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The Arctic is predominantly cloudy with intermittent clear sky periods. These clear periods have profound impacts on the surface energy budget and lower atmospheric stratification, connected to a lack of downwelling longwave radiation in the absence of cloud. Despite the importance of clear sky conditions, an understanding of the atmospheric processes leading to low-level cloud dissipation and formation events is relatively limited. A strict definition to identify clear periods at Utqiagvik (formerly Barrow), Alaska, during a five-year period (2014–2018) is developed. A suite of remote sensing and in situ instrumentation from the high-latitude observatory are analysed; we focus on comparing and contrasting atmospheric properties during low-level cloud dissipation and formation events to understand the processes controlling clear sky periods. Vertical profiles of lidar backscatter suggest that aerosol presence across the lower atmosphere is relatively invariant around the clear period bookends, which suggests that a sparsity of aerosol is not frequently a cause for cloud dissipation. Further meteorological analysis indicates two active processes ongoing that appear to support the formation of low clouds after a clear sky period and have a link to surface aerosol concentrations; namely, horizontal advection which was dominant in winter and early spring and quiescent air mass modification which was dominant in the summer. During summer, the dominant mode of cloud formation is a low cloud/fog layer developing near the surface. This low cloud formation is driven largely by air mass modification and pooling of aerosol particles near the surface under lower-atmosphere stratification.

The Arctic is predominantly cloudy with intermittent clear sky periods. These clear periods have profound impacts on the surface energy budget and lower atmospheric stratification, connected to a lack of downwelling longwave radiation in the absence of cloud. Despite the importance of clear sky conditions, an understanding of the atmospheric processes leading to low-level cloud dissipation and formation events is relatively limited. A strict definition to identify clear periods at Utqiagvik (formerly Barrow), Alaska, during a five-year period (2014–2018) is developed. A suite of remote sensing and in situ instrumentation from the high-latitude observatory are analysed; we focus on comparing and contrasting atmospheric properties during low-level cloud dissipation and formation events to understand the processes controlling clear sky periods. Vertical profiles of lidar backscatter suggest that aerosol presence across the lower atmosphere is relatively invariant around the clear period bookends, which suggests that a sparsity of aerosol is not frequently a cause for cloud dissipation. Further meteorological analysis indicates two active processes ongoing that appear to support the formation of low clouds after a clear sky period and have a link to surface aerosol concentrations; namely, horizontal advection which was dominant in winter and early spring and quiescent air mass modification which was dominant in the summer. During summer, the dominant mode of cloud formation is a low cloud/fog layer developing near the surface. This low cloud formation is driven largely by air mass modification and pooling of aerosol particles near the surface under lower-atmosphere stratification.

The Chequamegon Heterogeneous Ecosystem Energy-Balance Study Enabled by a High-Density Extensive Array of Detectors 2019 (CHEESEHEAD19) is an ongoing National Science Foundation project based on an intensive field campaign that occurred from June to October 2019. The purpose of the study is to examine how the atmospheric boundary layer (ABL) responds to spatial heterogeneity in surface energy fluxes. One of the main objectives is to test whether lack of energy balance closure measured by eddy covariance (EC) towers is related to mesoscale atmospheric processes. Finally, the project evaluates data-driven methods for scaling surface energy fluxes, with the aim to improve model–data comparison and integration. To address these questions, an extensive suite of ground, tower, profiling, and airborne instrumentation was deployed over a 10 km × 10 km domain of a heterogeneous forest ecosystem in the Chequamegon–Nicolet National Forest in northern Wisconsin, United States, centered on an existing 447-m tower that anchors an AmeriFlux/NOAA supersite (US-PFa/WLEF). The project deployed one of the world’s highest-density networks of above-canopy EC measurements of surface energy fluxes. This tower EC network was coupled with spatial measurements of EC fluxes from aircraft; maps of leaf and canopy properties derived from airborne spectroscopy, ground-based measurements of plant productivity, phenology, and physiology; and atmospheric profiles of wind, water vapor, and temperature using radar, sodar, lidar, microwave radiometers, infrared interferometers, and radiosondes. These observations are being used with large-eddy simulation and scaling experiments to better understand submesoscale processes and improve formulations of subgrid-scale processes in numerical weather and climate models.

A coordinated regional climate model (RCM) evaluation and intercomparison project based on observations from a July-October 2014 trans-Arctic Ocean field experiment (ACSE-Arctic Clouds during Summer Experiment) is presented. Six state-of-the-art RCMs were constrained with common reanalysis lateral boundary forcing and upper troposphere nudging techniques to explore how the RCMs represented the evolution of the surface energy budget (SEB) components and their relation to cloud properties. We find that the main reasons for the modeled differences in the SEB components are a direct consequence of the RCM treatment of cloud and cloud-radiative interactions. The RCMs could be separated into groups by their overestimation or underestimation of cloud liquid. While radiative and turbulent heat flux errors were relatively large, they often invoke compensating errors. In addition, having the surface sea-ice concentrations constrained by the reanalysis or satellite observations limited how errors in the modeled radiative fluxes could affect the SEB and ultimately the surface evolution and its coupling with lower tropospheric mixing and cloud properties. Many of these results are consistent with RCM biases reported in studies over a decade ago. One of the six models was a fully coupled ocean-ice-atmosphere model. Despite the biases in overestimating cloud liquid, and associated SEB errors due to too optically thick clouds, its simulations were useful in understanding how the fully coupled system is forced by, and responds to, the SEB evolution. Moving forward, we suggest that development of RCM studies need to consider the fully coupled climate system.

A coordinated regional climate model (RCM) evaluation and intercomparison project based on observations from a July–October 2014 trans‐Arctic Ocean field experiment (ACSE‐Arctic Clouds during Summer Experiment) is presented. Six state‐of‐the‐art RCMs were constrained with common reanalysis lateral boundary forcing and upper troposphere nudging techniques to explore how the RCMs represented the evolution of the surface energy budget (SEB) components and their relation to cloud properties. We find that the main reasons for the modeled differences in the SEB components are a direct consequence of the RCM treatment of cloud and cloud‐radiative interactions. The RCMs could be separated into groups by their overestimation or underestimation of cloud liquid. While radiative and turbulent heat flux errors were relatively large, they often invoke compensating errors. In addition, having the surface sea‐ice concentrations constrained by the reanalysis or satellite observations limited how errors in the modeled radiative fluxes could affect the SEB and ultimately the surface evolution and its coupling with lower tropospheric mixing and cloud properties. Many of these results are consistent with RCM biases reported in studies over a decade ago. One of the six models was a fully coupled ocean‐ice‐atmosphere model. Despite the biases in overestimating cloud liquid, and associated SEB errors due to too optically thick clouds, its simulations were useful in understanding how the fully coupled system is forced by, and responds to, the SEB evolution. Moving forward, we suggest that development of RCM studies need to consider the fully coupled climate system.

