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Abstract. Observations collected during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) provide a detailed description of the impact of thermodynamic and kinematic forcings on atmospheric boundary layer (ABL) stability in the central Arctic. This study reveals that the Arctic ABL is stable and near-neutral with similar frequencies, and strong stability is the most persistent of all stability regimes. MOSAiC radiosonde observations, in conjunction with observations from additional measurement platforms, including a 10 m meteorological tower, ceilometer, microwave radiometer, and radiation station, provide insight into the relationships between atmospheric stability and various atmospheric thermodynamic and kinematic forcings of ABL turbulence and how these relationships differ by season. We found that stronger stability largely occurs in low-wind (i.e., wind speeds are slow), low-radiation (i.e., surface radiative fluxes are minimal) environments; a very shallow mixed ABL forms in low-wind, high-radiation environments; weak stability occurs in high-wind, moderate-radiation environments; and a near-neutral ABL forms in high-wind, high-radiation environments. Surface pressure (a proxy for synoptic staging) partially explains the observed wind speeds for different stability regimes. Cloud frequency and atmospheric moisture contribute to the observed surface radiation budget. Unique to summer, stronger stability may also form when moist air is advected from over the warmer open ocean to over the colder sea ice surface, which decouples the colder near-surface atmosphere from the advected layer, and is identifiable through observations of fog and atmospheric moisture.

 

As part of the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC), the HELiX uncrewed aircraft system (UAS) was deployed over the sea ice in the central Arctic Ocean during summer 2020. Albedo measurements were obtained with stabilized pyranometers, and melt pond fraction was calculated from orthomosaic imagery from a surface-imaging multispectral camera. This study analyzed HELiX flight data to provide insights on the temporal and spatial evolution of albedo and melt pond fraction of the MOSAiC floe during the melt season as it drifted south through Fram Strait. The surface albedo distributions showed peak values changing from high albedo (0.55–0.6) to lower values (0.3) as the season advanced. Inspired by methods developed for satellite data, an algorithm was established to retrieve melt pond fraction from the orthomosaic images. We demonstrate that the near-surface observations of melt pond fraction were highly dependent on sample area, offering insight into the influence of subgrid scale features and spatial heterogeneity in satellite observations. Vertical observations conducted with the HELiX were used to quantify the influence of melt pond scales on observed surface albedo as a function of sensor footprint. These scaling results were used to link surface-based measurements collected during MOSAiC to broader-scale satellite data to investigate the influence of surface features on observed albedo. Albedo values blend underlying features within the sensor footprint, as determined by the melt pond size and concentration. This study framed the downscaling (upscaling) problem related to the airborne (surface) observations of surface albedo across a variety of spatial scales. 

The Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) was a yearlong expedition supported by the icebreakerR/V Polarstern, following the Transpolar Drift from October 2019 to October 2020. The campaign documented an annual cycle of physical, biological, and chemical processes impacting the atmosphere-ice-ocean system. Of central importance were measurements of the thermodynamic and dynamic evolution of the sea ice. A multi-agency international team led by the University of Colorado/CIRES and NOAA-PSL observed meteorology and surface-atmosphere energy exchanges, including radiation; turbulent momentum flux; turbulent latent and sensible heat flux; and snow conductive flux. There were four stations on the ice, a 10 m micrometeorological tower paired with a 23/30 m mast and radiation station and three autonomous Atmospheric Surface Flux Stations. Collectively, the four stations acquired ~928 days of data. This manuscript documents the acquisition and post-processing of those measurements and provides a guide for researchers to access and use the data products.

 

Supercooled fogs can have an important radiative impact at the surface of the Greenland Ice Sheet, but they are difficult to detect and our understanding of the factors that control their lifetime and radiative properties is limited by a lack of observations. This study demonstrates that spectrally resolved measurements of downwelling longwave radiation can be used to generate retrievals of fog microphysical properties (phase and particle effective radius) when the fog visible optical depth is greater than ∼0.25. For 12 cases of fog under otherwise clear skies between June and September 2019 at Summit Station in central Greenland, nine cases were mixed‐phase. The mean ice particle (optically‐equivalent sphere) effective radius was 24.0 ± 7.8 µm, and the mean liquid droplet effective radius was 14.0 ± 2.7 µm. These results, combined with measurements of aerosol particle number concentrations, provide evidence supporting the hypotheses that (a) low surface aerosol particle number concentrations can limit fog liquid water path, (b) fog can act to increase near‐surface aerosol particle number concentrations through enhanced mixing, and (c) multiple fog events in quiescent periods gradually deplete near‐surface aerosol particle number concentrations.

