基于卫星数据的2012~2022年中国近海低云物理特性的时空特征
Spatiotemporal Analysis of Low Cloud Physical Properties over China’s Coastal Seas Based on Satellite Data (2012~2022)
DOI: 10.12677/ccrl.2026.152029, PDF,    国家自然科学基金支持
作者: 张元振, 衣 立*：中国海洋大学山东省透明北极重点实验室，山东 青岛；中国海洋大学海洋与大气学院，山东 青岛
关键词: 低云；云滴有效半径；云水路径；云光学厚度；中国近海；Low Cloud； Cloud Effective Radius； Cloud Water Path； Cloud Optical Thickness； China’s Coastal Sea
摘要: 本文基于MODIS和CALIPSO卫星遥感资料，分析了2012~2022年中国近海日间低云(云顶高度低于2 km)的分布特征及其物理特性(云滴有效半径、云水路径以及光学厚度)的时空特征。结果显示：(1) 统计特征上，云滴有效半径平均值为10.96 μm，云水路径平均值为74.48 g·m−2，云光学厚度COT平均值为11.3，相比于西北太平洋远海的低云较小。(2) 空间上，中国近海低云云频最大值出现在南海北部的近岸海区，在渤海海区最低。云滴有效半径在近岸海域较小，向远海递增。云光学厚度高值区集中于近岸，对应云滴有效半径的低值区。(3) 季节上，低云云频表现为冬季高，夏季低的特征。云滴有效半径夏季最大，云水路径与光学厚度冬季最高。(4) 年际变化上，大部分海区低云云频在2012~2022年间有减少趋势，云滴有效半径和云水路径有增大趋势，低云的光学厚度在近岸海区表现为降低趋势。
Abstract: This study investigates daytime low cloud (cloud top height < 2 km) over China’s coastal seas from 2012 to 2022, utilizing MODIS and CALIPSO data. We analyse the spatial distribution, seasonal cycle, and interannual variability of low cloud frequency and physical parameters—including cloud effective radius (CER), cloud water path (CWP), and optical thickness (COT). Results indicate that: (1) Statistically, the mean values of CER, CWP, and COT are 10.96 μm, 74.48  g·m−2, and 11.3, respectively. These values are generally lower than those reported for low clouds over the open Northwest Pacific. (2) Spatially, the highest frequency of low clouds occurs over the nearshore areas of the northern South China Sea, while the lowest frequency is found in the Bohai Sea. The CER is smaller in coastal waters and increases toward the distant sea. Regions with high COT are concentrated along the coast, corresponding to areas of smaller CER. (3) Seasonally, low cloud frequency is higher in winter and lower in summer. CER peaks in summer, whereas both CWP and COT reach their maxima in winter. (4) Interannually, from 2012 to 2022, low cloud frequency exhibited a decreasing trend over most sea areas, while CER and CWP generally increased. In contrast, COT showed a declining trend in coastal regions.
文章引用：张元振, 衣立. 基于卫星数据的2012~2022年中国近海低云物理特性的时空特征[J]. 气候变化研究快报, 2026, 15(2): 237-250. https://doi.org/10.12677/ccrl.2026.152029

参考文献

[1] Fouquart, Y., Buriez, J.C., Herman, M. and Kandel, R.S. (1990) The Influence of Clouds on Radiation: A Climate‐modeling Perspective. Reviews of Geophysics, 28, 145-166. [Google Scholar] [CrossRef] 
[2] 汪宏七, 赵高祥. 云和辐射——(I)云气候学和云的辐射作用[J]. 大气科学, 1994(S1): 910-921.
[3] Wielicki, B.A., Harrison, E.F., Cess, R.D., King, M.D. and Randall, D.A. (1995) Mission to Planet Earth: Role of Clouds and Radiation in Climate. Bulletin of the American Meteorological Society, 76, 2125-2153. [Google Scholar] [CrossRef] 
[4] Allan, R.P. (2011) Combining Satellite Data and Models to Estimate Cloud Radiative Effect at the Surface and in the Atmosphere. Meteorological Applications, 18, 324-333. [Google Scholar] [CrossRef] 
[5] Tao, W., Lang, S., Simpson, J., Sui, C., Ferrier, B. and Chou, M. (1996) Mechanisms of Cloud-Radiation Interaction in the Tropics and Midlatitudes. Journal of the Atmospheric Sciences, 53, 2624-2651. [Google Scholar] [CrossRef] 
[6] 刘屹岷, 燕亚菲, 吕建华, 刘肖林. 基于CloudSat/CALIPSO卫星资料的青藏高原云辐射及降水的研究进展[J]. 大气科学, 2018, 42(4): 847-858.