A coordinated regional climate model (RCM) evaluation and intercomparison project based on observations from a July–October 2014 trans‐Arctic Ocean field experiment (ACSE‐Arctic Clouds during Summer Experiment) is presented. Six state‐of‐the‐art RCMs were constrained with common reanalysis lateral boundary forcing and upper troposphere nudging techniques to explore how the RCMs represented the evolution of the surface energy budget (SEB) components and their relation to cloud properties. We find that the main reasons for the modeled differences in the SEB components are a direct consequence of the RCM treatment of cloud and cloud‐radiative interactions. The RCMs could be separated into groups by their overestimation or underestimation of cloud liquid. While radiative and turbulent heat flux errors were relatively large, they often invoke compensating errors. In addition, having the surface sea‐ice concentrations constrained by the reanalysis or satellite observations limited how errors in the modeled radiative fluxes could affect the SEB and ultimately the surface evolution and its coupling with lower tropospheric mixing and cloud properties. Many of these results are consistent with RCM biases reported in studies over a decade ago. One of the six models was a fully coupled ocean‐ice‐atmosphere model. Despite the biases in overestimating cloud liquid, and associated SEB errors due to too optically thick clouds, its simulations were useful in understanding how the fully coupled system is forced by, and responds to, the SEB evolution. Moving forward, we suggest that development of RCM studies need to consider the fully coupled climate system.

A coordinated regional climate model (RCM) evaluation and intercomparison project based on observations from a July–October 2014 trans‐Arctic Ocean field experiment (ACSE‐Arctic Clouds during Summer Experiment) is presented. Six state‐of‐the‐art RCMs were constrained with common reanalysis lateral boundary forcing and upper troposphere nudging techniques to explore how the RCMs represented the evolution of the surface energy budget (SEB) components and their relation to cloud properties. We find that the main reasons for the modeled differences in the SEB components are a direct consequence of the RCM treatment of cloud and cloud‐radiative interactions. The RCMs could be separated into groups by their overestimation or underestimation of cloud liquid. While radiative and turbulent heat flux errors were relatively large, they often invoke compensating errors. In addition, having the surface sea‐ice concentrations constrained by the reanalysis or satellite observations limited how errors in the modeled radiative fluxes could affect the SEB and ultimately the surface evolution and its coupling with lower tropospheric mixing and cloud properties. Many of these results are consistent with RCM biases reported in studies over a decade ago. One of the six models was a fully coupled ocean‐ice‐atmosphere model. Despite the biases in overestimating cloud liquid, and associated SEB errors due to too optically thick clouds, its simulations were useful in understanding how the fully coupled system is forced by, and responds to, the SEB evolution. Moving forward, we suggest that development of RCM studies need to consider the fully coupled climate system.

A coordinated regional climate model (RCM) evaluation and intercomparison project based on observations from a July–October 2014 trans‐Arctic Ocean field experiment (ACSE‐Arctic Clouds during Summer Experiment) is presented. Six state‐of‐the‐art RCMs were constrained with common reanalysis lateral boundary forcing and upper troposphere nudging techniques to explore how the RCMs represented the evolution of the surface energy budget (SEB) components and their relation to cloud properties. We find that the main reasons for the modeled differences in the SEB components are a direct consequence of the RCM treatment of cloud and cloud‐radiative interactions. The RCMs could be separated into groups by their overestimation or underestimation of cloud liquid. While radiative and turbulent heat flux errors were relatively large, they often invoke compensating errors. In addition, having the surface sea‐ice concentrations constrained by the reanalysis or satellite observations limited how errors in the modeled radiative fluxes could affect the SEB and ultimately the surface evolution and its coupling with lower tropospheric mixing and cloud properties. Many of these results are consistent with RCM biases reported in studies over a decade ago. One of the six models was a fully coupled ocean‐ice‐atmosphere model. Despite the biases in overestimating cloud liquid, and associated SEB errors due to too optically thick clouds, its simulations were useful in understanding how the fully coupled system is forced by, and responds to, the SEB evolution. Moving forward, we suggest that development of RCM studies need to consider the fully coupled climate system.

Horizontal moisture transport has a manifold role in the Arctic climate system as it distributes atmospheric water vapour and thereby shapes the radiative and hydrological conditions. Moisture transport between the Arctic and the mid-latitudes was examined based on ERA-Interim reanalysis. The meridional net transport is only a small part of the water vapour exchange between the Arctic and mid-latitudes and does not give a complete view of temporal and spatial variations in the transport. Especially near the surface, most of the northwards moisture transport is balanced by the southwards transport, and therefore the meridional net moisture transport at 60 degrees-70 degrees N peaks approximately at 100 hPa higher altitude than the northwards and southwards moisture transports. The total moisture transport (sum of absolute northwards and southwards moisture transports) has a much larger seasonal variation than the net transport (mean meridional transport), and the strength of the total transport is related to atmospheric humidity rather than the wind field. Strong individual moisture transport events contribute to a large part of the northwards moisture transport. This is consistent with the result that the net moisture transport is essentially generated by temporal variations of moisture fluxes. The moisture transport due to stationary zonal variation in the mass flux mostly defines the spatial distribution of the meridional moisture transport. The seasonal cycle of the net moisture transport is related to the seasonal cycle of transient eddy moisture transport but inter-annual variations of the net moisture transport are largely influenced by the stationary eddy moisture transport.

Measurements from spaceborne sensors have the unique capacity to fill spatial and temporal gaps in ground-based atmospheric observing systems, especially over the Arctic, where long-term observing stations are limited to pan-Arctic landmasses and infrequent field campaigns. The AIRS level 3 (L3) daily averaged thermodynamic profile product is widely used for process understanding across the sparsely observed Arctic atmosphere. However, detailed investigations into the accuracy of the AIRS L3 thermodynamic profiles product using in situ observations over the high-latitude Arctic are lacking. To address this void, we compiled a wealth of radiosounding profiles from long-term Arctic land stations and included soundings from intensive icebreaker-based field campaigns. These are used to evaluate daily mean thermodynamic profiles from the AIRS L3 product so that the community can understand to what extent such data records can be applied in scientific studies. Results indicate that, while the mid- to upper-troposphere temperature and specific humidity are captured relatively well by AIRS, the lower troposphere is susceptible to specific seasonal, and even monthly, biases. These differences have a critical influence on the lower-tropospheric stability structure. The relatively coarse vertical resolution of the AIRS L3 product, together with infrared radiation through persistent low Arctic cloud layers, leads to artificial thermodynamic structures that fail to accurately represent the lower Arctic atmosphere. These thermodynamic errors are likely to introduce artificial errors in the boundary layer structure and analysis of associated physical processes.

