Surface Heat Budget Of The Arctic Ocean Research Articles

The characteristics of atmospheric boundary layer height over the Arctic Ocean during MOSAiC

Abstract. The important roles that the atmospheric boundary layer (ABL) plays in the central Arctic climate system have been recognized, but the atmospheric boundary layer height (ABLH), defined as the layer of continuous turbulence adjacent to the surface, has rarely been investigated. Using a year-round radiosonde dataset during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition, we improve a Richardson-number-based algorithm that takes cloud effects into consideration and subsequently analyze the characteristics and variability of the ABLH over the Arctic Ocean. The results reveal that the annual cycle is clearly characterized by a distinct peak in May and two respective minima in January and July. This annual variation in the ABLH is primarily controlled by the evolution of the ABL thermal structure. Temperature inversions in the winter and summer are intensified by seasonal radiative cooling and warm-air advection with the surface temperature constrained by melting, respectively, leading to the low ABLH at these times. Meteorological and turbulence variables also play a significant role in ABLH variation, including the near-surface potential temperature gradient, friction velocity, and turbulent kinetic energy (TKE) dissipation rate. In addition, the MOSAiC ABLH is more suppressed than the ABLH during the Surface Heat Budget of the Arctic Ocean (SHEBA) experiment in the summer, which indicates that there is large variability in the Arctic ABL structure during the summer melting season.

Modeling sea ice albedo and transmittance measurements with a fully-coupled radiative transfer model.

A rigorous treatment of the sea ice medium has been incorporated in the advanced Coupled Ocean-Atmosphere Radiative Transfer (COART) model. The inherent optical properties (IOPs) of brine pockets and air bubbles over the 0.25-4.0 µm spectral region are parameterized as a function of the sea ice physical properties (temperature, salinity and density). We then test the performance of the upgraded COART model using three physically-based modeling approaches to simulate the spectral albedo and transmittance of sea ice, and compare them with measurements collected during the Impacts of Climate on the Ecosystems and Chemistry of the Arctic Pacific Environment (ICESCAPE) and the Surface Heat Budget of the Arctic Ocean (SHEBA) field campaigns. The observations are adequately simulated when at least three layers are used to represent bare ice, including a thin surface scattering layer (SSL), and two layers to represent ponded ice. Treating the SSL as a low-density ice layer yields better model-observation agreement than treating it as a snow-like layer. Sensitivity results indicate that air volume (which determines the ice density) has the largest impact on the simulated fluxes. The vertical profile of density drives the optical properties but available measurements are scarce. The approach where the scattering coefficient for the bubbles is inferred in lieu of density leads to essentially equivalent modeling results. For ponded ice, the albedo and transmittance in the visible are mainly determined by the optical properties of the ice underlying the water layer. Possible contamination from light-absorbing impurities, such as black carbon or ice algae, is also implemented in the model and is able to effectively reduce the albedo and transmittance in the visible spectrum to further improve the model-observation agreement.

Arctic sea ice albedo: Spectral composition, spatial heterogeneity, and temporal evolution observed during the MOSAiC drift

The magnitude, spectral composition, and variability of the Arctic sea ice surface albedo are key to understanding and numerically simulating Earth’s shortwave energy budget. Spectral and broadband albedos of Arctic sea ice were spatially and temporally sampled by on-ice observers along individual survey lines throughout the sunlit season (April–September, 2020) during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition. The seasonal evolution of albedo for the MOSAiC year was constructed from spatially averaged broadband albedo values for each line. Specific locations were identified as representative of individual ice surface types, including accumulated dry snow, melting snow, bare and melting ice, melting and refreezing ponded ice, and sediment-laden ice. The area-averaged seasonal progression of total albedo recorded during MOSAiC showed remarkable similarity to that recorded 22 years prior on multiyear sea ice during the Surface Heat Budget of the Arctic Ocean (SHEBA) expedition. In accord with these and other previous field efforts, the spectral albedo of relatively thick, snow-free, melting sea ice shows invariance across location, decade, and ice type. In particular, the albedo of snow-free, melting seasonal ice was indistinguishable from that of snow-free, melting second-year ice, suggesting that the highly scattering surface layer that forms on sea ice during the summer is robust and stabilizing. In contrast, the albedo of ponded ice was observed to be highly variable at visible wavelengths. Notable temporal changes in albedo were documented during melt and freeze onset, formation and deepening of melt ponds, and during melt evolution of sediment-laden ice. While model simulations show considerable agreement with the observed seasonal albedo progression, disparities suggest the need to improve how the albedo of both ponded ice and thin, melting ice are simulated.

