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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.

 

The lake breeze circulation along Lake Michigan is associated with high tropospheric ozone concentrations at shoreline locations. The 2021 Wisconsin's Dynamic Influence of Shoreline Circulation on Ozone (WiscoDISCO-21) campaign involved atmospheric measurements over Chiwaukee Prairie State Natural Area in Southeastern Wisconsin from May 21–26, 2021. Three different platforms, two uncrewed aerial systems (UAS) and a Doppler lidar instrument, were used to collect data on this campaign, supplemented by a ground-based Wisconsin DNR maintained regulatory monitor at the site. A Purdue University M210 multirotor copter, and the University of Colorado RAAVEN fixed-wing aircraft were flown in coordination. Using data from the ground station, RAAVEN and onsite lidar, lake breezes were detected on several days of the campaign. The longest sustained lake breezes during the campaign were detected on May 22, 2021, from 17:00–21:38 UTC and on May 24, 2021, from 14:24–22:51 UTC. The presence of the lake breezes correlated with detected temperature inversions measured from the RAAVEN and high ozone events measured from the M210. Lake breezes were investigated with their relationship to vertical profiles measured on the UAS, ozone concentrations, and marine boundary layer height observed with Doppler lidar to demonstrate a multi-layered lower atmosphere. A buoyant internal boundary layer was observed over land from 40–100 m AGL below highest ozone concentrations. Marine layer extent was investigated through minimum buoyancy and Richardson number analysis, showing limited vertical mixing at altitudes up to 200 m AGL, below easterly lake breeze circulation patterns extending upward to 400 m AGL in the late day. 

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. 

Abstract. This study analyzes turbulent energy fluxes in the Arctic atmospheric boundary layer (ABL) using measurements with a small uncrewed aircraft system (sUAS). Turbulent fluxes constitute a major part of the atmospheric energy budget and influence the surface heat balance by distributing energy vertically in the atmosphere. However, only few in situ measurements of the vertical profile of turbulent fluxes in the Arctic ABL exist. The study presents a method to derive turbulent heat fluxes from DataHawk2 sUAS turbulence measurements, based on the flux gradient method with a parameterization of the turbulent exchange coefficient. This parameterization is derived from high-resolution horizontal wind speed measurements in combination with formulations for the turbulent Prandtl number and anisotropy depending on stability. Measurements were taken during the MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate) expedition in the Arctic sea ice during the melt season of 2020. For three example cases from this campaign, vertical profiles of turbulence parameters and turbulent heat fluxes are presented and compared to balloon-borne, radar, and near-surface measurements. The combination of all measurements draws a consistent picture of ABL conditions and demonstrates the unique potential of the presented method for studying turbulent exchange processes in the vertical ABL profile with sUAS measurements. 

Abstract. During the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition, meteorological conditions over the lowest1 km of the atmosphere were sampled with the DataHawk2 (DH2) fixed-wing uncrewed aircraft system (UAS). These in situ observations of the central Arctic atmosphere are some of the most extensive to date and provide unique insight into the atmospheric boundary layer (ABL) structure. The ABL is an important component of the Arctic climate, as it can be closely coupled to cloud properties, surface fluxes, and the atmospheric radiationbudget. The high temporal resolution of the UAS observations allows us to manually identify the ABL height (ZABL) for 65 out of the total89 flights conducted over the central Arctic Ocean between 23 March and 26 July 2020 by visually analyzing profiles of virtual potentialtemperature, humidity, and bulk Richardson number. Comparing this subjective ZABL with ZABL identified by various previouslypublished automated objective methods allows us to determine which objective methods are most successful at accurately identifying ZABL inthe central Arctic environment and how the success of the methods differs based on stability regime. The objective methods we use are theLiu–Liang, Heffter, virtual potential temperature gradient maximum, and bulk Richardson number methods. In the process of testing these objectivemethods on the DH2 data, numerical thresholds were adapted to work best for the UAS-based sampling. To determine if conclusions are robust acrossdifferent measurement platforms, the subjective and objective ZABL determination processes were repeated using the radiosonde profileclosest in time to each DH2 flight. For both the DH2 and radiosonde data, it is determined that the bulk Richardson number method is the mostsuccessful at identifying ZABL, while the Liu–Liang method is least successful. The results of this study are expected to be beneficialfor upcoming observational and modeling efforts regarding the central Arctic ABL. 