During the Arctic Clouds in Summer Experiment (ACSE) in summer 2014 a weeklong period of warm-air advection over melting sea ice, with the formation of a strong surface temperature inversion and dense fog, was observed. Based on an analysis of the surface energy budget, we formulated the hypothesis that, because of the airmass transformation, additional surface heating occurs during warm-air intrusions in a zone near the ice edge. To test this hypothesis, we explore all cases with surface inversions occurring during ACSE and then characterize the inversions in detail. We find that they always occur with advection from the south and are associated with subsidence. Analyzing only inversion cases over sea ice, we find two categories: one with increasing moisture in the inversion and one with constant or decreasing moisture with height. During surface inversions with increasing moisture with height, an extra 10-25 W m(-2) of surface heating was observed, compared to cases without surface inversions; the surface turbulent heat flux was the largest single term. Cases with less moisture in the inversion were often cloud free and the extra solar radiation plus the turbulent surface heat flux caused by the inversion was roughly balanced by the loss of net longwave radiation.

Springtime atmospheric preconditioning of Arctic sea ice for enhanced or buffered sea ice melt during the subsequent melt year has received considerable research focus. Studies have identified enhanced poleward atmospheric transport of moisture and heat during spring, leading to increased emission of longwave radiation to the surface. Simultaneously, these studies ruled out the role of shortwave radiation as an effective preconditioning mechanism because of relatively weak incident solar radiation, high surface albedo from sea ice and snow, and increased clouds during spring. These conclusions are derived primarily from atmospheric reanalysis, which may not always accurately represent the Arctic climate system. Here, top-of-atmosphere shortwave radiation observations from a state-of-the-art satellite sensor are compared with ERA-Interim reanalysis to examine similarities and differences in the springtime absorbed shortwave radiation (ASR) over the Arctic Ocean. Distinct biases in regional location and absolute magnitude of ASR anomalies are found between satellite-based measurements and reanalysis. Observations indicate separability between ASR anomalies in spring corresponding to anomalously low and high ice extents in September; the reanalysis fails to capture the full extent of this separability. The causes for the difference in ASR anomalies between observations and reanalysis are considered in terms of the variability in surface albedo and cloud presence. Additionally, biases in reanalysis cloud water during spring are presented and are considered for their impact on overestimating spring downwelling longwave anomalies. Taken together, shortwave radiation should not be overlooked as a contributing mechanism to springtime Arctic atmospheric preconditioning.

While there is an increasing scientific interest in the role of advection of warm and moist air into the Arctic, there is little understanding of the interactive processes between the advected air, boundary-layer clouds and turbulence during such events and almost all studies refer to winter conditions. We use large-eddy simulation (LES) to investigate these processes for an extreme warm-air advection episode observed during summer 2014. The results indicate that moisture advection is the critical factor for cloud formation; shutting off this supply resulted in cloud dissipation, regardless of heat advection being present or not. The dissipation of the cloud reduced the surface energy budget by up to 37W/m(2). Advection of heat suppresses cloud-driven mixing through enhancement of the atmospheric stability. Turning off the large-scale heat transport therefore resulted in a somewhat optically thicker cloud, on average increasing the liquid water path by approximate to 10g/m(2). The results showed little sensitivity to a number of assumptions and simplifications in the LES set-up, such as the prescribed cloud condensation nuclei concentration, friction velocity, surface albedo and the available moisture above the cloud layer.

The Arctic climate is changing; temperature changes in the Arctic are greater than at midlatitudes, and changing atmospheric conditions influence Arctic mixed-phase clouds, which are important for the Arctic surface energy budget. These low-level clouds are frequently observed across the Arctic. They impact the turbulent and radiative heating of the open water, snow, and sea-ice-covered surfaces and influence the boundary layer structure. Therefore the processes that affect mixed-phase cloud life cycles are extremely important, yet relatively poorly understood. In this study, we present sensitivity studies using semi-idealized large eddy simulations (LESs) to identify processes contributing to the dissipation of Arctic mixed-phase clouds. We found that one potential main contributor to the dissipation of an observed Arctic mixed-phase cloud, during the Arctic Summer Cloud Ocean Study (ASCOS) field campaign, was a low cloud droplet number concentration (CDNC) of about 2 cm-3. Introducing a high ice crystal concentration of 10 L-1 also resulted in cloud dissipation, but such high ice crystal concentrations were deemed unlikely for the present case. Sensitivity studies simulating the advection of dry air above the boundary layer inversion, as well as a modest increase in ice crystal concentration of 1 L-1, did not lead to cloud dissipation. As a requirement for small droplet numbers, pristine aerosol conditions in the Arctic environment are therefore considered an important factor determining the lifetime of Arctic mixed-phase clouds.

The Arctic climate is changing; temperature changes in the Arctic are greater than at midlatitudes, and changing atmospheric conditions influence Arctic mixed-phase clouds, which are important for the Arctic surface energy budget. These low-level clouds are frequently observed across the Arctic. They impact the turbulent and radiative heating of the open water, snow, and sea-ice-covered surfaces and influence the boundary layer structure. Therefore the processes that affect mixed-phase cloud life cycles are extremely important, yet relatively poorly understood. In this study, we present sensitivity studies using semi-idealized large eddy simulations (LESs) to identify processes contributing to the dissipation of Arctic mixed-phase clouds. We found that one potential main contributor to the dissipation of an observed Arctic mixed-phase cloud, during the Arctic Summer Cloud Ocean Study (ASCOS) field campaign, was a low cloud droplet number concentration (CDNC) of about 2 cm-3. Introducing a high ice crystal concentration of 10 L-1 also resulted in cloud dissipation, but such high ice crystal concentrations were deemed unlikely for the present case. Sensitivity studies simulating the advection of dry air above the boundary layer inversion, as well as a modest increase in ice crystal concentration of 1 L-1, did not lead to cloud dissipation. As a requirement for small droplet numbers, pristine aerosol conditions in the Arctic environment are therefore considered an important factor determining the lifetime of Arctic mixed-phase clouds.

While the atmospheric greenhouse effect always results in a warming at the surface, outgoing longwave radiation (OLR) to space always represents a cooling. During events of heat and moisture advection into the Arctic, increases in tropospheric temperature and moisture impact clouds, in turn impacting longwave (LW) radiation. State-of-the-art satellite measurements and atmospheric reanalysis consistently reveal an enhancement of summer Arctic monthly OLR cooling ranging 1.5-4Wm(-2) during months with anomalously high thermodynamic advection. This cooling anomaly is found to be of the same magnitude or slightly larger than associated downwelling LW surface warming anomalies. We identify a relationship between large-scale circulation variability and changing cloud properties permitting LW radiation at both the surface and top of the atmosphere to respond to variability in atmospheric thermodynamics. Driven by anomalous advection of warm air, the corresponding enhanced OLR cooling signal on monthly time scales represents an important buffer to regional Arctic warming.

