| Comparative Experiments on the Effect of Radar Data Assimilation and Increasing Horizontal Resolution on Short-term Numerical Weather Prediction |
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| 作者姓名： | SHENG Chunyan XUE Deqiang LEI Ting GAO Shouting |
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| 作者单位： | Laboratory of Cloud-Precipitation Physics and Severe Storms Institute of Atmospheric Physics，Chinese Academy of Sciences，Shandong Meteorological Observatory，Laboratory of Cloud-Precipitation Physics and Severe Storms，Institute of Atmospheric Physics，Chinese Academy of Sciences，Laboratory of Cloud-Precipitation Physics and Severe Storms，Institute of Atmospheric Physics，Chinese Academy of Sciences，Beijing 100029 Shandong Meteorological Observatory Jinan 250031 Graduate University of Chinese Academy of Sciences Beijing 100049，Jinan 250031，Beijing 100029，Beijing 100029 |
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| 摘 要： | To examine the effect of radar data assimilation and increasing horizontal resolution on the short-term numerical weather prediction, comparative numerical experiments are conducted for a Huabei (North China) torrential rainfall event by using the Advanced Regional Prediction System (ARPS) and ARPS Data Analysis System (ADAS). The experiments use five different horizontal grid spacings, i.e., 18, 15, 9, 6, and 3 km,respectively, under the two different types of analyses: one with radar data, the other without. Results show that, when radar data are not used in the analysis (i.e., only using the conventional observation data), increasing horizontal resolution can improve the short-term prediction of 6 h with better representation of the frontal structure and higher scores of the rainfall prediction, particularly for heavy rain situations. When radar data are assimilated, it significantly improves the rainfall prediction for the first 6 h, especially the locality and intensity of precipitation. Moreover, using radar data in the analysis is more effective in improving the short-term prediction than increasing horizontal resolution of the model alone, which is demonstrated by the fact that by using radar data in the analysis and a coarser resolution of the 18-km grid spacing, the predicted results are as good as that by using a higher resolution of the 3-km grid spacing without radar data. Further study of the results under the radar data assimilation with grid spacing of 18-3 km reveals that the rainfall prediction is more sensitive to the grid spacing in heavy rain situations (more than 40 mm) than in ordinary rain situations (less than 40 mm). When the horizontal grid spacing reduces from 6 to 3 km, there is no obvious improvement to the prediction results. This suggests that there is a limit to how far increasing horizontal resolution can do for the improvement of the prediction. Therefore, an effective approach to improve the short-term numerical prediction is to combine the radar data assimilation with an optimal horizontal resolution.
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| 关 键 词： | 雷达数据同化 水平分辨率 短期预报 数值天气预报 比较实验 |
| 收稿时间： | 1/8/2007 12:00:00 AM |
Comparative Experiments on the Effect of Radar Data Assimilation and Increasing Horizontal Resolution on Short-term Numerical Weather Prediction |
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| SHENG Chunyan,XUE Deqiang,LEI Ting,GAO Shouting.Comparative Experiments on the Effect of Radar Data Assimilation and Increasing Horizontal Resolution on Short-term Numerical Weather Prediction[J].Acta Meteorologica Sinica,2007,21(1):47-63. |
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| Authors: | SHENG Chunyan XUE Deqiang LEI Ting and GAO Shouting Laboratory of Cloud-Precipitation Physics and Severe Storms |
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| Institution: | [1]Laboratory of Cloud-Precipitation Physics and Severe Storms, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029 [2]Shandong Meteorological Observatory, Jinan 250031 [3]Graduate University of Chinese Academy of Sciences, Beijing 100049 |
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| Abstract: | To examine the effect of radar data assimilation and increasing horizontal resolution on the short-term numerical weather prediction, comparative numerical experiments are conducted for a Huabei (North China) torrential rainfall event by using the Advanced Regional Prediction System (ARPS) and ARPS Data Analysis System (ADAS). The experiments use five different horizontal grid spacings, i.e., 18, 15, 9, 6, and 3 km,respectively, under the two different types of analyses: one with radar data, the other without. Results show that, when radar data are not used in the analysis (i.e., only using the conventional observation data), increasing horizontal resolution can improve the short-term prediction of 6 h with better representation of the frontal structure and higher scores of the rainfall prediction, particularly for heavy rain situations. When radar data are assimilated, it significantly improves the rainfall prediction for the first 6 h, especially the locality and intensity of precipitation. Moreover, using radar data in the analysis is more effective in improving the short-term prediction than increasing horizontal resolution of the model alone, which is demonstrated by the fact that by using radar data in the analysis and a coarser resolution of the 18-km grid spacing, the predicted results are as good as that by using a higher resolution of the 3-km grid spacing without radar data. Further study of the results under the radar data assimilation with grid spacing of 18-3 km reveals that the rainfall prediction is more sensitive to the grid spacing in heavy rain situations (more than 40 mm) than in ordinary rain situations (less than 40 mm). When the horizontal grid spacing reduces from 6 to 3 km, there is no obvious improvement to the prediction results. This suggests that there is a limit to how far increasing horizontal resolution can do for the improvement of the prediction. Therefore, an effective approach to improve the short-term numerical prediction is to combine the radar data assimilation with an optimal horizontal resolution. |
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| Keywords: | radar data assimilation increasing horizontal resolution comparative experiments short-term prediction |
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