No abstract

The rate of warming in the Arctic depends upon the response of low‐level microphysical and radiative cloud properties to aerosols advected from distant anthropogenic and biomass‐burning sources. Cloud droplet cross‐section density increases with higher concentrations of cloud condensation nuclei, leading to an increase of cloud droplet absorption and scattering radiative cross sections. The challenge of assessing the magnitude of the effect has been decoupling the aerosol impacts on clouds from how clouds change solely due to natural meteorological variability. Here we address this issue with large, multi‐year satellite, meteorological, and tracer transport model data sets to show that the response of low‐level clouds in the Arctic to anthropogenic aerosols lies close to a theoretical maximum and is between 2 and 8 times higher than has been observed elsewhere. However, a previously described response of arctic clouds to biomass‐burning plumes appears to be overstated because the interactions are rare and modification of cloud radiative properties appears better explained by coincident changes in temperature, humidity, and atmospheric stability.

Abstract. The properties of low-level liquid clouds in the Arctic can be altered by long-range pollution transport to the region. Satellite, tracer transport model, and meteorological data sets are used here to determine a net aerosol-cloud interaction (ACI net ) parameter that expresses the ratio of relative changes in cloud microphysical properties to relative variations in pollution concentrations while accounting for dry or wet scavenging of aerosols en route to the Arctic. For a period between 2008 and 2010, ACI net is calculated as a function of the cloud liquid water path, temperature, altitude, specific humidity, and lower tropospheric stability. For all data, ACI net averages 0.12±0.02 for cloud-droplet effective radius and 0.16±0.02 for cloud optical depth. It increases with specific humidity and lower tropospheric stability and is highest when pollution concentrations are low. Carefully controlling for meteorological conditions we find that the liquid water path of arctic clouds does not respond strongly to aerosols within pollution plumes. Or, not stratifying the data according to meteorological state can lead to artificially exaggerated calculations of the magnitude of the impacts of pollution on arctic clouds.

Abstract. The properties of clouds in the Arctic can be altered by long-range aerosol transport to the region. The goal of this study is to use satellite, tracer transport model, and meteorological data sets to determine the effects of pollution on cloud microphysics due only to pollution itself and not to the meteorological state. Here, A-Train, POLDER-3 and MODIS satellite instruments are used to retrieve low-level liquid cloud microphysical properties over the Arctic between 2008 and 2010. Cloud retrievals are co-located with simulated pollution represented by carbon-monoxide concentrations from the FLEXPART tracer transport model. The sensitivity of clouds to pollution plumes – including aerosols – is constrained for cloud liquid water path, temperature, altitude, specific humidity, and lower tropospheric stability (LTS). We define an Indirect Effect (IE) parameter from the ratio of relative changes in cloud microphysical properties to relative variations in pollution concentrations. Retrievals indicate that, depending on the meteorological regime, IE parameters range between 0 and 0.34 for the cloud droplet effective radius, and between −0.10 and 0.35 for the optical depth, with average values of 0.12 ± 0.02 and 0.15 ± 0.02 respectively. The IE parameter increases with increasing specific humidity and LTS. Further, the results suggest that for a given set of meteorological conditions, the liquid water path of arctic clouds does not respond strongly to pollution. Or, not constraining sufficiently for meteorology may lead to artifacts that exaggerate the magnitude of the aerosol indirect effect. The converse is that the response of arctic clouds to pollution does depend on the meteorologic state. Finally, we find that IE values are highest when pollution concentrations are low, and that they depend on the source of pollution.