Abstract. The DataHawk2 (DH2) is a small, fixed-wing, uncrewed aircraft system, or UAS,developed at the University of Colorado (CU) primarily for taking detailedthermodynamic measurements of the atmospheric boundary layer. The DH2 weighs1.7 kg and has a wingspan of 1.3 m, with a flight endurance of approximately60 min, depending on configuration. In the DH2's most modern form, theaircraft carries a Vaisala RSS-421 sensor for pressure, temperature, andrelative humidity measurements, two CU-developed infrared temperaturesensors, and a CU-developed fine-wire array, in addition to sensors requiredto support autopilot function (pitot tube with pressure sensor, GPSreceiver, inertial measurement unit), from which wind speed and directioncan also be estimated. This paper presents a description of the DH2,including information on its design and development work, and puts the DH2 intocontext with respect to other contemporary UASs. Data from recent field work(MOSAiC, the Multidisciplinary drifting Observatory for the Study of ArcticClimate) is presented and compared with radiosondes deployed during thatcampaign to provide an overview of sensor and system performance. These datashow good agreement across pressure, temperature, and relative humidity aswell as across wind speed and direction. Additional examples of measurementsprovided by the DH2 are given from a variety of previous campaigns inlocations ranging from the continental United States to Japan and northernAlaska. Finally, a look toward future system improvements and upcomingresearch campaign participation is given. 

Abstract Frequency and intensity of warm and moist air-mass intrusions into the Arctic have increased over the past decades and have been related to sea ice melt. During our year-long expedition in the remote central Arctic Ocean, a record-breaking increase in temperature, moisture and downwelling-longwave radiation was observed in mid-April 2020, during an air-mass intrusion carrying air pollutants from northern Eurasia. The two-day intrusion, caused drastic changes in the aerosol size distribution, chemical composition and particle hygroscopicity. Here we show how the intrusion transformed the Arctic from a remote low-particle environment to an area comparable to a central-European urban setting. Additionally, the intrusion resulted in an explosive increase in cloud condensation nuclei, which can have direct effects on Arctic clouds’ radiation, their precipitation patterns, and their lifetime. Thus, unless prompt actions to significantly reduce emissions in the source regions are taken, such intrusion events are expected to continue to affect the Arctic climate. 

A0 level data from HELiX Uncrewed Aircraft System correspond to the raw data in Matlab format collected in the Central Arctic Ocean during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition. Synchronized and quality-controlled B1 level data are available in the Arctic Data Center. Users are encouraged to primarily use the B1 level data for analysis (doi:10.18739/A2GH9BB0Q). Raw data are the initial inputs in the processing routines to obtain the B1 and A1 level data (doi:10.18739/A2M90243X). Matlab files include hemispheric irradiance measurements from Kipp and Zonen pyranometers and thermodynamic parameters from Vaisala RSS421 sensors. Autopilot positions and attitudes, along with gimbal attitudes are also provided. Each field of measurements has its own time stamped based on a common clock and associated acquisition frequency. As no Coordinated Universal Time (UTC) time was provided in the FlexLogger acquisition files, the additional A0_PixHawk Matlab files obtained directly from the PixHawk autopilot are used to add UTC time for B1 level data. Please contact the authors if you need to use this dataset. More information on the data and method can be found in de Boer, G. R. Calmer, G. Jozef, J. Cassano, J. Hamilton, D. Lawrence, S. Borenstein, A. Doddi, C. Cox, J. Schmale, A. Preußer and B. Argrow (2022): Observing the Central Arctic Atmosphere and Surface with University of Colorado Uncrewed Aircraft Systems, Nature Scientific Data, in prep. 

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.

 

This dataset includes unprocessed raw data from DataHawk2 fixed-wind uncrewed aircraft system (UAS) flights that were conducted in the central Arctic Ocean over sea ice during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition. Synchronized and quality controlled data are available in the Arctic Data Center at doi:10.18739/A22Z12Q8X for data provided at their native frequency logged on board the aircraft’s secure digital (SD) card (A1 level files), or at doi:10.18739/A2Z60C34R for data interpolated to a common 10 hertz (Hz) clock (B1 level files). Users are encouraged to primarily use the B1 level data for analysis. Please contact the authors if you plan to use this dataset. More information on data collection with the DataHawk2 can be found in de Boer, G. R. Calmer, G. Jozef, J. Cassano, J. Hamilton, D. Lawrence, S. Borenstein, A. Doddi, C. Cox, J. Schmale, A. Preußer and B. Argrow (2022): Observing the Central Arctic Atmosphere and Surface with University of Colorado Uncrewed Aircraft Systems, Nature Scientific Data, submitted.