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Retrieval Single-Doppler Radar Wind with Variational Assimilation Method-Part I: Objective Selection of Functional Weighting Factors


doi: 10.1007/s00376-998-0032-6

  • In variational problem, the selection of functional weighting factors (FWF) is one of the key points for discussing many relevant studies. To overcome arbitrariness and subjectivity of the empirical selecting methods used widely at present, this paper tries to put forward in optimal objective selecting method of FWF. The focus of the study is on the weighting factors optimal selection in the variation retrieval single-Doppler radar wind field with the simple adjoint models. Weighting factors in the meaning of minimal variance are calculated out with the matrix theory and the finite difference method of partial differential equation. Experiments show that the result is more objective comparing with the factors obtained with the empirical method.
  • [1] WANG Yuesi, HU Yuqiong, JI Baoming, LIU Guangren, XUE Min, 2003: An Investigation on the Relationship Between Emission/Uptake of Greenhouse Gases and Environmental Factors in Semiarid Grassland, ADVANCES IN ATMOSPHERIC SCIENCES, 20, 119-127.  doi: 10.1007/BF03342056
    [2] S.K. Sinha, D.R. Talwalkar, S.G. Narkhedkar, S. Rajamani, 1989: A Scheme for Objective Analysis of Wind Field Incorporating Multi-Weighting Functions in the Optimum Interpolation Method, ADVANCES IN ATMOSPHERIC SCIENCES, 6, 435-446.  doi: 10.1007/BF03342547
    [3] Hongke CAI, Yaqin MAO, Xuanhao ZHU, Yunfei FU, Renjun ZHOU, 2024: Comparison of the Minimum Bounding Rectangle and Minimum Circumscribed Ellipse of Rain Cells from TRMM, ADVANCES IN ATMOSPHERIC SCIENCES, 41, 391-406.  doi: 10.1007/s00376-023-2281-9
    [4] Michael B. RICHMAN, Lance M. LESLIE, Theodore B. TRAFALIS, Hicham MANSOURI, 2015: Data Selection Using Support Vector Regression, ADVANCES IN ATMOSPHERIC SCIENCES, 32, 277-286.  doi: 10.1007/s00376-014-4072-9
    [5] Wang Mingxing, 1985: SOURCE IDENTIFICATION AND APPORTIONMENT FOR ATMOSPHERIC AEROSOL BY FACTOR ANALYSIS, ADVANCES IN ATMOSPHERIC SCIENCES, 2, 469-477.  doi: 10.1007/BF02678745
    [6] Sayed M. Elshazly, 1996: A Study of Linke Turbidity Factor over Qena / Egypt, ADVANCES IN ATMOSPHERIC SCIENCES, 13, 519-532.  doi: 10.1007/BF03342042
    [7] Wen ZHOU, Richard C. Y. LI, Eric C. H. CHOW, 2017: Intraseasonal Variation of Visibility in Hong Kong, ADVANCES IN ATMOSPHERIC SCIENCES, 34, 26-38.  doi: 10.1007/s00376-016-6056-4
    [8] Fu Baopu, 1987: VARIATION IN WIND VELOCITY OVER WATER, ADVANCES IN ATMOSPHERIC SCIENCES, 4, 93-104.  doi: 10.1007/BF02656665
    [9] HUA Wei, Samuel S. P. SHEN, WANG Huijun, 2014: Analysis of Sampling Error Uncertainties and Trends in Maximum and Minimum Temperatures in China, ADVANCES IN ATMOSPHERIC SCIENCES, 31, 263-272.  doi: 10.1007/s00376-013-2316-8
    [10] Qian Yongfu, Zhang Qiong, Yao Yonghong, Zhang Xuehong, 2002: Seasonal Variation and Heat Preference of the South Asia High, ADVANCES IN ATMOSPHERIC SCIENCES, 19, 821-836.  doi: 10.1007/s00376-002-0047-3
    [11] Li Chongyin, Li Guilong, 2000: The NPO/ NAO and Interdecadal Climate Variation in China, ADVANCES IN ATMOSPHERIC SCIENCES, 17, 555-561.  doi: 10.1007/s00376-000-0018-5
