摘要
针对卫星Aqua/AIRS观测到的与2011年7月25日山东省乳山市特大暴雨相伴的一次平流层重力波过程,利用中尺度数值模式WRF进行暴雨诱发平流层重力波的数值模拟.对模式输出的垂直速度场和温度扰动场的分析表明,暴雨在平流层内的弧状波结构主要集中在降水云系东侧,水平影响范围大于1000km,且随着高度的增加,圆弧状结构趋于闭合,波动能量显著增强.此外,对垂直速度剖面结构分析表明,受高空东风和风切变的影响,重力波在上传过程中逆着背景风场向东传输,不同高度波动形态各异.基于快速傅里叶变换(FFT)的功率谱分析结果表明,此次暴雨激发的平流层重力波在35km高度的周期为7~20h,水平波长约为1000km,垂直波长为5~10km.通过分析动量通量的垂直输送,定量反映出重力波上传过程中的动力学变化特征.
In order to analyze the characteristics of the deep convection-induced stratospheric gravity waves in Chinese continental region, a stratospheric gravity wave process, which is observed by the satellite Aqua/AIRS and accompanied with the heavy rainstorm process on July 25 th. 2011 in Rushan, is simulated using the mesoscale numerical WRF(Weather Research and Forcasting) model.The analysis of the vertical velocity field and the temperature disturbance field of the mode output show that the structure of the torrential wave in the stratosphere is mainly concentrated in the east of the precipitation cloud system, and the horizontal influence range is more than 1000 km. With the increase of the height, the structure of the torrential wave tends to close, and the wave energy is also significantly enhanced. The results of power spectrum analysis based on Fast Fourier Transform(FFT) show that the stratospheric gravity wave induced by the storm at 35 km has the horizontal wavelength of about 1000 km and the vertical wavelength of 5~10 km. Finally, the parameterized forcing in gravity wave uploading process is quantifiably reflected by analyzing the vertical transport of momentum flux reflects.
作者
孙睿
姚志刚
韩志刚
赵增亮
崔新东
严卫
SUN Rui;YAO Zhigang;HAN Zhigang;ZHAO Zengliang;CUI Xindong;YAN Wei(No.91954 Troops of PLA Yongzhou 425000;Beijing Institute of Applied Meteorology Beijing 100029;Institute of Meteorology and Oceanography,National University of Defense Technology,Nanjing 211101)
出处
《空间科学学报》
CAS
CSCD
北大核心
2018年第4期469-481,共13页
Chinese Journal of Space Science
基金
国家自然科学基金项目(41575031)
中国博士后基金项目(2015M580124)共同资助
关键词
平流层
重力波
中尺度天气预报模式
数值模拟
Stratosphere
Gravity waves
Weather Research and Forcasting (WRF) model
Nu-merical simulation