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  • 1
    Publication Date: 2020-05-12
    Description: The combination of downward-looking airborne lidar, radar, microwave, and imaging spectrometer measurements was exploited to characterize the vertical and small-scale (down to 10 m) horizontal distribution of the thermodynamic phase of low-level Arctic mixed-layer clouds. Two cloud cases observed in a cold air outbreak and a warm air advection event observed during the Arctic CLoud Observations Using airborne measurements during polar Day (ACLOUD) campaign were investigated. Both cloud cases exhibited the typical vertical mixed-phase structure with mostly liquid water droplets at cloud top and ice crystals in lower layers. The horizontal, small-scale distribution of the thermodynamic phase as observed during the cold air outbreak is dominated by the liquid water close to the cloud top and shows no indication of ice in lower cloud layers. Contrastingly, the cloud top variability in the case observed during a warm air advection showed some ice in areas of low reflectivity or cloud holes. Radiative transfer simulations considering homogeneous mixtures of liquid water droplets and ice crystals were able to reproduce the horizontal variability in this warm air advection. Large eddy simulations (LESs) were performed to reconstruct the observed cloud properties, which were used subsequently as input for radiative transfer simulations. The LESs of the cloud case observed during the cold air outbreak, with mostly liquid water at cloud top, realistically reproduced the observations. For the warm air advection case, the simulated ice water content (IWC) was systematically lower than the measured IWC. Nevertheless, the LESs revealed the presence of ice particles close to the cloud top and confirmed the observed horizontal variability in the cloud field. It is concluded that the cloud top small-scale horizontal variability is directly linked to changes in the vertical distribution of the cloud thermodynamic phase. Passive satellite-borne imaging spectrometer observations with pixel sizes larger than 100 m miss the small-scale cloud top structures.
    Print ISSN: 1680-7316
    Electronic ISSN: 1680-7324
    Topics: Geosciences
    Published by Copernicus on behalf of European Geosciences Union.
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  • 2
    Publication Date: 2023-01-25
    Description: Two airborne field campaigns focusing on observations of Arctic mixed-phase clouds and boundary layer processes and their role with respect to Arctic amplification have been carried out in spring 2019 and late summer 2020 over the Fram Strait northwest of Svalbard. The latter campaign was closely connected to the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition. Comprehensive datasets of the cloudy Arctic atmosphere have been collected by operating remote sensing instruments, in-situ probes, instruments for the measurement of turbulent fluxes of energy and momentum, and dropsondes on board the AWI research aircraft Polar 5. In total, 24 flights with 111 flight hours have been performed over open ocean, the marginal sea ice zone, and sea ice. The datasets follow documented methods and quality assurance and are suited for studies on Arctic mixedphase clouds and their transformation processes, for studies with a focus on Arctic boundary layer processes, and for satellite validation applications. All datasets are freely available via the world data center PANGAEA.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , isiRev
    Format: application/pdf
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  • 3
    Publication Date: 2023-10-28
    Keywords: AC3; ALTITUDE; Arctic Amplification; Atmospheric Physics @ AWI; AWI_AtmoPhy; AWIPEV; AWIPEV_based; Calibration using the GRUAN radiosounding product; Comment; DATE/TIME; Factor; Koldeway Aerosol Raman Lidar (KARL), Raman channels; Monitoring station; MONS; NYA; Ny-Ålesund; Ny-Ålesund, Spitsbergen; Signal/noise ratio; Signal strength; Water vapour mixing ratio
    Type: Dataset
    Format: text/tab-separated-values, 411226 data points
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  • 4
    Publication Date: 2023-10-28
    Keywords: AC3; ALTITUDE; Arctic Amplification; Atmospheric Physics @ AWI; AWI_AtmoPhy; AWIPEV; AWIPEV_based; Calibration using the GRUAN radiosounding product; Comment; DATE/TIME; Factor; Koldeway Aerosol Raman Lidar (KARL), Raman channels; Monitoring station; MONS; NYA; Ny-Ålesund; Ny-Ålesund, Spitsbergen; Signal/noise ratio; Signal strength; Water vapour mixing ratio
    Type: Dataset
    Format: text/tab-separated-values, 224905 data points
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  • 5
    Publication Date: 2023-10-28
    Keywords: AC3; ALTITUDE; Arctic Amplification; Atmospheric Physics @ AWI; AWI_AtmoPhy; AWIPEV; AWIPEV_based; Comment; DATE/TIME; Factor; Koldeway Aerosol Raman Lidar (KARL), Raman channels; Monitoring station; MONS; NYA; Ny-Ålesund; Ny-Ålesund, Spitsbergen; Processed by the Vaisala Algorithm; Signal/noise ratio; Signal strength; Water vapour mixing ratio
    Type: Dataset
    Format: text/tab-separated-values, 631716 data points
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  • 6
    Publication Date: 2023-10-28
    Keywords: AC3; ALTITUDE; Arctic Amplification; Atmospheric Physics @ AWI; AWI_AtmoPhy; AWIPEV; AWIPEV_based; Comment; DATE/TIME; Factor; Koldeway Aerosol Raman Lidar (KARL), Raman channels; Monitoring station; MONS; NYA; Ny-Ålesund; Ny-Ålesund, Spitsbergen; Processed by the Vaisala Algorithm; Signal/noise ratio; Signal strength; Water vapour mixing ratio
    Type: Dataset
    Format: text/tab-separated-values, 539277 data points
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  • 7
    Publication Date: 2023-10-28
    Keywords: AC3; ALTITUDE; Arctic Amplification; Atmospheric Physics @ AWI; AWI_AtmoPhy; AWIPEV; AWIPEV_based; Comment; DATE/TIME; Factor; Koldeway Aerosol Raman Lidar (KARL), Raman channels; Monitoring station; MONS; NYA; Ny-Ålesund; Ny-Ålesund, Spitsbergen; Processed by the Vaisala Algorithm; Signal/noise ratio; Signal strength; Water vapour mixing ratio
    Type: Dataset
    Format: text/tab-separated-values, 1050446 data points
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  • 8
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    PANGAEA
    In:  Supplement to: Kulla, Birte Solveig; Ritter, Christoph (2019): Water vapor calibration: Using a Raman lidar and radiosoundings to obtain highly resolved water vapor profiles. Remote Sensing, 11(6), 616, https://doi.org/10.3390/rs11060616
    Publication Date: 2023-10-28
    Description: Using the Raman channels of the Koldeway Aerosol Raman Lidar (KARL) a water vapour mixing ratio is derived. Data is availiable for all measurements during the dark season since 2015. Calibration in the winters 2015/2016 and 2016/2017 was performed using the GRUAN radiosounding product. For comparison those winters where recalculated with radiosounding measurements processed by the Vaisala Algorithm. The winter 2017/2018 is calibrated using radiosounding measurement from the RS41processed by the Vaisala Algrithm. The details of the calibration of this water vapour product are explained in Kulla & Ritter 2019.
