| 云海-2掩星资料在区域数值预报中的同化应用评估 |
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| 引用本文： | 蔡其发,王业桂,张斌,李娟,兰伟仁,王广杰.云海-2掩星资料在区域数值预报中的同化应用评估[J].大气科学,2021,45(1):217-228. |
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| 作者姓名： | 蔡其发 王业桂 张斌 李娟 兰伟仁 王广杰 |
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| 作者单位： | 61741部队，北京 100094 |
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| 基金项目： | 国家自然科学基金项目41375105 |
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| 摘 要： | 针对中国自主的云海-2掩星资料，基于WRF模式和GSI三维变分同化系统，以2019年5月首次开展了区域同化预报试验，试验结果表明:同化云海-2掩星资料后，风场、温度场的改善主要体现在预报的中后期，而湿度场的改善则贯穿于整个预报时间段，风场、温度场和湿度场的改善程度随着预报时间延长趋于一致；风场和温度场的改善主要体现在模式中层，而水汽混合比的改善则主要体现在模式的中低层；同化云海-2掩星资料能够合理的调整模式的位势高度场、湿度场、温度场和风场，进而改善降水预报结果。
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| 关 键 词： | 云海-2掩星资料 三维变分 预报 均方根误差 降水 增量 |
| 收稿时间： | 2020-04-02 |
Evaluation on Assimilation Application of Yunhai-2 Occultation Data in Regional Numerical Weather Prediction Model |
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| CAI Qifa,WANG Yegui,ZHANG Bin,LI Juan,LAN Weiren,WANG Guangjie.Evaluation on Assimilation Application of Yunhai-2 Occultation Data in Regional Numerical Weather Prediction Model[J].Chinese Journal of Atmospheric Sciences,2021,45(1):217-228. |
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| Authors: | CAI Qifa WANG Yegui ZHANG Bin LI Juan LAN Weiren WANG Guangjie |
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| Institution: | Unit 61741, PLA, Beijing 100094 |
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| Abstract: | Based on the WRF (Weather Research and Forecasting) model and GSI (Gridpoint Statistical Interpolation analysis system) three-dimensional variational assimilation system, regional assimilation and prediction experiments for China’s autonomic Yunhai-2 occultation data were performed for the first time in May 2019. The results of the experiments demonstrated that after assimilating Yunhai-2 occultation data, the improvement for the wind and temperature fields is mainly reflected in the middle and later stages of the forecast, while the improvement for the humidity field is witnessed through the entire forecast period. The results also showed that the improvement degree of the wind, temperature, and humidity fields tends to be consistent with the extension of forecast time. It was found that the improvement for the wind and temperature fields is mainly reflected in the middle layer of the model, while the improvement for the water vapor mixing ratio is mainly reflected in the middle and lower layers of the model. Thus, assimilating Yunhai-2 occultation data can reasonably adjust the potential height, humidity, temperature, and wind fields in the model, thereby improving the precipitation forecast results. |
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