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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

游婷 张华 王海波 赵敏

游婷, 张华, 王海波, 等. 2020. 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[J]. 大气科学, 44(4): 835−850 doi:  10.3878/j.issn.1006-9895.1909.19160
引用本文: 游婷, 张华, 王海波, 等. 2020. 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[J]. 大气科学, 44(4): 835−850 doi:  10.3878/j.issn.1006-9895.1909.19160
YOU Ting, ZHANG Hua, WANG Haibo, et al. 2020. Distribution of Different Cloud Types and Their Effects on Near-Surface Air Temperature during Summer Daytime in Central Eastern China [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 44(4): 835−850 doi:  10.3878/j.issn.1006-9895.1909.19160
Citation: YOU Ting, ZHANG Hua, WANG Haibo, et al. 2020. Distribution of Different Cloud Types and Their Effects on Near-Surface Air Temperature during Summer Daytime in Central Eastern China [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 44(4): 835−850 doi:  10.3878/j.issn.1006-9895.1909.19160

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

doi: 10.3878/j.issn.1006-9895.1909.19160
基金项目: 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
详细信息
    作者简介:

    游婷,女,1995年出生,硕士研究生,主要从事云气候效应研究。E-mail: 657133756@qq.com

    通讯作者:

    张华,E-mail: huazhang@cma.gov.cn

  • 中图分类号: P401

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

Funds: National Key R&D Program of China (Grant 2017YFA0603502), National Natural Science Foundation of China (Grants 91644211, 41575002), Public Meteorology Special Foundation of MOST (Grant GYHY201406023)
  • 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°C、−2.7°C、−2.2°C和−1.7°C。其中,低云在华北平原降温可达−5°C;中低云和中高云在四川盆地和云贵高原降温可达−7.8°C。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。
  • 图  1  一维辐射对流模式(RCM)流程图(石广玉,1992

    Figure  1.  Flowchart for Radiative-Convective Model (RCM) (Shi, 1992)

    图  2  2001~2017年中国中东部夏季白天平均云量分布:(a)总云;(b)高云;(c)中高云;(d)中低云;(e)低云

    Figure  2.  The mean daytime cloud fraction in the summer over central eastern China during 2001–2017: (a) Total clouds; (b) high clouds; (c) upper-middle clouds; (d) lower-middle clouds; (e) low clouds

    图  3  2001~2017年中国中东部夏季白天平均云光学厚度分布:(a)总云;(b)高云;(c)中高云;(d)中低云;(e)低云

    Figure  3.  The mean daytime cloud optical thickness in summer over central eastern China during 2001–2017: (a) Total clouds; (b) high clouds; (c) upper-middle clouds; (d) lower-middle clouds; (e) low clouds

    图  4  2001~2017年中国中东部夏季白天平均云量年变化率分布(单位:a−1):(a)总云;(b)高云;(c)中高云;(d)中低云;(e)低云。黑点区域表示通过95%的显著性检验,下同

    Figure  4.  The annual variability distribution of mean daytime cloud fraction in summer over central eastern China during 2001–2017 (units: a−1): (a) Total clouds; (b) high clouds; (c) upper-middle clouds; (d) lower-middle clouds; (e) low clouds. The dots in the figures represent confidence levels greater than 95%, the same below

    图  6  2001~2017年中国中东部夏季白天不同类型云的云量和云光学厚度的年际变化:(a)总云量;(b)高云量;(c)中高云量;(d)中低云量;(e)低云量;(f)总云光学厚度;(g)高云光学厚度;(h)中高云光学厚度;(i)中低云光学厚度;(j)低云光学厚度

    Figure  6.  The interannual variations of the cloud fraction and cloud optical thickness of various cloud types during summer daytime over central eastern China in 2001–2017: (a) Total cloud fraction; (b) high cloud fraction; (c) upper-middle cloud fraction; (d) lower-middle cloud fraction; (e) low cloud optical thickness; (f) total cloud optical thickness; (g) high cloud optical thickness; (h) upper-middle cloud optical thickness; (i) lower-middle cloud optical thickness; (j) low cloud optical thickness

    图  5  2001~2017年中国中东部夏季白天平均云光学厚度年变化率分布(单位:a−1):(a)总云;(b)高云;(c)中高云;(d)中低云;(e)低云

    Figure  5.  The annual variability distribution of mean daytime cloud optical thickness in summer over central eastern China during 2001–2017 (units: a−1): (a) Total clouds; (b) high clouds; (c) upper-middle clouds; (d) lower-middle clouds; (e) low clouds

    图  7  2001~2017年中国中东部夏季白天平均总云量与近地表气温的相关性分布:(a)ERA5再分析资料;(b)RCM多层云模式输出结果

    Figure  7.  Correlation coefficient between the mean daytime total cloud fraction and near-surface air temperature in summer over central eastern China during 2001–2017: (a) ERA5 reanalysis data; (b) RCM model results

    图  8  2001~2017年中国中东部夏季白天平均地表云净辐射强迫的空间分布(单位:W m−2

    Figure  8.  Spatial distribution of the mean daytime cloud radiative forces at the surface in the summer over central eastern China during 2001–2017 (units: W m−2)

    图  9  2001~2017年中国中东部夏季白天平均总云量与近地表气温(ERA5再分析资料)距平的年际变化

    Figure  9.  The interannual variations of the mean daytime total cloud fraction anomalies and the near-surface air temperature anomalies derived from the ERA5 reanalysis data in the summer over central eastern China during 2001–2017

    图  10  2001~2017年中国中东部夏季白天平均地表云短波和净辐射强迫距平的年际变化(黑线为RCM结果,红线为CERES_SYN1deg_Ed4A数据结果,**表示通过95%的显著性检验,下同)

    Figure  10.  The interannual variations of the mean daytime shortwave cloud radiative forcing (SWCRF) anomalies and net cloud radiative forcing (NCRF) anomalies in the summer over central eastern China during 2001–2017 (The black line is RCM model result, the red line is CERES_SYN1deg_Ed4A data, and ** represent confidence levels greater than 95%, the same below)

    图  11  2001~2017年中国中东部夏季白天平均云温度效应(CET)的空间分布(单位:°C):(a)总云;(b)高云;(c)中高云;(d)中低云;(e)低云

    Figure  11.  Spatial distribution of the mean cloud effect temperature (CET) in the summer daytime over central eastern China during 2001–2017 (units: °C): (a) Total cloud; (b) high cloud; (c) upper-middle cloud; (d) lower-middle cloud; (e) low cloud

    图  12  2001~2017年中国中东部夏季白天CET和近地表气温(ERA5再分析资料)的年际变化:(a)总云;(b)高云;(c)中高云;(d)中低云;(e)低云;(f)近地表气温(NSAT)

    Figure  12.  The interannual variations of CET and the near-surface air temperature (NSAT) derived from the ERA5 reanalysis data): (a) CET of total cloud; (b) CET of high cloud; (c) CET of upper-middle cloud; (d) CET of lower-middle cloud; (e) CET of low cloud; (f) near-surface air temperature

    表  1  云对近地表气温影响试验设计

    Table  1.   Experiments on the influence of clouds on the near-surface air temperature

    试验序号研究内容模式设置云高
    试验1不同类型云对近地表气温的影响单层云模式低云(850.9~1013.0 hPa)
    试验2总云对近地表气温的影响多层云模式中低云(590.1hPa~710.0 hPa)中高云(398.2~487.0 hPa)高云(165.6~209.0 hPa)
    下载: 导出CSV
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出版历程
  • 收稿日期:  2019-05-07
  • 网络出版日期:  2019-10-31
  • 刊出日期:  2020-07-25

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