088/1674-1056/23/9/099401

• GEOPHYSICS, ASTRONOMY, AND ASTROPHYSICS • 上一篇    下一篇

New reconstruction and forecasting algorithm for TEC data

王俊a, 盛峥b c, 江宇b, 石汉青b   

  1. a National Key Laboratory on Electromagnetic Environmental Effects and Electro-optical Engineering, PLA University of Science and Technology, Nanjing 210007, China;
    b College of Meteorology and Oceangraphy, PLA University of Science and Technology, Nanjing 211101, China;
    c Jiangsu Key Laboratory of Meteorological Observation and Information Processing, Nanjing University of Information Science and Technology, Nanjing 210044, China
  • 收稿日期:2013-12-06 修回日期:2014-04-02 出版日期:2014-09-15 发布日期:2014-09-15
  • 基金资助:
    Project supported by the National Natural Science Foundation of China (Grant No. 41105013, 41375028, and 61271106), the National Natural Science Foundation of Jiangsu Province, China (Grant No. BK2011122), and the Key Laboratory of Meteorological Observation and Information Processing Scientific Research Fund of Jiangsu Province, China (Grant No. KDXS1205).

New reconstruction and forecasting algorithm for TEC data

Wang Jun (王俊)a, Sheng Zheng (盛峥)b c, Jiang Yu (江宇)b, Shi Han-Qing (石汉青)b   

  1. a National Key Laboratory on Electromagnetic Environmental Effects and Electro-optical Engineering, PLA University of Science and Technology, Nanjing 210007, China;
    b College of Meteorology and Oceangraphy, PLA University of Science and Technology, Nanjing 211101, China;
    c Jiangsu Key Laboratory of Meteorological Observation and Information Processing, Nanjing University of Information Science and Technology, Nanjing 210044, China
  • Received:2013-12-06 Revised:2014-04-02 Online:2014-09-15 Published:2014-09-15
  • Contact: Sheng Zheng E-mail:19994035@sina.com
  • Supported by:
    Project supported by the National Natural Science Foundation of China (Grant No. 41105013, 41375028, and 61271106), the National Natural Science Foundation of Jiangsu Province, China (Grant No. BK2011122), and the Key Laboratory of Meteorological Observation and Information Processing Scientific Research Fund of Jiangsu Province, China (Grant No. KDXS1205).

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摘要： To reconstruct the missing data of the total electron content (TEC) observations, a new method is proposed, which is based on the empirical orthogonal functions (EOF) decomposition and the value of eigenvalue itself. It is a self-adaptive EOF decomposition without any prior information needed, and the error of reconstructed data can be estimated. The interval quartering algorithm and cross-validation algorithm are used to compute the optimal number of EOFs for reconstruction. The interval quartering algorithm can reduce the computation time. The application of the data interpolating empirical orthogonal functions (DINEOF) method to the real data have demonstrated that the method can reconstruct the TEC map with high accuracy, which can be employed on the real-time system in the future work.

关键词: reconstruction, total electron content (TEC) data, empirical orthogonal function (EOF) decomposition, interval quartering algorithm

Abstract: To reconstruct the missing data of the total electron content (TEC) observations, a new method is proposed, which is based on the empirical orthogonal functions (EOF) decomposition and the value of eigenvalue itself. It is a self-adaptive EOF decomposition without any prior information needed, and the error of reconstructed data can be estimated. The interval quartering algorithm and cross-validation algorithm are used to compute the optimal number of EOFs for reconstruction. The interval quartering algorithm can reduce the computation time. The application of the data interpolating empirical orthogonal functions (DINEOF) method to the real data have demonstrated that the method can reconstruct the TEC map with high accuracy, which can be employed on the real-time system in the future work.

Key words: reconstruction, total electron content (TEC) data, empirical orthogonal function (EOF) decomposition, interval quartering algorithm

中图分类号:  (Ionospheric modeling and forecasting)

  • 94.20.Cf
02.60.Ed (Interpolation; curve fitting)