This study investigates aerosol particle transport from the free troposphere to the boundary layer in the summertime high Arctic. Observations from the Arctic Summer Cloud Ocean Study field campaign show several occurrences of high aerosol particle concentrations above the boundary layer top. Large-eddy simulations suggest that when these enhanced aerosol concentrations are present, they can be an important source of aerosol particles for the boundary layer. Most particles are transported to the boundary layer by entrainment. However, it is found that mixed-phase stratocumulus clouds, which often extend into the inversion layer, also can mediate the transport of particles into the boundary layer by activation at cloud top and evaporation below cloud base. Finally, the simulations also suggest that aerosol properties at the surface sometimes may not be good indicators of aerosol properties in the cloud layer.

The mostly ice covered Arctic Ocean is dominated by low-level liquid-or mixed-phase clouds. Turbulence within stratocumulus is primarily driven by cloud top cooling that induces convective instability. Using a suite of in situ and remote sensing instruments we characterize turbulent mixing in Arctic stratocumulus, and for the first time we estimate profiles of the gradient Richardson number at relatively high resolution in both time (10 min) and altitude (10 m). It is found that the mixing occurs both within the cloud, as expected, and by wind shear instability near the surface. About 75% of the time these two layers are separated by a stably stratified inversion at 100-200 m altitude. Exceptions are associated with low cloud bases that allow the cloud-driven turbulence to reach the surface. The results imply that turbulent coupling between the surface and the cloud is sporadic or intermittent. Plain Language Summary: The lower atmosphere over the summertime Arctic Ocean often consists of two well-mixed layers-a surface mixed layer and a cloud mixed layer-that are separated by a weak decoupling layer at about 100 to 300 m above the surface. In these cases, the cloud cannot interact directly with the surface. Large-scale forecast and climate models consistently fail to reproduce this observed structure and may thus fail to correctly reproduce the cloud properties and the amount of energy absorbed by or emitted from the surface as solar and infrared radiation. This contributes to errors in reproducing changes in sea ice concentration over time. Here we use measurements made in the central Arctic to study the processes controlling whether or not the cloud is coupled to the surface. The effect of wind at the surface is found not to be a controlling factor. The depth of the cloud mixed layer is critical, but the multiple processes influencing it cannot be separated using the data available here. However, cooling at cloud top by infrared radiation is key, as is the extens

The Arctic climate is changing; temperature changes in the Arctic are greater than at midlatitudes, and changing atmospheric conditions influence Arctic mixed-phase clouds, which are important for the Arctic surface energy budget. These low-level clouds are frequently observed across the Arctic. They impact the turbulent and radiative heating of the open water, snow, and sea-ice-covered surfaces and influence the boundary layer structure. Therefore the processes that affect mixed-phase cloud life cycles are extremely important, yet relatively poorly understood. In this study, we present sensitivity studies using semi-idealized large eddy simulations (LESs) to identify processes contributing to the dissipation of Arctic mixed-phase clouds. We found that one potential main contributor to the dissipation of an observed Arctic mixed-phase cloud, during the Arctic Summer Cloud Ocean Study (ASCOS) field campaign, was a low cloud droplet number concentration (CDNC) of about 2 cm-3. Introducing a high ice crystal concentration of 10 L-1 also resulted in cloud dissipation, but such high ice crystal concentrations were deemed unlikely for the present case. Sensitivity studies simulating the advection of dry air above the boundary layer inversion, as well as a modest increase in ice crystal concentration of 1 L-1, did not lead to cloud dissipation. As a requirement for small droplet numbers, pristine aerosol conditions in the Arctic environment are therefore considered an important factor determining the lifetime of Arctic mixed-phase clouds.

The Arctic climate is changing; temperature changes in the Arctic are greater than at midlatitudes, and changing atmospheric conditions influence Arctic mixed-phase clouds, which are important for the Arctic surface energy budget. These low-level clouds are frequently observed across the Arctic. They impact the turbulent and radiative heating of the open water, snow, and sea-ice-covered surfaces and influence the boundary layer structure. Therefore the processes that affect mixed-phase cloud life cycles are extremely important, yet relatively poorly understood. In this study, we present sensitivity studies using semi-idealized large eddy simulations (LESs) to identify processes contributing to the dissipation of Arctic mixed-phase clouds. We found that one potential main contributor to the dissipation of an observed Arctic mixed-phase cloud, during the Arctic Summer Cloud Ocean Study (ASCOS) field campaign, was a low cloud droplet number concentration (CDNC) of about 2 cm(-3). Introducing a high ice crystal concentration of 10 L-1 also resulted in cloud dissipation, but such high ice crystal concentrations were deemed unlikely for the present case. Sensitivity studies simulating the advection of dry air above the boundary layer inversion, as well as a modest increase in ice crystal concentration of 1 L-1, did not lead to cloud dissipation. As a requirement for small droplet numbers, pristine aerosol conditions in the Arctic environment are therefore considered an important factor determining the lifetime of Arctic mixed-phase clouds.

The Arctic climate is changing; temperature changes in the Arctic are greater than at midlatitudes, and changing atmospheric conditions influence Arctic mixed-phase clouds, which are important for the Arctic surface energy budget. These low-level clouds are frequently observed across the Arctic. They impact the turbulent and radiative heating of the open water, snow, and sea-ice-covered surfaces and influence the boundary layer structure. Therefore the processes that affect mixed-phase cloud life cycles are extremely important, yet relatively poorly understood. In this study, we present sensitivity studies using semi-idealized large eddy simulations (LESs) to identify processes contributing to the dissipation of Arctic mixed-phase clouds. We found that one potential main contributor to the dissipation of an observed Arctic mixed-phase cloud, during the Arctic Summer Cloud Ocean Study (ASCOS) field campaign, was a low cloud droplet number concentration (CDNC) of about 2 cm-3. Introducing a high ice crystal concentration of 10 L-1 also resulted in cloud dissipation, but such high ice crystal concentrations were deemed unlikely for the present case. Sensitivity studies simulating the advection of dry air above the boundary layer inversion, as well as a modest increase in ice crystal concentration of 1 L-1, did not lead to cloud dissipation. As a requirement for small droplet numbers, pristine aerosol conditions in the Arctic environment are therefore considered an important factor determining the lifetime of Arctic mixed-phase clouds.

