Jia Hailing, Ma Xiaoyan, Yu Fangqun, Quaas Johannes
Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, and Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, School of Atmospheric Physics, Nanjing University of Information Science & Technology, Nanjing, China.
Atmospheric Sciences Research Center, University at Albany, Albany, NY, USA.
Nat Commun. 2021 Jun 15;12(1):3649. doi: 10.1038/s41467-021-23888-1.
Satellite-based estimates of radiative forcing by aerosol-cloud interactions (RF) are consistently smaller than those from global models, hampering accurate projections of future climate change. Here we show that the discrepancy can be substantially reduced by correcting sampling biases induced by inherent limitations of satellite measurements, which tend to artificially discard the clouds with high cloud fraction. Those missed clouds exert a stronger cooling effect, and are more sensitive to aerosol perturbations. By accounting for the sampling biases, the magnitude of RFaci (from -0.38 to -0.59 W m) increases by 55 % globally (133 % over land and 33 % over ocean). Notably, the RF further increases to -1.09 W m when switching total aerosol optical depth (AOD) to fine-mode AOD that is a better proxy for CCN than AOD. In contrast to previous weak satellite-based RF, the improved one substantially increases (especially over land), resolving a major difference with models.
基于卫星的气溶胶-云相互作用辐射强迫（RF）估算值一直小于全球模型的估算值，这妨碍了对未来气候变化的准确预测。我们在此表明，通过校正卫星测量固有局限性所导致的采样偏差，这种差异可大幅减小，这些局限性往往会人为地舍弃高云量的云。那些被遗漏的云具有更强的冷却效应，并且对气溶胶扰动更为敏感。通过考虑采样偏差，全球范围内RFaci的幅度（从-0.38至-0.59 W m²）增加了55%（陆地增加133%，海洋增加33%）。值得注意的是，当将总气溶胶光学厚度（AOD）切换为细模态AOD（它比AOD更能代表云凝结核）时，RF进一步增加至-1.09 W m²。与之前基于卫星的较弱RF不同，改进后的RF大幅增加（尤其是在陆地上），解决了与模型的一个主要差异。
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