This study presents Cloudnet retrievals of Arctic clouds from measurements conducted during a 3-month research expedition along the Siberian shelf during summer and autumn 2014. During autumn, we find a strong reduction in the occurrence of liquid clouds and an increase for both mixed-phase and ice clouds at low levels compared to summer. About 80 % of all liquid clouds observed during the research cruise show a liquid water path below the infrared black body limit of approximately 50 g m(-2). The majority of mixed-phase and ice clouds had an ice water path below 20 g m(-2). Cloud properties are analysed with respect to cloud-top temperature and boundary layer structure. Changes in these parameters have little effect on the geometric thickness of liquid clouds while mixed-phase clouds during warm-air advection events are generally thinner than when such events were absent. Cloud-top temperatures are very similar for all mixed-phase clouds. However, more cases of lower cloudtop temperature were observed in the absence of warm-air advection. Profiles of liquid and ice water content are normalized with respect to cloud base and height. For liquid water clouds, the liquid water content profile reveals a strong increase with height with a maximum within the upper quarter of the clouds followed by a sharp decrease towards cloud top. Liquid water content is lowest for clouds observed below an inversion during warm-air advection events. Most mixedphase clouds show a liquid water content profile with a very similar shape to that of liquid clouds but with lower maximum values during events with warm air above the planetary boundary layer. The normalized ice water content profiles in mixed-phase clouds look different from those of liquid water content. They show a wider range in maximum values with the lowest ice water content for clouds below an inversion and the highest values for clouds above or extending through an inversion. The ice water content profile generally peaks at a height below the peak in the liquid water content profile - usually in the centre of the cloud, sometimes closer to cloud base, likely due to particle sublimation as the crystals fall through the cloud.

An ensemble of model runs with the COAMPS (c) regional model is compared to observations in the central Arctic for August 2001 from the Arctic Ocean Experiment 2001 (AOE-2001). The results are from a 6-km horizontal resolution 2nd, inner, nest of the model while the outermost model domain covers the pan-Arctic region, including the marginal ice zone and some of the land areas around the Arctic Ocean. Sea surface temperature and ice cover were prescribed from satellite data while sea-ice surface properties were modeled with an energy balance model, assuming a constant ice thickness. Five ensemble members were generated by altering the initialization time for the innermost nest, the surface roughness and the turbulent mixing scheme for clouds. The large size of the outer domain means that the model simulations have substantial deviations from the observations at synoptic-scale time scales. Therefore the evaluation focuses on statistical measures, rather than in details of individual ensemble member performance as compared directly to observations. In this context, the ensemble members are surprisingly similar even though details differ significantly. The ensemble average results features two main systematic problems: a consistent temperature bias, with too low temperatures below 2-3 km and slightly high temperatures through the rest of the troposphere, and a significant underestimation of the lowest clouds. In terms of total cloud cover, however, the model produces a realistic result; it is the very lowest clouds that are essentially missing. The temperature bias initially appears to be related to an interaction between clouds and radiation; the shape of the mean radiative heating-rate profile is very similar to that of the temperature bias. The lack of the lowest clouds could be due to the too low temperatures in conjunction with a cloud scheme that overestimates the transfer of cloud droplets to ice particles that precipitate. The different terms in the surface energy balance as well as the surface stress has only small systematic errors and are surprisingly consistent between the members.

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 extension of cloud into the temperature inversion-a unique feature of Arctic clouds.

The Arctic climate system is host to many processes which interact vertically over the tightly coupled atmosphere, sea ice and ocean. The coupled Atmosphere-Ocean Single-Column Model (AOSCM) allows to decouple local small-scale and large-scale processes to investigate the model performance in an idealized setting. Here, an observed Arctic warm air intrusion event is used to show how to identify model deficiencies using the AOSCM. The AOSCM allows us to effectively produce a large number of perturbation simulations, around 1,000, to map sensitivities of the model results due to changes in physical and model properties as well as to the large-scale tendencies. The analysis of the summary diagnostics, that is, aggregated results from sensitivity experiments evaluated against modeled physical properties, such as surface energy budget and mean sea ice thickness, reveals sensitivities to the chosen parameters. Further, we discuss how the conclusions can be used to understand the behavior of the global host model. The simulations confirm that the horizontal advection of heat and moisture plays an important role for maintaining a low-level cloud cover, as in earlier studies. The combined cloud layers increase the energy input to the surface, which in turn enhances the ongoing melt. The clouds present an additional sensitivity in terms of how they are represented but also their interaction with the large-scale advection and the model time step. The methodology can be used for a variety of other regions, where the coupling to the ocean is important.

