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夏季白天中国中东部不同类型云分布特征及其对近地表气温的影响
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国家重点研发计划项目2017YFA0603502,国家自然科学基金项目91644211、41575002,科技部公益性行业(气象)科研专项GYHY201406023


Distribution of Different Cloud Types and Their Effects on Near-Surface Air Temperature during Summer Daytime in Central Eastern China
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    摘要:

    本文利用2001~2017年ERA5再分析资料以及CERES卫星资料,探究夏季白天中国中东部不同类型云的云量及其光学厚度的时空变化特征,并利用一维辐射对流模式定量分析不同类型云对近地表气温的影响。观测结果表明:夏季白天中国中东部总云量及其光学厚度整体呈由南向北逐渐减小的分布特征,且中高云量占主导地位。总云量整体呈−0.3% a−1显著减少趋势,其中低云的贡献(−0.27% a−1)最大;总云光学厚度为0~0.1 a−1增加趋势,其中低云光学厚度(0.06 a−1)和中低云光学厚度(0.03 a−1)呈增加趋势,而中高云光学厚度(−0.08 a−1)和高云光学厚度(−0.03 a−1)呈减少趋势。模式结果表明:四种不同类型云的温度效应(Cloud Effect Temperature, CET)均为负值,表现为降温效应。低云、中低云、中高云和高云的年均CET值分别为−2.9℃、−2.7℃、−2.2℃和−1.7℃。其中,低云在华北平原降温可达−5℃;中低云和中高云在四川盆地和云贵高原降温可达−7.8℃。不同类型云温度效应与近地表气温的年际变化具有较好的一致性,具体表现为:2004年前(后)近地表气温呈现下降(上升)趋势,不同类型云的CET在此期间呈下降(上升)趋势,表现为云的降温效应增强(减弱)与近地表气温下降(上升)相对应,体现了夏季白天中国中东部4种不同类型云温度效应与近地表气温都呈正相关关系。特别地,夏季白天中国中东部中高云量占主导地位,其CET与近地表气温的相关系数高达0.63。综上,夏季白天中国中东部不同类型云温度效应对近地表气温的影响不同,但均呈正相关关系。定量分析不同类型云对近地表气温的影响可以为定量研究云反馈对区域增暖的作用以及合理预估未来区域增暖情景提供必要的科学参考。

    Abstract:

    The spatial–temporal variation characteristics of the daytime cloud fraction and cloud optical thickness of various cloud types over central eastern China in summer are explored using ERA5 reanalysis data and CERES satellite data during the period of 2001–2017. The effects of various cloud types on the near-surface air temperature are quantitatively analyzed using a radiative–convective model. The observations show that the annual mean daytime total cloud fraction and its optical thickness decrease gradually from south to north, while the upper-middle cloud fraction dominates the total cloud fraction. For annual mean changing rates, the total cloud fraction shows a significant decrease of 0.3% a-1 with the largest contribution from low clouds (-0.27% a-1). The increasing trend of total cloud optical thickness ranges from 0 to 0.1 a-1, where low and lower-middle cloud optical thickness show an increase of 0.06 a-1 and 0.03 a-1, respectively, while the upper-middle and high cloud optical thickness show a decreasing trend of 0.08 a-1 and 0.03 a-1, respectively. The model results show that the annual mean CET (Cloud Effect Temperature) of the four different cloud types are negative, with values of 2.9℃, 2.7℃, 2.2℃, and 1.7℃ for low, lower-middle, upper-middle, and high clouds, respectively, indicating the cooling effects of various cloud types. The low cloud CET in the North China Plain is up to -5℃, while the lower-middle and upper-middle clouds are up to -7.8℃ in the Sichuan Basin and Yunnan–Guizhou Plateau. The interannual variations of CETof different cloud types and near-surface air temperature have good consistency. The near-surface air temperature decreases (increases) before (after) 2004, while the CET of different cloud types decrease (increase) during this period, which indicates good correspondence between the strengthening (weakening) of the cloud cooling effect and the decrease (increase) of the near-surface temperature. Specifically, a positive correlation of the four cloud types and near-surface air temperature over central eastern China occurs during the daytime in the summer. The annual mean daytime upper-middle cloud fraction plays an important role in all types of clouds over central eastern China in the summer, and the correlation coefficient between the CET and near-surface air temperature is as high as 0.63. In summary, the effects of different cloud types on the near-surface air temperature are different, but all show positive correlations. The quantitative analysis of the influence of different cloud types on the near-surface air temperature can provide a scientific reference for the accurate measurement of global warming, the role of cloud feedback in regional warming, and accurate prediction of regional warming scenarios.

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游婷,张华,王海波,赵敏.夏季白天中国中东部不同类型云分布特征及其对近地表气温的影响.大气科学,2020,44(4):835~850 YOU Ting, ZHANG Hua, WANG Haibo, ZHAO Min. Distribution of Different Cloud Types and Their Effects on Near-Surface Air Temperature during Summer Daytime in Central Eastern China. Chinese Journal of Atmospheric Sciences (in Chinese),2020,44(4):835~850

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  • 收稿日期:2019-05-07
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  • 在线发布日期: 2020-07-28
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