 

The amount of snow on Arctic sea ice impacts the ice mass budget. Wind redistribution of snow into open water in leads is hypothesized to cause significant wintertime snow loss. However, there are no direct measurements of snow loss into Arctic leads. We measured the snow lost in four leads in the Central Arctic in winter 2020. We find, contrary to expectations, that under typical winter conditions, minimal snow was lost into leads. However, during a cyclone that delivered warm air temperatures, high winds, and snowfall, 35.0 ± 1.1 cm snow water equivalent (SWE) was lost into a lead (per unit lead area). This corresponded to a removal of 0.7–1.1 cm SWE from the entire surface—∼6%–10% of this site's annual snow precipitation. Warm air temperatures, which increase the length of time that wintertime leads remain unfrozen, may be an underappreciated factor in snow loss into leads.

 

Abstract. This study presents the first full annual cycle (2019–2020) of ambient surface aerosol particle number concentration measurements (condensationnuclei > 20 nm, N20) collected at Summit Station (Summit), in the centre of the Greenland Ice Sheet (72.58∘ N, −38.45∘ E; 3250 ma.s.l.). The mean surface concentration in 2019 was 129 cm−3, with the 6 h mean ranging between 1 and 1441 cm−3. The highest monthly mean concentrations occurred during the late spring and summer, with the minimum concentrations occurring in February (mean: 18 cm−3). High-N20 events are linked to anomalous anticyclonic circulation over Greenland and the descent of free-tropospheric aerosol down to the surface, whereas low-N20 events are linked to anomalous cyclonic circulation over south-east Greenland that drives upslope flow and enhances precipitation en route to Summit. Fog strongly affects particle number concentrations, on average reducing N20 by 20 % during the first 3 h of fog formation. Extremely-low-N20 events (< 10 cm−3) occur in all seasons, and we suggest that fog, and potentially cloud formation, can be limited by low aerosol particle concentrations over central Greenland. 

Abstract. Improvements to climate model results in polar regions require improvedknowledge of cloud properties. Surface-based infrared (IR) radiancespectrometers have been used to retrieve cloud properties in polar regions,but measurements are sparse. Reductions in cost and power requirements toallow more widespread measurements could be aided by reducing instrumentresolution. Here we explore the effects of errors and instrument resolutionon cloud property retrievals from downwelling IR radiances for resolutionsof 0.1 to 20 cm−1. Retrievals are tested on 336 radiance simulationscharacteristic of the Arctic, including mixed-phase, verticallyinhomogeneous, and liquid-topped clouds and a variety of ice habits.Retrieval accuracy is found to be unaffected by resolution from 0.1 to 4 cm−1, after which it decreases slightly. When cloud heights areretrieved, errors in retrieved cloud optical depth (COD) and ice fractionare considerably smaller for clouds with bases below 2 km than for higherclouds. For example, at a resolution of 4 cm−1, with errors imposed(noise and radiation bias of 0.2 mW/(m2 sr cm−1) and biases intemperature of 0.2 K and in water vapor of −3 %), using retrieved cloudheights, root-mean-square errors decrease from 1.1 to 0.15 for COD, 0.3 to0.18 for ice fraction (fice), and 10 to 7 µm for iceeffective radius (errors remain at 2 µm for liquid effective radius).These results indicate that a moderately low-resolution, surface-based IRspectrometer could provide cloud property retrievals with accuracycomparable to existing higher-resolution instruments and that such aninstrument would be particularly useful for low-level clouds. 

