Cloud and boundary layer interactions over the Arctic sea ice in late summer

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 weeklong 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, backtrajectory 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 processes kept the mixed layer in equilibrium with the near-surface environment. Rather than contributing buoyancy forcing for the mixed-layer dynamics, the surface instead simply appeared to respond to the mixedlayer processes aloft. Clouds in these cases often contained slightly higher condensed water amounts, potentially due to additional moisture sources from below

Near-surface profiles of aerosol number concentration and temperature over the Arctic Ocean

Temperature and particle number concentration profiles were measured at small height intervals above open and frozen leads and snow surfaces in the central Arctic. The device used was a gradient pole designed to investigate potential particle sources over the central Arctic Ocean. The collected data were fitted according to basic logarithmic flux-profile relationships to calculate the sensible heat flux and particle deposition velocity. Independent measurements by the eddy covariance technique were conducted at the same location. General agreement was observed between the two methods when logarithmic profiles could be fitted to the gradient pole data. In general, snow surfaces behaved as weak particle sinks with a maximum deposition velocity vd = 1.3 mm s−1 measured with the gradient pole. The lead surface behaved as a weak particle source before freeze-up with an upward flux Fc = 5.7 × 104 particles m−2 s−1, and as a relatively strong heat source after freeze-up, with an upward maximum sensible heat flux H = 13.1 W m−2. Over the frozen lead, however, we were unable to resolve any significant aerosol profiles

Atmospheric conditions during the Arctic Clouds in Summer Experiment (ACSE): Contrasting open-water and sea-ice surfaces during melt and freeze-up seasons

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 into 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 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 into 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

Large-eddy simulation of a two-layer boundary-layer cloud system from the Arctic Ocean 2018 expedition

Climate change is particularly noticeable in the Arctic. The most common type of cloud at these latitudes is mixed-phase stratocumulus. These clouds occur frequently and persistently during all seasons and play a critical role in the Arctic energy budget. Previous observations in the central (north of 80&deg; N) Arctic have shown a high occurrence of prolonged periods of a shallow, single-layer mixed-phase stratocumulus at the top of the boundary layer (BL; altitudes ~300 to 400 m). However, recent observations from the summer of 2018 instead showed a prevalence of a two-layer boundary-layer cloud system. Here we use large-eddy simulation to examine the maintenance of one of the cloud systems observed in the summer of 2018 as well as the sensitivity of the cloud layers to different micro- and macro-scale parameters. We find that the model generally reproduces the observed thermodynamic structure well, with two near-neutrally stratified layers in the BL caused by a low cloud (located within the first few hundred meters) capped by a lower temperature inversion, and an upper cloud layer (based around one km or slightly higher) capped by the main temperature inversion of the BL. The investigated cloud structure is persistent unless there are low aerosol number concentrations (&le; 5 cm-3), which cause the upper cloud layer to dissipate, or high large-scale wind speeds (greater than or equal 8.5 m s-1), which erode the lower inversion and the related cloud layer. These types of changes in cloud structure lead to a substantial reduction of the net longwave radiation at the surface due to a lower emissivity or higher altitude of the remaining cloud layer. The findings highlight the importance of better understanding and representing aerosol sources and sinks over the central Arctic Ocean. Furthermore, they underline the significance of meteorological parameters, such as the large-scale wind speed, for maintaining the two-layer boundary-layer cloud structure encountered in the lower atmosphere of the central Arctic.</p

The impact of radiosounding observations on numerical weather prediction analyses in the Arctic

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 (12h forecasts) from ECMWF for January 2016 – 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

Arctic summer airmass transformation, surface inversions, and the surface energy budget

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

Measurement of wind profiles by motion-stabilised ship-borne Doppler lidar

Three months of Doppler lidar wind measurements were obtained during the Arctic Cloud Summer Experiment on the icebreaker Oden during the summer of 2014. Such ship-borne Doppler measurements require active stabilisation to remove the effects of ship motion. We demonstrate that the combination of a commercial Doppler lidar with a custom-made motion-stabilisation platform enables the retrieval of wind profiles in the Arctic atmospheric boundary layer during both cruising and ice-breaking with statistical uncertainties comparable to land-based measurements. This held true particularly within the atmospheric boundary layer even though the overall aerosol load was very low. Motion stabilisation was successful for high wind speeds in open water and the resulting wave conditions. It allows for the retrieval of vertical winds with a random error below 0.2 m s?1. The comparison of lidar-measured wind and radio soundings gives a mean bias of 0.3 m s?1 (2°) and a mean standard deviation of 1.1 m s?1 (12°) for wind speed (wind direction). The agreement for wind direction degrades with height. The combination of a motion-stabilised platform with a low-maintenance autonomous Doppler lidar has the potential to enable continuous long-term high-resolution ship-based wind profile measurements over the oceans.<br/