[7] Zelinka, M.D., Klein, S.A., Taylor, K.E., Andrews, T., Webb, M.J., Gregory, J.M., et al. (2013) Contributions of Different Cloud Types to Feedbacks and Rapid Adjustments in CMIP5. Journal of Climate, 26, 5007-5027. [Google Scholar] [CrossRef] 
[8] Chen, Y., Christensen, M.W., Stephens, G.L. and Seinfeld, J.H. (2014) Satellite-Based Estimate of Global Aerosol-Cloud Radiative Forcing by Marine Warm Clouds. Nature Geoscience, 7, 643-646. [Google Scholar] [CrossRef] 
[9] Zhou, C., Zelinka, M.D., Dessler, A.E. and Klein, S.A. (2015) The Relationship between Interannual and Long‐Term Cloud Feedbacks. Geophysical Research Letters, 42, 10463-10469. [Google Scholar] [CrossRef] 
[10] Mace, G.G., Benson, S. and Kato, S. (2006) Cloud Radiative Forcing at the Atmospheric Radiation Measurement Program Climate Research Facility: 2. Vertical Redistribution of Radiant Energy by Clouds. Journal of Geophysical Research: Atmospheres, 111, D11S91. [Google Scholar] [CrossRef] 
[11] Twomey, S. (1974) Pollution and the Planetary Albedo. Atmospheric Environment (1967), 8, 1251-1256. [Google Scholar] [CrossRef] 
[12] 刘玉芝, 石广玉, 赵剑琦. 一维辐射对流模式对云辐射强迫的数值模拟研究[J]. 大气科学, 2007, 31(3): 486-494.
[13] Hartmann, D.L., Ockert-Bell, M.E. and Michelsen, M.L. (1992) The Effect of Cloud Type on Earth’s Energy Balance: Global Analysis. Journal of Climate, 5, 1281-1304. [Google Scholar] [CrossRef] 
[14] Slingo, A. (1990) Sensitivity of the Earth’s Radiation Budget to Changes in Low Clouds. Nature, 343, 49-51. [Google Scholar] [CrossRef] 
[15] Twomey, S. (1977) The Influence of Pollution on the Shortwave Albedo of Clouds. Journal of the Atmospheric Sciences, 34, 1149-1152. [Google Scholar] [CrossRef] 
[16] Brient, F. and Bony, S. (2012) Interpretation of the Positive Low-Cloud Feedback Predicted by a Climate Model under Global Warming. Climate Dynamics, 40, 2415-2431. [Google Scholar] [CrossRef] 
[17] Storelvmo, T., Tan, I. and Korolev, A.V. (2015) Cloud Phase Changes Induced by CO2 Warming—A Powerful Yet Poorly Constrained Cloud-Climate Feedback. Current Climate Change Reports, 1, 288-296. [Google Scholar] [CrossRef] 
[18] 丁守国，石广玉，赵春生. 利用ISCCP D2资料分析近20年全球不同云类云量的变化及其对气候可能的影响[J]. 科学通报, 2004(11): 1105-1111.
[19] Zelinka, M.D., Myers, T.A., McCoy, D.T., Po‐Chedley, S., Caldwell, P.M., Ceppi, P., et al. (2020) Causes of Higher Climate Sensitivity in CMIP6 Models. Geophysical Research Letters, 47, e2019GL085782. [Google Scholar] [CrossRef] 
[20] 孙鸿娉, 李培仁, 闫世明, 晋立军, 申东东, 封秋娟, 李义宇. 山西省2008-2010年64架次飞机云物理观测结果分析[J]. 气象科技, 2014, 42(4): 682-689.
[21] Miao, H., Wang, X., Liu, Y. and Wu, G. (2021) Characterization of Cloud Microphysical Properties in Different Cloud Types over East Asia Based on CloudSat/CALIPSO Satellite Products. Atmospheric and Oceanic Science Letters, 14, Article ID: 100050. [Google Scholar] [CrossRef] 
[22] 窦芳丽, 商建, 吴琼, 谷松岩. 风云三号卫星被动微波反演海洋上空云液态水含量[J]. 遥感学报, 2021, 24(6): 766-775.
[23] Tao, Y., Cao, J., Lan, G. and Su, Q. (2015) The Zonal Movement of the Indian-East Asian Summer Monsoon Interface in Relation to the Land-Sea Thermal Contrast Anomaly over East Asia. Climate Dynamics, 46, 2759-2771. [Google Scholar] [CrossRef] 
[24] Cai, H., Feng, X., Chen, Q., Sun, Y., Wu, Z. and Tie, X. (2017) Spatial and Temporal Features of the Frequency of Cloud Occurrence over China Based on CALIOP. Advances in Meteorology, 2017, Article ID: 4548357. [Google Scholar] [CrossRef] 
[25] 贾海灵, 马晓燕, 熊飞麟. 中国东部大陆和邻近海域暖云特性时空分布及其与气象条件的关系[J]. 气候与环境研究, 2018, 23(6): 737-748.
