Sensitivities of cloud radiative effects to large-scale meteorology and aerosols from global observations

• Published in: Atmospheric chemistry and physics 2023-09, Vol.23 (18), p.10775-10794
• Main Authors: Andersen, Hendrik, Cermak, Jan, Douglas, Alyson, Myers, Timothy A, Nowack, Peer, Stier, Philip, Wall, Casey J, Wilson Kemsley, Sarah
• Format: Article
• Language: English
• Subjects: Aerosol-cloud interactions; Aerosols; Air entrainment; Altitude; Analysis; Anomalies; Atmosphere; Atmospheric aerosols; Carbon dioxide; Climate; Climate change; Climate models; Cloud systems; Clouds; Cooling; Cooling effects; Cyclones; Energy; Energy balance; Entrainment; Environmental changes; Estimates; Feedback; Global aerosols; Global climate; Global climate models; Global warming; Humidity; Meridional wind; Meteorology; Proxies; Radiation; Regression; Satellite observation; Satellites; Sea surface; Sea surface temperature; Sensitivity analysis; Statistical analysis; Stratocumulus clouds; Surface temperature; Temperature; Trends; Troposphere; Turbulence; Uncertainty; Upper troposphere; Variability; Vertical velocities; Weather; Wind; Wind shear
• ISSN: 1680-7324; 1680-7316; 1680-7324
• DOI: 10.5194/acp-23-10775-2023

The radiative effects of clouds make a large contribution to the Earth's energy balance, and changes in clouds constitute the dominant source of uncertainty in the global warming response to carbon dioxide forcing. To characterize and constrain this uncertainty, cloud-controlling factor (CCF) analyses have been suggested that estimate sensitivities of clouds to large-scale environmental changes, typically in cloud-regime-specific multiple linear regression frameworks. Here, local sensitivities of cloud radiative effects to a large number of controlling factors are estimated in a regime-independent framework from 20 years (2001–2020) of near-global (60∘ N–60∘ S) satellite observations and reanalysis data using statistical learning. A regularized linear regression (ridge regression) is shown to skillfully predict anomalies of shortwave (R2=0.63) and longwave cloud radiative effects (CREs) (R2=0.72) in independent test data on the basis of 28 CCFs, including aerosol proxies. The sensitivity of CREs to selected CCFs is quantified and analyzed. CRE sensitivities to sea surface temperature and estimated inversion strength are particularly pronounced in low-cloud regions and generally in agreement with previous studies. The analysis of CRE sensitivities to three-dimensional wind field anomalies reflects the fact that CREs in tropical ascent regions are mainly driven by variability of large-scale vertical velocity in the upper troposphere. In the subtropics, CRE is sensitive to free-tropospheric zonal and meridional wind anomalies, which are likely to encapsulate information on synoptic variability that influences subtropical cloud systems by modifying wind shear and thus turbulence and dry-air entrainment in stratocumulus clouds, as well as variability related to midlatitude cyclones. Different proxies for aerosols are analyzed as CCFs, with satellite-derived aerosol proxies showing a larger CRE sensitivity than a proxy from an aerosol reanalysis, likely pointing to satellite aerosol retrieval biases close to clouds, leading to overestimated aerosol sensitivities. Sensitivities of shortwave CREs to all aerosol proxies indicate a pronounced cooling effect from aerosols in stratocumulus regions that is counteracted to a varying degree by a longwave warming effect. The analysis may guide the selection of CCFs in future sensitivity analyses aimed at constraining cloud feedback and climate forcings from aerosol–cloud interactions using data from both observations and