An ensemble-based method for the observation system simulation experiment(OSSE)is employed to design optimal observation stations and assess the present observation stations in the northeastern South China Sea(SCS).We...An ensemble-based method for the observation system simulation experiment(OSSE)is employed to design optimal observation stations and assess the present observation stations in the northeastern South China Sea(SCS).We employed the 20-year(1992-2012)sea surface height(SSH)data to design an array to monitor the intraseasonal to interannual variability.The results show that the most key region was found located at the northwest of Luzon Island(LI)where the energetic Luzon cyclonic gyre(LCG)occurs;other key regions include the edge of the LCG,the northwest of the Luzon Strait(LS),and the southwest of Taiwan,China.By contrast,we found that the present observation stations might oversample at the northwest of the LS and undersample at the northwest of LI.In addition,the optimal stations perform better in a larger area than the present stations.In vertical direction,the key layer is located within the upper 200-m depth,of which the surface and subsurface layers are most valuable to the observing system.展开更多
In this paper, several sets of observing system simulation experiments (OSSEs) were designed for three typhoon cases to determine whether or not the additional observation data in the sensitive regions identified by c...In this paper, several sets of observing system simulation experiments (OSSEs) were designed for three typhoon cases to determine whether or not the additional observation data in the sensitive regions identified by conditional nonlinear optimal perturbations (CNOPs) could improve the short-range forecast of typhoons. The results show that the CNOPs capture the sensitive regions for typhoon forecasts, which implies that conducting additional observation in these specific regions and eliminating initial errors could reduce forecast errors. It is inferred from the results that dropping sondes in the CNOP sensitive regions could lead to improvements in typhoon forecasts.展开更多
为了科学设计黄渤海海洋气象边界层观测站网并研究观测网布局对数值天气预报模式的影响,本文采用模式误差、海洋气象要素特征区域资料统计分析和观测系统模拟试验(OSSE)方法,根据边界层雾、层云降水、小风与中等风速天气条件设计布局方...为了科学设计黄渤海海洋气象边界层观测站网并研究观测网布局对数值天气预报模式的影响,本文采用模式误差、海洋气象要素特征区域资料统计分析和观测系统模拟试验(OSSE)方法,根据边界层雾、层云降水、小风与中等风速天气条件设计布局方案,并分析站点观测要素对数值预报模式的要素预报的影响。模拟试验数据使用了每6 h NCEP再分析资料FNL(NCEP Final Operational Global Analysis data)、NCEP每天平均的高分辨率海温资料RTG_SST(Real-Time Global Sea Surface Temperature)和石油平台、浮标站等每小时实况观测资料,评估了黄渤海海洋气象站网布局各个方案的优缺点。评估结果表明,湿度和风的要素预报受实况风向风速条件影响,偏东和偏北风个例湿度要素预报较好。然而,在偏南中等风速个例中,风场预报要素更接近实况。温度场的分析综合结果显示,在海气相互作用影响较大的天气过程中,特征区域布站能明显提高温度要素的预报准确率。最后,综合分析多项模拟试验的结果,给出了改进数值预报准确率的海洋布站建议。展开更多
The conditional nonlinear optimal perturbations（CNOPs） obtained by a fast algorithm are applied to determining the sensitive area for the targeting observation of Typhoon Matsa in 2005 using an operational regional ...The conditional nonlinear optimal perturbations（CNOPs） obtained by a fast algorithm are applied to determining the sensitive area for the targeting observation of Typhoon Matsa in 2005 using an operational regional prediction model-the Global/Regional Assimilation and PrEdiction System（GRAPES）.Through a series of sensitivity experiments,several issues on targeting strategy design are discussed,including the effectivity of different guidances to determine the sensitive area（or targeting area） and the impact of sensitive area size on improving the 24-h forecast.In this study,three guidances are used along with the CNOP to find sensitive area for improving the 24-h prediction of sea level pressure and accumulated rainfall in the verification region.The three guidances