| 基于多源卫星资料的中国地区云宏微观特征研究 |
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| 引用本文： | 黄乾,殷馨玉,王子欣,姚素香.基于多源卫星资料的中国地区云宏微观特征研究[J].气象科学,2023,43(2):143-154. |
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| 作者姓名： | 黄乾 殷馨玉 王子欣 姚素香 |
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| 作者单位： | 南京信息工程大学 中国气象局气溶胶与云降水重点开放实验室/气象灾害预报预警与评估协同创新中心, 南京 210044 |
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| 基金项目： | 国家重点研发计划项目（2019YFC0214604）；国家自然科学基金资助项目（42030612；41775096） |
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| 摘 要： | 利用2007—2016年国际卫星云气候计划（International Satellite Cloud Climatology Project，ISCCP）、云和地球辐射能量系统（Clouds and the Earth''s Radiant Energy System，CERES）和中分辨率成像光谱仪（Moderate Resolution Imaging Spectroradiometer，MODIS）卫星反演云产品，对比分析了不同数据反演的中国地区云系结构的宏微观特征，并采用复合评价指标定量评估了不同数据之间时间和空间上的一致性。结果表明：三套卫星数据都能较好地反演出中国地区总云量呈南高北低、东高西低、夏高冬低的分布特征，但通过比较时间技巧（Temporal Skill，ST）及空间技巧（Spatial Skill，SS）复合评价指标及其各项分量发现，与MODIS相比，CERES与ISCCP数据反演的总云量时间序列演变特征明显更为一致，且其评分均有南方优于北方，夏季优于冬季的特征；进一步分析不同高度云量的ST评分发现，CERES和ISCCP两套数据在南方地区的总云量差异主要来自于低云量的绝对偏差，而北方地区的偏差则同时存在于低云和中云；对比分析MODIS和CERES反演的云滴有效半径发现，高云对应的冰相云一致性较高，而中低云相对应的液相云的偏差则有夏季高于冬季的规律。针对夏季液相和冰相云滴粒径及概率密度分析则表明，相比CERES数据，MODIS对夏季液水和冰水粒子的有效半径在不同地区均有不同程度的高估，液（冰）水谱宽则更宽（窄）。
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| 关 键 词： | 卫星数据 云垂直结构 总云量 复合评价指标 |
| 收稿时间： | 2021/8/30 0:00:00 |
| 修稿时间： | 2022/1/30 0:00:00 |
Study on cloud macro and micro characteristics in China based on multi-source satellite data |
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| HUANG Qian,YIN Xinyu,WANG Zixin,YAO Suxiang.Study on cloud macro and micro characteristics in China based on multi-source satellite data[J].Scientia Meteorologica Sinica,2023,43(2):143-154. |
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| Authors: | HUANG Qian YIN Xinyu WANG Zixin YAO Suxiang |
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| Institution: | Key Laboratory of Meteorological Disaster(NUIST), Ministry of Education/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science & Technology, Nanjing 210044, China |
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| Abstract: | Based on ISCCP(International Satellite Cloud Climatology Project), CERES(Clouds and the Eart''s Radiant Energy System), MODIS(Moderate-resolution Imaging Spectroradiometer) satellite inversion cloud products from 2007 to 2016, a comparative analysis of the macro and micro characteristics of the cloud structure in China in the past decade was made. The composite evaluation index is used to quantitatively evaluate the temporal and spatial consistency between these data sets. The results show that the three sets of satellite data can better reflect the distribution characteristics of the total cloud cover in China, which is high in the south(east) and low in the north(west), and high in summer and low in winter. However, by comparing temporal skill (ST) and spatial skill (SS) of the composite evaluation index and its components, it was found that the evolution characteristics of the total cloud cover time series retrieved by CERES and ISCCP data are significantly more consistent than MODIS. The spatial and temporal characteristics of the south is better than the north, and the summer is better than the winter. Further analysis of the ST scores of different heights of cloud cover found that the difference in total cloud cover of CERES and ISCCP data in the southern region is mainly due to the absolute deviation of low cloud cover, while the bias in the northern region exists in both low and medium cloud. The comparative analysis of the effective radius of the cloud drop retrieved by MODIS and CERES found that the ice phase cloud corresponding to the high cloud has a higher consistency, while the deviation of the liquid phase cloud corresponding to the middle and low cloud is much higher in summer than in winter. The analysis of cloud droplet size and probability density of liquid and ice phase in summer shows that compared with CERES data, the effective radius of cloud droplet size of different phases retrieved by MODIS has different degrees of overestimation in different regions, while the liquid (ice) water spectrum width is wider (narrower). |
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| Keywords: | satellite data cloud vertical structure total cloud cover composite evaluation index |
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