Arctic sea ice is declining rapidly and its annual ice extent minima reached record lows twice during the last decade. Large environmental and socioeconomic implications related to sea ice reduction in a warming world necessitate realistic simulations of the Arctic climate system, not least to formulate relevant environmental policies on an international scale. However, despite considerable progress in the last few decades, future climate projections from numerical models still exhibit the largest uncertainties over the polar regions. The lack of sufficient observations of essential climate variables is partly to blame for the poor representation of key atmospheric processes, and their coupling to the surface, in climate models. Observations from the hyper spectral Atmospheric Infrared Sounder (AIRS) instrument on board National Aeronautics and Space Administration (NASA)'s Aqua satellite are contributing toward improved understanding of the vertical structure of the atmosphere over the poles since 2002, including the lower troposphere. This part of the atmosphere is especially important in the Arctic, as it directly impacts sea ice and its short-term variability. Although in situ measurements provide invaluable ground truth, they are spatially and temporally inhomogeneous and sporadic over the Arctic. A growing number of studies are exploiting AIRS data to investigate the thermodynamic structure of the Arctic atmosphere, with applications ranging from understanding processes to deriving climatologies; all of which are also useful to test and improve parameterizations in climate models. As the AIRS data record now extends more than a decade, a select few of many such noteworthy applications of AIRS data over this challenging and rapidly changing landscape are highlighted here.

Mixed-phase clouds are an integral part of the Arctic climate system, for precipitation and for their interactions with radiation and thermodynamics. Mixed-phase processes are often poorly represented in global models and many use an empirically based diagnostic partition between the liquid and ice phases that is dependent solely on temperature. However, increasingly more complex microphysical parametrizations are being implemented allowing a more physical representation of mixed-phase clouds. This study uses in situ observations from the Arctic Summer Cloud Ocean Study (ASCOS) field campaign in the central Arctic to assess the impact of a change from a diagnostic to a prognostic parametrization of mixed-phase clouds and increased vertical resolution in the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecast System (IFS). The newer cloud scheme improves the representation of the vertical structure of mixed-phase clouds, with supercooled liquid water at cloud top and ice precipitating below, improved further with higher vertical resolution. Increased supercooled liquid water and decreased ice content are both in closer agreement with observations. However, these changes do not result in any substantial improvement in surface radiation, and a warm and moist bias in the lowest part of the atmosphere remains. Both schemes also fail to capture the transitions from overcast to cloud-free conditions. Moreover, whereas the observed cloud layer is frequently decoupled from the surface, the modelled clouds remain coupled to the surface most of the time. The changes implemented to the cloud scheme are an important step forward in improving the representation of Arctic clouds, but improvements in other aspects such as boundary-layer turbulence, cloud radiative properties, sensitivity to low aerosol concentrations and representation of the sea-ice surface may also need to be addressed.

The Arctic Clouds in Summer Experiment (ACSE) was conducted during summer and early autumn 2014, providing a detailed view of the seasonal transition from ice melt into freeze-up. Measurements were taken over both ice-free and ice-covered surfaces, near the ice edge, offering insight to the role of the surface state in shaping the atmospheric conditions. The initiation of the autumn freeze-up was related to a change in air mass, rather than to changes in solar radiation alone; the lower atmosphere cooled abruptly leading to a surface heat loss. During melt season, strong surface inversions persisted over the ice, while elevated inversions were more frequent over open water. These differences disappeared during autumn freeze-up, when elevated inversions persisted over both ice-free and ice-covered conditions. These results are in contrast to previous studies that found a well-mixed boundary layer persisting in summer and an increased frequency of surface-based inversions in autumn, suggesting that our knowledge derived from measurements taken within the pan-Arctic area and on the central ice-pack does not necessarily apply closer to the ice-edge. This study offers an insight to the atmospheric processes that occur during a crucial period of the year; understanding and accurately modeling these processes is essential for the improvement of ice-extent predictions and future Arctic climate projections.

Direct observations during intense warm-air advection over the East Siberian Sea reveal a period of rapid sea-ice melt. A semistationary, high-pressure system north of the Bering Strait forced northward advection of warm, moist air from the continent. Air-mass transformation over melting sea ice formed a strong, surface-based temperature inversion in which dense fog formed. This induced a positive net longwave radiation at the surface while reducing net solar radiation only marginally; the inversion also resulted in downward turbulent heat flux. The sum of these processes enhanced the surface energy flux by an average of similar to 15Wm(-2) for a week. Satellite images before and after the episode show sea-ice concentrations decreasing from > 90% to similar to 50% over a large area affected by the air-mass transformation. We argue that this rapid melt was triggered by the increased heat flux from the atmosphere due to the warm-air advection.

The climate in the Arctic is changing faster than anywhere else on earth. Poorly understood feedback processes relating to Arctic clouds and aerosol-cloud interactions contribute to a poor understanding of the present changes in the Arctic climate system, and also to a large spread in projections of future climate in the Arctic. The problem is exacerbated by the paucity of research-quality observations in the central Arctic. Improved formulations in climate models require such observations, which can only come from measurements in situ in this difficult-to-reach region with logistically demanding environmental conditions. The Arctic Summer Cloud Ocean Study (ASCOS) was the most extensive central Arctic Ocean expedition with an atmospheric focus during the International Polar Year (IPY) 2007-2008. ASCOS focused on the study of the formation and life cycle of low-level Arctic clouds. ASCOS departed from Longyearbyen on Svalbard on 2 August and returned on 9 September 2008. In transit into and out of the pack ice, four short research stations were undertaken in the Fram Strait: two in open water and two in the marginal ice zone. After traversing the pack ice northward, an ice camp was set up on 12 August at 87 degrees 21' N, 01 degrees 29' W and remained in operation through 1 September, drifting with the ice. During this time, extensive measurements were taken of atmospheric gas and particle chemistry and physics, mesoscale and boundary-layer meteorology, marine biology and chemistry, and upper ocean physics. ASCOS provides a unique interdisciplinary data set for development and testing of new hypotheses on cloud processes, their interactions with the sea ice and ocean and associated physical, chemical, and biological processes and interactions. For example, the first-ever quantitative observation of bubbles in Arctic leads, combined with the unique discovery of marine organic material, polymer gels with an origin in the ocean, inside cloud droplets suggests the possi

The climate in the Arctic is changing faster than anywhere else on earth. Poorly understood feedback processes relating to Arctic clouds and aerosol-cloud interactions contribute to a poor understanding of the present changes in the Arctic climate system, and also to a large spread in projections of future climate in the Arctic. The problem is exacerbated by the paucity of research-quality observations in the central Arctic. Improved formulations in climate models require such observations, which can only come from measurements in situ in this difficult-to-reach region with logistically demanding environmental conditions. The Arctic Summer Cloud Ocean Study (ASCOS) was the most extensive central Arctic Ocean expedition with an atmospheric focus during the International Polar Year (IPY) 2007-2008. ASCOS focused on the study of the formation and life cycle of low-level Arctic clouds. ASCOS departed from Longyearbyen on Svalbard on 2 August and returned on 9 September 2008. In transit into and out of the pack ice, four short research stations were undertaken in the Fram Strait: two in open water and two in the marginal ice zone. After traversing the pack ice northward, an ice camp was set up on 12 August at 87 degrees 21' N, 01 degrees 29' W and remained in operation through 1 September, drifting with the ice. During this time, extensive measurements were taken of atmospheric gas and particle chemistry and physics, mesoscale and boundary-layer meteorology, marine biology and chemistry, and upper ocean physics. ASCOS provides a unique interdisciplinary data set for development and testing of new hypotheses on cloud processes, their interactions with the sea ice and ocean and associated physical, chemical, and biological processes and interactions. For example, the first-ever quantitative observation of bubbles in Arctic leads, combined with the unique discovery of marine organic material, polymer gels with an origin in the ocean, inside cloud droplets suggests the possi