[26] 司钰文, 郑宁, 杨洪海, 陈勇航, 刘琼, 夏俊荣, 张华. 东亚单层低云特性及其短波辐射强迫的季节变化[J]. 干旱区研究, 2020, 37(1): 37-45.
[27] 龙景超, 冯梓雅, 王云. 南海低层季风环流对低云时空分布的影响[J]. 海洋湖沼通报, 2021, 43(4): 23-30.
[28] Dye, A.W., Rastogi, B., Clemesha, R.E.S., Kim, J.B., Samelson, R.M., Still, C.J., et al. (2020) Spatial Patterns and Trends of Summertime Low Cloudiness for the Pacific Northwest, 1996-2017. Geophysical Research Letters, 47, e2020GL088121. [Google Scholar] [CrossRef] [PubMed]
[29] 张苏平, 鲍献文. 近十年中国海雾研究进展[J]. 中国海洋大学学报: 自然科学版, 2008, 38(3): 359-366.
[30] 王亚男, 李永平. 冷空气影响下的黄东海海雾特征分析[J]. 热带气象学报, 2009(2): 216-221.
[31] Liu, J., Xie, S., Yang, S. and Zhang, S. (2016) Low-Cloud Transitions across the Kuroshio Front in the East China Sea. Journal of Climate, 29, 4429-4443. [Google Scholar] [CrossRef] 
[32] Winker, D.M., Pelon, J., Coakley, J.A., Ackerman, S.A., Charlson, R.J., Colarco, P.R., et al. (2010) The CALIPSO Mission: A Global 3D View of Aerosols and Clouds. Bulletin of the American Meteorological Society, 91, 1211-1230. [Google Scholar] [CrossRef] 
[33] Wu, D., Lu, B., Zhang, T. and Yan, F. (2015) A Method of Detecting Sea Fogs Using CALIOP Data and Its Application to Improve MODIS-Based Sea Fog Detection. Journal of Quantitative Spectroscopy and Radiative Transfer, 153, 88-94. [Google Scholar] [CrossRef] 
[34] World Meteorological Organization (1975) International Cloud Atlas, Volume I: Manual on the Observation of Clouds and Other Meteors (WMO-No. 407).
[35] King, M.D., Tsay, S.C., Platnick, S.E., Wang, M. and Liou, K.N. (1997) Cloud Retrieval Algorithms for MODIS: Op-tical Thickness, Effective Particle Radius, and Thermodynamic Phase. MODIS Algorithm Theoretical Basis Document, 440.
[36] 黎梦雅, 时晓曚, 吴晓京, 衣立. 基于卷积神经网络的西北太平洋夜间海雾/低云卫星检测方法研究[J]. 海洋气象学报, 2023, 43(1): 1-11.
[37] Cho, H., Zhang, Z., Meyer, K., Lebsock, M., Platnick, S., Ackerman, A.S., et al. (2015) Frequency and Causes of Failed MODIS Cloud Property Retrievals for Liquid Phase Clouds over Global Oceans. Journal of Geophysical Research: Atmospheres, 120, 4132-4154. [Google Scholar] [CrossRef] [PubMed]
[38] Zhao, M., Zhang, H., Wang, H., Zhou, X., Zhu, L., An, Q., et al. (2020) The Change of Cloud Top Height over East Asia during 2000-2018. Advances in Climate Change Research, 11, 110-117. [Google Scholar] [CrossRef] 
[39] Kawamoto, K. and Suzuki, K. (2013) Comparison of Water Cloud Microphysics over Mid-Latitude Land and Ocean Using Cloudsat and MODIS Observations. Journal of Quantitative Spectroscopy and Radiative Transfer, 122, 13-24. [Google Scholar] [CrossRef] 
[40] 杨爽, 刘敬武, 张苏平. 低云在不同季节对东海黑潮海洋锋响应的个例研究[J]. 中国海洋大学学报: 自然科学版, 2015(10): 7-17.
[41] 孟宪贵, 张苏平. 夏季黄海表面冷水对大气边界层及海雾的影响[J]. 中国海洋大学学报(自然科学版), 2012, 42(6): 16-23.
[42] Hu, Y.X. and Stamnes, K. (1993) An Accurate Parameterization of the Radiative Properties of Water Clouds Suitable for Use in Climate Models. Journal of Climate, 6, 728-742. [Google Scholar] [CrossRef] 
[43] 杨大生, 王普才. 中国地区夏季云粒子尺寸的时空分布特征[J]. 气候与环境研究, 2012, 17(4): 11.
[44] Sun, L., Cui, W., Ma, N., Hong, J., Zhu, Y., Gao, Y., et al. (2024) Variations in Cloud Concentration Nuclei Related to Continental Air Pollution Control and Maritime Fuel Regulation over the Northwest Pacific Ocean. Atmosphere, 15, Article No. 972. [Google Scholar] [CrossRef] 

为你推荐