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  • 1
    Publication Date: 2024-04-20
    Description: Wind lidar measurements of the atmospheric boundary layer (ABL) were performed during the Multidisciplinary drifting Observatory for Study of Arctic Climate (MOSAiC) from September 2019 to October 2020. A “Halo-Photonics Streamline” (HPS) scanning wind lidar was used, which operates at a wavelength of 1.5 μm. The lidar can operate with a maximum range of 10km and is a programmable scanner, which enables vertical scans in all hemispheric directions. The scan patterns are the vertical azimuth display (VAD), the range-height indicator (RHI), and scans in one direction (STARE). The VAD is used for the determination of wind profiles above the lidar. The RHI scans are performed with different elevation angles. This allows for measurements of cross-sections, but also for the estimation of turbulent kinetic energy (TKE) profiles. Vertical STARE data can be used to compute the vertical wind variance profile. The HALO lidar measurements were performed in cooperation with the University of Leeds (PI Ian Brooks, Brooks 2022a), where the same quality control procedure was applied to the raw data of both HALO wind lidars of the University of Leeds and the University of Trier leading to the level 1 data of this data publication. The lidar raw data are high resolution (~3m along-beam and a few seconds temporal) measurements of lidar backscatter ratio and along-beam Doppler velocity. Data is only available where sufficient particles are available to backscatter the laser beam. The Doppler velocities were corrected for lidar orientation (pitch/roll/heading) and the drift speed of the ice. The result are true earth-relative velocities. The Level 1 data are the data for single beams, and are the basis for the calculation of derived quantities such as the vertical wind profile and wind variances. For the calculation of wind profiles from the single beams of the data e.g. as in Zentek et al. (2018), the lidar_heading must be taken into account. The horizontal direction is the sum of the variables [azimuth_true]+[lidar_heading]. Wind profiles will be published in a separate data publication. Data are provided only for the drift periods. Major data gaps occurred for 14 Feb. 2020 - 17 March 2020 and for 25 March 2020 - 28 March 2020.
    Keywords: Arctic Ocean; atmospheric boundary layer; Binary Object; Doppler Wind-LiDAR; File content; MOSAiC; MOSAiC_ATMOS; MOSAiC20192020; Multidisciplinary drifting Observatory for the Study of Arctic Climate; Polarstern; PS122/1; PS122/1_1-45; PS122/2; PS122/2_14-136; PS122/3; PS122/3_28-20; PS122/4; PS122/4_43-2; PS122/5; PS122/5_99-88; wind lidar; W-LiDAR
    Type: Dataset
    Format: text/tab-separated-values, 8 data points
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  • 2
    Publication Date: 2024-04-20
    Description: During the MOSAiC expedition 2019-2020 atmospheric thermodynamic profile measurements have been conducted from a meteorological (Met) Tower on the sea ice, as well as via collocated radiosondes that were launched approximately every six hours from aboard Polarstern. While the radiosondes lack the lowermost 10 m above the sea ice, the Met Tower profile can be used to fill this gap (observations at 0, 2, 6 and 10 meters). This is a blended data product that merges the Met Tower profile (data version 3.4, doi:10.18739/A2PV6B83F) in the minute of the radiosonde launch with the radiosonde profile aloft (data version 3, doi:10.1594/PANGAEA.943870). Parameters included are temperature (T), relative humidity (RH), wind speed and -direction, and air pressure. The aim of this product is two-fold: (1) To provide comprehensive atmospheric profiles for each radiosonde launch, that additionally retain the lowermost meters of the atmospheric boundary layer above the sea ice and (2) to remove potential unrealistic T/RH values from the radiosonde profiles that can emerge in the lowermost 100 m due to the influence of the ship on the measurement. Examples for the latter are occasional warm anomalies due to the heat island effect of the ship, or elevated, vertically confined peaks that can arise from the ship's exhaust plume. The potential effect of the exhaust plume on the T profile is estimated by comparing the radiosonde at 30 m height to the concurring Polarstern meteorological observation (doi:10.1594/PANGAEA.935263 - doi:10.1594/PANGAEA.935267). Given the geometrical constellation of the Polarstern observation towards the bow of the ship and the sounding launch platform at the aft of the ship, and depending on the wind direction relative to the ship, it can be assumed that at least one of the T measurements is less impacted from the ship exhaust than the other, and is retained. In a next step, the 10 - 30 m height segment in T and RH is filled with a linear interpolation between the Met Tower at 10 m and the radiosonde observation at 30 m. When identified, remaining T/RH peaks in the lowermost 100 m of the profile are removed and filled with a linear interpolation from below to above the peak. T/RH flags are provided to indicate where the profiles have been manipulated from the original data, and to indicate the reason for missing data in the profile. Compared to the original profiles, this blended product adds value and quality control in the lowest 100 m, which makes it better suitable, for example, for boundary layer analyses.