The vertical structure of Arctic low-level clouds and Arctic boundary layer is studied, using observations from ASCOS (Arctic Summer Cloud Ocean Study), in the central Arctic, in late summer 2008. Two general types of cloud structures are examined: the "neutrally stratified" and "stably stratified" clouds. Neutrally stratified are mixed-phase clouds where radiative-cooling near cloud top produces turbulence that generates a cloud-driven mixed layer. When this layer mixes with the surface-generated turbulence, the cloud layer is coupled to the surface, whereas when such an interaction does not occur, it remains decoupled; the latter state is most frequently observed. The decoupled clouds are usually higher compared to the coupled; differences in thickness or cloud water properties between the two cases are however not found. The surface fluxes are also very similar for both states. The decoupled clouds exhibit a bimodal thermodynamic structure, depending on the depth of the sub-cloud mixed layer (SCML): clouds with shallower SCMLs are disconnected from the surface by weak inversions, whereas those that lay over a deeper SCML are associated with stronger inversions at the decoupling height. Neutrally stratified clouds generally precipitate; the evaporation/sublimation of precipitation often enhances the decoupling state. Finally, stably stratified clouds are usually lower, geometrically and optically thinner, non-precipitating liquid-water clouds, not containing enough liquid to drive efficient mixing through cloud-top cooling.

The climate in the Arctic is changing faster than anywhere else on earth. Poorly understood feedback processes relating to Arctic clouds and aerosol-cloud interactions contribute to a poor understanding of the present changes in the Arctic climate system, and also to a large spread in projections of future climate in the Arctic. The problem is exacerbated by the paucity of research-quality observations in the central Arctic. Improved formulations in climate models require such observations, which can only come from measurements in situ in this difficult-to-reach region with logistically demanding environmental conditions. The Arctic Summer Cloud Ocean Study (ASCOS) was the most extensive central Arctic Ocean expedition with an atmospheric focus during the International Polar Year (IPY) 2007-2008. ASCOS focused on the study of the formation and life cycle of low-level Arctic clouds. ASCOS departed from Longyearbyen on Svalbard on 2 August and returned on 9 September 2008. In transit into and out of the pack ice, four short research stations were undertaken in the Fram Strait: two in open water and two in the marginal ice zone. After traversing the pack ice northward, an ice camp was set up on 12 August at 87 degrees 21' N, 01 degrees 29' W and remained in operation through 1 September, drifting with the ice. During this time, extensive measurements were taken of atmospheric gas and particle chemistry and physics, mesoscale and boundary-layer meteorology, marine biology and chemistry, and upper ocean physics. ASCOS provides a unique interdisciplinary data set for development and testing of new hypotheses on cloud processes, their interactions with the sea ice and ocean and associated physical, chemical, and biological processes and interactions. For example, the first-ever quantitative observation of bubbles in Arctic leads, combined with the unique discovery of marine organic material, polymer gels with an origin in the ocean, inside cloud droplets suggests the possi, AuthorCount:43

The Arctic climate system includes numerous highly interactive small-scale physical processes in the atmosphere, sea ice, and ocean. During and since the International Polar Year 2007-2009, significant advances have been made in understanding these processes. Here, these recent advances are reviewed, synthesized, and discussed. In atmospheric physics, the primary advances have been in cloud physics, radiative transfer, mesoscale cyclones, coastal, and fjordic processes as well as in boundary layer processes and surface fluxes. In sea ice and its snow cover, advances have been made in understanding of the surface albedo and its relationships with snow properties, the internal structure of sea ice, the heat and salt transfer in ice, the formation of superimposed ice and snow ice, and the small-scale dynamics of sea ice. For the ocean, significant advances have been related to exchange processes at the ice-ocean interface, diapycnal mixing, double-diffusive convection, tidal currents and diurnal resonance. Despite this recent progress, some of these small-scale physical processes are still not sufficiently understood: these include wave-turbulence interactions in the atmosphere and ocean, the exchange of heat and salt at the ice-ocean interface, and the mechanical weakening of sea ice. Many other processes are reasonably well understood as stand-alone processes but the challenge is to understand their interactions with and impacts and feedbacks on other processes. Uncertainty in the parameterization of small-scale processes continues to be among the greatest challenges facing climate modelling, particularly in high latitudes. Further improvements in parameterization require new year-round field campaigns on the Arctic sea ice, closely combined with satellite remote sensing studies and numerical model experiments., AuthorCount:16

Over the Arctic Ocean, little is known on cloud-generated buoyant overturning vertical motions within mixed-phase stratocumulus clouds. Characteristics of such motions are important for understanding the diabatic processes associated with the vertical motions, the lifetime of the cloud layer and its micro- and macrophysical characteristics. In this study, we exploit a suite of surface-based remote sensors over the high Arctic sea ice during a week-long period of persistent stratocumulus in August 2008 to derive the in-cloud vertical motion characteristics. In-cloud vertical velocity skewness and variance profiles are found to be strikingly different from observations within lower-latitude stratocumulus, suggesting these Arctic mixed-phase clouds interact differently with the atmospheric thermodynamics (cloud tops extending above a stable temperature inversion base) and with a different coupling state between surface and cloud. We find evidence of cloud-generated vertical mixing below cloud base, regardless of surface-cloud coupling state, although a decoupled surface-cloud state occurred most frequently. Detailed case studies are examined focusing on 3 levels within the cloud layer, where wavelet and power spectral analyses are applied to characterize the dominant temporal and horizontal scales associated with cloud-generated vertical motions. In general, we find a positively-correlated vertical motion signal amongst vertical levels within the cloud and across the full cloud layer depth. The coherency is dependent upon other non-cloud controlled factors, such as larger, mesoscale weather passages and radiative shielding of low-level stratocumulus by one or more cloud layers above. Despite the coherency in vertical velocity across the cloud, the velocity variances were always weaker near cloud top, relative to cloud mid and base. Taken in combination with the skewness, variance and thermodynamic profile characteristics, we observe vertical motions near cloud-top that

