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Observations from the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) were used to evaluate the Coupled Arctic Forecast System (CAFS) model’s ability to simulate the atmospheric boundary layer (ABL) structure in the central Arctic. MOSAiC observations of the lower atmosphere from radiosondes, downwelling longwave radiation (LWD) from a pyranometer, and near-surface wind conditions from a meteorological tower were compared to 6-hourly CAFS output. A self-organizing map (SOM) analysis reveals that CAFS reproduces the range of stability structures identified by the SOM trained with MOSAiC observations of virtual potential temperature (θv) profiles, but not necessarily with the correct frequency or at the correct time. Additionally, the wind speed profiles corresponding to a particular θv profile are not consistent between CAFS and the observations. When categorizing profiles by static stability, it was revealed that CAFS simulates all observed stability regimes, but overrepresents the frequency of near-surface strong stability, and underrepresents the frequency of strong stability between the top of the ABL and 1 km. The 10 m wind speeds corresponding to each stability regime consistently have larger values in CAFS versus observed, and this offset increases with decreasing stability. Whether LWD is over or underestimated in CAFS is dependent on stability regime. Both variables are most greatly overestimated in spring, leading to the largest near-surface θv bias, and the greatest underrepresentation of strong stability in spring. The results of this article serve to highlight the positive aspects of CAFS for representing the ABL and reveal impacts of misrepresentations of physical processes dictating energy, moisture, and momentum transfer in the lower troposphere on the simulation of central Arctic ABL structure and stability. This highlights potential areas for improvement in CAFS and other numerical weather prediction models. The SOM-based analysis especially provides a unique opportunity for process-based model evaluation. 

Abstract. Observations collected during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) provide an annual cycle of the vertical thermodynamic and kinematic structure of the atmospheric boundary layer (ABL) in the central Arctic. A self-organizing map (SOM) analysis conducted using radiosonde observations shows a range in the Arctic ABL vertical structure from very shallow and stable, with a strong surface-based virtual potential temperature (θv) inversion, to deep and near neutral, capped by a weak elevated θv inversion. The patterns identified by the SOM allowed for the derivation of criteria to categorize stability within and just above the ABL, which revealed that the Arctic ABL during MOSAiC was stable and near neutral with similar frequencies, and there was always a θv inversion within the lowest 1 km, which usually had strong to moderate stability. In conjunction with observations from additional measurement platforms, including a 10 m meteorological tower, ceilometer, and microwave radiometer, the radiosonde observations and SOM analysis provide insight into the relationships between atmospheric vertical structure and stability, as well as a variety of atmospheric thermodynamic and kinematic features. A low-level jet was observed in 76 % of the radiosondes, with stronger winds and low-level jet (LLJ) core located more closely to the ABL corresponding with weaker stability. Wind shear within the ABL was found to decrease, and friction velocity was found to increase, with decreasing ABL stability. Clouds were observed within the 30 min preceding the radiosonde launch 64 % of the time. These were typically low clouds, corresponding to weaker stability, where high clouds or no clouds largely coincided with a stable ABL. 

Low-level clouds in the Arctic affect the surface energy budget and vertical transport of heat and moisture. The limited availability of cloud-droplet-forming aerosol particles strongly impacts cloud properties and lifetime. Vertical particle distributions are required to study aerosol–cloud interaction over sea ice comprehensively. This article presents vertically resolved measurements of aerosol particle number concentrations and sizes using tethered balloons. The data were collected during the Multidisciplinary drifting Observatory for the Study of Arctic Climate expedition in the summer of 2020. Thirty-four profiles of aerosol particle number concentration were observed in 2 particle size ranges: 12–150 nm (N12−150) and above 150 nm (N>150). Concurrent balloon-borne meteorological measurements provided context for the continuous profiles through the cloudy atmospheric boundary layer. Radiosoundings, cloud remote sensing data, and 5-day back trajectories supplemented the analysis. The majority of aerosol profiles showed more particles above the lowest temperature inversion, on average, double the number concentration compared to below. Increased N12−150 up to 3,000 cm−3 were observed in the free troposphere above low-level clouds related to secondary particle formation. Long-range transport of pollution increased N>150 to 310 cm−3 in a warm, moist air mass. Droplet activation inside clouds caused reductions of N>150 by up to 100%, while the decrease in N12−150 was less than 50%. When low-level clouds were thermodynamically coupled with the surface, profiles showed 5 times higher values of N12−150 in the free troposphere than below the cloud-capping temperature inversion. Enhanced N12−150 and N>150 interacting with clouds were advected above the lowest inversion from beyond the sea ice edge when clouds were decoupled from the surface. Vertically discontinuous aerosol profiles below decoupled clouds suggest that particles emitted at the surface are not transported to clouds in these conditions. It is concluded that the cloud-surface coupling state and free tropospheric particle abundance are crucial when assessing the aerosol budget for Arctic low-level clouds over sea ice. 

Abstract. Atmospheric measurements taken over the span of an entire year between October 2019 and September 2020 during the icebreaker-based Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition provide insight into processes acting in the Arctic atmosphere. Through the merging of disparate, yet complementary in situ observations, we can derive information about these thermodynamic and kinematic processes with great detail. This paper describes methods used to create a lower atmospheric properties dataset containing information on several key features relating to the central Arctic atmospheric boundary layer, including properties of temperature inversions, low-level jets, near-surface meteorological conditions, cloud cover, and the surface radiation budget. The lower atmospheric properties dataset was developed using observations from radiosondes launched at least four times per day, a 10 m meteorological tower and radiation station deployed on the sea ice near the Research Vessel Polarstern, and a ceilometer located on the deck of the Polarstern. This lower atmospheric properties dataset, which can be found at *insert DOI when published*, contains metrics which fall into the overarching categories of temperature, wind, stability, clouds, and radiation at the time of each radiosonde launch. The purpose of the lower atmospheric properties dataset is to provide a consistent description of general atmospheric boundary layer conditions throughout the MOSAiC year which can aid in research applications with the overall goal of gaining a greater understanding of the atmospheric processes governing the central Arctic and how they may contribute to future climate change. 

Abstract Over a five-month time window between March and July 2020, scientists deployed two small uncrewed aircraft systems (sUAS) to the central Arctic Ocean as part of legs three and four of the MOSAiC expedition. These sUAS were flown to measure the thermodynamic and kinematic state of the lower atmosphere, including collecting information on temperature, pressure, humidity and winds between the surface and 1 km, as well as to document ice properties, including albedo, melt pond fraction, and open water amounts. The atmospheric state flights were primarily conducted by the DataHawk2 sUAS, which was operated primarily in a profiling manner, while the surface property flights were conducted using the HELiX sUAS, which flew grid patterns, profiles, and hover flights. In total, over 120 flights were conducted and over 48 flight hours of data were collected, sampling conditions that included temperatures as low as −35 °C and as warm as 15 °C, spanning the summer melt season.