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 radiosounding network in the Arctic, despite being sparse, is a crucial part of the atmospheric observing system for weather prediction and reanalysis. The spatial coverage of the network was evaluated using a numerical weather prediction model, comparing radiosonde observations from Arctic land stations and expeditions in the central Arctic Ocean with operational analyses and background fields (12-hr forecasts) from European Centre for Medium-Range Weather Forecasts for January 2016 to September 2018. The results show that the impact of radiosonde observations on analyses has large geographical variation. In data-sparse areas, such as the central Arctic Ocean, high-quality radiosonde observations substantially improve the analyses, while satellite observations are not able to compensate for the large spatial gap in the radiosounding network. In areas where the network is reasonably dense, the quality of background field is more related to how radiosonde observations are utilized in the assimilation and to the quality of those observations.

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.

Snow surface and sea-ice energy budgets were measured near 87.5A degrees N during the Arctic Summer Cloud Ocean Study (ASCOS), from August to early September 2008. Surface temperature indicated four distinct temperature regimes, characterized by varying cloud, thermodynamic and solar properties. An initial warm, melt-season regime was interrupted by a 3-day cold regime where temperatures dropped from near zero to -7A degrees C. Subsequently mean energy budget residuals remained small and near zero for 1 week until once again temperatures dropped rapidly and the energy budget residuals became negative. Energy budget transitions were dominated by the net radiative fluxes, largely controlled by the cloudiness. Variable heat, moisture and cloud distributions were associated with changing air-masses. Surface cloud radiative forcing, the net radiative effect of clouds on the surface relative to clear skies, is estimated. Shortwave cloud forcing ranged between -50 W m(-2) and zero and varied significantly with surface albedo, solar zenith angle and cloud liquid water. Longwave cloud forcing was larger and generally ranged between 65 and 85 W m(-2), except when the cloud fraction was tenuous or contained little liquid water; thus the net effect of the clouds was to warm the surface. Both cold periods occurred under tenuous, or altogether absent, low-level clouds containing little liquid water, effectively reducing the cloud greenhouse effect. Freeze-up progression was enhanced by a combination of increasing solar zenith angles and surface albedo, while inhibited by a large, positive surface cloud forcing until a new air-mass with considerably less cloudiness advected over the experiment area.

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.

Data from the Arctic Ocean Experiment 2001 (AOE-2001) are used to study the vertical structure and diurnal cycle of the summertime central Arctic cloud-capped boundary layer. Mean conditions show a shallow stratocumulus-capped boundary layer, with a nearly moist neutrally stratified cloud layer, although cloud tops often penetrated into the stable inversion. The subcloud layer was more often stably stratified. Conditions near the surface were relatively steady, with a strong control on temperature and moisture by the melting ice surface. A statistically significant diurnal cycle was found in many parameters, although weak in near-surface temperature and moisture. Near-surface wind speed and direction and friction velocity had a pronounced cycle, while turbulent kinetic energy showed no significant diurnal variability. The cloud layer had the most pronounced diurnal variability, with lowest cloud-base height midday followed by enhanced drizzle and temporarily higher cloud-top heights in the afternoon. This is opposite to the cycle found in midlatitude or subtropical marine stratocumulus. The cloud layer was warmest (coolest) and more (less) stably stratified midafternoon (midmorning), coinciding with the coolest (warmest) but least (most) stably stratified capping inversion layer. It is speculated that drizzle is important in regulating the diurnal variability in the cloud layer, facilitated by enhanced midday mixing due to a differential diurnal variability in cloud and subcloud layer stability. Changing the Arctic aerosol climate could change these clouds to a more typical "marine stratocumulus structure," which could act as a negative feedback on Arctic warming.

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.