Volume 38 Issue 2
Mar.  2018
Turn off MathJax
Article Contents
Article Navigation >  Chinese Journal of Space Science  > 2018  >  38(2): 211-220
LIU Tao, XIAO Cunying, HU Xiong, TU Cui, YANG Junfeng, XU Qingchen. Application of Time Series Method in Forecasting Near-space Atmospheric Windormalsize[J]. Chinese Journal of Space Science, 2018, 38(2): 211-220. doi: 10.11728/cjss2018.02.211
Citation: LIU Tao, XIAO Cunying, HU Xiong, TU Cui, YANG Junfeng, XU Qingchen. Application of Time Series Method in Forecasting Near-space Atmospheric Windormalsize[J]. Chinese Journal of Space Science, 2018, 38(2): 211-220. doi: 10.11728/cjss2018.02.211
shu

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

doi: 10.11728/cjss2018.02.211

  • 1. National Space Science Center, Chinese Academy of Sciences, Beijing 100190;

  • 2. University of Chinese Academy of Sciences, Beijing 100049

  • Received Date: 2017-02-20
  • Rev Recd Date: 2017-08-13
  • Publish Date: 2018-03-15
    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.

     

    • FullText(HTML)
  • loading
    • References(22)
  • [1]
    ERZGRÄBER H, STROZZI F, ZALDÍVAR J M, et al. Time series analysis and long range correlations of Nordic spot electricity market data[J]. Phys. A:Statist. Mech. Appl., 2008, 387(26):6567-6574
    [2]
    GHIRMAY T. Financial development and economic growth in Sub-Saharan African countries:evidence from time series analysis[J]. Afr. Dev. Rev., 2004, 16(3):415-432
    [3]
    LEE J H, SOHN K T. Prediction of monthly mean surface air temperature in a region of China[J]. Adv. Atmos. Sci., 2007, 24(3):503-508
    [4]
    RUHF R J, CUTRIM E M C. Time series analysis of 20 years of hourly precipitation in southwest Michigan[J]. J. Great Lakes Res., 2003, 29(2):256-267
    [5]
    TIAN Y X, LIU Q Y, HU Z Y, et al. Wind speed forecasting based on Time series-Adaptive Kalman filtering algorithm[C]//Proceedings of 2014 IEEE Far East Forum on Nondestructive Evaluation/Testing. Chengdu, China:IEEE, 2014:315-319
    [6]
    FAN Y T, CHEN Y N, LI W H, et al. Impacts of temperature and precipitation on runoff in the Tarim River during the past 50 years[J]. J. Arid Land, 2011, 3(3):220-230
    [7]
    SALCEDO R L R, ALVIM FERRAZ M C M, ALVES C A, et al. Time-series analysis of air pollution data[J]. Atmos. Environ., 1999, 33(15):2361-2372
    [8]
    LIU Siqing, ZHONG Qiuzhen, WEN Jing, et al. Modeling research of 10.7cm solar radio flux 27-day forecast (I)[J]. Chin. J. Space Sci., 2010, 30(1):1-8(刘四清, 钟秋珍, 温靖, 等. 太阳10.7cm射电流量中期预报模型研究(I)[J]. 空间科学学报, 2010, 30(1):1-8)
    [9]
    WEN Jing, ZHONG Qiuzhen, LIU Siqing. Model research of 10.7cm solar radio flux 27-day forecast (Ⅱ)[J]. Chin. J. Space Sci., 2010, 30(3):198-204(温靖, 钟秋珍, 刘四清. 太阳10.7cm射电流量中期预报模型研究(Ⅱ)[J]. 空间科学学报, 2010, 30(3):198-204)
    [10]
    WANG Hongbo, XIONG Jianning, ZHAO Changyin. The medium-term forecast method of solar radiation index F_10.7[J]. Acta Astronom. Sin., 2014, 55(4):302-312(汪宏波, 熊建宁, 赵长印. 太阳辐射指数F_10.7的中期预报方法[J]. 天文学报, 2014, 55(4):302-312)
    [11]
