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    請使用永久網址來引用或連結此文件: https://ir.lib.ncu.edu.tw/handle/987654321/100147


    題名: Improving the model convective storm quantitative precipitation nowcasting by assimilating state variables retrieved from multiple-Doppler radar observations
    作者: 廖宇慶;Liou, Yu-Chieng;Chiou, Jian-Luen;Chen, Wei-Hao;Yu, Hsin-Yu
    貢獻者: 地球科學學院大氣科學學系
    關鍵詞: Algorithms;Boundary conditions;Data assimilation;Data collection;Doppler effect;Doppler radar;Doppler radar observation;Doppler sonar;Information retrieval;Kalman filters;Mathematical models;Methods;Modelling;Moisture;Moisture effects;Nowcasting;Numerical models;Precipitation;Procedures;Radar;Radar data;Radiosondes;Rain;Rainfall;Rainfall forecasting;Retrieval;State variable;Storms;Studies;Thermodynamics;Velocity;Weather;Wind;Wind measurement
    日期: 2014-01-01
    上傳時間: 2026-04-21 13:51:11 (UTC+8)
    出版者: American Meteorological Society;Washington: American Meteorological Society
    摘要: 摘要: AbstractThis research combines an advanced multiple-Doppler radar synthesis technique with the thermodynamic retrieval method, originally proposed by Gal-Chen, and a moisture/temperature adjustment scheme, and formulates a sequential procedure. The focus is on applying this procedure to improve the model quantitative precipitation nowcasting (QPN) skill in the convective scale up to 3 hours. A series of (observing system simulation experiment) OSSE-type tests and a real case study are conducted to investigate the performance of this algorithm under different conditions.It is shown that by using the retrieved three-dimensional wind, thermodynamic, and microphysical parameters to reinitialize a fine-resolution numerical model, its QPN skill can be significantly improved. Since the Gal-Chen method requires the horizontal average properties of the weather system at each altitude, utilization of in situ radiosonde(s) to obtain this additional information for the retrieval is tested. When sounding data are not available, it is demonstrated that using the model results to replace the role played by observing devices is also a feasible choice. The moisture field is obtained through a simple, but effective, adjusting scheme and is found to be beneficial to the rainfall forecast within the first hour after the reinitialization of the model.Since this algorithm retrieves the unobserved state variables instantaneously from the wind measurements and directly uses them to reinitialize the model, fewer radar data and a shorter model spinup time are needed to correct the rainfall forecasts, in comparison with other data assimilation techniques such as four-dimensional variational data assimilation (4DVAR) or ensemble Kalman filter (EnKF) methods.
    出版者: Washington: American Meteorological Society
    出版日期: 2014-11-01
    出處: Monthly Weather Review, 2014-11, Vol.142 (11), p.4017-4035
    資源來源: EBSCOhost OmniFile Full Text Select
    版權: Copyright American Meteorological Society Nov 2014
    版權: Copyright American Meteorological Society 2014
    識別號: ISSN: 0027-0644
    識別號: EISSN: 1520-0493
    識別號: DOI: 10.1175/mwr-d-13-00315.1
    識別號: CODEN: MWREAB
    顯示於類別:[大氣科學學系] 期刊論文

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