| FY-2E云导风的算法改进及其在GRAPES中的同化应用研究 |
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| 引用本文： | 万晓敏,田伟红,韩威,王瑞文,张其松,张晓虎.FY-2E云导风的算法改进及其在GRAPES中的同化应用研究[J].气象,2017,43(1):1-10. |
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| 作者姓名： | 万晓敏 田伟红 韩威 王瑞文 张其松 张晓虎 |
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| 作者单位： | 中国气象局数值预报中心，北京 100081,中国气象局数值预报中心，北京 100081,中国气象局数值预报中心，北京 100081,中国气象局数值预报中心，北京 100081,中国气象局数值预报中心，北京 100081,中国气象局数值预报中心，北京 100081 |
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| 基金项目： | GRAPES专项(GRAPES FZZX 2016 05)、公益性行业(气象)科研专项(GYHY201506002和GYHY201406012)共同资助 |
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| 摘 要： | 2014年国家卫星气象中心全面改进了风云二号卫星云导风产品算法,为评估算法改进后FY-2E云导风资料对我国GRAPES数值模式同化和预报的影响,根据国家卫星气象中心提供的2013年8月算法改进前后的FY-2E红外通道云导风资料,对比分析了两者的观测分布及偏差特征,并利用GRAPES全球模式进行了一个月的连续试验。结果表明,改进算法后的FY-2E红外通道云导风观测数量明显增加,观测误差在600~200 hPa有所减小,风的平均偏差在高层减少,更满足正态分布;连续试验结果表明北半球和东亚地区风场在300~150 hPa分析中改进显著,风的平均偏差和均方根误差明显减少;预报结果显示500 hPa高度场预报距平相关系数略提高,均方根误差略减小;说明改进算法后的FY-2E红外通道云导风对GRAPES数值模式同化和预报均有一定改善。
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| 关 键 词： | FY 2E红外云导风资料，GRAPES数值模式，资料同化，影响试验 |
| 收稿时间： | 2016/8/9 0:00:00 |
| 修稿时间： | 2016/11/2 0:00:00 |
The Evaluation of FY 2E Reprocessed IR AMVs in GRAPES |
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| WAN Xiaomin,TIAN Weihong,HAN Wei,WANG Ruiwen,ZHANG Qisong,ZHANG Xiaohu.The Evaluation of FY 2E Reprocessed IR AMVs in GRAPES[J].Meteorological Monthly,2017,43(1):1-10. |
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| Authors: | WAN Xiaomin TIAN Weihong HAN Wei WANG Ruiwen ZHANG Qisong ZHANG Xiaohu |
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| Institution: | CMA Numerical Prediction Centre, Beijing 100081,CMA Numerical Prediction Centre, Beijing 100081,CMA Numerical Prediction Centre, Beijing 100081,CMA Numerical Prediction Centre, Beijing 100081,CMA Numerical Prediction Centre, Beijing 100081 and CMA Numerical Prediction Centre, Beijing 100081 |
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| Abstract: | Atmospheric Motion Vectors (AMVs) can supply plenty of useful information for numerical weather prediction. With the improvement in the image navigation, data calibration and derivation algorithm, the quality of FY 2E is expected to be improved. Therefore, it is necessary to evaluate the improvement of FY 2E AMVs for the analysis field and precipitation forecast in GRAPES (Global/Regional Assimilation and Prediction System) of China. In this study, the old and the reprocessed FY 2E AMVs are used to analyze the characteristics of their horizontal and vertical structures and applied to GRAPES 3Dvar Global Assimilation Prediction System to compare their differences on the assimilation and prediction. The experiments using the data collected in August 2013 show some encouraging results, which show neutral to positive impact on wind analysis field, especially in high levels. Furthermore, due to the improvement of the initial fields for the model prediction, the performance of the anomaly correlation coefficient (ACC) and root mean square error (RMSE) slightly improved. Especially the observation error of the reprocessed FY 2E is lower than the old from 600 hPa to 200 hPa, which needs a further investigation. Conclusively, the reprocessed FY 2E AMVs have more positive impact on wind assimilation and forecast improvement in GRAPES. |
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