    Keywords: Arctic Ocean; boundary layer; DATE/TIME; Event label; FLUX_TOWER; Flux tower; LATITUDE; LONGITUDE; MOSAiC; MOSAiC20192020; Multidisciplinary drifting Observatory for the Study of Arctic Climate; North Greenland Sea; Other event; Polarstern; Profile; PS122/1; PS122/1_10-103; PS122/1_10-105; PS122/1_10-106; PS122/1_10-107; PS122/1_10-108; PS122/1_10-134; 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_2-10; PS122/1_2-100; PS122/1_2-101; PS122/1_2-102; PS122/1_2-103; PS122/1_2-104; PS122/1_2-105; PS122/1_2-106; PS122/1_2-107; PS122/1_2-11; 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_2-12; 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_2-141; PS122/1_2-142; 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_2-16; PS122/1_2-160; PS122/1_2-161; PS122/1_2-162; PS122/1_2-163; PS122/1_2-17; 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_2-20; PS122/1_2-204; PS122/1_2-205; PS122/1_2-21; PS122/1_2-27; PS122/1_2-28; PS122/1_2-29; PS122/1_2-31; PS122/1_2-32; PS122/1_2-33; PS122/1_2-34; PS122/1_2-36; PS122/1_2-37; PS122/1_2-38; PS122/1_2-39; PS122/1_2-4; PS122/1_2-41; PS122/1_2-42; PS122/1_2-43; PS122/1_2-44; PS122/1_2-49; PS122/1_2-5; 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_2-6; PS122/1_2-60; PS122/1_2-61; PS122/1_2-62; PS122/1_2-69; PS122/1_2-7; 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_2-86; PS122/1_2-87; PS122/1_2-88; PS122/1_2-9; 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_5-37; 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_6-53; 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_7-29; 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_9-100; 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_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_16-3; 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_16-67; 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_17-104; 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_18-28; 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_19-25; 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_21-132; 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_22-41; 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_22-86; 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-
    Type: Dataset
    Format: text/tab-separated-values, 3036 data points
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  • 3
    Publication Date: 2016-10-31
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , isiRev
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  • 4
    Publication Date: 2022-05-25
    Description: Author Posting. © American Meteorological Society, 2009. This article is posted here by permission of The UK–SOLAS projects were funded by the Natural Environment Research Council Grants NE/C001826/1 (HiWASE), NE/C001842/1 (SEASAW), NE/C001702/1 (DOGEE), and NE/E011489/1 (DMS Fluxes); and by NSF Grants ATM05-26341 (Hawaii), OCE-0623450 (Miami), and NSF-OCE 0549887/0834340/0550000 (APL-UW). for personal use, not for redistribution. The definitive version was published in Bulletin of the American Meteorological Society 90 (2009): 629-644, doi:10.1175/2008BAMS2578.1.
    Description: As part of the U.K. contribution to the international Surface Ocean–Lower Atmosphere Study, a series of three related projects—DOGEE, SEASAW, and HiWASE—undertook experimental studies of the processes controlling the physical exchange of gases and sea spray aerosol at the sea surface. The studies share a common goal: to reduce the high degree of uncertainty in current parameterization schemes. The wide variety of measurements made during the studies, which incorporated tracer and surfactant release experiments, included direct eddy correlation fluxes, detailed wave spectra, wind history, photographic retrievals of whitecap fraction, aerosol-size spectra and composition, surfactant concentration, and bubble populations in the ocean mixed layer. Measurements were made during three cruises in the northeast Atlantic on the RRS Discovery during 2006 and 2007; a fourth campaign has been making continuous measurements on the Norwegian weather ship Polarfront since September 2006. This paper provides an overview of the three projects and some of the highlights of the measurement campaigns.
