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  • 1
    Publication Date: 2024-04-20
    Description: This dataset contains information about the state of the central Arctic lower atmosphere during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition. Through the merging of MOSAiC radiosonde, 10-m meteorological tower, ceilometer, and radiation station observations, this dataset provides information about the atmospheric boundary layer (depth and stability), temperature features (near-surface temperature and temperature inversion characteristics), wind features (near-surface wind speed and low-level jet characteristics), moisture features (near-surface mixing ratio and cloud characteristics), and surface radiation budget (up- and downwelling longwave and shortwave radiative flux) at the time of each MOSAiC radiosonde launch (approximately 4 times per day between September 2019 and October 2020). The dataset is structured in a NetCDF4 file, which follows the CF-1.10 convention. The objective of this dataset is to provide the user community with a consistent description of general lower atmospheric conditions throughout the MOSAiC year.
    Keywords: ABL; Arctic; Arctic Ocean; Atmosphere; Automatic weather station; AWS; FLUX_TOWER; Flux tower; meteorological data; MOSAiC; MOSAiC20192020; Multidisciplinary drifting Observatory for the Study of Arctic Climate; North Greenland Sea; Polarstern; PS122/1; PS122/1_10-103; PS122/1_10-105; PS122/1_10-106; PS122/1_10-107; PS122/1_10-108; PS122/1_10-135; PS122/1_10-21; PS122/1_10-22; PS122/1_10-23; PS122/1_10-24; PS122/1_10-28; PS122/1_10-29; PS122/1_10-3; PS122/1_10-30; PS122/1_10-31; PS122/1_10-4; PS122/1_10-53; PS122/1_10-54; PS122/1_10-56; PS122/1_10-57; PS122/1_10-73; PS122/1_10-74; PS122/1_10-75; PS122/1_10-76; PS122/1_10-94; PS122/1_10-95; PS122/1_10-99; PS122/1_11-10; PS122/1_11-29; PS122/1_11-30; PS122/1_11-31; PS122/1_11-32; PS122/1_11-33; PS122/1_11-43; PS122/1_11-44; PS122/1_11-45; PS122/1_11-46; PS122/1_11-5; PS122/1_11-6; PS122/1_11-7; PS122/1_11-8; PS122/1_11-9; PS122/1_1-299; PS122/1_1-341; PS122/1_1-345; PS122/1_2-100; PS122/1_2-101; PS122/1_2-103; PS122/1_2-104; PS122/1_2-105; PS122/1_2-106; PS122/1_2-107; PS122/1_2-110; PS122/1_2-111; PS122/1_2-112; PS122/1_2-113; PS122/1_2-115; PS122/1_2-116; PS122/1_2-117; PS122/1_2-118; PS122/1_2-119; PS122/1_2-120; PS122/1_2-121; PS122/1_2-122; PS122/1_2-123; PS122/1_2-127; PS122/1_2-135; PS122/1_2-136; PS122/1_2-137; PS122/1_2-139; PS122/1_2-140; PS122/1_2-141; PS122/1_2-143; PS122/1_2-144; PS122/1_2-145; PS122/1_2-146; PS122/1_2-147; PS122/1_2-148; PS122