Type‐Dependent Responses of Ice Cloud Properties to Aerosols From Satellite Retrievals

Abstract

Aerosol‐cloud interactions represent one of the largest uncertainties in external forcings on our climate system. Compared with liquid clouds, the observational evidence for the aerosol impact on ice clouds is much more limited and shows conflicting results, partly because the distinct features of different ice cloud and aerosol types were seldom considered. Using 9‐year satellite retrievals, we find that, for convection‐generated (anvil) ice clouds, cloud optical thickness, cloud thickness, and cloud fraction increase with small‐to‐moderate aerosol loadings (<0.3 aerosol optical depth) and decrease with further aerosol increase. For in situ formed ice clouds, however, these cloud properties increase monotonically and more sharply with aerosol loadings. An increase in loading of smoke aerosols generally reduces cloud optical thickness of convection‐generated ice clouds, while the reverse is true for dust and anthropogenic pollution aerosols. These relationships between different cloud/aerosol types provide valuable constraints on the modeling assessment of aerosol‐ice cloud radiative forcing.

Intra-annual variations of regional aerosol optical depth, vertical distribution, and particle types from multiple satellite and ground-based observational datasets

“…B. Zhao et al: Intra-annual variations of aerosol loading and properties Aerosol optical depth (AOD) has been widely used to represent the column aerosol loading and to assess the aerosol impacts on radiation, clouds, and precipitation Niu and Li, 2012;Zhao et al, 2018b;Song et al, 2017). However, the wide ranges of particle optical properties and size distribution mean that even for the same AOD, different aerosol types have different effects on not only the magnitude, but also the sign, of aerosol radiative forcing (IPCC, 2013;Gu et al, 2006;Garrett et al, 2004).…”

A Global Survey of Apparent Aerosol‐Cloud Interaction Signals

“…Nevertheless, column AOD, as the most readily available quantity directly retrievable from satellites, has a long track record as the variable of choice in studies with objectives and philosophy similar to ours (e.g., Zhao et al, 2018). Column AOD is, however, not an ideal variable for probing aerosol-cloud-precipitation-radiation interaction (ACPRI) because it comprises the extinction contribution of aerosol particles that may have not been involved in cloud formation and subsequent modification through ACPRI.…”

“…Some of the column's aerosol particles may not be participating in cloud processes because of vertical separation from the cloud, or intrinsic inability to act as condensation or ice nuclei due to composition or specific meteorological conditions. Nevertheless, column AOD, as the most readily available quantity directly retrievable from satellites, has a long track record as the variable of choice in studies with objectives and philosophy similar to ours (e.g., Zhao et al, 2018). Consequently, we have once again settled on column AOD (hereafter just "AOD") to represent aerosol concentration in this study, even though in reanalysis data sets other aerosol properties beyond columnar extinction are available and can potentially be employed for the problem at hand.…”

Enhancement of Atmospheric Stability by Anomalous Elevated Aerosols During Winter in China

“…CALIPSO can distinguish clouds from aerosols with high confidence (>90%; Omar et al, ). CALIPSO observations also have indicated that aerosols in China are mainly composed of dust, smoke, polluted dust, and polluted continental aerosols (Zhao et al, ). Previous studies have verified that the total consistency of aerosol subtypes between CALIPSO and the Aerosol Robotic Network (AERONET) is 70% (Mielonen et al, ), and the highest agreement is achieved for dust (91%).…”