Impacts of active satellite sensors' low-level cloud detection limitations on cloud radiative forcing in the Arctic

Abstract. Previous studies revealed that satellites sensors with the best detection capability identify 25 %–40 % and 0 %–25 % fewer clouds below 0.5 and between 0.5–1.0 km, respectively, over the Arctic. Quantifying the impacts of cloud detection limitations on the radiation flux are critical especially over the Arctic Ocean considering the dramatic changes in Arctic sea ice. In this study, the proxies of the space-based radar, CloudSat, and lidar, CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations), cloud masks are derived based on simulated radar reflectivity with QuickBeam and cloud optical thickness using retrieved cloud properties from surface-based radar and lidar during the Surface Heat Budget of the Arctic Ocean (SHEBA) experiment. Limitations in low-level cloud detection by the space-based active sensors, and the impact of these limitations on the radiation fluxes at the surface and the top of the atmosphere (TOA), are estimated with radiative transfer model Streamer. The results show that the combined CloudSat and CALIPSO product generally detects all clouds above 1 km, while detecting 25 % (9 %) fewer in absolute values below 600 m (600 m to 1 km) than surface observations. These detection limitations lead to uncertainties in the monthly mean cloud radiative forcing (CRF), with maximum absolute monthly mean values of 2.5 and 3.4 Wm−2 at the surface and TOA, respectively. Cloud information from only CALIPSO or CloudSat lead to larger cloud detection differences compared to the surface observations and larger CRF uncertainties with absolute monthly means larger than 10.0 Wm−2 at the surface and TOA. The uncertainties for individual cases are larger – up to 30 Wm−2. These uncertainties need to be considered when radiation flux products from CloudSat and CALIPSO are used in climate and weather studies.

On the u☆-U Relationship in the Stable Atmospheric Boundary Layer over Arctic Sea Ice

A relationship between the friction velocity u☆ and mean wind speed U in a stable atmospheric boundary layer (ABL) over Arctic sea ice was considered. To that aim, the observations collected during the Surface Heat Budget of the Arctic Ocean (SHEBA) experiment were used. The observations showed the so-called “hockey-stick” shape of the u☆−U relationship, which consists of a slow increase of u☆ with increasing wind speed for U<Utr and a more rapid almost linear increase of u☆ for U>Utr, where Utr is the wind speed of transition between the two regimes. Such a relationship is most pronounced at the highest observational levels, namely at 9 and 14 m, and is also sharper when the air-surface temperature difference exceeds its average values for stable conditions. It is shown that the Monin–Obukhov similarity theory (MOST) reproduces the observed u☆−U relationship rather well. This suggests that at least for the SHEBA dataset, there is no contradiction between MOST and the “hockey-stick” shape of the u☆−U relationship. However, the SHEBA data, as well as the single-column simulations show that for cases with strong stability, u☆ significantly decreases with height due to the shallowness of the ABL. It was shown that when u☆ was assumed independent of height, the value of the normalized drag coefficient, i.e., of the so-called stability correction function for momentum, calculated using observations at a certain level, can be significantly underestimated. To overcome this, the decrease of u☆ with height was taken into account in the framework of MOST using local scaling instead of the scaling with surface fluxes. Using such an extended MOST brought the estimates of the normalized drag coefficient closer to the Businger–Dyer relation.

