| 探空资料云检测及其统计研究 |
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| 引用本文： | 李绍辉,孙学金,张日伟,赵阳.探空资料云检测及其统计研究[J].气象科学,2017,37(3):403-408. |
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| 作者姓名： | 李绍辉 孙学金 张日伟 赵阳 |
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| 作者单位： | 解放军理工大学 气象海洋学院, 南京 211101,解放军理工大学 气象海洋学院, 南京 211101,解放军理工大学 气象海洋学院, 南京 211101,解放军理工大学 气象海洋学院, 南京 211101 |
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| 基金项目： | 国家自然科学基金资助项目（41575020） |
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| 摘 要： | 基于已知的云垂直结构判断的方法,将相对湿度阈值法与温度露点法相结合,并加以改进,得到更加科学有效的云垂直结构判断方法。利用南京地区探空站的探空资料数据,分析得到了该地区的云垂直结构参数,并对全年云垂直结构特征进行了统计分析。经过统计分析发现:这种改进的相对湿度阈值法是科学有效的;南京地区夏秋季节有云的概率大,多层云的状况较多;春冬季节有云的概率相对较小,单层云的状况较多;云层厚度呈现出"夏厚冬薄"、中低云厚而高云薄的规律。
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| 关 键 词： | 云垂直结构 探空资料 相对湿度 温度露点差 |
| 收稿时间： | 2015/10/30 0:00:00 |
| 修稿时间： | 2016/3/22 0:00:00 |
Cloud determination of radiosonde data and its statistical study |
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| LI Shaohui,SUN Xuejin,ZHANG Riwei and ZHAO Yang.Cloud determination of radiosonde data and its statistical study[J].Scientia Meteorologica Sinica,2017,37(3):403-408. |
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| Authors: | LI Shaohui SUN Xuejin ZHANG Riwei and ZHAO Yang |
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| Institution: | School of Meteorology and Oceanography, PLA University of Science and Technology, Nanjing 211101, China,School of Meteorology and Oceanography, PLA University of Science and Technology, Nanjing 211101, China,School of Meteorology and Oceanography, PLA University of Science and Technology, Nanjing 211101, China and School of Meteorology and Oceanography, PLA University of Science and Technology, Nanjing 211101, China |
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| Abstract: | Based on the known cloud vertical structure judgment method, combined with the relative humidity threshold method and the temperature dew point method, a more scientific and effective method was obtained. Moreover, the radiosonde data in Nanjing was used to collect the cloud vertical structure parameter of Nanjing, in order to statistically analyze the cloud vertical structure features. It was found that this new method is feasible; cloud occurs more frequently in summer and autumn in Nanjing than in spring and winter, especially for the multilayer cloud; and the cloud thickness is thicker in summer than in winter and decreases with the cloud height. |
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| Keywords: | Cloud vertical structure Radiosonde data Relative humidity Temperature dewpoint method |
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