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A Data-Adaptive Filter of the Tahiti-Darwin Southern Oscillation Index and the Associate Scheme of Filling Data Gaps


doi: 10.1007/BF02658165

  • The Tahiti-Darwin Southern Oscillation index provided by Climate Analysis Center of USA has been used in numerous studies. But, it has some deficiency. It contains noise mainly due to high month-to-month variability. In order to reduce the level of noise in the SO index, this, paper introduces a fully data-adaptive filter based on singular spectrum analysis. Another interesting aspect of the filter is that it can be used to fill data gaps of the SO index by an iterative process. Eventually, a noiseless long-period data series without any gaps is obtained.
  • [1] Liu Jianwen, Dong Peiming, 2001: Short-range Climate Prediction Experiment of the Southern Oscillation Index Based on the Singular Spectrum Analysis, ADVANCES IN ATMOSPHERIC SCIENCES, 18, 873-881.
    [2] Xiaogu ZHENG, 2009: An Adaptive Estimation of Forecast Error Covariance Parameters for Kalman Filtering Data Assimilation, ADVANCES IN ATMOSPHERIC SCIENCES, 26, 154-160.  doi: 10.1007/s00376-009-0154-5
    [3] Fuqing ZHANG, Meng ZHANG, James A. HANSEN, 2009: Coupling Ensemble Kalman Filter with Four-dimensional Variational Data Assimilation, ADVANCES IN ATMOSPHERIC SCIENCES, 26, 1-8.  doi: 10.1007/s00376-009-0001-8
    [4] LIU Ye, YAN Changxiang, 2010: Application of a Recursive Filter to a Three-Dimensional Variational Ocean Data Assimilation System, ADVANCES IN ATMOSPHERIC SCIENCES, 27, 293-302.  doi: 10.1007/s00376-009-8112-9
    [5] CUI Limei, SUN Jianhua, QI Linlin, LEI Ting, 2011: Application of ATOVS Radiance-Bias Correction to Typhoon Track Prediction with Ensemble Kalman Filter Data Assimilation, ADVANCES IN ATMOSPHERIC SCIENCES, 28, 178-186.  doi: 10.1007/s00376-010-9145-9
    [6] YAO Zhigang, LIN Longfu, CHEN Hongbin, FEI Jianfang, 2008: A Scheme for Estimating Tropical Cyclone Intensity Using AMSU-A Data, ADVANCES IN ATMOSPHERIC SCIENCES, 25, 96-106.  doi: 10.1007/s00376-008-0096-3
    [7] Xu Youfeng, 1986: THE NONLINEAR INTERACTION BETWEEN DIFFERENT WAVE COMPONENTS AND THE PROCESS OF INDEX CYCLE OF GENERAL CIRCULATION, ADVANCES IN ATMOSPHERIC SCIENCES, 3, 478-488.  doi: 10.1007/BF02657937
    [8] Kefeng ZHU, Ming XUE, Yujie PAN, Ming HU, Stanley G. BENJAMIN, Stephen S. WEYGANDT, Haidao LIN, 2019: The Impact of Satellite Radiance Data Assimilation within a Frequently Updated Regional Forecast System Using a GSI-based Ensemble Kalman Filter, ADVANCES IN ATMOSPHERIC SCIENCES, 36, 1308-1326.  doi: 10.1007/s00376-019-9011-3
    [9] Jian YUE, Zhiyong MENG, Cheng-Ku YU, Lin-Wen CHENG, 2017: Impact of Coastal Radar Observability on the Forecast of the Track and Rainfall of Typhoon Morakot (2009) Using WRF-based Ensemble Kalman Filter Data Assimilation, ADVANCES IN ATMOSPHERIC SCIENCES, 34, 66-78.  doi: 10.1007/s00376-016-6028-8
    [10] LI Jianping, Julian X.L.WANG, 2003: A New North Atlantic Oscillation Index and Its Variability, ADVANCES IN ATMOSPHERIC SCIENCES, 20, 661-676.  doi: 10.1007/BF02915394
    [11] LIU Ximing, CHENG Xueling, WU Qiong, FU Minning, ZENG Qingcun, 2013: Some Characteristics of the Surface Boundary Layer of a Strong Cold Air Process over Southern China, ADVANCES IN ATMOSPHERIC SCIENCES, 30, 210-218.  doi: 10.1007/s00376-012-1223-8