Meteorological and cloud conditions during the Arctic Ocean 2018 expedition

Abstract. The Arctic Ocean 2018 (AO2018) took place in the central Arctic Ocean in August and September 2018 on the Swedish icebreaker Oden. An extensive suite of instrumentation provided detailed measurements of surface water chemistry and biology, sea ice and ocean physical and biogeochemical properties, surface exchange processes, aerosols, clouds, and the state of the atmosphere. The measurements provide important information on the coupling of the ocean and ice surface to the atmosphere and in particular to clouds. This paper provides (i) an overview of the synoptic-scale atmospheric conditions and their climatological anomaly to help interpret the process studies and put the detailed observations from AO2018 into a larger context, both spatially and temporally; (ii) a statistical analysis of the thermodynamic and near-surface meteorological conditions, boundary layer, cloud, and fog characteristics; and (iii) a comparison of the results to observations from earlier Arctic Ocean expeditions – in particular AOE1996 (Arctic Ocean Expedition 1996), SHEBA (Surface Heat Budget of the Arctic Ocean), AOE2001 (Arctic Ocean Experiment 2001), ASCOS (Arctic Summer Cloud Ocean Study), ACSE (Arctic Clouds in Summer Experiment), and AO2016 (Arctic Ocean 2016) – to provide an assessment of the representativeness of the measurements. The results show that near-surface conditions were broadly comparable to earlier experiments; however the thermodynamic vertical structure was quite different. An unusually high frequency of well-mixed boundary layers up to about 1 km depth occurred, and only a few cases of the “prototypical” Arctic summer single-layer stratocumulus deck were observed. Instead, an unexpectedly high amount of multiple cloud layers and mid-level clouds were present throughout the campaign. These differences from previous studies are related to the high frequency of cyclonic activity in the central Arctic in 2018.

Following moist intrusions into the Arctic using SHEBA observations in a Lagrangian perspective

AbstractWarm and moist air masses are transported into the Arctic from lower latitudes throughout the year. Especially in winter, such moist intrusions (MIs) can trigger cloud formation and surface warming. While a typical cloudy state of the Arctic winter boundary layer has been linked to the advection of moist air masses, direct observations of the transformation from moist midlatitude to dry Arctic air are lacking. Here, we have used observations from the Surface Heat Budget of the Arctic Ocean (SHEBA) project to compile Eulerian observations along the trajectories of warm and cold air masses in a Lagrangian sense, showing the cooling and drying of air masses over sea ice and moistening over the open ocean. Air masses originating mostly over open water generate cloudy conditions over the observation site, whereas air masses originating over continents or sea ice generate radiatively clear conditions. We recommend using our case‐studies and the method of linking expeditions to station soundings via back‐trajectories for modelling work in future campaigns.

New Modified and Extended Stability Functions for the Stable Boundary Layer based on SHEBA and Parametrizations of Bulk Transfer Coefficients for Climate Models

Abstract Climate models still have deficits in reproducing the surface energy and momentum budgets in Arctic regions. One of the reasons is that currently used transfer coefficients occurring in parameterizations of the turbulent fluxes are based on stability functions derived from measurements over land and not over sea ice. An improved parameterization is developed using the Monin–Obukhov similarity theory (MOST) and corresponding stability functions that reproduce measurements over sea ice obtained during the Surface Heat Budget of the Arctic Ocean (SHEBA) campaign. The new stability functions for the stable surface layer represent a modification of earlier ones also based on SHEBA measurements. It is shown that the new functions are superior to the former ones with respect to the representation of the measured relationship between the MOST stability parameter and the bulk Richardson number. Nevertheless, the functions fulfill the same criteria of applicability as the earlier functions and contain, as an extension, a dependence on the neutral-limit turbulent Prandtl number. Applying the new functions we develop an efficient noniterative parameterization of the near-surface turbulent fluxes of momentum and heat with transfer coefficients as a function of the bulk Richardson number (Rib) and roughness parameters. A hierarchy of transfer coefficients is recommended for weather and climate models. They agree better with SHEBA data for strong stability (Rib > 0.1) than previous parameterizations and they agree well with those based on the Businger–Dyer functions in the range Rib ≤ 0.1.