Reduced precipitation rates allow pollution within air parcels from midlatitudes to reach the Arctic without being scavenged. We use satellite and tracer transport model data sets to evaluate the degree of supercooling required for 50% of a chosen ensemble of low-level clouds to be in the ice phase for a given meteorological regime. Our results suggest that smaller cloud droplet effective radii are related to higher required amounts of supercooling but that, overall, pollution plumes from fossil fuel combustion lower the degree of supercooling that is required for freezing by approximately 4 ∘ C. The relationship between anthropogenic plumes and the freezing transition temperature from liquid to ice remains to be explained.Plain Language Summary Anthropogenic pollution plumes from midlatitudes can be transported long distances to the Arctic. In this study, we analyze the impact of these plumes on how easily liquid clouds over the Arctic Ocean freeze by using a novel combination of satellite measurements and a pollution transport model. We find that liquid clouds in polluted air switch phase to become ice clouds at temperatures that are 4 ∘ C higher they would otherwise in pristine air. Because ice clouds in the Arctic precipitate more easily than liquid clouds, the potential is that distant industrial pollution sources are acting to reduce arctic cloud life time.

Between −37 and 0 °C, clouds are liquid, ice, or mixed phase. Nearly all retrieval algorithms for passive instruments provide binary phase information—ice or liquid—making it difficult to retrieve mixed‐phase cloud properties. Based on measurements from the geostationary space‐based instrument Spinning Enhanced Visible and InfraRed Imager (SEVIRI), we show that the retrieved ice crystal effective radius is smaller than the liquid droplet effective radius for 48% of 230 analyzed cloud thermodynamic phase transitions—phase transition from liquid to ice of rising convective clouds—while ice crystals are expected to be larger than cloud droplets. We simulate mixed‐phase cloud radiances with the numerical model Santa Barbara DISORT Atmospheric Radiative Transfer for which we compare simulated effective radius retrievals with observations. The phase retrieval algorithm from SEVIRI does not represent well mixed‐phase clouds, and categorizing clouds by only ice and liquid is not enough to accurately represent mixed‐phase cloud optical properties. We conclude that the mixed‐phase nature of clouds explains that retrieved cloud droplet radii are larger than ice crystal radii directly before and after the phase transition. However, from a cloud tracking algorithm perspective, the variation of the effective radius enables the detection of mixed‐phase convective clouds from binary phase information.

Phase transitions leading to cloud glaciation occur at temperatures that vary between −38°C and 0°C depending on aerosol types and concentrations, the meteorology, and cloud microphysical and macrophysical parameters, although the relationships remain poorly understood. Here, we statistically retrieve a cloud glaciation temperature from two passive space‐based instruments that are part of the NASA/CNES A‐Train, the POLarization and Directionality of the Earth's Reflectances (POLDER) and the MODerate resolution Imaging Spectroradiometer (MODIS). We compare the glaciation temperature for varying bins of cloud droplet effective radius, latitude, and large‐scale vertical pressure velocity and specific humidity at 700 hPa. Cloud droplet size has the strongest influence on glaciation temperature: For cloud droplets larger than 21  normalμm, the glaciation temperature is 6°C higher than for cloud droplets smaller than 9  normalμm. Stronger updrafts are also associated with lower glaciation temperatures.

Ice-nucleating particles (INPs) facilitate the formation of ice crystals in clouds by lowering the energy barrier for heterogeneous ice nucleation relative to homogeneous ice nucleation (Rogers & Yau, 1989). Ice crystals commonly coexist with supercooled liquid droplets in mixed-phase clouds at temperatures between 0 and ∼−38°C (Korolev et al., 2017). These clouds are radiatively important, particularly in the Arctic (poleward of 60°N), where they are ubiquitous in the boundary layer (Mioche et al., 2017). Despite their inherent thermodynamic instability, observations have revealed that Arctic mixed-phase clouds are persistent as a result of interactions between microphysical processes such as ice nucleation, as well as radiative and turbulent processes (Morrison et al., 2012). However, these processes are poorly represented in global climate models (GCMs) for a number of reasons. The coarse spatial resolution of GCMs necessitates parameterizations of many unresolved processes that are not consistently represented. There is also a lack of consistent and reliable observations available to constrain GCM processes. As a result, Arctic mixed-phase clouds tend to glaciate too rapidly in GCMs and lead to a reduction in downward longwave (LW) radiation compared to what would have otherwise been a cloudy state. This in turn leads to a positive bias in lower tropospheric stability (LTS) and colder Arctic surface temperatures (Barton