    [12] Yongjian HE, Zhi'an SUN, Guoping SHI, Jingmiao LIU, Jiandong LI, 2017: Modification of the SUNFLUX Solar Radiation Scheme with a New Aerosol Parameterization and Its Validation Using Observation Network Data, ADVANCES IN ATMOSPHERIC SCIENCES, 34, 1301-1315.  doi: 10.1007/s00376-016-6262-0
    [13] SHOU Yixuan, LI Shenshen, SHOU Shaowen, ZHAO Zhongming, 2006: Application of a Cloud-Texture Analysis Scheme to the Cloud Cluster Structure Recognition and Rainfall Estimation in a Mesoscale Rainstorm Process, ADVANCES IN ATMOSPHERIC SCIENCES, 23, 767-774.  doi: 10.1007/s00376-006-0767-x
    [14] WU Fanghua, LIN Pengfei, LIU Hailong, 2012: Influence of a Southern Shift of the ITCZ from Quick Scatterometer Data on the Pacific North Equatorial Countercurrent, ADVANCES IN ATMOSPHERIC SCIENCES, 29, 1292-1304.  doi: 10.1007/s00376-012-1149-1
    [15] HOU Tuanjie, Fanyou KONG, CHEN Xunlai, LEI Hengchi, HU Zhaoxia, 2015: Evaluation of Radar and Automatic Weather Station Data Assimilation for a Heavy Rainfall Event in Southern China, ADVANCES IN ATMOSPHERIC SCIENCES, 32, 967-978.  doi: 10.1007/s00376-014-4155-7
    [16] YUE Xu, WANG Huijun, 2008: The Springtime North Asia Cyclone Activity Index and the Southern Annular Mode, ADVANCES IN ATMOSPHERIC SCIENCES, 25, 673-679.  doi: 10.1007/s00376-008-0673-5
    [17] Qin XU, Jie CAO, 2021: Iterative Methods for Solving the Nonlinear Balance Equation with Optimal Truncation, ADVANCES IN ATMOSPHERIC SCIENCES, 38, 755-770.  doi: 10.1007/s00376-020-0291-4
    [18] Yujie PAN, Mingjun WANG, 2019: Impact of the Assimilation Frequency of Radar Data with the ARPS 3DVar and Cloud Analysis System on Forecasts of a Squall Line in Southern China, ADVANCES IN ATMOSPHERIC SCIENCES, 36, 160-172.  doi: 10.1007/s00376-018-8087-5
    [19] Pavla PEKAROVA, Jan PEKAR, 2007: Teleconnections of Inter-Annual Streamflow Fluctuation in Slovakia with Arctic Oscillation, North Atlantic Oscillation, Southern Oscillation, and Quasi-Biennial Oscillation Phenomena, ADVANCES IN ATMOSPHERIC SCIENCES, 24, 655-663.  doi: 10.1007/s00376-007-0655-z
    [20] K.D. Prasad, S.V. Singh, 1988: MONSOON RAINFALL AND SOUTHERN OSCILLATION RESPONSES IN THE PRESSURES OVER THE NORTHERN INDIAN OCEAN, ADVANCES IN ATMOSPHERIC SCIENCES, 5, 243-251.  doi: 10.1007/BF02656785

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Manuscript History

Manuscript received: 10 October 1994
Manuscript revised: 10 October 1994
通讯作者: 陈斌, bchen63@163.com
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A Data-Adaptive Filter of the Tahiti-Darwin Southern Oscillation Index and the Associate Scheme of Filling Data Gaps

  • 1. Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100080

Abstract: The Tahiti-Darwin Southern Oscillation index provided by Climate Analysis Center of USA has been used in numerous studies. But, it has some deficiency. It contains noise mainly due to high month-to-month variability. In order to reduce the level of noise in the SO index, this, paper introduces a fully data-adaptive filter based on singular spectrum analysis. Another interesting aspect of the filter is that it can be used to fill data gaps of the SO index by an iterative process. Eventually, a noiseless long-period data series without any gaps is obtained.

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