Annual Cycles of Sea Ice Motion and Deformation Derived From Buoy Measurements in the Western Arctic Ocean Over Two Ice Seasons

AbstractData collected by two buoy arrays that operated during the ice seasons of 2014/2015 and 2016/2017 were used to characterize annual cycles of ice motion and deformation in the western Arctic Ocean. An anomalously strong and weak Beaufort Gyre in 2014/2015 and 2016/2017 induced generally anticyclonic and cyclonic sea ice drift during 2014/2015 and 2016/2017, respectively. Cyclonic ice motion resulted in higher contributions of ice divergence to total ice deformation in 2016/2017 than in 2014/2015. In 2014, the autumn ice concentration and multiyear ice coverage were higher than in 2016; consequently, the response of ice motion to wind forcing was weak, and less ice deformation was observed in autumn 2014. During the autumn‐winter transition, the ice‐wind speed ratio, ice deformation rate and its spatial and temporal scaling exponents, and localization of ice deformation decreased markedly in both 2014/2015 and 2016/2017 as a result of freeze‐up and consolidation of ice floes. Such dynamic behavior was maintained through to spring with the further thickening of ice cover. Ice deformation increased due to weakened ice strength as summer approached. The amplitude of the annual cycle of ice deformation rate in the western Arctic Ocean in 2014/2015 and especially in 2016/2017 was larger than that observed during the Surface Heat Budget of the Arctic Ocean (SHEBA) program in 1997/1998. We attribute this phenomenon to ice loss during the recent summers, especially of thick multiyear ice.

Meteorological conditions in a thinner Arctic sea ice regime from winter to summer during the Norwegian Young Sea Ice expedition (N‐ICE2015)

AbstractAtmospheric measurements were made over Arctic sea ice north of Svalbard from winter to early summer (January–June) 2015 during the Norwegian Young Sea Ice (N‐ICE2015) expedition. These measurements, which are available publicly, represent a comprehensive meteorological data set covering the seasonal transition in the Arctic Basin over the new, thinner sea ice regime. Winter was characterized by a succession of storms that produced short‐lived (less than 48 h) temperature increases of 20 to 30 K at the surface. These storms were driven by the hemispheric scale circulation pattern with a large meridional component of the polar jet stream steering North Atlantic storms into the high Arctic. Nonstorm periods during winter were characterized by strong surface temperature inversions due to strong radiative cooling (“radiatively clear state”). The strength and depth of these inversions were similar to those during the Surface Heat Budget of the Arctic Ocean (SHEBA) campaign. In contrast, atmospheric profiles during the “opaquely cloudy state” were different to those from SHEBA due to differences in the synoptic conditions and location within the ice pack. Storm events observed during spring/summer were the result of synoptic systems located in the Barents Sea and the Arctic Basin rather than passing directly over N‐ICE2015. These synoptic systems were driven by a large‐scale circulation pattern typical of recent years, with an Arctic Dipole pattern developing during June. Surface temperatures became near‐constant 0°C on 1 June marking the beginning of summer. Atmospheric profiles during the spring and early summer show persistent lifted temperature and moisture inversions that are indicative of clouds and cloud processes.

Assessment of Gradient-Based Similarity Functions in the Stable Boundary Layer Derived from a Large-Eddy Simulation

Gradient-based similarity functions, evaluated based on data generated by a large-eddy simulation model of the stably stratified boundary layer, are compared with analogous similarity functions, derived from field observations in the surface layer during the Surface Heat Budget of the Arctic Ocean (SHEBA) experiment in the Arctic. The comparison is performed in terms of explicit and implicit local scaling systems, for the temperature and momentum fluxes, standard deviations of the vertical velocity and of temperature, as well as dissipation rates for the turbulent kinetic energy and for the temperature variance. The comparison shows the best agreement of the SHEBA-based similarity functions with analogous functions evaluated using the large-eddy simulation data in the range of the Richardson number \(0.01<{ Ri}< 0.1\).

Linking atmospheric synoptic transport, cloud phase, surface energy fluxes, and sea-ice growth: observations of midwinter SHEBA conditions

