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The main energy input to the polar regions in winter is the advection of warm, moist air from lower latitudes. This makes the polar climate sensitive to the temperature and moisture of extrapolar air. Here, we study this sensitivity from an air-mass transformation perspective. We perform simulations of an idealized maritime air mass brought into contact with sea ice employing a three-dimensional large-eddy simulation model coupled to a one-dimensional multilayer sea ice model. We study the response of cloud dynamics and surface warming during the air-mass transformation process to varying initial temperature and humidity conditions of the air mass. We find in all cases that a mixed-phase cloud is formed, initially near the surface but rising continuously with time. Surface warming of the sea ice is driven by downward longwave surface fluxes, which are largely controlled by the temperature and optical depth of the cloud. Cloud temperature, in turn, is robustly constrained by the initial dewpoint temperature of the air mass. Since dewpoint only depends on moisture, the overall result is that surface warming depends almost exclusively on initial humidity and is largely independent of initial temperature. We discuss possible climate implications of this result}in particular, for polar amplification of surface warming and the role played by atmospheric energy transports. [ABSTRACT FROM AUTHOR]

We perform a model intercomparison of summertime high Arctic (>80N) clouds observed during the 2008 Arctic Summer Cloud Ocean Study (ASCOS) campaign, when observed cloud condensation nuclei (CCN) concentrations fell below 1cm-3. Previous analyses have suggested that at these low CCN concentrations the liquid water content (LWC) and radiative properties of the clouds are determined primarily by the CCN concentrations, conditions that have previously been referred to as the tenuous cloud regime. The intercomparison includes results from three large eddy simulation models (UCLALES-SALSA, COSMO-LES, and MIMICA) and three numerical weather prediction models (COSMO-NWP, WRF, and UM-CASIM). We test the sensitivities of the model results to different treatments of cloud droplet activation, including prescribed cloud droplet number concentrations (CDNC) and diagnostic CCN activation based on either fixed aerosol concentrations or prognostic aerosol with in-cloud processing. There remains considerable diversity even in experiments with prescribed CDNCs and prescribed ice crystal number concentrations (ICNC). The sensitivity of mixed-phase Arctic cloud properties to changes in CDNC depends on the representation of the cloud droplet size distribution within each model, which impacts on autoconversion rates. Our results therefore suggest that properly estimating aerosol-cloud interactions requires an appropriate treatment of the cloud droplet size distribution within models, as well as in-situ observations of hydrometeor size distributions to constrain them. The results strongly support the hypothesis that the liquid water content of these clouds is CCN-limited. For the observed meteorological conditions, the cloud generally did not collapse when the CCN concentration was held constant at the relatively high CCN concentrations measured during the cloudy period, but the cloud thins or collapses as the CCN concentration is reduced. The CCN concentration at which collapse occurs varies substantially between models. Only one model predicts complete dissipation of the cloud due to glaciation, and this occurs only for the largest prescribed ICNC tested in this study. Global and regional models with either prescribed CDNCs or prescribed aerosol concentrations would not reproduce these dissipation events. Additionally, future increases in Arctic aerosol concentrations would be expected to decrease the frequency of occurrence of such cloud dissipation events, with implications for the radiative balance at the surface. Our results also show that cooling of the sea-ice surface following cloud dissipation increases atmospheric stability near the surface, further suppressing cloud formation. Therefore, this suggests that linkages between aerosol and clouds, as well as linkages between clouds, surface temperatures and atmospheric stability need to be considered for weather and climate predictions in this region. [ABSTRACT FROM AUTHOR]

Arctic air mass transformation is linked to the evolution of low-level mixed-phase clouds. These clouds can alter the structure of the boundary layer and modify the surface energy budget due to their greenhouse warming effect. In this study, we used a large-eddy simulation model (MIMICA) coupled to a bulk sea ice model to study in detail wintertime advection of moist and warm air over sea ice from a Lagrangian perspective. We examined the stages of cloud formation, evolution and decay and thus the transition from a stable to a well-mixed boundary layer and vice versa. Furthermore, we conducted sensitivity tests in order to examine how different dynamical and cloud microphysical parameters affect the liquid water path (LWP), ice water path (IWP), net surface longwave radiative flux and lifetime of the cloud. All simulations were carried out assuming prescribed constant cloud condensation nuclei (CCN) and ice crystal number concentrations (ICNC). The results show that radiative cooling at the surface give rise to fog formation which is elevated and transformed into a mixed-phase cloud. Due to top-down convection, the boundary layer becomes well-mixed as a coupling between the surface and cloud turbulent regimes is achieved. In our baseline simulation, the cloud persists for about 5 days altering the surface energy balance by increasing the downward longwave radiative flux. The net surface longwave radiative flux is balanced mainly by the conductive heat flux from the ocean beneath the sea ice to the atmosphere. After approximately 5 days of simulation, the cloud glaciates due to the Wegeron-Bergeron-Findeisen (WBF) process leading to a sharp decrease of the surface temperature. The sensitivity tests show that the LWP is mostly affected by the CCN concentration and ICNC but also by the drizzle formation. The IWP is most sensitive to horizontal convergence and divergence and thereafter to the ICNC. During the time period before the cloud reaches its maximum LWP, the net surface longwave radiative flux is mostly sensitive to the LWP. After the maximum is reached, the IWP becomes more important in determining the surface energy budget. Horizontal convergence and divergence strongly affect cloud lifetime. A change in these values modified the cloud lifetime in our simulations to between 2 to more than 6 days. Changes in the ICNC and CCN concentration also modified the cloud lifetime, but to a lesser extent (about half a day). However, if drizzle was suppressed completely, the cloud glaciated much faster than in the baseline case so that the lifetime decreased to approximately 4 days. [ABSTRACT FROM AUTHOR]