摘要
在原模式版本TRAMS-V2.0的基础上,通过对三维静力参考大气、拉格朗日矢量投影、云降水物理和辐射等技术方案进行改进,并且针对高分辨率模式易产生强垂直运动和小尺度扰动等问题,引入水平扩散、垂直运动耗散等技术方案,同时优化模式动力物理过程各功能块的调用方式和一些技术参数,最终形成适合热带高分辨率的模式版本TRAMS-V3.0。批量测试表明,新版模式TRAMS-V3.0的预报性能明显优于TRAMS-V2.0,新版模式不仅对形势场和地面要素的预报误差较小,而且各量级降水预报的准确率也比较高,如48小时2 m温度预报RMS由原来的2.4℃降低为1.8℃,晴雨48小时预报准确率由原来的0.736提高到0.810等。基于TRAMS-V3.0建立的预报系统,实时业务应用中展现了系统在晴雨、暴雨、地面要素等方面预报的优势。并针对暴雨空漏报等问题进行了初步的分析,提出下一步技术改进的设想。
The present study improves 3D reference,Lagrange vector projection,cloud precipitation physics and radiation schemes.In addition,to solve the problem that high-resolution models are prone to generate strong vertical motion and small-scale disturbance,the present study introduces technical schemes such as horizontal diffusion and w-damping,based on the original model version TRAMS-V2.0.Meanwhile,the model calculation and some technical parameters are optimized,and the tropical highresolution TRAMS-V3.0 is finally formed.Batch tests show that the prediction performance of the new model TRAMS-V3.0 is significantly better than that of the origin model TRAMS-V2.0.The new model not only has a smaller prediction error for the isobaric field and surface elements,but also has a higher accuracy rate for precipitation forecast at all levels.The prediction system is established based on TRAMSV3.0,and the real-time application shows the advantages of the system in the forecast of fine rain,heavy rain,and surface elements,etc.In the research,problems such as heavy rain forecast that missed the mark are analysis,and some technological improvements for the next step are proposed.
作者
陈子通
徐道生
戴光丰
张艳霞
钟水新
黄燕燕
CHEN Zi-tong;XU Dao-sheng;DAI Guang-feng;ZHANG Yan-xia;ZHONG Shui-xin;HUANG Yan-yan(Guangzhou Institute of Tropical and Marine Meteorology/Guangdong Provincial Key Laboratory of Regional Numerical Weather Prediction,CMA,Guangzhou 510641,China)
出处
《热带气象学报》
CSCD
北大核心
2020年第4期444-454,共11页
Journal of Tropical Meteorology
基金
国家重点研发计划(2018YFC1506901)
广州市科技计划项目(201804020038)共同资助。
关键词
热带
高分辨率
数值预报
业务
暴雨
tropical
high resolution
numerical weather prediction
operation
heavy rain