Observations of cloud properties and thermodynamics from two Arctic locations, Barrow, Alaska, and Surface Heat Budget of the Arctic (SHEBA), are examined. A comparison of in-cloud thermodynamic mixing characteristics for low-level, single-layer clouds from nearly a decade of data at Barrow and one full annual cycle over the sea ice at SHEBA is performed. These cloud types occur relatively frequently, evident in 27%-30% of all cloudy cases. To understand the role of liquid water path (LWP), or lack thereof, on static in-cloud mixing, cloud layers are separated into optically thin and optically thick LWP subclasses. Clouds with larger LWPs tend to have a deeper in-cloud mixed layer relative to optically thinner clouds. However, both cloud LWP subclasses are frequently characterized by an in-cloud stable layer above the mixed layer top. The depth of the stable layer generally correlates with an increased temperature gradient across the layer. This layer often contains a specific humidity inversion, but it is more frequently present when cloud LWP is optically thinner (LWP, 50 gm(-2)). It is suggested that horizontal thermodynamic advection plays a key role modifying the vertical extent of in-cloud mixing and likewise the depth of in-cloud stable layers. Furthermore, longwave atmospheric opacity above the cloud top is generally enhanced during cases with optically thinner clouds. Thermodynamic advection, cloud condensate distribution within the stable layer, and enhanced atmospheric radiation above the cloud are found to introduce a thermodynamic-radiative feedback that potentially modifies the extent of LWP and subsequent in-cloud mixing.

Unique measurements of vertical size-resolved aerosol particle concentrations, trace gas concentrations and meteorological data were obtained during the Arctic Summer Cloud Ocean Study (ASCOS, www.ascos.se), an International Polar Year project aimed at establishing the processes responsible for formation and evolution of low-level clouds over the high Arctic summer pack ice. The experiment was conducted from on board the Swedish icebreaker Oden, and provided both ship-and helicopter-based measurements. This study focuses on the vertical helicopter profiles and onboard measurements obtained during a three-week period when Oden was anchored to a drifting ice floe, and sheds light on the characteristics of Arctic aerosol particles and their distribution throughout the lower atmosphere. Distinct differences in aerosol particle characteristics within defined atmospheric layers are identified. Within the lowermost couple hundred metres, transport from the marginal ice zone (MIZ), condensational growth and cloud processing develop the aerosol population. During two of the four representative periods defined in this study, such influence is shown. At altitudes above about 1 km, long-range transport occurs frequently. However, only infrequently does large-scale subsidence descend such air masses to become entrained into the mixed layer in the high Arctic, and there-fore long-range transport plumes are unlikely to directly influence low-level stratiform cloud formation. Nonetheless, such plumes can influence the radiative balance of the planetary boundary layer (PBL) by influencing formation and evolution of higher clouds, as well as through precipitation transport of particles downwards. New particle formation was occasionally observed, particularly in the near-surface layer. We hypothesize that the origin of these ultrafine particles could be in biological processes, both primary and secondary, within the open leads between the pack ice and/or along the MIZ. In general, loc

Observations from the Arctic Summer Cloud Ocean Study (ASCOS), in the central Arctic sea-ice pack in late summer 2008, provide a detailed view of cloud-atmosphere-surface interactions and vertical mixing processes over the sea-ice environment. Measurements from a suite of ground-based remote sensors, near-surface meteorological and aerosol instruments, and profiles from radiosondes and a helicopter are combined to characterize a week-long period dominated by low-level, mixed-phase, stratocumulus clouds. Detailed case studies and statistical analyses are used to develop a conceptual model for the cloud and atmosphere structure and their interactions in this environment. Clouds were persistent during the period of study, having qualities that suggest they were sustained through a combination of advective influences and in-cloud processes, with little contribution from the surface. Radiative cooling near cloud top produced buoyancy-driven, turbulent eddies that contributed to cloud formation and created a cloud-driven mixed layer. The depth of this mixed layer was related to the amount of turbulence and condensed cloud water. Coupling of this cloud-driven mixed layer to the surface boundary layer was primarily determined by proximity. For 75% of the period of study, the primary stratocumulus cloud-driven mixed layer was decoupled from the surface and typically at a warmer potential temperature. Since the near-surface temperature was constrained by the ocean-ice mixture, warm temperatures aloft suggest that these air masses had not significantly interacted with the sea-ice surface. Instead, back-trajectory analyses suggest that these warm air masses advected into the central Arctic Basin from lower latitudes. Moisture and aerosol particles likely accompanied these air masses, providing necessary support for cloud formation. On the occasions when cloud-surface coupling did occur, back trajectories indicated that these air masses advected at low levels, while mixing proce

The record sea ice minimum (SIM) extents observed during the summers of 2007 and 2012 in the Arctic are stark evidence of accelerated sea ice loss during the last decade. Improving our understanding of the Arctic atmosphere and accurate quantification of its characteristics becomes ever more crucial, not least to improve predictions of such extreme events in the future. In this context, the Atmospheric Infrared Sounder (AIRS) instrument onboard NASA's Aqua satellite provides crucial insights due to its ability to provide 3-D information on atmospheric thermodynamics. Here, we facilitate comparisons in the evolution of the thermodynamic state of the Arctic atmosphere during these two SIM events using a decade-long AIRS observational record (2003-2012). It is shown that the meteorological conditions during 2012 were not extreme, but three factors of preconditioning from winter through early summer played an important role in accelerating sea ice melt. First, the marginal sea ice zones along the central Eurasian and North Atlantic sectors remained warm throughout winter and early spring in 2012 preventing thicker ice build-up. Second, the circulation pattern favoured efficient sea ice transport out of the Arctic in the Atlantic sector during late spring and early summer in 2012 compared to 2007. Third, additional warming over the Canadian archipelago and southeast Beaufort Sea from May onward further contributed to accelerated sea ice melt. All these factors may have lead the already thin and declining sea ice cover to pass below the previous sea ice extent minimum of 2007. In sharp contrast to 2007, negative surface temperature anomalies and increased cloudiness were observed over the East Siberian and Chukchi seas in the summer of 2012. The results suggest that satellite-based monitoring of atmospheric preconditioning could be a critical source of information in predicting extreme sea ice melting events in the Arctic.

