Significant underestimation of radiative forcing by aerosol–cloud interactions derived from satellite-based methods
Hailing Jia, Xiaoyan Ma, Fangqun Yu, Johannes Quaas
Abstract
Abstract Satellite-based estimates of radiative forcing by aerosol–cloud interactions (RF aci ) 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 −2 ) increases by 55 % globally (133 % over land and 33 % over ocean). Notably, the RF aci further increases to −1.09 W m −2 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 aci , the improved one substantially increases (especially over land), resolving a major difference with models.