Abstract. Quantifying global cloud condensation nuclei (CCN) concentrations is crucial for reducing uncertainties in radiative forcing resulting from aerosol-cloud interactions. This study analyzes two novel, independent, open-source global CCN datasets derived from spaceborne Cloud Aerosol Lidar with Orthogonal Polarization (CALIOP) measurements and Copernicus Atmosphere Monitoring Service (CAMS) reanalysis and examines the spatio-temporal variability of CCN concentrations pertinent to liquid clouds. The results reveal consistent large-scale patterns in both CALIOP and CAMS datasets, although CALIOP values are approximately 79 % higher than those from CAMS. Comparisons with existing literature demonstrate that these datasets effectively bound the regionally observed CCN concentrations, with CALIOP typically representing the upper bound and CAMS the lower bound. Monthly and annual variations in CCN concentrations obtained from the two datasets largely agree over the Northern Hemisphere and align with previously reported variations. However, inconsistencies emerge over pristine oceans, particularly in the Southern Hemisphere, where the datasets show not only opposing seasonal changes but also contrasting annual trends. A closure study of trends in CCN and cloud droplet concentrations suggests that dust-influenced and pristine-maritime environments primarily limit our current understanding of CCN-cloud-droplet relationships. Long-term CCN observations in these regions are crucial for improving global datasets and advancing our understanding of aerosol-cloud interactions.

中文翻译：

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原始海洋控制着气溶胶-云相互作用的不确定性


摘要。量化全球云凝结核（CCN）浓度对于减少气溶胶-云相互作用引起的辐射强迫的不确定性至关重要。本研究分析了两个新颖、独立、开源的全球 CCN 数据集，这些数据集源自星载云气溶胶激光雷达正交偏振 (CALIOP) 测量和哥白尼大气监测服务 (CAMS) 再分析，并检查与液云相关的 CCN 浓度的时空变化。结果揭示了 CALIOP 和 CAMS 数据集中一致的大规模模式，尽管 CALIOP 值比 CAMS 的值高出约 79%。与现有文献的比较表明，这些数据集有效地限制了区域观察到的 CCN 浓度，CALIOP 通常代表上限，CAMS 代表下限。从两个数据集中获得的 CCN 浓度的月度和年度变化在北半球基本一致，并且与之前报告的变化一致。然而，原始海洋上出现了不一致的情况，特别是在南半球，那里的数据集不仅显示出相反的季节变化，而且还显示出截然不同的年度趋势。对 CCN 和云滴浓度趋势的封闭研究表明，受尘埃影响和原始海洋环境主要限制了我们目前对 CCN-云-滴关系的理解。这些地区的长期 CCN 观测对于改善全球数据集和增进我们对气溶胶-云相互作用的理解至关重要。