    LIU Shiqing, LUO Bingxian, ZHONG Qiuzhen, et al. Medium and short term forecasting of Ap index related to coronal holes[J]. Chin. J. Space Sci., 2009, 29(6):545-551(刘四清, 罗冰显, 钟秋珍, 等. 冕洞相关地磁Ap指数中短期预报方法研究[J]. 空间科学学报, 2009, 29(6):545-551)
    [12]
    ALLEN D R, COY L, ECKERMANN S D, et al. NOGAPS-ALPHA simulations of the 2002 Southern Hemisphere stratospheric major warming[J]. Mon. Wea. Rev., 2006, 134:498-518
    [13]
    RONEY J A. Statistical wind analysis for near-space applications[J]. J. Atmos. Sol.-Terr. Phys., 2007, 69(13):1485-1501
    [14]
    HU Xiong, GONG Jianchun, YANG Junfeng, et al. A study of near-space atmospheric prediction methods[C]//The 3rd China High Resolution Earth Observation Conference. Beijing, 2014(胡雄, 龚建村, 杨钧烽, 等. 临近空间大气预报方法研究[C]//第三届高分辨率对地观测学术年会优秀论文集. 北京, 2014)
    [15]
    MA Guanglin. Study of MF Rader Signal Sampling-Processing System and Wind Retrievals[D]. Beijing:Graduate University of Chinese Academy of Sciences(Center for Space Science and Applied Research), 2010(马广林. 中频雷达数据采集处理与风场反演的研究[D]. 北京:中国科学院研究生院(空间科学与应用研究中心), 2010)
    [16]
    XIAO C Y, HU X, ZHANG X X, et al. Interpretation of the mesospheric and lower thermospheric mean winds observed by MF radar at about 30°N with the 2D-SOCRATES model[J]. Adv. Space Res., 2007, 39(8):1267-1277
    [17]
    XIAO C Y, HU X, SMITH A K, et al. Short-term variability and summer-2009 averages of the mean wind and tides in the mesosphere and lower thermosphere over Langfang, China (39.4°N, 116.7°E)[J]. J. Atmos. Sol.-Terr. Phys., 2013, 92:65-77
    [18]
    CHEN Xuxing, HU Xiong, XIAO Cunying. The responses of wind and perturbation to stratospheric sudden warming events in the mesosphere and lower thermosphere[C]//Chinese Geophysics. Beijing, 2012(陈旭杏, 胡雄, 肖存英. 中纬度MLT风场和波动对平流层爆发性增温的响应[C]//中国地球物理. 北京, 2012)
    [19]
    YANG J F, XIAO C Y, HU X, et al. Responses of zonal wind at~40°N to stratospheric sudden warming events in the stratosphere, mesosphere and lower thermosphere[J]. Sci. China Technol. Sci., 2017, 60(6):935-945
    [20]
    YANG Junfeng. Researches on the Variations of Atmospheric Winds in Near Space at Mid-Latitude[D]. Beijing:National Space Science Center, the Chinese Academy of Sciences, 2016(杨钧烽. 中纬度临近空间大气风场变化特性研究[D]. 北京:中国科学院国家空间科学中心, 2016)
    [21]
    AN Xiaoxiao. The Model about ARMA and its Application[D]. Qinhuangdao:Yanshan University, 2008(安潇潇. ARMA相关模型及其应用[D]. 秦皇岛:燕山大学, 2008)
    [22]
    GEORGE E P B, GWILYM M J, GREGORY C R, et al. Time Series Analysis:Forecasting and Control[M]. 4th Edition. Beijing:China Machine Press, 2011
    • Relative Articles
    • Supplements(0)
    • Cited By
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索
    Get Citation
    PDF
    XML

    Article Metrics

    Article Views(1311) PDF Downloads(820) Cited by()
    Proportional views
    Related

    Journal Introduction

    ISSN 0254-6124       CN 11-1783/V

    Copyright © Editorial Office of Chinese Journal of Space Science.  京ICP备08100722号

    Supported by: Beijing Renhe Information Technology Co., Ltd.  

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return