are based on winds only;on winds,geopotential height,and specific humidity;and on winds,geopotential height,specific humidity,and observation error,respectively.The distribution and effectivity of the sensitive areas are compared with each other,and the results show that the sensitive areas identified by the three guidances are different in terms of convergence and effectivity.All the sensitive areas determined by these guidances can lead to improvement of the 24-h forecast of interest. The second and third guidances are more effective and can identify more similar sensitive areas than the first one.Further,the size of sensitive areas is changed the same way for three guidances and the 24-h accumulated rainfall prediction is examined.The results suggest that a larger sensitive area can result in better prediction skill,provided that the guidance is sensitive to the size of sensitive areas.展开更多
利用基于集合预报的相关方法对2009年7月23日发生在北京及周边地区的暴雨过程的观测敏感区进行了分析。通过WRF(Weather Research Forecast)三维变分方法对初始场进行随机扰动,形成30个初始集合样本,做了预报时效为12 h的集合预报。利...利用基于集合预报的相关方法对2009年7月23日发生在北京及周边地区的暴雨过程的观测敏感区进行了分析。通过WRF(Weather Research Forecast)三维变分方法对初始场进行随机扰动,形成30个初始集合样本,做了预报时效为12 h的集合预报。利用该方法分析检验区(北京及周边地区)累积降水[14:00(北京时间,下同)至20:00]相对于初始时刻(08:00)各基本要素的敏感性,确定感性要素及其对应的区域。研究发现初步确定的敏感性要素为水汽和温度,对应的敏感区分别位于北京的西南侧和北京的东北侧,且通过实况分析可知初步确定的敏感性要素和对应的敏感区具有明确的物理意义。还进一步通过观测系统模拟试验(OSSE)的资料同化验证所确定的敏感区,结果表明在水汽对应的敏感区内同化水汽对降水的预报结果有明显的改进;在温度对应的敏感区内同化温度,降水的预报准确率有了明显的提高,说明了初步确定的敏感性要素和敏感区的正确性。在水汽对应的敏感区内同化水汽的同时在温度对应的敏感区内同化温度,使降水预报的技巧有大幅度的提高,说明了温度和水汽的共同作用对提高降水预报准确率贡献最大。因此,通过基于集合预报的相关方法能够快速的确定敏感区。研究结果将为确定北京暴雨的观测敏感区提供参考。展开更多
同化大量观测资料可以有效地改进模式预报结果,但不同观测对预报的影响有着显著差异,合理评估观测对预报的贡献是数值模式中最具挑战性的诊断之一。本文采用基于伴随的预报对观测的敏感性(Forecast Sensitivity to Observation,简称FSO...同化大量观测资料可以有效地改进模式预报结果,但不同观测对预报的影响有着显著差异,合理评估观测对预报的贡献是数值模式中最具挑战性的诊断之一。本文采用基于伴随的预报对观测的敏感性(Forecast Sensitivity to Observation,简称FSO)方法,构建WRFDA(Weather Research and Forecasting model’sData Assimilation)框架下的WRFDA-FSO系统。基于2019年9月超大城市项目在北京地区获取的风廓线雷达(Wind Profile Radar,简称WPR)和地基微波辐射计(Microwave Radiometer,简称MWR)观测数据,利用WRFDA-FSO系统,开展观测对WRF模式12 h预报的影响试验,并分析风温湿观测对预报的贡献。结果表明:(1)同化的观测资料(MWR、WPR、Sound、Synop和Geoamv)均减小了WRF模式12 h预报误差,对预报为正贡献,其中MWR观测对预报的影响最大,WPR风场观测对预报的改进效果优于Sound的风场观测。(2)WPR的U、V观测和MWR的T、Q观测中,V观测和T观测对预报的正贡献值更高,对预报的改进效果更优。(3)WPR和MWR多数高度层的观测均减小了预报误差,对预报为正贡献,其中MWR的T观测对预报的正贡献主要位于近地面800 h Pa以下。展开更多
北大西洋地区除了存在约70 a周期的AMO(Atlantic Multidecadal Oscillation,北大西洋年代际振荡)之外,历史长期气候记录中英格兰温度(Central England Temperature,CET)与格陵兰冰芯净雪累计率还存在显著的20 a周期波动。本研究利用CCSM...北大西洋地区除了存在约70 a周期的AMO(Atlantic Multidecadal Oscillation,北大西洋年代际振荡)之外,历史长期气候记录中英格兰温度(Central England Temperature,CET)与格陵兰冰芯净雪累计率还存在显著的20 a周期波动。本研究利用CCSM4(Community Climate System Model version 4)耦合模式工业革命前控制试验(piControl)结果中的海表面温度(Sea Surface Temperature,SST),通过10~50 a带通滤波与扩展经验正交函数(Extended Empirical Orthogonal Function,EEOF)分解,得到在北大西洋副极地海区存在准20 a振荡的逆时针旋转模态。此周期与其临近地区的CET、格陵兰冰芯净雪累计率的准20 a振荡周期相吻合,说明这种北大西洋副极地海区准20 a振荡的海洋模态与其临近地区的大气准20 a振荡之间可能存在相应的联系。进一步利用CAM4(the Community Atmosphere Model version4)大气模式,以北大西洋副极地海区准20 a振荡SST旋转模态为强迫场进行敏感性试验,进一步验证了这种联系。展开更多
Conditional Nonlinear Optimal Perturbation （CNOP） is a new method proposed by Mu et al. in 2003, which generalizes the linear singular vector （LSV） to include nonlinearity. It has become a powerful tool for studyi...Conditional Nonlinear Optimal Perturbation （CNOP） is a new method proposed by Mu et al. in 2003, which generalizes the linear singular vector （LSV） to include nonlinearity. It has become a powerful tool for studying predictability and sensitivity among other issues in nonlinear systems. This is because the CNOP is able to represent, while the LSV is unable to deal with, the fastest developing perturbation in a nonlinear system. The wide application of this new method, however, has been