Abstract Despite the importance of high-latitude surface energy budgets (SEBs) for land-climate interactions in the rapidly changing Arctic, uncertainties in their prediction persist. Here, we harmonize SEB observations across a network of vegetated and glaciated sites at circumpolar scale (1994–2021). Our variance-partitioning analysis identifies vegetation type as an important predictor for SEB-components during Arctic summer (June-August), compared to other SEB-drivers including climate, latitude and permafrost characteristics. Differences among vegetation types can be of similar magnitude as between vegetation and glacier surfaces and are especially high for summer sensible and latent heat fluxes. The timing of SEB-flux summer-regimes (when daily mean values exceed 0 Wm −2 ) relative to snow-free and -onset dates varies substantially depending on vegetation type, implying vegetation controls on snow-cover and SEB-flux seasonality. Our results indicate complex shifts in surface energy fluxes with land-cover transitions and a lengthening summer season, and highlight the potential for improving future Earth system models via a refined representation of Arctic vegetation types. 

Abstract. Radiation fogs at Summit Station, Greenland (72.58^∘&thinsp;N,38.48^∘&thinsp;W; 3210&thinsp;m&thinsp;a.s.l.), are frequently reported by observers. Thefogs are often accompanied by fogbows, indicating the particles are composedof liquid; and because of the low temperatures at Summit, this liquid issupercooled. Here we analyze the formation of these fogs as well as theirphysical and radiative properties. In situ observations of particle size anddroplet number concentration were made using scattering spectrometers near 2 and 10&thinsp;m height from 2012 to 2014. These data are complemented bycolocated observations of meteorology, turbulent and radiative fluxes, andremote sensing. We find that liquid fogs occur in all seasons with thehighest frequency in September and a minimum in April. Due to thecharacteristics of the boundary-layer meteorology, the fogs are elevated,forming between 2 and 10&thinsp;m, and the particles then fall toward the surface.The diameter of mature particles is typically 20–25&thinsp;µm in summer.Number concentrations are higher at warmer temperatures and, thus, higher insummer compared to winter. The fogs form at temperatures as warm as −5&thinsp;^∘C, while the coldest form at temperatures approaching −40&thinsp;^∘C. Facilitated by the elevated condensation, in winter two-thirds offogs occurred within a relatively warm layer above the surface when thenear-surface air was below −40&thinsp;^∘C, as cold as −57&thinsp;^∘C,which is too cold to support liquid water. This implies that fog particlessettling through this layer of cold air freeze in the air column beforecontacting the surface, thereby accumulating at the surface as ice withoutriming. Liquid fogs observed under otherwise clear skies annually imparted1.5&thinsp;W&thinsp;m⁻² of cloud radiative forcing (CRF). While this is a smallcontribution to the surface radiation climatology, individual events areinfluential. The mean CRF during liquid fog events was 26&thinsp;W&thinsp;m⁻², andwas sometimes much higher. An extreme case study was observed toradiatively force 5&thinsp;^∘C of surface warming during the coldest partof the day, effectively damping the diurnal cycle. At lower elevations ofthe ice sheet where melting is more common, such damping could signal a rolefor fogs in preconditioning the surface for melting later in the day.

 

Abstract. Polar regions are characterized by their remoteness, making measurements challenging, but an improved knowledge of clouds and radiation is necessary to understand polar climate change. Infrared radiance spectrometers can operate continuously from the surface and have low power requirements relative to active sensors. Here we explore the feasibility of retrieving cloud height with an infrared spectrometer that would be designed for use in remote polar locations. Using a wide variety of simulated spectra of mixed-phase polar clouds at varying instrument resolutions, retrieval accuracy is explored using the CO₂ slicing/sorting and the minimum local emissivity variance (MLEV) methods. In the absence of imposed errors and for clouds with optical depths greater than  ∼ 0.3, cloud-height retrievals from simulated spectra using CO₂ slicing/sorting and MLEV are found to have roughly equivalent high accuracies: at an instrument resolution of 0.5cm⁻¹, mean biases are found to be  ∼ 0.2km for clouds with bases below 2 and −0.2km for higher clouds. Accuracy is found to decrease with coarsening resolution and become worse overall for MLEV than for CO₂ slicing/sorting; however, the two methods have differing sensitivity to different sources of error, suggesting an approach that combines them. For expected errors in the atmospheric state as well as both instrument noise and bias of 0.2mW/(m²srcm⁻¹), at a resolution of 4cm⁻¹, average retrieval errors are found to be less than  ∼ 0.5km for cloud bases within 1km of the surface, increasing to  ∼ 1.5km at 4km. This sensitivity indicates that a portable, surface-based infrared radiance spectrometer could provide an important complement in remote locations to satellite-based measurements, for which retrievals of low-level cloud are challenging.