| 基于VDRAS的快速更新雷达四维变分分析系统 |
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| 引用本文： | 陈明轩,高峰,孙娟珍,肖现,刘莲,王迎春.基于VDRAS的快速更新雷达四维变分分析系统[J].应用气象学报,2016,27(3):257-272. |
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| 作者姓名： | 陈明轩 高峰 孙娟珍 肖现 刘莲 王迎春 |
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| 作者单位： | 1.中国气象局北京城市气象研究所，北京 100089 |
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| 基金项目： | 资助项目： 公益性行业（气象）科研专项（GYHY201306008，GYHY201506004），国家自然科学基金项目（41075036，41575050） |
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| 摘 要： | 基于雷达资料快速更新四维变分同化 (RR4DVar) 技术和三维数值云模式，初步研发了一个针对对流尺度数值模拟的快速更新雷达四维变分分析系统。系统通过对京津冀6部多普勒天气雷达资料进行RR4DVar同化，并融合5 min自动气象站观测和中尺度数值模式结果，可快速分析得到12~18 min更新的低层大气三维动力、热力场的对流尺度结构特征。针对2009年7月22日发生在京津冀的一次强风暴个例，通过一系列敏感性试验，并利用局地加密资料进行检验对比，表明有效的雷达资料RR4DVar同化及自动气象站和中尺度模式资料融合方案、恰当的中尺度背景场设置和动力约束方法是获得合理结果的关键。研究也表明:恰当的系统配置能够模拟出与对流生消发展密切相关的近风暴环境特征，包括低层入流、垂直风切变、低层辐合上升和暖舌等，以及风暴自身形成的冷池、出流等与风暴演变密切相关的对流尺度结构。
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| 关 键 词： | 雷达 四维变分 快速更新 对流风暴 敏感性试验 |
| 收稿时间： | 2015-10-08 |
An Analysis System Using Rapid updating 4 D Variational Radar Data Assimilation Based on VDRAS |
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| Chen Mingxuan,Gao Feng,Sun Juanzhen,Xiao Xian,Liu Lian and Wang Yingchun.An Analysis System Using Rapid updating 4 D Variational Radar Data Assimilation Based on VDRAS[J].Quarterly Journal of Applied Meteorology,2016,27(3):257-272. |
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| Authors: | Chen Mingxuan Gao Feng Sun Juanzhen Xiao Xian Liu Lian and Wang Yingchun |
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| Affiliation: | 1.Institute of Urban Meteorology, China Meteorological Administration, Beijing 1000892.School of Atmospheric Sciences, Nanjing University, Nanjing 2100463.National Center for Atmospheric Research, Boulder, CO 803074.Chinese Academy of Meteorological Sciences, Beijing 1000815.Beijing Meteorological Service, Beijing 100089 |
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| Abstract: | On the basis of further improvement and development of Variational Doppler Radar Analysis System (VDRAS), a rapid updating 4 D variational analysis system focusing on convective scale numerical simulation and aiming at nowcasting convective storm has been preliminarily set up and tuned. The system is based on rapid updating 4 D variational assimilation (RR4DVar) techniques of multi Doppler radar observations, a 3 D cloud scale numerical model with simplified microphysics scheme which includes rainwater evaporation cooling and precipitation sedimentation processes, and an adjoint model. The system can rapidly get low level 3 D analysis fields including convective scale dynamical, thermo dynamical and microphysical structures with 12-18 min updating cycles by assimilating both reflectivity and radial velocity observations from 6 CINRAD Doppler radars in Beijing Tianjin Hebei region using the RR4DVar scheme. It also integrates 5 min observations from regional auto weather stations (AWS) and forecast results from a meso scale numerical model. Allowing for a strong convective storm case occurred in the region on 22 July 2009, simulated results from a series of sensitivity experiments including control, full troposphere and full microphysics, meso scale background, and radar data assimilation are analyzed. These results are also compared and evaluated using intensive local observations from four wind profiler radars, two microwave radiometers, and two boundary layer towers. Some key factors for the system to produce appropriate analysis fields are illuminated. The system using low level settings with the simplified microphysics scheme has comparable skill with full troposphere settings and full microphysics scheme. In the system, most significant RR4DVar assimilation of radar observations can be obtained using two or three scanning volumes from each radar within an assimilation window. As an effective supplement to radar observations on the ground, the AWS data is also very important on the RR4DVar assimilation of radar observations and simulations of dynamical and thermo dynamical structures at several lower model levels. The meso scale background and dynamical constraint for the RR4DVar assimilation of radar observations are sensitive to convective scale simulation in both cold and warm start updating cycles. Results also indicate the system can produce robust pre storm environment features including low level inflows, vertical wind shear, low level small scale convergence, updraft and warm tongues. On the other hand, storm associated convective scale structures including cold pools and outflows can also be reasonably analyzed by the system. |
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| Keywords: | radar 4 D variational assimilation rapid updating convective storm sensitivity experiment |
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