limited due to its large computational cost related to the use of an adjoint technique. In order to greatly reduce the computational cost, we hereby propose a fast algorithm for solving the CNOP based on the empirical orthogonal function （EOF）. The algorithm is tested in target observation experiments of Typhoon Matsa using the Global/Regional Assimilation and PrEdiction System （GRAPES）, an operational regional forecast model of China. The effectivity and feasibility of the algorithm to determine the sensitivity （target） area is evaluated through two observing system simulation experiments （OSSEs）. The results, as expected, show that the energy of the CNOP solved by the new algorithm develops quickly and nonlinearly. The sensitivity area is effectively identified with the CNOP from the new algorithm, using 24 h as the prediction time window. The 24-h accumulated rainfall prediction errors （ARPEs） in the verification region are reduced significantly compared with the ＂true state,＂ when the initial conditions （ICs） in the sensitivity area are replaced with the ＂observations.＂ The decrease of the ARPEs can be achieved for even longer prediction times （e.g., 72 h）. Further analyses reveal that the decrease of the 24-h ARPEs in the verification region is attributable to improved simulations of the typhoon＇s initial warm-core, upper level relative vorticity, water vapor conditions, etc., as a result of the updated ICs in the sensitivity area.展开更多
基金Supported by the National Key Research&Development Plan of China(Nos.2016YFC1401703,2016YFC1401702,2018YFC0309803)the National Natural Science Foundation of China(Nos.41506002,41676010,41476011,41676015,41606026)+1 种基金the Institution of South China Sea Ecology and Environmental Engineering,Chinese Academy of Sciences(No.ISEE2019ZR0)the Guangzhou Science and Technology Foundation(No.201804010133)。
文摘An ensemble-based method for the observation system simulation experiment(OSSE)is employed to design optimal observation stations and assess the present observation stations in the northeastern South China Sea(SCS).We employed the 20-year(1992-2012)sea surface height(SSH)data to design an array to monitor the intraseasonal to interannual variability.The results show that the most key region was found located at the northwest of Luzon Island(LI)where the energetic Luzon cyclonic gyre(LCG)occurs;other key regions include the edge of the LCG,the northwest of the Luzon Strait(LS),and the southwest of Taiwan,China.By contrast,we found that the present observation stations might oversample at the northwest of the LS and undersample at the northwest of LI.In addition,the optimal stations perform better in a larger area than the present stations.In vertical direction,the key layer is located within the upper 200-m depth,of which the surface and subsurface layers are most valuable to the observing system.
基金sponsored by the National Natural Science Foundation of China (Grant Nos. 40830955 and 40821092)the Project of China Meteorological Administration (Grant No. GYHY200906009)
文摘In this paper, several sets of observing system simulation experiments (OSSEs) were designed for three typhoon cases to determine whether or not the additional observation data in the sensitive regions identified by conditional nonlinear optimal perturbations (CNOPs) could improve the short-range forecast of typhoons. The results show that the CNOPs capture the sensitive regions for typhoon forecasts, which implies that conducting additional observation in these specific regions and eliminating initial errors could reduce forecast errors. It is inferred from the results that dropping sondes in the CNOP sensitive regions could lead to improvements in typhoon forecasts.
