以CAPS(Center for Analysis and Prediction of Storm)研发的ARPS模式(The Advanced RegionalPrediction System V5.2.4)为基础,结合我国多普勒雷达资料,模拟2001年7月13日安徽省的一次暴雨过程,采用3DVAR(3-dimensional variational d...以CAPS(Center for Analysis and Prediction of Storm)研发的ARPS模式(The Advanced RegionalPrediction System V5.2.4)为基础,结合我国多普勒雷达资料,模拟2001年7月13日安徽省的一次暴雨过程,采用3DVAR(3-dimensional variational data assimilation)同化方法,做多时次同化雷达资料试验,前一时次模拟的结果作为下一时次的初始场,不断调整。结果表明,加入雷达资料后的风场、湿度场等都有明显调整,可以明显提高3 h降水模拟效果;同化的雷达时次越多,对上述各要素场和降水的模拟与实际观测的对应效果越好。展开更多
应用新一代中尺度预报模式WRF模式及其3DVar同化系统,针对江苏地区2009年6月14日飑线过程进行了多普勒雷达资料的同化试验研究,在对雷达资料进行严格质量控制的基础上,设计一系列尺度化因子优化调整及同化频率的敏感性试验。试验结果表...应用新一代中尺度预报模式WRF模式及其3DVar同化系统,针对江苏地区2009年6月14日飑线过程进行了多普勒雷达资料的同化试验研究,在对雷达资料进行严格质量控制的基础上,设计一系列尺度化因子优化调整及同化频率的敏感性试验。试验结果表明:同化后初始场得到不同程度改善,适当的尺度化因子设定,能够有效改进对模式初始场中700 h Pa风场和850 h Pa温度场以及组合反射率因子等要素的分析,进而改善短时降水预报和风暴的垂直结构配置;并且同化频率越高,对初始场的组合反射率因子分布与观测更为接近,短时降水预报越准确。展开更多
基于GSI(Community Gridpoint Statistical Interpolation)同化系统和WRF(Weather Research and Forecasting)模式,探讨了多部多普勒雷达的反射率因子和径向速度资料同化对2016年6月23日江苏阜宁龙卷模拟的改进效果和影响过程。结果表明...基于GSI(Community Gridpoint Statistical Interpolation)同化系统和WRF(Weather Research and Forecasting)模式,探讨了多部多普勒雷达的反射率因子和径向速度资料同化对2016年6月23日江苏阜宁龙卷模拟的改进效果和影响过程。结果表明:(1)仅同化雷达反射率因子和仅同化径向速度均能在一定程度上改进模式对阜宁龙卷及其环境场的模拟,且雷达径向速度同化的改进作用更大;同时同化两种资料改进效果最佳。(2)雷达反射率因子同化是利用复杂云分析技术,直接修正了水凝物含量,增加了潜热释放,对低层大气热力场进行了正温度扰动调整,从而主要改进了初始场的水汽条件和热力条件;而雷达径向速度同化通过三维变分技术直接修正了风场,进而引起水汽输送变化影响水凝物的调整和大气热力场的变化,对初始场的动力条件和热力条件修正较大;同时同化两种资料修正了初始场的动力和热力结构,保证了两者物理上的协调,综合了两者的改进作用,从而取得最佳模拟效果。(3)同时同化雷达反射率因子和径向速度后,模式在阜宁附近模拟出了明显的涡旋结构,尽管涡旋强度和龙卷结构与实况仍有一定差距,但涡旋发生发展过程、路径、地面小时极大风和降水等模拟与实况吻合度均明显高于对照试验。展开更多
Assimilation configurations have significant impacts on analysis results and subsequent forecasts. A squall line system that occurred on 23 April 2007 over southern China was used to investigate the impacts of the dat...Assimilation configurations have significant impacts on analysis results and subsequent forecasts. A squall line system that occurred on 23 April 2007 over southern China was used to investigate the impacts of the data assimilation frequency of radar data on analyses and forecasts. A three-dimensional variational system was used to assimilate radial velocity data,and a cloud analysis system was used for reflectivity assimilation with a 2-h assimilation window covering the initial stage of the squall line. Two operators of radar reflectivity for cloud analyses corresponding to single-and double-moment schemes were used. In this study, we examined the sensitivity of assimilation frequency using 10-, 20-, 30-, and 60-min assimilation intervals. The results showed that analysis fields were not consistent with model dynamics and microphysics in general;thus, model states, including dynamic and microphysical variables, required approximately 20 min to reach a new balance after data assimilation in all experiments. Moreover, a 20-min data assimilation interval generally produced better forecasts for both single-and double-moment schemes in terms of equitable threat and bias scores. We conclude that a higher data assimilation frequency can produce a more intense cold pool and rear inflow jets but does not necessarily lead to a better forecast.展开更多
