| SVD-En3DVar方法同化多普勒雷达速度观测资料 I. 模拟资料试验 |
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| 引用本文： | 徐道生,邵爱梅,邱崇践.SVD-En3DVar方法同化多普勒雷达速度观测资料 I. 模拟资料试验[J].大气科学,2011,35(4):753-766. |
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| 作者姓名： | 徐道生 邵爱梅 邱崇践 |
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| 作者单位： | 半干旱气候变化教育部重点实验室, 兰州大学大气科学学院, 兰州 730000 |
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| 基金项目： | 国家自然科学基金资助项目40875063， 兰州大学中央高校基本科研业务费专项资金资助项目lzujbky－2010－9 |
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| 摘 要： | 利用WRF模式及模式模拟的资料,开展了利用SVD-En3DVar(基于集合和SVD技术的三维变分同化方法)方法同化雷达径向速度资料的试验.由于雷达观测经常出现大面积空缺,同化时引入了一种局地化方法避免远距离虚假相关的影响.试验着重研究了不同的初始扰动样本产生方法以及不同的样本积分时间对同化结果的影响.提出了一种为预报集...
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| 关 键 词： | 多普勒雷达 集合 资料同化 3DVar SVD |
Assimilation of Doppler Radar Velocity Observations with SVD-En3DVar MethodPart I:Simulated Data Experiments |
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| XU Daosheng,SHAO Aimei and QIU Chongjian.Assimilation of Doppler Radar Velocity Observations with SVD-En3DVar MethodPart I:Simulated Data Experiments[J].Chinese Journal of Atmospheric Sciences,2011,35(4):753-766. |
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| Authors: | XU Daosheng SHAO Aimei and QIU Chongjian |
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| Institution: | Key Laboratory for Semi-Arid Climate Change of the Ministry of Education, College of Atmospheric Sciences, Lanzhou University, Lanzhou 730000 |
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| Abstract: | The ensemble-based 3DVar (three-dimensional variational technique) method with SVD (singular value decomposition) technique (SVD-En3DVar) is used to assimilate simulated Doppler radial velocity observations. A localization scheme is introduced to the method to reduce spurious error covariance among distant points. The impact of different methods of producing initial perturbation and integration time lengths for forecast samples on the assimilation is emphatically investigated. A new scheme producing initial perturbation samples is proposed. This scheme takes the pseudo-random perturbation fields of temperature and specific humidity as the observation innovation and a 3DVar system is utilized to yield the initial perturbation fields of all variables from the observation innovation. Experiments using the simulated observations by WRF(weather research forecasting) model demonstrate that in the initial perturbation fields produced by using the new scheme the compatibility between different variables is better and the perturbation will not decay quickly in the forecast, so the spin-up time is cut down and the time interval of assimilation cycle can be shortened. The forecasts of temperature, humidity, horizontal wind, and rainfall within 12 hours are improved after assimilating the radar velocity data. |
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| Keywords: | Doppler radar ensemble data assimilation 3Dvar SVD |
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