文摘为了科学设计黄渤海海洋气象边界层观测站网并研究观测网布局对数值天气预报模式的影响,本文采用模式误差、海洋气象要素特征区域资料统计分析和观测系统模拟试验(OSSE)方法,根据边界层雾、层云降水、小风与中等风速天气条件设计布局方案,并分析站点观测要素对数值预报模式的要素预报的影响。模拟试验数据使用了每6 h NCEP再分析资料FNL(NCEP Final Operational Global Analysis data)、NCEP每天平均的高分辨率海温资料RTG_SST(Real-Time Global Sea Surface Temperature)和石油平台、浮标站等每小时实况观测资料,评估了黄渤海海洋气象站网布局各个方案的优缺点。评估结果表明,湿度和风的要素预报受实况风向风速条件影响,偏东和偏北风个例湿度要素预报较好。然而,在偏南中等风速个例中,风场预报要素更接近实况。温度场的分析综合结果显示,在海气相互作用影响较大的天气过程中,特征区域布站能明显提高温度要素的预报准确率。最后,综合分析多项模拟试验的结果,给出了改进数值预报准确率的海洋布站建议。
基金Supported by the State Key 11th Five-Year Project on Sci.& Tech.under Grant No.2006BAC02B03the China Meteorological Administration R & D Special Fund for Public Welfare(meteorology) under Grant No.GYHY(QX)2007-6-12the National Natural Science Foundation of China under Grant No.40605018
文摘The conditional nonlinear optimal perturbations（CNOPs） obtained by a fast algorithm are applied to determining the sensitive area for the targeting observation of Typhoon Matsa in 2005 using an operational regional prediction model-the Global/Regional Assimilation and PrEdiction System（GRAPES）.Through a series of sensitivity experiments,several issues on targeting strategy design are discussed,including the effectivity of different guidances to determine the sensitive area（or targeting area） and the impact of sensitive area size on improving the 24-h forecast.In this study,three guidances are used along with the CNOP to find sensitive area for improving the 24-h prediction of sea level pressure and accumulated rainfall in the verification region.The three guidances are based on winds only;on winds,geopotential height,and specific humidity;and on winds,geopotential height,specific humidity,and observation error,respectively.The distribution and effectivity of the sensitive areas are compared with each other,and the results show that the sensitive areas identified by the three guidances are different in terms of convergence and effectivity.All the sensitive areas determined by these guidances can lead to improvement of the 24-h forecast of interest. The second and third guidances are more effective and can identify more similar sensitive areas than the first one.Further,the size of sensitive areas is changed the same way for three guidances and the 24-h accumulated rainfall prediction is examined.The results suggest that a larger sensitive area can result in better prediction skill,provided that the guidance is sensitive to the size of sensitive areas.
文摘利用基于集合预报的相关方法对2009年7月23日发生在北京及周边地区的暴雨过程的观测敏感区进行了分析。通过WRF(Weather Research Forecast)三维变分方法对初始场进行随机扰动,形成30个初始集合样本,做了预报时效为12 h的集合预报。利用该方法分析检验区(北京及周边地区)累积降水[14:00(北京时间,下同)至20:00]相对于初始时刻(08:00)各基本要素的敏感性,确定感性要素及其对应的区域。研究发现初步确定的敏感性要素为水汽和温度,对应的敏感区分别位于北京的西南侧和北京的东北侧,且通过实况分析可知初步确定的敏感性要素和对应的敏感区具有明确的物理意义。还进一步通过观测系统模拟试验(OSSE)的资料同化验证所确定的敏感区,结果表明在水汽对应的敏感区内同化水汽对降水的预报结果有明显的改进;在温度对应的敏感区内同化温度,降水的预报准确率有了明显的提高,说明了初步确定的敏感性要素和敏感区的正确性。在水汽对应的敏感区内同化水汽的同时在温度对应的敏感区内同化温度,使降水预报的技巧有大幅度的提高,说明了温度和水汽的共同作用对提高降水预报准确率贡献最大。因此,通过基于集合预报的相关方法能够快速的确定敏感区。研究结果将为确定北京暴雨的观测敏感区提供参考。