雷达资料同化对提高数值天气预报准确率具有重要意义。针对2016年7月5-6日武汉一次梅雨期暴雨过程,采用改进的雷达资料同化方案STMAS(Space and Time Multiscale Analysis System)同化雷达径向速度和反射率因子。通过与LAPS(Local Analy...雷达资料同化对提高数值天气预报准确率具有重要意义。针对2016年7月5-6日武汉一次梅雨期暴雨过程,采用改进的雷达资料同化方案STMAS(Space and Time Multiscale Analysis System)同化雷达径向速度和反射率因子。通过与LAPS(Local Analysis and Prediction System)方案的结果对比初始动力场、水汽条件、热力场、预报天气形势、降水和雷达回波等的差异,并着重分析了STMAS方案对初始场及降水预报的改进及其原因。结果表明:(1)同化雷达径向速度时,STMAS方案在三维变分基础上引入连续方程做强约束条件,对初始场中动力场改善效果较为明显。(2)同化雷达反射率因子时,STMAS方案增加利用雷达回波直接调整湿度步骤,强迫雷达回波高于阈值区域饱和,使得初始场的水汽条件更加充沛,对流不稳定能量更大。(3)由于STMAS方案初始场的改善,使得预报场中高低空天气系统配置较好,最终使得预报的雨带和强降水落区在位置和强度上更接近实况,其中100 mm以上强降水预报能力尤为突出。展开更多
The traditional threat score based on fixed thresholds for precipitation verification is sensitive to intensity forecast bias. In this study, the neighborhood precipitation threat score is modified by defining the thr...The traditional threat score based on fixed thresholds for precipitation verification is sensitive to intensity forecast bias. In this study, the neighborhood precipitation threat score is modified by defining the thresholds in terms of the percentiles of overall precipitation instead of fixed threshold values. The impact of intensity forecast bias on the calculated threat score is reduced. The method is tested with the forecasts of a tropical storm that re-intensified after making landfall and caused heavy flooding. The forecasts are produced with and without radar data assimilation. The forecast with assimilation of both radial velocity and reflectivity produce precipitation patterns that better match observations but have large positive intensity bias. When using fixed thresholds, the neighborhood threat scores fail to yield high scores for forecasts that have good pattern match with observations, due to large intensity bias. In contrast, the percentile-based neighborhood method yields the highest score for the forecast with the best pattern match and the smallest position error. The percentile-based method also yields scores that are more consistent with object-based verifications, which are less sensitive to intensity bias, demonstrating the potential value of percentile-based verification.展开更多
文摘以CAPS(Center for Analysis and Prediction of Storm)研发的ARPS模式(The Advanced RegionalPrediction System V5.2.4)为基础,结合我国多普勒雷达资料,模拟2001年7月13日安徽省的一次暴雨过程,采用3DVAR(3-dimensional variational data assimilation)同化方法,做多时次同化雷达资料试验,前一时次模拟的结果作为下一时次的初始场,不断调整。结果表明,加入雷达资料后的风场、湿度场等都有明显调整,可以明显提高3 h降水模拟效果;同化的雷达时次越多,对上述各要素场和降水的模拟与实际观测的对应效果越好。
文摘应用新一代中尺度预报模式WRF模式及其3DVar同化系统,针对江苏地区2009年6月14日飑线过程进行了多普勒雷达资料的同化试验研究,在对雷达资料进行严格质量控制的基础上,设计一系列尺度化因子优化调整及同化频率的敏感性试验。试验结果表明:同化后初始场得到不同程度改善,适当的尺度化因子设定,能够有效改进对模式初始场中700 h Pa风场和850 h Pa温度场以及组合反射率因子等要素的分析,进而改善短时降水预报和风暴的垂直结构配置;并且同化频率越高,对初始场的组合反射率因子分布与观测更为接近,短时降水预报越准确。
文摘基于GSI(Community Gridpoint Statistical Interpolation)同化系统和WRF(Weather Research and Forecasting)模式,探讨了多部多普勒雷达的反射率因子和径向速度资料同化对2016年6月23日江苏阜宁龙卷模拟的改进效果和影响过程。结果表明:(1)仅同化雷达反射率因子和仅同化径向速度均能在一定程度上改进模式对阜宁龙卷及其环境场的模拟,且雷达径向速度同化的改进作用更大;同时同化两种资料改进效果最佳。(2)雷达反射率因子同化是利用复杂云分析技术,直接修正了水凝物含量,增加了潜热释放,对低层大气热力场进行了正温度扰动调整,从而主要改进了初始场的水汽条件和热力条件;而雷达径向速度同化通过三维变分技术直接修正了风场,进而引起水汽输送变化影响水凝物的调整和大气热力场的变化,对初始场的动力条件和热力条件修正较大;同时同化两种资料修正了初始场的动力和热力结构,保证了两者物理上的协调,综合了两者的改进作用,从而取得最佳模拟效果。(3)同时同化雷达反射率因子和径向速度后,模式在阜宁附近模拟出了明显的涡旋结构,尽管涡旋强度和龙卷结构与实况仍有一定差距,但涡旋发生发展过程、路径、地面小时极大风和降水等模拟与实况吻合度均明显高于对照试验。
基金supported by the National Key R&D Program of China (Grant No.2017YFC1502104)the National Natural Science Foundation of China (Grant Nos.41775099 and 41605026)Grant No.NJCAR2016ZD02,and the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD)