    Description: As part of the U.K. contribution to the international Surface Ocean–Lower Atmosphere Study, a series of three related projects—DOGEE, SEASAW, and HiWASE—undertook experimental studies of the processes controlling the physical exchange of gases and sea spray aerosol at the sea surface. The studies share a common goal: to reduce the high degree of uncertainty in current parameterization schemes. The wide variety of measurements made during the studies, which incorporated tracer and surfactant release experiments, included direct eddy correlation fluxes, detailed wave spectra, wind history, photographic retrievals of whitecap fraction, aerosol-size spectra and composition, surfactant concentration, and bubble populations in the ocean mixed layer. Measurements were made during three cruises in the northeast Atlantic on the RRS Discovery during 2006 and 2007; a fourth campaign has been making continuous measurements on the Norwegian weather ship Polarfront since September 2006. This paper provides an overview of the three projects and some of the highlights of the measurement campaigns.
    Repository Name: Woods Hole Open Access Server
    Type: Article
    Format: application/pdf
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  • 5
    Publication Date: 2022-05-26
    Description: © 2008 The Authors. This article is distributed under the terms of the Creative Commons Attribution 3.0 License. The definitive version was published in Ocean Science 4 (2008): 247-263, doi: 10.5194/os-4-247-2008
    Description: The current status of meteorological sensors used aboard ships and buoys to measure the air-sea fluxes of momentum, heat, and freshwater is reviewed. Methods of flux measurement by the bulk aerodynamic, inertial dissipation and eddy-correlation methods are considered; and areas are identified where improvements are needed in measurement of the basic variables. In some cases, what is required is the transition from emergent to operational technology, in others new technologies are needed. Uncertainties in measured winds caused by flow distortion over the ship are discussed; and the possible role of computational fluid mechanics models to obtain corrections is considered. Basic studies are also needed on the influence of waves and rain on the fluxes. The issues involved in the specification of sea surface temperature are described, and the relative merits of the available sensors are discussed. The improved capability of buoy-mounted systems will depend on the emergence of low-power instruments, and/or new means of increasing the available power capacity. Other issues covered include the continuing uncertainty about the performance of rain gauges and short-wave radiometers. Also, the requirements for new instruments to extend the range of observations to extreme wind conditions are outlined, and the latest developments in the measurement of aerosol fluxes by eddy-correlation are presented.
    Description: The lead author acknowledges support of the NOAA Climate Observation Program.
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 6
    Publication Date: 2022-05-26
    Description: © The Author(s), 2019. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Renfrew, I. A., Pickart, R. S., Vage, K., Moore, G. W. K., Bracegirdle, T. J., Elvidge, A. D., Jeansson, E., Lachlan-Cope, T., McRaven, L. T., Papritz, L., Reuder, J., Sodemann, H., Terpstra, A., Waterman, S., Valdimarsson, H., Weiss, A., Almansi, M., Bahr, F., Brakstad, A., Barrell, C., Brooke, J. K., Brooks, B. J., Brooks, I. M., Brooks, M. E., Bruvik, E. M., Duscha, C., Fer, I., Golid, H. M., Hallerstig, M., Hessevik, I., Huang, J., Houghton, L., Jonsson, S., Jonassen, M., Jackson, K., Kvalsund, K., Kolstad, E. W., Konstali, K., Kristiansen, J., Ladkin, R., Lin, P., Macrander, A., Mitchell, A., Olafsson, H., Pacini, A., Payne, C., Palmason, B., Perez-Hernandez, M. D., Peterson, A. K., Petersen, G. N., Pisareva, M. N., Pope, J. O., Seidl, A., Semper, S., Sergeev, D., Skjelsvik, S., Soiland, H., Smith, D., Spall, M. A., Spengler, T., Touzeau, A., Tupper, G., Weng, Y., Williams, K. D., Yang, X., & Zhou, S. The Iceland Greenland Seas Project. Bulletin of the American Meteorological Society, 100(9), (2019): 1795-1817, doi:10.1175/BAMS-D-18-0217.1.