/1_2-149; PS122/1_2-150; PS122/1_2-160; PS122/1_2-161; PS122/1_2-162; PS122/1_2-163; PS122/1_2-171; PS122/1_2-172; PS122/1_2-173; PS122/1_2-174; PS122/1_2-179; PS122/1_2-180; PS122/1_2-181; PS122/1_2-182; PS122/1_2-184; PS122/1_2-185; PS122/1_2-186; PS122/1_2-187; PS122/1_2-188; PS122/1_2-189; PS122/1_2-190; PS122/1_2-191; PS122/1_2-192; PS122/1_2-193; PS122/1_2-51; PS122/1_2-52; PS122/1_2-53; PS122/1_2-54; PS122/1_2-55; PS122/1_2-56; PS122/1_2-59; PS122/1_2-60; PS122/1_2-61; PS122/1_2-62; PS122/1_2-69; PS122/1_2-70; PS122/1_2-71; PS122/1_2-72; PS122/1_2-73; PS122/1_2-74; PS122/1_2-75; PS122/1_2-76; PS122/1_2-77; PS122/1_2-78; PS122/1_2-79; PS122/1_2-80; PS122/1_2-81; PS122/1_2-82; PS122/1_2-83; PS122/1_2-85; PS122/1_2-86; PS122/1_2-87; PS122/1_2-88; PS122/1_2-91; PS122/1_2-92; PS122/1_2-93; PS122/1_2-94; PS122/1_4-19; PS122/1_4-20; PS122/1_4-21; PS122/1_4-22; PS122/1_4-30; PS122/1_4-31; PS122/1_4-32; PS122/1_4-33; PS122/1_4-35; PS122/1_4-36; PS122/1_4-4; PS122/1_4-5; PS122/1_4-6; PS122/1_4-7; PS122/1_4-8; PS122/1_4-9; PS122/1_5-10; PS122/1_5-11; PS122/1_5-12; PS122/1_5-13; PS122/1_5-20; PS122/1_5-21; PS122/1_5-22; PS122/1_5-23; PS122/1_5-31; PS122/1_5-32; PS122/1_5-33; PS122/1_5-34; PS122/1_5-36; PS122/1_5-38; PS122/1_5-39; PS122/1_5-49; PS122/1_5-50; PS122/1_5-51; PS122/1_5-52; PS122/1_5-6; PS122/1_5-7; PS122/1_5-72; PS122/1_5-73; PS122/1_5-74; PS122/1_5-75; PS122/1_5-79; PS122/1_5-80; PS122/1_6-112; PS122/1_6-113; PS122/1_6-114; PS122/1_6-115; PS122/1_6-12; PS122/1_6-125; PS122/1_6-126; PS122/1_6-13; PS122/1_6-14; PS122/1_6-15; PS122/1_6-24; PS122/1_6-25; PS122/1_6-26; PS122/1_6-27; PS122/1_6-3; PS122/1_6-4; PS122/1_6-53; PS122/1_6-54; PS122/1_6-55; PS122/1_6-56; PS122/1_6-71; PS122/1_6-72; PS122/1_6-73; PS122/1_6-74; PS122/1_6-82; PS122/1_6-83; PS122/1_6-84; PS122/1_6-85; PS122/1_7-100; PS122/1_7-101; PS122/1_7-102; PS122/1_7-107; PS122/1_7-108; PS122/1_7-109; PS122/1_7-110; PS122/1_7-113; PS122/1_7-114; PS122/1_7-13; PS122/1_7-14; PS122/1_7-26; PS122/1_7-27; PS122/1_7-28; PS122/1_7-29; PS122/1_7-30; PS122/1_7-43; PS122/1_7-44; PS122/1_7-45; PS122/1_7-46; PS122/1_7-63; PS122/1_7-64; PS122/1_7-65; PS122/1_7-66; PS122/1_7-83; PS122/1_7-84; PS122/1_7-85; PS122/1_7-86; PS122/1_7-99; PS122/1_8-101; PS122/1_8-11; PS122/1_8-115; PS122/1_8-116; PS122/1_8-117; PS122/1_8-118; PS122/1_8-12; PS122/1_8-120; PS122/1_8-121; PS122/1_8-13; PS122/1_8-14; PS122/1_8-39; PS122/1_8-40; PS122/1_8-41; PS122/1_8-42; PS122/1_8-5; PS122/1_8-6; PS122/1_8-63; PS122/1_8-64; PS122/1_8-65; PS122/1_8-66; PS122/1_8-80; PS122/1_8-81; PS122/1_8-82; PS122/1_8-83; PS122/1_8-95; PS122/1_8-96; PS122/1_8-97; PS122/1_9-101; PS122/1_9-102; PS122/1_9-105; PS122/1_9-106; PS122/1_9-13; PS122/1_9-14; PS122/1_9-18; PS122/1_9-19; PS122/1_9-20; PS122/1_9-21; PS122/1_9-41; PS122/1_9-42; PS122/1_9-43; PS122/1_9-44; PS122/1_9-57; PS122/1_9-58; PS122/1_9-59; PS122/1_9-60; PS122/1_9-77; PS122/1_9-78; PS122/1_9-79; PS122/1_9-80; PS122/1_9-88; PS122/1_9-89; PS122/1_9-90; PS122/1_9-91; PS122/1_99-46; PS122/1_99-47; PS122/1_9-99; PS122/2; PS122/2_14-119; PS122/2_14-13; PS122/2_14-14; PS122/2_15-1; PS122/2_15-13; PS122/2_15-2; PS122/2_15-3; PS122/2_15-4; PS122/2_15-5; PS122/2_15-7; PS122/2_16-10; PS122/2_16-11; PS122/2_16-13; PS122/2_16-16; PS122/2_16-17; PS122/2_16-18; PS122/2_16-19; PS122/2_16-2; PS122/2_16-20; PS122/2_16-3; PS122/2_16-30; PS122/2_16-31; PS122/2_16-32; PS122/2_16-33; PS122/2_16-4; PS122/2_16-40; PS122/2_16-41; PS122/2_16-42; PS122/2_16-43; PS122/2_16-5; PS122/2_16-57; PS122/2_16-58; PS122/2_16-59; PS122/2_16-6; PS122/2_16-60; PS122/2_16-67; PS122/2_16-68; PS122/2_16-69; PS122/2_16-7; PS122/2_16-70; PS122/2_16-76; PS122/2_17-10; PS122/2_17-102; PS122/2_17-103; PS122/2_17-104; PS122/2_17-105; PS122/2_17-11; PS122/2_17-110; PS122/2_17-12; PS122/2_17-21; PS122/2_17-22; PS122/2_17-23; PS122/2_17-24; PS122/2_17-35; PS122/2_17-36; PS122/2_17-37; PS122/2_17-38; PS122/2_17-55; PS122/2_17-56; PS122/2_17-57; PS122/2_17-58; PS122/2_17-71; PS122/2_17-72; PS122/2_17-73; PS122/2_17-74; PS122/2_17-92; PS122/2_17-93; PS122/2_17-94; PS122/2_17-95; PS122/2_18-100; PS122/2_18-11; PS122/2_18-12; PS122/2_18-13; PS122/2_18-20; PS122/2_18-21; PS122/2_18-22; PS122/2_18-27; PS122/2_18-29; PS122/2_18-30; PS122/2_18-31; PS122/2_18-48; PS122/2_18-49; PS122/2_18-50; PS122/2_18-51; PS122/2_18-67; PS122/2_18-68; PS122/2_18-69; PS122/2_18-70; PS122/2_18-85; PS122/2_18-86; PS122/2_18-87; PS122/2_18-88; PS122/2_18-94; PS122/2_18-95; PS122/2_18-96; PS122/2_18-97; PS122/2_19-10; PS122/2_19-100; PS122/2_19-11; PS122/2_19-12; PS122/2_19-124; PS122/2_19-125; PS122/2_19-126; PS122/2_19-127; PS122/2_19-143; PS122/2_19-22; PS122/2_19-23; PS122/2_19-24; PS122/2_19-25; PS122/2_19-47; PS122/2_19-48; PS122/2_19-49; PS122/2_19-50; PS122/2_19-71; PS122/2_19-72; PS122/2_19-73; PS122/2_19-74; PS122/2_19-84; PS122/2_19-85; PS122/2_19-86; PS122/2_19-87; PS122/2_19-97; PS122/2_19-98; PS122/2_19-99; PS122/2_20-10; PS122/2_20-103; PS122/2_20-104; PS122/2_20-105; PS122/2_20-106; PS122/2_20-119; PS122/2_20-120; PS122/2_20-121; PS122/2_20-122; PS122/2_20-135; PS122/2_20-19; PS122/2_20-20; PS122/2_20-21; PS122/2_20-22; PS122/2_20-37; PS122/2_20-38; PS122/2_20-39; PS122/2_20-40; PS122/2_20-66; PS122/2_20-67; PS122/2_20-68; PS122/2_20-69; PS122/2_20-8; PS122/2_20-84; PS122/2_20-85; PS122/2_20-86; PS122/2_20-87; PS122/2_20-9; PS122/2_21-106; PS122/2_21-107; PS122/2_21-108; PS122/2_21-109; PS122/2_21-115; PS122/2_21-116; PS122/2_21-117; PS122/2_21-118; PS122/2_21-132; PS122/2_21-133; PS122/2_21-134; PS122/2_21-135; PS122/2_21-136; PS122/2_21-21; PS122/2_21-22; PS122/2_21-23; PS122/2_21-37; PS122/2_21-38; PS122/2_21-39; PS122/2_21-40; PS122/2_21-57; PS122/2_21-58; PS122/2_21-59; PS122/2_21-60; PS122/2_21-79; PS122/2_21-80; PS122/2_21-81; PS122/2_21-82; PS122/2_22-10; PS122/2_22-102; PS122/2_22-103; PS122/2_22-104; PS122/2_22-105; PS122/2_22-11; PS122/2_22-111; PS122/2_22-20; PS122/2_22-21; PS122/2_22-22; PS122/2_22-23; PS122/2_22-38; PS122/2_22-39; PS122/2_22-40; PS122/2_22-41; PS122/2_22-57; PS122/2_22-58; PS122/2_22-59; PS122/2_22-60; PS122/2_22-78; PS122/2_22-79; PS122/2_22-80; PS122/2_22-81; PS122/2_22-87; PS122/2_22-88; PS122/2_22-89; PS122/2_22-9; PS122/2_23-101; PS122/2_23-102; PS122/2_23-103; PS122/2_23-104; PS122/2_23-117; PS122/2_23-118; PS122/2_23-119; PS122/2_23-120; PS122/2_23-129; PS122/2_23-22; PS122/2_23-23; PS122/2_23-24; PS122/2_23-25; PS122/2_23-41; PS122/2_23-42; PS122/2_23-43; PS122/2_23-44; PS122/2_23-54; PS122/2_23-55; PS122/2_23-56; PS122/2_23-57; PS122/2_23-6; PS122/2_23-7; PS122/2_23-8; PS122/2_23-80; PS122/2_23-81; PS122/
    Type: Dataset
    Format: application/x-hdf, 440 kBytes
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  • 2
    Publication Date: 2024-04-20
    Description: 6-hourly output from CAFS 10-day forecasts from 1 October 2019 to 12 September 2020. Dataset includes vertical profiles of temperature, specific humidity, pressure, and zonal and meridional wind speed at the Polarstern location. CAFS is an experimental fully coupled pan-Arctic short-term weather forecast model (Solomon et al., 2023) adapted from the Regional Arctic System Model (Maslowski et al., 2012). CAFS component models include the Weather Research and Forecasting (WRF3.6.1) atmospheric model, the Parallel Ocean Program (POP2) model, the Los Alamos Community Ice Model (CICE5.1) sea ice model, and the NCAR Community Land Model (CLM4.5) coupled using a regionalized version of the CESM flux coupler (CPL7). CAFS is run at a 10 km horizontal resolution with 40 vertical levels, including 11 vertical levels between 12 m and 1 km. The model is initialized at 00 UTC each day with initial and lateral boundary conditions from the National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) weather forecast model (National Centers for Environmental Information).