A new satellite-derived climate dataset - denoted CLARA-A1 ("The CM SAF cLoud, Albedo and RAdiation dataset from AVHRR data") - is described. The dataset covers the 28 yr period from 1982 until 2009 and consists of cloud, surface albedo, and radiation budget products derived from the AVHRR (Advanced Very High Resolution Radiometer) sensor carried by polar-orbiting operational meteorological satellites. Its content, anticipated accuracies, limitations, and potential applications are described. The dataset is produced by the EUMETSAT Climate Monitoring Satellite Application Facility (CM SAF) project. The dataset has its strengths in the long duration, its foundation upon a homogenized AVHRR radiance data record, and in some unique features, e. g. the availability of 28 yr of summer surface albedo and cloudiness parameters over the polar regions. Quality characteristics are also well investigated and particularly useful results can be found over the tropics, mid to high latitudes and over nearly all oceanic areas. Being the first CM SAF dataset of its kind, an intensive evaluation of the quality of the datasets was performed and major findings with regard to merits and shortcomings of the datasets are reported. However, the CM SAF's long-term commitment to perform two additional reprocessing events within the time frame 2013-2018 will allow proper handling of limitations as well as upgrading the dataset with new features (e. g. uncertainty estimates) and extension of the temporal coverage.

Unique measurements of vertical size-resolved aerosol particle concentrations, trace gas concentrations and meteorological data were obtained during the Arctic Summer Cloud Ocean Study (ASCOS, www.ascos.se), an International Polar Year project aimed at establishing the processes responsible for formation and evolution of low-level clouds over the high Arctic summer pack ice. The experiment was conducted from on board the Swedish icebreaker Oden, and provided both ship-and helicopter-based measurements. This study focuses on the vertical helicopter profiles and onboard measurements obtained during a three-week period when Oden was anchored to a drifting ice floe, and sheds light on the characteristics of Arctic aerosol particles and their distribution throughout the lower atmosphere. Distinct differences in aerosol particle characteristics within defined atmospheric layers are identified. Within the lowermost couple hundred metres, transport from the marginal ice zone (MIZ), condensational growth and cloud processing develop the aerosol population. During two of the four representative periods defined in this study, such influence is shown. At altitudes above about 1 km, long-range transport occurs frequently. However, only infrequently does large-scale subsidence descend such air masses to become entrained into the mixed layer in the high Arctic, and there-fore long-range transport plumes are unlikely to directly influence low-level stratiform cloud formation. Nonetheless, such plumes can influence the radiative balance of the planetary boundary layer (PBL) by influencing formation and evolution of higher clouds, as well as through precipitation transport of particles downwards. New particle formation was occasionally observed, particularly in the near-surface layer. We hypothesize that the origin of these ultrafine particles could be in biological processes, both primary and secondary, within the open leads between the pack ice and/or along the MIZ. In general, loc

A new satellite-derived climate dataset - denoted CLARA-A1 ("The CM SAF cLoud, Albedo and RAdiation dataset from AVHRR data") - is described. The dataset covers the 28 yr period from 1982 until 2009 and consists of cloud, surface albedo, and radiation budget products derived from the AVHRR (Advanced Very High Resolution Radiometer) sensor carried by polar-orbiting operational meteorological satellites. Its content, anticipated accuracies, limitations, and potential applications are described. The dataset is produced by the EUMETSAT Climate Monitoring Satellite Application Facility (CM SAF) project. The dataset has its strengths in the long duration, its foundation upon a homogenized AVHRR radiance data record, and in some unique features, e. g. the availability of 28 yr of summer surface albedo and cloudiness parameters over the polar regions. Quality characteristics are also well investigated and particularly useful results can be found over the tropics, mid to high latitudes and over nearly all oceanic areas. Being the first CM SAF dataset of its kind, an intensive evaluation of the quality of the datasets was performed and major findings with regard to merits and shortcomings of the datasets are reported. However, the CM SAF's long-term commitment to perform two additional reprocessing events within the time frame 2013-2018 will allow proper handling of limitations as well as upgrading the dataset with new features (e. g. uncertainty estimates) and extension of the temporal coverage.

The record sea ice minimum (SIM) extents observed during the summers of 2007 and 2012 in the Arctic are stark evidence of accelerated sea ice loss during the last decade. Improving our understanding of the Arctic atmosphere and accurate quantification of its characteristics becomes ever more crucial, not least to improve predictions of such extreme events in the future. In this context, the Atmospheric Infrared Sounder (AIRS) instrument onboard NASA's Aqua satellite provides crucial insights due to its ability to provide 3-D information on atmospheric thermodynamics. Here, we facilitate comparisons in the evolution of the thermodynamic state of the Arctic atmosphere during these two SIM events using a decade-long AIRS observational record (2003-2012). It is shown that the meteorological conditions during 2012 were not extreme, but three factors of preconditioning from winter through early summer played an important role in accelerating sea ice melt. First, the marginal sea ice zones along the central Eurasian and North Atlantic sectors remained warm throughout winter and early spring in 2012 preventing thicker ice build-up. Second, the circulation pattern favoured efficient sea ice transport out of the Arctic in the Atlantic sector during late spring and early summer in 2012 compared to 2007. Third, additional warming over the Canadian archipelago and southeast Beaufort Sea from May onward further contributed to accelerated sea ice melt. All these factors may have lead the already thin and declining sea ice cover to pass below the previous sea ice extent minimum of 2007. In sharp contrast to 2007, negative surface temperature anomalies and increased cloudiness were observed over the East Siberian and Chukchi seas in the summer of 2012. The results suggest that satellite-based monitoring of atmospheric preconditioning could be a critical source of information in predicting extreme sea ice melting events in the Arctic.

Observations from the Arctic Summer Cloud Ocean Study (ASCOS), in the central Arctic sea-ice pack in late summer 2008, provide a detailed view of cloud-atmosphere-surface interactions and vertical mixing processes over the sea-ice environment. Measurements from a suite of ground-based remote sensors, near-surface meteorological and aerosol instruments, and profiles from radiosondes and a helicopter are combined to characterize a week-long period dominated by low-level, mixed-phase, stratocumulus clouds. Detailed case studies and statistical analyses are used to develop a conceptual model for the cloud and atmosphere structure and their interactions in this environment. Clouds were persistent during the period of study, having qualities that suggest they were sustained through a combination of advective influences and in-cloud processes, with little contribution from the surface. Radiative cooling near cloud top produced buoyancy-driven, turbulent eddies that contributed to cloud formation and created a cloud-driven mixed layer. The depth of this mixed layer was related to the amount of turbulence and condensed cloud water. Coupling of this cloud-driven mixed layer to the surface boundary layer was primarily determined by proximity. For 75% of the period of study, the primary stratocumulus cloud-driven mixed layer was decoupled from the surface and typically at a warmer potential temperature. Since the near-surface temperature was constrained by the ocean-ice mixture, warm temperatures aloft suggest that these air masses had not significantly interacted with the sea-ice surface. Instead, back-trajectory analyses suggest that these warm air masses advected into the central Arctic Basin from lower latitudes. Moisture and aerosol particles likely accompanied these air masses, providing necessary support for cloud formation. On the occasions when cloud-surface coupling did occur, back trajectories indicated that these air masses advected at low levels, while mixing proce