    Description: The Iceland Greenland Seas Project (IGP) is a coordinated atmosphere–ocean research program investigating climate processes in the source region of the densest waters of the Atlantic meridional overturning circulation. During February and March 2018, a field campaign was executed over the Iceland and southern Greenland Seas that utilized a range of observing platforms to investigate critical processes in the region, including a research vessel, a research aircraft, moorings, sea gliders, floats, and a meteorological buoy. A remarkable feature of the field campaign was the highly coordinated deployment of the observing platforms, whereby the research vessel and aircraft tracks were planned in concert to allow simultaneous sampling of the atmosphere, the ocean, and their interactions. This joint planning was supported by tailor-made convection-permitting weather forecasts and novel diagnostics from an ensemble prediction system. The scientific aims of the IGP are to characterize the atmospheric forcing and the ocean response of coupled processes; in particular, cold-air outbreaks in the vicinity of the marginal ice zone and their triggering of oceanic heat loss, and the role of freshwater in the generation of dense water masses. The campaign observed the life cycle of a long-lasting cold-air outbreak over the Iceland Sea and the development of a cold-air outbreak over the Greenland Sea. Repeated profiling revealed the immediate impact on the ocean, while a comprehensive hydrographic survey provided a rare picture of these subpolar seas in winter. A joint atmosphere–ocean approach is also being used in the analysis phase, with coupled observational analysis and coordinated numerical modeling activities underway.
    Description: The IGP has received funding from the U.S. National Science Foundation: Grant OCE-1558742; the U.K.’s Natural Environment Research Council: AFIS (NE/N009754/1); the Research Council of Norway: MOCN (231647), VENTILATE (229791), SNOWPACE (262710) and FARLAB (245907); and the Bergen Research Foundation (BFS2016REK01). We thank all those involved in the field work associated with the IGP, particularly the officers and crew of the Alliance, and the operations staff of the aircraft campaign.
    Repository Name: Woods Hole Open Access Server
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  • 7
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    In:  EPIC3Elementa: Science of the Anthropocene, 10(1), ISSN: 2325-1026
    Publication Date: 2022-10-18
    Description: We present an annual characterization of low-level jets (LLJs) over the Arctic Ocean using wind profiles from radiosondes launched during the Multidisciplinary drifting Observatory for the Study of Arctic Climate expedition, from October 2019 through September 2020. Our results show LLJs to be common throughout the entire year, with a mean annual frequency of occurrence of more than 40%, a typical height below 400 m, peaking at 120–180 m, and speed between 6 and 14 m s–1. Jet characteristics show some seasonal variability: During winter and the freeze-up period, they are more common and faster, with an average occurrence of 55% and speeds of 8–16 m s–1, while in summer and the transition period, they have a mean occurrence of 46% and speeds of 6–10 m s–1. They have a similar height all year, with a peak between 120 and 180 m. The ERA5 reanalysis shows a similar frequency of occurrence, but a 75 m high bias in altitude, and a small, 0.28 m s–1, slow bias in speed. The height biases are greater in the transition period, more than 130 m, while the bias in speed is similar all year. Examining jets in ERA5 over the full year and whole Arctic Ocean, we find that the frequency of occurrence depends strongly on both the season and the distance to the sea-ice edge.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , peerRev
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  • 8
    Publication Date: 2022-05-26
    Description: Author Posting. © American Meteorological Society, 2009. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Bulletin of the American Meteorological Society 90 (2009): ES9-ES16, doi:10.1175/2008BAMS2578.2.
    Repository Name: Woods Hole Open Access Server
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  • 9
    Publication Date: 2023-09-15
    Description: 〈jats:p〉Regional climate models are a valuable tool for the study of the climate processes and climate change in polar regions, but the performance of the models has to be evaluated using experimental data. The regional climate model CCLM was used for simulations for the MOSAiC period with a horizontal resolution of 14 km (whole Arctic). CCLM was used in a forecast mode (nested in ERA5) and used a thermodynamic sea ice model. Sea ice concentration was taken from AMSR2 data (C15 run) and from a high-resolution data set (1 km) derived from MODIS data (C15MOD0 run). The model was evaluated using radiosonde data and data of different profiling systems with a focus on the winter period (November–April). The comparison with radiosonde data showed very good agreement for temperature, humidity, and wind. A cold bias was present in the ABL for November and December, which was smaller for the C15MOD0 run. In contrast, there was a warm bias for lower levels in March and April, which was smaller for the C15 run. The effects of different sea ice parameterizations were limited to heights below 300 m. High-resolution lidar and radar wind profiles as well as temperature and integrated water vapor (IWV) data from microwave radiometers were used for the comparison with CCLM for case studies, which included low-level jets. LIDAR wind profiles have many gaps, but represent a valuable data set for model evaluation. Comparisons with IWV and temperature data of microwave radiometers show very good agreement.〈/jats:p〉
    Repository Name: EPIC Alfred Wegener Institut
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  • 10
    Publication Date: 2024-01-31
    Description: The Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) was a yearlong expedition supported by the icebreaker R/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.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , isiRev
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