文摘同化大量观测资料可以有效地改进模式预报结果,但不同观测对预报的影响有着显著差异,合理评估观测对预报的贡献是数值模式中最具挑战性的诊断之一。本文采用基于伴随的预报对观测的敏感性(Forecast Sensitivity to Observation,简称FSO)方法,构建WRFDA(Weather Research and Forecasting model’sData Assimilation)框架下的WRFDA-FSO系统。基于2019年9月超大城市项目在北京地区获取的风廓线雷达(Wind Profile Radar,简称WPR)和地基微波辐射计(Microwave Radiometer,简称MWR)观测数据,利用WRFDA-FSO系统,开展观测对WRF模式12 h预报的影响试验,并分析风温湿观测对预报的贡献。结果表明:(1)同化的观测资料(MWR、WPR、Sound、Synop和Geoamv)均减小了WRF模式12 h预报误差,对预报为正贡献,其中MWR观测对预报的影响最大,WPR风场观测对预报的改进效果优于Sound的风场观测。(2)WPR的U、V观测和MWR的T、Q观测中,V观测和T观测对预报的正贡献值更高,对预报的改进效果更优。(3)WPR和MWR多数高度层的观测均减小了预报误差,对预报为正贡献,其中MWR的T观测对预报的正贡献主要位于近地面800 h Pa以下。
文摘北大西洋地区除了存在约70 a周期的AMO(Atlantic Multidecadal Oscillation,北大西洋年代际振荡)之外,历史长期气候记录中英格兰温度(Central England Temperature,CET)与格陵兰冰芯净雪累计率还存在显著的20 a周期波动。本研究利用CCSM4(Community Climate System Model version 4)耦合模式工业革命前控制试验(piControl)结果中的海表面温度(Sea Surface Temperature,SST),通过10~50 a带通滤波与扩展经验正交函数(Extended Empirical Orthogonal Function,EEOF)分解,得到在北大西洋副极地海区存在准20 a振荡的逆时针旋转模态。此周期与其临近地区的CET、格陵兰冰芯净雪累计率的准20 a振荡周期相吻合,说明这种北大西洋副极地海区准20 a振荡的海洋模态与其临近地区的大气准20 a振荡之间可能存在相应的联系。进一步利用CAM4(the Community Atmosphere Model version4)大气模式,以北大西洋副极地海区准20 a振荡SST旋转模态为强迫场进行敏感性试验,进一步验证了这种联系。
基金Supported by the "973" Project of the Ministry of Science and Technology of China under Grant No. 2004CB418304the China Meteorological Administration R&D Special Fund for Public Welfare (meteorology) under Grant No. GYHY(QX)2007-6-15
文摘Conditional Nonlinear Optimal Perturbation （CNOP） is a new method proposed by Mu et al. in 2003, which generalizes the linear singular vector （LSV） to include nonlinearity. It has become a powerful tool for studying predictability and sensitivity among other issues in nonlinear systems. This is because the CNOP is able to represent, while the LSV is unable to deal with, the fastest developing perturbation in a nonlinear system. The wide application of this new method, however, has been limited due to its large computational cost related to the use of an adjoint technique. In order to greatly reduce the computational cost, we hereby propose a fast algorithm for solving the CNOP based on the empirical orthogonal function （EOF）. The algorithm is tested in target observation experiments of Typhoon Matsa using the Global/Regional Assimilation and PrEdiction System （GRAPES）, an operational regional forecast model of China. The effectivity and feasibility of the algorithm to determine the sensitivity （target） area is evaluated through two observing system simulation experiments （OSSEs）. The results, as expected, show that the energy of the CNOP solved by the new algorithm develops quickly and nonlinearly. The sensitivity area is effectively identified with the CNOP from the new algorithm, using 24 h as the prediction time window. The 24-h accumulated rainfall prediction errors （ARPEs） in the verification region are reduced significantly compared with the ＂true state,＂ when the initial conditions （ICs） in the sensitivity area are replaced with the ＂observations.＂ The decrease of the ARPEs can be achieved for even longer prediction times （e.g., 72 h）. Further analyses reveal that the decrease of the 24-h ARPEs in the verification region is attributable to improved simulations of the typhoon＇s initial warm-core, upper level relative vorticity, water vapor conditions, etc., as a result of the updated ICs in the sensitivity area.