    Keywords: Arctic Ocean; atmospheric boundary layer; CT; DATE/TIME; forecasts; LATITUDE; LONGITUDE; Model output, NetCDF format; Model output, NetCDF format (File Size); MOSAiC_ATMOS; MOSAiC20192020; Polarstern; PS122/1; PS122/1-track; PS122/2; PS122/2-track; PS122/3; PS122/3-track; PS122/4; PS122/4-track; PS122/5; PS122/5-track; Underway cruise track measurements
    Type: Dataset
    Format: text/tab-separated-values, 348 data points
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  • 3
    Publication Date: 2022-11-02
    Description: 〈jats:title〉Abstract〈/jats:title〉〈jats:p〉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.〈/jats:p〉
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , NonPeerReviewed
    Format: application/pdf
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  • 4
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    COPERNICUS GESELLSCHAFT MBH
    In:  EPIC3Atmospheric Measurement Techniques, COPERNICUS GESELLSCHAFT MBH, 15(13), pp. 4001-4022, ISSN: 1867-1381
    Publication Date: 2022-07-11
    Description: During the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition, meteorological conditions over the lowest 1 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 radiation budget. The high temporal resolution of the UAS observations allows us to manually identify the ABL height (ZABL) for 65 out of the total 89 flights conducted over the central Arctic Ocean between 23 March and 26 July 2020 by visually analyzing profiles of virtual potential temperature, humidity, and bulk Richardson number. Comparing this subjective ZABL with ZABL identified by various previously published automated objective methods allows us to determine which objective methods are most successful at accurately identifying ZABL in the central Arctic environment and how the success of the methods differs based on stability regime. The objective methods we use are the Liu–Liang, Heffter, virtual potential temperature gradient maximum, and bulk Richardson number methods. In the process of testing these objective methods on the DH2 data, numerical thresholds were adapted to work best for the UAS-based sampling. To determine if conclusions are robust across different measurement platforms, the subjective and objective ZABL determination processes were repeated using the radiosonde profile closest in time to each DH2 flight. For both the DH2 and radiosonde data, it is determined that the bulk Richardson number method is the most successful at identifying ZABL, while the Liu–Liang method is least successful. The results of this study are expected to be beneficial for upcoming observational and modeling efforts regarding the central Arctic ABL.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , NonPeerReviewed
    Format: application/pdf
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  • 5
    Publication Date: 2024-04-23
    Description: With the Arctic rapidly changing, the needs to observe, understand, and model the changes are essential. To support these needs, an annual cycle of observations of atmospheric properties, processes, and interactions were made while drifting with the sea ice across the central Arctic during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition from October 2019 to September 2020. An international team designed and implemented the comprehensive program to document and characterize all aspects of the Arctic atmospheric system in unprecedented detail, using a variety of approaches, and across multiple scales. These measurements were coordinated with other observational teams to explore cross- cutting and coupled interactions with the Arctic Ocean, sea ice, and ecosystem through a variety of physical and biogeochemical processes. This overview outlines the breadth and complexity of the atmospheric research program, which was organized into 4 subgroups: atmospheric state, clouds and precipitation, gases and aerosols, and energy budgets. Atmospheric variability over the annual cycle revealed important influences from a persistent large-scale winter circulation pattern, leading to some storms with pressure and winds that were outside the interquartile range of past conditions suggested by long-term reanalysis. Similarly, the MOSAiC location was warmer and wetter in summer than the reanalysis climatology, in part due to its close proximity to the sea ice edge.The comprehensiveness of the observational program for characterizing and analyzing atmospheric phenomena is demonstrated via a winter case study examining air mass transitions and a summer case study examining vertical atmospheric evolution. Overall, the MOSAiC atmospheric program successfully met its objectives and was the most comprehensive atmospheric measurement program to date conducted over the Arctic sea ice. The obtained data will support a broad range of coupled-system scientific research and provide an important foundation for advancing multiscale modeling capabilities in the Arctic.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , isiRev
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  • 6
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