Shipborne eddy covariance observations of methane fluxes constrain Arctic sea emissions

We demonstrate direct eddy covariance (EC) observations of methane (CH4) fluxes between the sea and atmosphere from an icebreaker in the eastern Arctic Ocean. EC-derived CH4 emissions averaged 4.58, 1.74, and 0.14 mg m−2 day−1 in the Laptev, East Siberian, and Chukchi seas, respectively, corresponding to annual sea-wide fluxes of 0.83, 0.62, and 0.03 Tg year−1. These EC results answer concerns that previous diffusive emission estimates, which excluded bubbling, may underestimate total emissions. We assert that bubbling dominates sea-air CH4 fluxes in only small constrained areas: A ~100-m2 area of the East Siberian Sea showed sea-air CH4 fluxes exceeding 600 mg m−2 day−1; in a similarly sized area of the Laptev Sea, peak CH4 fluxes were ~170 mg m−2 day−1. Calculating additional emissions below the noise level of our EC system suggests total ESAS CH4 emissions of 3.02 Tg year−1, closely matching an earlier diffusive emission estimate of 2.9 Tg year−1

Direct determination of the air-sea CO₂ gas transfer velocity in Arctic sea-ice regions

The Arctic Ocean is an important sink for atmospheric CO₂. The impact of decreasing sea-ice extent and expanding marginal ice zones on Arctic air-sea CO₂ exchange depends on the rate of gas transfer in the presence of sea ice. Sea ice acts to limit air-sea gas exchange by reducing contact between air and water, but is also hypothesised to enhance gas transfer rates across surrounding open water surfaces through physical processes such as increased surface-ocean turbulence from ice-water shear and ice-edge form drag. Here we present the first direct determination of the CO₂ air-sea gas transfer velocity in a wide range of Arctic sea-ice conditions. We show that the gas transfer velocity increases near-linearly with decreasing sea-ice concentration. We also show that previous modeling approaches overestimate gas transfer rates in sea-ice regions

The Arctic summer atmosphere: an evaluation of reanalyses using ASCOS data

The Arctic has experienced large climate changes over recent decades, the largest for any region on Earth. To understand the underlying reasons for this climate sensitivity, reanalysis is an invaluable tool. The Arctic System Reanalysis (ASR) is a regional reanalysis, forced by ERA-Interim at the lateral boundaries and incorporating model physics adapted to Arctic conditions, developed to serve as a state-of-the-art, high-resolution synthesis tool for assessing Arctic climate variability and monitoring Arctic climate change. <br><br> We use data from Arctic Summer Cloud-Ocean Study (ASCOS) to evaluate the performance of ASR and ERA-Interim for the Arctic Ocean. The ASCOS field experiment was deployed on the Swedish icebreaker <i>Oden</i> north of 87° N in the Atlantic sector of the Arctic during August and early September 2008. Data were collected during the transits from and to Longyearbyen and the 3-week ice drift with <i>Oden</i> moored to a drifting multiyear ice floe. These data are independent and detailed enough to evaluate process descriptions. <br><br> The reanalyses captures basic meteorological variations coupled to the synoptic-scale systems, but have difficulties in estimating clouds and atmospheric moisture. While ERA-Interim has a systematic warm bias in the lowest troposphere, ASR has a cold bias of about the same magnitude on average. The results also indicate that more sophisticated descriptions of cloud microphysics in ASR did not significantly improve the modeling of cloud properties compared to ERA-Interim. This has consequences for the radiation balance, and hence the surface temperature, and illustrate how a modeling problem in one aspect of the atmosphere, here the clouds, feeds back to other parameters, especially near the surface and in the boundary layer