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Chinese Journal of Space Science ›› 2018, Vol. 38 ›› Issue (2): 211-220.doi: 10.11728/cjss2018.02.211

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Application of Time Series Method in Forecasting Near-space Atmospheric Windormalsize

LIU Tao1,2, XIAO Cunying1, HU Xiong1, TU Cui1, YANG Junfeng1, XU Qingchen1   

  1. 1. National Space Science Center, Chinese Academy of Sciences, Beijing 100190;
    2. University of Chinese Academy of Sciences, Beijing 100049
  • Received:2017-02-20 Revised:2017-08-13 Online:2018-03-15 Published:2018-03-09

Abstract:

Due to many factors, near-space environment is complex and variable. Atmospheric environmental elements are hard to be forecasted. In this paper time series method is applied to the near-space wind forecasting. Autoregressive Moving Average (ARMA) model is adopted. The zonal wind data at 88km altitude of Langfang (39.4°N, 116.7°W) MF radar form September 24 to October 24, 2015 is used for the forecasting test. In this test the data of past 7 days was used to forecast the data of the 8th day. Results suggest that ARMA model has certain applicability in forecasting the near-space atmospheric wind. The forecast effect is better when the winds have stronger regularity of change, i.e., when the sample data show a significant 24-hour cycle, the forecast effect is better, and is worse when the winds have a mutation. Compared with the observed data, results show that the forecast error of ARMA model is 9~27m·s-1, and the forecast result of ARMA model is better than that of AR model with the same order, and is slightly better than that of higher-order AR model.

Key words: Near space, Atmospheric wind, Time series method, ARMA model, Forecast

CLC Number: