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| 利用多普勒天气雷达资料对一次暴雨过程的同化模拟 | |
| 引用本文： | 杨艳蓉,王振会,张沛源.利用多普勒天气雷达资料对一次暴雨过程的同化模拟[J].南京气象学院学报,2008,31(5):633-639. |
| 作者姓名： | 杨艳蓉 王振会 张沛源 |
| 作者单位： | 1. 南京信息工程大学,江苏省气象灾害重点实验室,江苏,南京,210044;南京信息工程大学,遥感学院,江苏,南京,210044;南京林业大学,森林资源与环境学院,江苏,南京,210037 2. 南京信息工程大学,江苏省气象灾害重点实验室,江苏,南京,210044;南京信息工程大学,遥感学院,江苏,南京,210044 3. 中国气象科学研究院,北京,100081 |
| 基金项目： | 江苏省气象灾害重点实验室基金，国家自然科学基金 |
| 摘 要： | 以CAPS（Center for Analysis and Prediction of Storm）研发的ARPS模式（The Advanced Regional Prediction 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3h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。 |
| 关 键 词： | 雷达资料同化 降水模拟 同化次数 |
A Rainstorm Simulation with Assimilated Doppler Radar Observations |
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| YANG Yan-rong,WANG Zhen-hui,ZHANG Pei-yuan.A Rainstorm Simulation with Assimilated Doppler Radar Observations[J].Journal of Nanjing Institute of Meteorology,2008,31(5):633-639. | |
| Authors: | YANG Yan-rong WANG Zhen-hui ZHANG Pei-yuan |
| Institution: | YANG Yan-rong, WANG Zhen-hui, ZHANG Pei-yuan (1. Jiangsu Key Laboratory of Meteorological Disaster,NUIST,Nanjing 210044,China; 2. School of Remote Sensing, NUIST, Nanjing 210044, China; 3. College of Forest Resources and Environment,NJFU,Nanjing 210037,China; 4. Chinese Academy of Meteorological Sciences,Beijing 100081 ,China) |
| Abstract: | The rainstorm in Anhui Province on July 13th,2001 is simulated by numerical model ARPS （Advanced regional prediction system） and its 3D-VAR （3-dimensional variational data assimilation） system developed by CAPS （Center for analysis and prediction of storm） and Doppler radar data in China. Assimilation experiments are carried on by adding Doppler radar data at 10 and 30 minutes intervals, respectively, with the former results as the followed one＇s initial fields adjusted continuously. It is found that the winds and water vapor fields are obviously improved after inducing Doppler radar data, especially the 3-h precipitation simulations. And more times radar data induced, better the forecast simulations. |
| Keywords: | radar data assimilation rainfall simulation assimilation times |
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