    [12] Liu Liping, Feng Jinming, Chu Rongzhong, Zhou Yunjun, K. Ueno, 2002: The Diurnal Variation of Precipitation in Monsoon Season in the Tibetan Plateau, ADVANCES IN ATMOSPHERIC SCIENCES, 19, 365-378.  doi: 10.1007/s00376-002-0028-6
    [13] LI Chongyin, HE Jinhai, ZHU Jinhong, 2004: A Review of Decadal/Interdecadal Climate Variation Studies in China, ADVANCES IN ATMOSPHERIC SCIENCES, 21, 425-436.  doi: 10.1007/BF02915569
    [14] Xu Guochang, Li Meifang, Zhang Zhiyin, 1985: SEASONAL VARIATION OF RAIN-BELTS OVER CHINA, ADVANCES IN ATMOSPHERIC SCIENCES, 2, 368-375.  doi: 10.1007/BF02677253
    [15] J.M. Pathan, 1994: Diurnal Variation of Southwest Monsoon Rainfall at Indian Stations, ADVANCES IN ATMOSPHERIC SCIENCES, 11, 111-120.  doi: 10.1007/BF02657000
    [16] Wang Huijun, 1994: Modelling the Interannual Variation of Regional Precipitation over China, ADVANCES IN ATMOSPHERIC SCIENCES, 11, 230-238.  doi: 10.1007/BF02666549
    [17] S.K. Sinha, S. Rajamani, 1995: Multivariate Objective Analysis of Wind and Height Fields in the Tropics, ADVANCES IN ATMOSPHERIC SCIENCES, 12, 233-244.  doi: 10.1007/BF02656836
    [18] Mengru FENG, Yujing QIN, Chuhan LU, 2021: An Objective Identification Method for Wintertime Cold Fronts in Eurasia, ADVANCES IN ATMOSPHERIC SCIENCES, 38, 1695-1705.  doi: 10.1007/s00376-021-0315-8
    [19] Chunsheng ZHAO, Yingli YU, Ye KUANG, Jiangchuan TAO, Gang ZHAO, 2019: Recent Progress of Aerosol Light-scattering Enhancement Factor Studies in China, ADVANCES IN ATMOSPHERIC SCIENCES, 36, 1015-1026.  doi: 10.1007/s00376-019-8248-1
    [20] Dangfu YANG, Shengjun LIU, Yamin HU, Xinru LIU, Jiehong XIE, Liang ZHAO, 2023: Predictor Selection for CNN-based Statistical Downscaling of Monthly Precipitation, ADVANCES IN ATMOSPHERIC SCIENCES, 40, 1117-1131.  doi: 10.1007/s00376-022-2119-x

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Manuscript History

Manuscript received: 10 October 1998
Manuscript revised: 10 October 1998
通讯作者: 陈斌, bchen63@163.com
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Retrieval Single-Doppler Radar Wind with Variational Assimilation Method-Part I: Objective Selection of Functional Weighting Factors

  • 1. Department of Atmospheric Sciences, Nanjing University, Nanjing 210093,Department of Atmospheric Sciences, Nanjing University, Nanjing 210093,Department of Atmospheric Sciences, Nanjing University, Nanjing 210093,Institute for Hydrospheric-Atmospheric Sciences, Nagoya University, Japan

Abstract: In variational problem, the selection of functional weighting factors (FWF) is one of the key points for discussing many relevant studies. To overcome arbitrariness and subjectivity of the empirical selecting methods used widely at present, this paper tries to put forward in optimal objective selecting method of FWF. The focus of the study is on the weighting factors optimal selection in the variation retrieval single-Doppler radar wind field with the simple adjoint models. Weighting factors in the meaning of minimal variance are calculated out with the matrix theory and the finite difference method of partial differential equation. Experiments show that the result is more objective comparing with the factors obtained with the empirical method.

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