Observations from the Surface Heat Budget of the Arctic Ocean (SHEBA) project are used to describe a sequence of events linking midwinter long-range advection of atmospheric heat and moisture into the Arctic Basin, formation of supercooled liquid water clouds, enhancement of net surface energy fluxes through increased downwelling longwave radiation, and reduction in near-surface conductive heat flux loss due to a warming of the surface, thereby leading to a reduction in sea-ice bottom growth. The analyses provide details of two events during Jan. 1–12, 1998, one entering the Arctic through Fram Strait and the other from northeast Siberia; winter statistics extend the results. Both deep, precipitating frontal clouds and post-frontal stratocumulus clouds impact the surface radiation and energy budget. Cloud liquid water, occurring preferentially in stratocumulus clouds extending into the base of the inversion, provides the strongest impact on surface radiation and hence modulates the surface forcing, as found previously. The observations suggest a minimum water vapor threshold, likely case dependent, for producing liquid water clouds. Through responses to the radiative forcing and surface warming, this cloud liquid water also modulates the turbulent and conductive heat fluxes, and produces a thermal wave penetrating into the sea ice. About 20–33 % of the observed variations of bottom ice growth can be directly linked to variations in surface conductive heat flux, with retarded ice growth occurring several days after these moisture plumes reduce the surface conductive heat flux. This sequence of events modulate pack-ice wintertime environmental conditions and total ice growth, and has implications for the annual sea-ice evolution, especially for the current conditions of extensive thinner ice.

Improving the WRF model's (version 3.6.1) simulation over sea ice surface through coupling with a complex thermodynamic sea ice model (HIGHTSI)

Abstract. Sea ice plays an important role in the air–ice–ocean interaction, but it is often represented simply in many regional atmospheric models. The Noah sea ice scheme, which is the only option in the current Weather Research and Forecasting (WRF) model (version 3.6.1), has a problem of energy imbalance due to its simplification in snow processes and lack of ablation and accretion processes in ice. Validated against the Surface Heat Budget of the Arctic Ocean (SHEBA) in situ observations, Noah underestimates the sea ice temperature which can reach −10 °C in winter. Sensitivity tests show that this bias is mainly attributed to the simulation within the ice when a time-dependent ice thickness is specified. Compared with the Noah sea ice model, the high-resolution thermodynamic snow and ice model (HIGHTSI) uses more realistic thermodynamics for snow and ice. Most importantly, HIGHTSI includes the ablation and accretion processes of sea ice and uses an interpolation method which can ensure the heat conservation during its integration. These allow the HIGHTSI to better resolve the energy balance in the sea ice, and the bias in sea ice temperature is reduced considerably. When HIGHTSI is coupled with the WRF model, the simulation of sea ice temperature by the original Polar WRF is greatly improved. Considering the bias with reference to SHEBA observations, WRF-HIGHTSI improves the simulation of surface temperature, 2 m air temperature and surface upward long-wave radiation flux in winter by 6, 5 °C and 20 W m−2, respectively. A discussion on the impact of specifying sea ice thickness in the WRF model is presented. Consistent with previous research, prescribing the sea ice thickness with observational information results in the best simulation among the available methods. If no observational information is available, we present a new method in which the sea ice thickness is initialized from empirical estimation and its further change is predicted by a complex thermodynamic sea ice model. The ice thickness simulated by this method depends much on the quality of the initial guess of the ice thickness and the role of the ice dynamic processes.

An Evaluation of HIRS Near-Surface Air Temperature Product in the Arctic with SHEBA Data

AbstractThe accuracy of cloud-screened 2-m air temperatures derived from the intersatellite-calibrated brightness temperatures based on the High Resolution Infrared Radiation Sounder (HIRS) measurements on board the National Oceanic and Atmospheric Administration (NOAA) Polar-Orbiting Operational Environmental Satellite (POES) series is evaluated by comparing HIRS air temperatures to 1-yr quality-controlled measurements collected during the Surface Heat Budget of the Arctic Ocean (SHEBA) project (October 1997–September 1998). The mean error between collocated HIRS and SHEBA 2-m air temperature is found to be on the order of 1°C, with a slight sensitivity to spatial and temporal radii for collocation. The HIRS temperatures capture well the temporal variability of SHEBA temperatures, with cross-correlation coefficients higher than 0.93, all significant at the 99.9% confidence level. More than 87% of SHEBA temperature variance can be explained by linear regression of collocated HIRS temperatures. The analysis found a strong dependency of mean temperature errors on cloud conditions observed during SHEBA, indicating that availability of an accurate cloud mask in the region is essential to further improve the quality of HIRS near-surface air temperature products. This evaluation establishes a baseline of accuracy of HIRS temperature retrievals, providing users with information on uncertainty sources and estimates. It is a first step toward development of a new long-term 2-m air temperature product in the Arctic that utilizes intersatellite-calibrated remote sensing data from the HIRS instrument.

