Revisiting Estimates of Aerosol Indirect Effects in Thin, Liquid-Containing Arctic Clouds

Of the uncertainties surrounding our understanding of global climate, one of the largest involves the relationships between aerosols and clouds along with the resulting impacts on atmospheric radiation and precipitation. Due to very limited profiling of aerosol properties, traditionally aerosol-cloud interactions have been evaluated using surface-based aerosol measurements as a proxy for aerosol at cloud height. At low- and mid-latitudes, clouds often form atop a well-mixed atmospheric boundary layer, meaning that the use of surface-based aerosol measurements is not necessarily unreasonable. At high latitudes, however, the atmosphere is often very stratified. This stratification limits vertical mixing of aerosols, meaning aerosol properties (e.g. number, hygroscopicity, scattering, size) observed at the Earth's surface may be very different from those at cloud height. This limitation makes it challenging to interpret previous efforts (e.g. Lubin and Vogelmann, 2006; Garrett and Zhao, 2006) to understand the impacts of aerosols on liquid-containing Arctic clouds.

In this work, we combine a variety of measurements obtained at the US Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program's North Slope of Alaska (NSA) site to revisit the derivation of relationships between aerosol and cloud properties. Included in the mix of measurements used is a derived estimate of the turbulent dissipation rate from the Doppler velocity measured using a Millimeter Cloud Radar (MMCR, see Shupe et al., 2012 for details on estimation of turbulent dissipation rate). This estimate of the turbulent dissipation rate is used to separate single-layer liquid containing cloud cases into time periods where mixing is occurring between the surface and cloud height, and time periods where mixing does not connect these two locations. Using surface aerosol measurements from the National Oceanographic and Atmospheric Administration site in Barrow, we estimate the relative level of pollution. Combined with cloud microphysical and cloud emissivity estimates from the Atmospheric Emitted Radiance Interferometer (AERI) we derive relationships between aerosol amount and cloud radiative properties. This evaluation will span a multi-year period of measurements.