A hybrid grid-point statistical interpolation-ensemble transform Kalman filter (GSI-ETKF) data assimilation system for the Weather Research and Forecasting (WRF) model was developed and applied to typhoon track foreca...A hybrid grid-point statistical interpolation-ensemble transform Kalman filter (GSI-ETKF) data assimilation system for the Weather Research and Forecasting (WRF) model was developed and applied to typhoon track forecast with simulated dropsonde observations. This hybrid system showed significantly improved results with respect to tropical cyclone track forecast compared to the standard GSI system in the case of Muifa in 2011. Further analyses revealed that the flow-dependent ensemble covariance was the major contributor to the better performance of the GSI-ETKF system than the standard GSI system; the GSI-ETKF system was found to be potentially able to adjust the position of the typhoon vortex systematically and better update the environmental field.展开更多
An anisotropic diffusion filter can be used to model a flow-dependent background error covariance matrix,which can be achieved by solving the advection-diffusion equation.Because of the directionality of the advection...An anisotropic diffusion filter can be used to model a flow-dependent background error covariance matrix,which can be achieved by solving the advection-diffusion equation.Because of the directionality of the advection term,the discrete method needs to be chosen very carefully.The finite analytic method is an alternative scheme to solve the advection-diffusion equation.As a combination of analytical and numerical methods,it not only has high calculation accuracy but also holds the characteristic of the auto upwind.To demonstrate its ability,the one-dimensional steady and unsteady advection-diffusion equation numerical examples are respectively solved by the finite analytic method.The more widely used upwind difference method is used as a control approach.The result indicates that the finite analytic method has higher accuracy than the upwind difference method.For the two-dimensional case,the finite analytic method still has a better performance.In the three-dimensional variational assimilation experiment,the finite analytic method can effectively improve analysis field accuracy,and its effect is significantly better than the upwind difference and the central difference method.Moreover,it is still a more effective solution method in the strong flow region where the advective-diffusion filter performs most prominently.展开更多
A new sequential data assimilation method named "Monte Carlo H ∞ filter" is introduced based on H ∞ filter technique and Monte Carlo method in this paper. This method applies to nonlinear systems in condit...A new sequential data assimilation method named "Monte Carlo H ∞ filter" is introduced based on H ∞ filter technique and Monte Carlo method in this paper. This method applies to nonlinear systems in condition of lacking the statistical properties of observational errors. In order to compare the as- similation capability of Monte Carlo H ∞ filter with that of the ensemble Kalman filter (EnKF) in solving practical problems caused by temporal correlation or spatial correlation of observational errors, two numerical experiments are performed by using Lorenz (1963) system and shallow-water equations re- spectively. The result is that the assimilation capability of the new method is better than that of EnKF method. It is also shown that Monte Carlo H ∞ filter assimilation method is effective and suitable to nonlinear systems in that it does not depend on the statistical properties of observational errors and has better robustness than EnKF method when the statistical properties of observational errors are varying. In addition, for the new method, the smallest level factor founded by search method is flow-dependent.展开更多
目的系统评价补充叶酸降低高同型半胱氨酸血症患者血清同型半胱氨酸水平及改善内皮功能的效果。方法计算机检索Cochrane图书馆、PUBMED、Web of Science、万方数据库、中国学术期刊网(CNKI)、中国生物医学文献数据库(CBM)从建库至2014年...目的系统评价补充叶酸降低高同型半胱氨酸血症患者血清同型半胱氨酸水平及改善内皮功能的效果。方法计算机检索Cochrane图书馆、PUBMED、Web of Science、万方数据库、中国学术期刊网(CNKI)、中国生物医学文献数据库(CBM)从建库至2014年1月收录补充叶酸治疗高同型半胱氨酸血症患者临床随机对照试验(RCT),并对纳入的文献采用RevMan 5.0软件进行Meta分析。结果共纳入RCT 12篇、患者926例,其中服用叶酸449例,服用安慰剂477例。Meta分析结果表明:叶酸可以明显降低患者血浆中的同型半胱氨酸水平(WMD=-2.82,95%CI-3.61^-2.04,P<0.01),同时补充叶酸后可有效改善内皮依赖性舒张功能(FMD)(WMD=2.00,95%CI 0.99~3.00,P=0.000 1),其中3篇文献比较了血管内膜中层厚度(IMT),结果表明补充叶酸治疗后不能有效改善颈动脉血管IMT(WMD=-0.05,95%CI-0.10~0.00,P=0.06)。结论补充叶酸可有效降低高同型半胱氨酸血症患者血清同型半胱氨酸水平,同时也可改善患者内皮舒张功能,但不能明确对血管IMT的疗效。展开更多
