The present study identifies wintertime cold fronts in Eurasia from gridded datasets using a new objective two-step identification scheme.The simple and classic conception of a front is adopted,where a cold front is i...The present study identifies wintertime cold fronts in Eurasia from gridded datasets using a new objective two-step identification scheme.The simple and classic conception of a front is adopted,where a cold front is identified as the warm boundary of the frontal zone with a suitable horizontal temperature gradient and cold advection.We combine the traditional thermal front parameter with temperature advection to first identify the cold frontal zone,and then its eastern and southern boundaries are objectively plotted as a cold front in Eurasia.By comparing different cold front identification methods,the results from this two-step cold front identification method and subjective analysis are more consistent,and the positions of the cold front identified with our method are more reasonable.This objective technique is also applied to a nationwide cold wave event over China.Results show that the horizontal extent and movement of the cold front are in good agreement with the related circulation and the associated cold weather.The proposed method and results in this study may shed light on the rapid identification of cold fronts in operational weather analysis and facilitate further research on the long-term activity characteristics of continental cold fronts.展开更多
基于WRF(Weather Research and Forecasting Model,天气预报模式)及其三维变分同化系统3DVAR,利用江苏省GPS/PWV(PWV:Precipitable Water Vapor,GPS反演得到可降水量)资料,并将其与探空资料比对订正,针对2011年6月18日梅雨锋暴雨进行3 ...基于WRF(Weather Research and Forecasting Model,天气预报模式)及其三维变分同化系统3DVAR,利用江苏省GPS/PWV(PWV:Precipitable Water Vapor,GPS反演得到可降水量)资料,并将其与探空资料比对订正,针对2011年6月18日梅雨锋暴雨进行3 h循环同化模拟。在降水参数化方案敏感性试验与单点同化试验基础上,设计多组试验对6 h降水量进行TS(Threat Score)评估。结果表明:(1)同化订正GPS/PWV资料对降水预报能力显著提高,特别是大雨、暴雨量级以上的预报能力;(2)降水量的RMSE(Root Mean Squared Error,均方根误差)相比控制试验均减小,CC(Correlation Coefficient,相关系数)均增大,最显著试验RMSE从19.1 mm下降到12.6 mm,CC从0.45上升到0.74;(3)NMC方法统计的背景误差协方差条件下中雨至暴雨量级TS评分均有一定程度提高,默认的背景误差协方差在大雨以上量级TS评分大幅提高。展开更多
基金This work is supported by the National Key Research and Development Pro-gram of China under contract(Grant No.2019YFC1510201 and Grant No.2018YFC1505602).
文摘The present study identifies wintertime cold fronts in Eurasia from gridded datasets using a new objective two-step identification scheme.The simple and classic conception of a front is adopted,where a cold front is identified as the warm boundary of the frontal zone with a suitable horizontal temperature gradient and cold advection.We combine the traditional thermal front parameter with temperature advection to first identify the cold frontal zone,and then its eastern and southern boundaries are objectively plotted as a cold front in Eurasia.By comparing different cold front identification methods,the results from this two-step cold front identification method and subjective analysis are more consistent,and the positions of the cold front identified with our method are more reasonable.This objective technique is also applied to a nationwide cold wave event over China.Results show that the horizontal extent and movement of the cold front are in good agreement with the related circulation and the associated cold weather.The proposed method and results in this study may shed light on the rapid identification of cold fronts in operational weather analysis and facilitate further research on the long-term activity characteristics of continental cold fronts.
文摘基于WRF(Weather Research and Forecasting Model,天气预报模式)及其三维变分同化系统3DVAR,利用江苏省GPS/PWV(PWV:Precipitable Water Vapor,GPS反演得到可降水量)资料,并将其与探空资料比对订正,针对2011年6月18日梅雨锋暴雨进行3 h循环同化模拟。在降水参数化方案敏感性试验与单点同化试验基础上,设计多组试验对6 h降水量进行TS(Threat Score)评估。结果表明:(1)同化订正GPS/PWV资料对降水预报能力显著提高,特别是大雨、暴雨量级以上的预报能力;(2)降水量的RMSE(Root Mean Squared Error,均方根误差)相比控制试验均减小,CC(Correlation Coefficient,相关系数)均增大,最显著试验RMSE从19.1 mm下降到12.6 mm,CC从0.45上升到0.74;(3)NMC方法统计的背景误差协方差条件下中雨至暴雨量级TS评分均有一定程度提高,默认的背景误差协方差在大雨以上量级TS评分大幅提高。