文摘Assimilation configurations have significant impacts on analysis results and subsequent forecasts. A squall line system that occurred on 23 April 2007 over southern China was used to investigate the impacts of the data assimilation frequency of radar data on analyses and forecasts. A three-dimensional variational system was used to assimilate radial velocity data,and a cloud analysis system was used for reflectivity assimilation with a 2-h assimilation window covering the initial stage of the squall line. Two operators of radar reflectivity for cloud analyses corresponding to single-and double-moment schemes were used. In this study, we examined the sensitivity of assimilation frequency using 10-, 20-, 30-, and 60-min assimilation intervals. The results showed that analysis fields were not consistent with model dynamics and microphysics in general;thus, model states, including dynamic and microphysical variables, required approximately 20 min to reach a new balance after data assimilation in all experiments. Moreover, a 20-min data assimilation interval generally produced better forecasts for both single-and double-moment schemes in terms of equitable threat and bias scores. We conclude that a higher data assimilation frequency can produce a more intense cold pool and rear inflow jets but does not necessarily lead to a better forecast.
文摘雷达资料同化对提高数值天气预报准确率具有重要意义。针对2016年7月5-6日武汉一次梅雨期暴雨过程,采用改进的雷达资料同化方案STMAS(Space and Time Multiscale Analysis System)同化雷达径向速度和反射率因子。通过与LAPS(Local Analysis and Prediction System)方案的结果对比初始动力场、水汽条件、热力场、预报天气形势、降水和雷达回波等的差异,并着重分析了STMAS方案对初始场及降水预报的改进及其原因。结果表明:(1)同化雷达径向速度时,STMAS方案在三维变分基础上引入连续方程做强约束条件,对初始场中动力场改善效果较为明显。(2)同化雷达反射率因子时,STMAS方案增加利用雷达回波直接调整湿度步骤,强迫雷达回波高于阈值区域饱和,使得初始场的水汽条件更加充沛,对流不稳定能量更大。(3)由于STMAS方案初始场的改善,使得预报场中高低空天气系统配置较好,最终使得预报的雨带和强降水落区在位置和强度上更接近实况,其中100 mm以上强降水预报能力尤为突出。
基金primarily supported by the National 973 Fundamental Research Program of China(Grant No.2013CB430103)the Department of Transportation Federal Aviation Administration(Grant No.NA17RJ1227)through the National Oceanic and Atmospheric Administration+1 种基金supported by the National Science Foundation of China(Grant No.41405100)the Fundamental Research Funds for the Central Universities(Grant No.20620140343)
文摘The traditional threat score based on fixed thresholds for precipitation verification is sensitive to intensity forecast bias. In this study, the neighborhood precipitation threat score is modified by defining the thresholds in terms of the percentiles of overall precipitation instead of fixed threshold values. The impact of intensity forecast bias on the calculated threat score is reduced. The method is tested with the forecasts of a tropical storm that re-intensified after making landfall and caused heavy flooding. The forecasts are produced with and without radar data assimilation. The forecast with assimilation of both radial velocity and reflectivity produce precipitation patterns that better match observations but have large positive intensity bias. When using fixed thresholds, the neighborhood threat scores fail to yield high scores for forecasts that have good pattern match with observations, due to large intensity bias. In contrast, the percentile-based neighborhood method yields the highest score for the forecast with the best pattern match and the smallest position error. The percentile-based method also yields scores that are more consistent with object-based verifications, which are less sensitive to intensity bias, demonstrating the potential value of percentile-based verification.
