Abstract
Satellite-based estimates of radiative forcing by aerosol–cloud interactions (RFaci) 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 RFaci 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 RFaci, the improved one substantially increases (especially over land), resolving a major difference with models.
Highlights
Satellite-based estimates of radiative forcing by aerosol–cloud interactions (RFaci) are consistently smaller than those from global models, hampering accurate projections of future climate change
Extensive investigations have been made to quantify the radiative forcing by aerosol–cloud interaction (RFaci), significant uncertainties remain on its magnitude[3,4]
To explore the influences of sampling biases quantitatively, analyses under different scenarios are conducted by combining cloud retrievals from the Clouds and the Earth’s Radiant Energy System (CERES)[30] with the MODerate Resolution Imaging Spectroradiometer (MODIS) aerosol retrievals[31] and the Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2) aerosol reanalysis[32]
Summary
Satellite-based estimates of radiative forcing by aerosol–cloud interactions (RFaci) are consistently smaller than those from global models, hampering accurate projections of future climate change. 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. If aerosol information is available at cloud base altitude, an even stronger aerosol–cloud relationship would be expected[22] All of these tend to underestimate the RFaci[19,23]
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