Seasonal evolution of melt ponds on Arctic sea ice

AbstractThe seasonal evolution of melt ponds has been well documented on multiyear and landfast first‐year sea ice, but is critically lacking on drifting, first‐year sea ice, which is becoming increasingly prevalent in the Arctic. Using 1 m resolution panchromatic satellite imagery paired with airborne and in situ data, we evaluated melt pond evolution for an entire melt season on drifting first‐year and multiyear sea ice near the 2011 Applied Physics Laboratory Ice Station (APLIS) site in the Beaufort and Chukchi seas. A new algorithm was developed to classify the imagery into sea ice, thin ice, melt pond, and open water classes on two contrasting ice types: first‐year and multiyear sea ice. Surprisingly, melt ponds formed ∼3 weeks earlier on multiyear ice. Both ice types had comparable mean snow depths, but multiyear ice had 0–5 cm deep snow covering ∼37% of its surveyed area, which may have facilitated earlier melt due to its low surface albedo compared to thicker snow. Maximum pond fractions were 53 ± 3% and 38 ± 3% on first‐year and multiyear ice, respectively. APLIS pond fractions were compared with those from the Surface Heat Budget of the Arctic Ocean (SHEBA) field campaign. APLIS exhibited earlier melt and double the maximum pond fraction, which was in part due to the greater presence of thin snow and first‐year ice at APLIS. These results reveal considerable differences in pond formation between ice types, and underscore the importance of snow depth distributions in the timing and progression of melt pond formation.

Spatial Variability of Surface-Level State Variables over Arctic Sea Ice

AbstractNumerical models of the atmosphere, oceans, and sea ice are divided into horizontal grid cells that can range in size from a few kilometers to hundreds of kilometers. In these models, many surface-level variables are assumed to be uniform over a grid cell. Using a year of in situ data from the experiment to study the Surface Heat Budget of the Arctic Ocean (SHEBA), the authors investigate the accuracy of this assumption of gridcell uniformity for the surface-level variables pressure, air temperature, wind speed, humidity, and incoming longwave radiation. The paper bases its analysis on three statistics: the monthly average and, for each season, the spatial correlation function and the spatial bias. For five SHEBA sites, which had a maximum separation of 12 km, the analysis supports the assumption of gridcell uniformity in pressure, air temperature, wind speed, and humidity in all seasons. In winter, when the incidence of fractional cloudiness is largest, the incoming longwave radiation may not be uniform over a grid cell. In other seasons, the bimodal distribution in cloud cover—either clear skies or total cloud cover—tends to homogenize the incoming radiation at scales of 12 km and less.

A Shear-Based Parameterization of Turbulent Mixing in the Stable Atmospheric Boundary Layer

AbstractIn this study, shear-based parameterizations of turbulent mixing in the stable atmospheric boundary layer (SABL) are proposed. A relevant length-scale estimate for the mixing length of the turbulent momentum field is constructed from the turbulent kinetic energy and the mean shear rate S as . Using observational data from two field campaigns—the Surface Heat Budget of the Arctic Ocean (SHEBA) experiment and the 1999 Cooperative Atmosphere–Surface Exchange Study (CASES-99)— is shown to have a strong correlation with . The relationship between and corresponds to the ratio of the magnitude of the tangential components of the turbulent momentum flux tensor to , known as stress intensity ratio, . The field data clearly show that is linked to stability. The stress intensity ratio also depends on the flow energetics that can be assessed using a shear-production Reynolds number, , where P is shear production of turbulent kinetic energy and is the kinematic viscosity. This analysis shows that high mixing rates can indeed persist at strong stability. On this basis, shear-based parameterizations are proposed for the eddy diffusivity for momentum, , and eddy diffusivity for heat, , showing remarkable agreement with the exact quantities. Furthermore, a broader assessment of the proposed parameterizations is given through an a priori evaluation of large-eddy simulation (LES) data from the first GEWEX Atmospheric Boundary Layer Study (GABLS). The shear-based parameterizations outperform many existing models in predicting turbulent mixing in the SABL. The results of this study provide a framework for improved representation of the SABL in operational models.