基金supported by the Project for public welfare (Meteorology) of China(Grant No.GYHY201206006)the National Natural Science Foundation of China(Grant Nos.40975067 and 41175094)
文摘A hybrid grid-point statistical interpolation-ensemble transform Kalman filter (GSI-ETKF) data assimilation system for the Weather Research and Forecasting (WRF) model was developed and applied to typhoon track forecast with simulated dropsonde observations. This hybrid system showed significantly improved results with respect to tropical cyclone track forecast compared to the standard GSI system in the case of Muifa in 2011. Further analyses revealed that the flow-dependent ensemble covariance was the major contributor to the better performance of the GSI-ETKF system than the standard GSI system; the GSI-ETKF system was found to be potentially able to adjust the position of the typhoon vortex systematically and better update the environmental field.
基金The National Key Research and Development Program of China under contract Nos 2022YFC3104804,2021YFC3101501,and 2017YFC1404103the National Programme on Global Change and Air-Sea Interaction of China under contract No.GASI-IPOVAI-04the National Natural Science Foundation of China under contract Nos 41876014,41606039,and 11801402.
文摘An anisotropic diffusion filter can be used to model a flow-dependent background error covariance matrix,which can be achieved by solving the advection-diffusion equation.Because of the directionality of the advection term,the discrete method needs to be chosen very carefully.The finite analytic method is an alternative scheme to solve the advection-diffusion equation.As a combination of analytical and numerical methods,it not only has high calculation accuracy but also holds the characteristic of the auto upwind.To demonstrate its ability,the one-dimensional steady and unsteady advection-diffusion equation numerical examples are respectively solved by the finite analytic method.The more widely used upwind difference method is used as a control approach.The result indicates that the finite analytic method has higher accuracy than the upwind difference method.For the two-dimensional case,the finite analytic method still has a better performance.In the three-dimensional variational assimilation experiment,the finite analytic method can effectively improve analysis field accuracy,and its effect is significantly better than the upwind difference and the central difference method.Moreover,it is still a more effective solution method in the strong flow region where the advective-diffusion filter performs most prominently.
基金Supported by the National Natural Science Foundation of China (Grant Nos. 40275032, 40505005 and 40405019) Opening Foundation of Institute of Heavy Rain, CMA (Grant No. IHR2006G13)
文摘A new sequential data assimilation method named "Monte Carlo H ∞ filter" is introduced based on H ∞ filter technique and Monte Carlo method in this paper. This method applies to nonlinear systems in condition of lacking the statistical properties of observational errors. In order to compare the as- similation capability of Monte Carlo H ∞ filter with that of the ensemble Kalman filter (EnKF) in solving practical problems caused by temporal correlation or spatial correlation of observational errors, two numerical experiments are performed by using Lorenz (1963) system and shallow-water equations re- spectively. The result is that the assimilation capability of the new method is better than that of EnKF method. It is also shown that Monte Carlo H ∞ filter assimilation method is effective and suitable to nonlinear systems in that it does not depend on the statistical properties of observational errors and has better robustness than EnKF method when the statistical properties of observational errors are varying. In addition, for the new method, the smallest level factor founded by search method is flow-dependent.