Cloud Microphysical Properties Retrieved from Downwelling Infrared Radiance Measurements Made at Eureka, Nunavut, Canada (2006–09)

AbstractThe radiative properties of clouds are related to cloud microphysical and optical properties, including water path, optical depth, particle size, and thermodynamic phase. Ground-based observations from remote sensors provide high-quality, long-term, continuous measurements that can be used to obtain these properties. In the Arctic, a more comprehensive understanding of cloud microphysics is important because of the sensitivity of the Arctic climate to changes in radiation. Eureka, Nunavut (80°N, 86°25′W, 10 m), Canada, is a research station located on Ellesmere Island. A large suite of ground-based remote sensors at Eureka provides the opportunity to make measurements of cloud microphysics using multiple instruments and methodologies. In this paper, cloud microphysical properties are presented using a retrieval method that utilizes infrared radiances obtained from an infrared spectrometer at Eureka between March 2006 and April 2009. These retrievals provide a characterization of the microphysics of ice and liquid in clouds with visible optical depths between 0.25 and 6, which are a class of clouds whose radiative properties depend greatly on their microphysical properties. The results are compared with other studies that use different methodologies at Eureka, providing context for multimethod perspectives. The authors’ findings are supportive of previous studies, including seasonal cycles in phase and liquid particle size, weak temperature–phase dependencies, and frequent occurrences of supercooled water. Differences in microphysics are found between mixed-phase and single-phase clouds for both ice and liquid. The Eureka results are compared with those obtained using a similar retrieval technique during the Surface Heat Budget of the Arctic Ocean (SHEBA) experiment.

Energy budget of first‐year Arctic sea ice in advanced stages of melt

During an 8 day drift in July–August 2012 in the Nansen Basin, all components of the energy budget of melting first‐year sea ice were observed. Absorption of solar radiation by the ice and ponds was the largest source of energy to the ice at almost all times during the drift. However, oceanic heat flux also provided significant heating and dominated during one wind event. Longwave fluxes provided a relatively small cooling effect, and atmospheric heat fluxes were negligible. The aggregate scale albedo of this younger, thinner ice was significantly lower than at Surface Heat Budget of the Arctic Ocean (SHEBA), and the transmittance was significantly higher here, despite similar pond and open water fractions. The oceanic heat flux was only half of the solar flux through the ice to the water, producing warm water near the surface that might delay ice growth in autumn, an important effect of the transition to thinner first‐year ice in the high Arctic.

Validation of parameterizations for the surface turbulent fluxes over sea ice with CHINARE 2010 and SHEBA data

This study examines the modelled surface turbulent fluxes over sea ice from the bulk algorithms of the Beijing Climate Centre Climate System Model (BCC_CSM), the European Centre for Medium-Range Weather Forecasts (ECMWF) model and the Community Earth System Model (CESM) with data from the fourth Chinese National Arctic Research Expedition (CHINARE 2010) and the Surface Heat Budget of the Arctic Ocean (SHEBA) experiment. Of all the model algorithms, wind stresses are replicated well and have small annual biases (-0.6% in BCC_CSM, 0.2% in CESM and 17% in ECMWF) with observations, annual sensible heat fluxes are consistently underestimated by 83-141%, and annual latent heat fluxes are generally overestimated by 49-73%. Five sets of stability functions for stable stratification are evaluated based on theoretical and observational analyses, and the superior stability functions are employed in a new bulk algorithm proposal, which also features varying roughness lengths. Compared to BCC_CSM, the new algorithm can estimate the friction velocity with significantly reduced bias, 84% smaller in winter and 56% smaller in summer, respectively. For the sensible heat flux, the bias of the new algorithm is 30% smaller in winter and 19% smaller in summer than that of BCC_CSM. Finally, the bias of modelled latent heat fluxes is 27% smaller in summer. Keywords: Iceatmosphere coupling; turbulent flux parameterization; MoninObukhov similarity theory; SHEBA; stable boundary layer (Published: 23 September 2013) Citation: Polar Research 2013, 32 , 20818, http://dx.doi.org/10.3402/polar.v32i0.20818