    Keywords: AC3; Arctic Amplification; Atmospheric Physics @ AWI; AWI_AtmoPhy; AWIPEV; AWIPEV_based; Monitoring station; MONS; NYA; Ny-Ålesund; Ny-Ålesund, Spitsbergen
    Type: Dataset
    Format: application/zip, 5 datasets
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  • 9
    Publication Date: 2024-04-20
    Description: During the AFLUX aircraft campaign (21.3.2019 - 11.4.2019) the AMALi Lidar was installed mostly nadir pointing. This dataset contains the cloud top altitudes below the aircraft (altitudes with strong signal increase), as well as a cloud mask, derived from the optical depth of the column. The majority of the data was collected northwest of the Svalbard archipelago. More details on the campaign can be found here (https://home.uni-leipzig.de/~ehrlich/AFLUX_wiki_doku). Please check the data documentation before using this dataset.
    Keywords: AC; AC3; AFLUX; airborne; airborne lidar; airborne measurements; Airborne Mobile Aerosol Lidar; aircraft; Aircraft; AMALi; Arctic; Arctic Amplification; Binary Object; Binary Object (File Size); cloud; cloud top altitude; Date/Time of event; Event label; Latitude of event; Lidar; Longitude of event; mixed-phase clouds; P5_216_AFLUX_2019; P5_216_AFLUX_2019_1903210301; P5_216_AFLUX_2019_1903230401; P5_216_AFLUX_2019_1903240501; P5_216_AFLUX_2019_1903250602; P5_216_AFLUX_2019_1903300701; P5_216_AFLUX_2019_1903310801; P5_216_AFLUX_2019_1904010901; P5_216_AFLUX_2019_1904031002; P5_216_AFLUX_2019_1904041101; P5_216_AFLUX_2019_1904061202; P5_216_AFLUX_2019_1904071301; P5_216_AFLUX_2019_1904081401; Polar 5; POLAR 5; RF03; RF04; RF05; RF06; RF07; RF08; RF09; RF10; RF11; RF12; RF13; RF14; Svalbard
    Type: Dataset
    Format: text/tab-separated-values, 12 data points
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  • 10
    Publication Date: 2024-04-20
    Description: The data set contains measurements performed by the passive radiometer as part of the MiRAC (Microwave Radar and radiometer for Arctic Clouds) operated on board the Polar 5 research aircraft during 14 flights of the Airborne measurements of radiative and turbulent FLUXes of energy and momentum in the Arctic boundary layer (AFLUX) campaign, carried out in spring 2019 northwest of Svalbard (Norway). The measurement campaign is embedded in the Transregional Collaborative Research Centre TR 172 (ArctiC Amplification: Climate Relevant Atmospheric and SurfaCe Processes, and Feedback Mechanisms (AC)3. The published data set consists of brightness temperature measurements at nadir view with respect to the aircrafts fuselage at six frequencies in the water vapor absorption band at around 183.31 GHz and at two additional channels at 243 and 340 GHz. It should be considerd, that the brightness temperatures have not been corrected for aircraft attitude. The data set has been quality checked and is available in netcdf format for each flight separately. Details on the instrument can be found in Mech et al. (2019, doi:10.5194/amt-12-5019-2019).
    Keywords: AC; AC3; AFLUX; airborne measurements; Aircraft; Arctic; Arctic Amplification; Binary Object; Binary Object (File Size); brightness temperature; clouds; Date/Time of event; Event label; ICI; Latitude of event; Longitude of event; microwave; Microwave Radar and radiometer for Arctic Clouds; MiRAC; P5_216_AFLUX_2019; P5_216_AFLUX_2019_1903190201; P5_216_AFLUX_2019_1903210301; P5_216_AFLUX_2019_1903230401; P5_216_AFLUX_2019_1903240501; P5_216_AFLUX_2019_1903250602; P5_216_AFLUX_2019_1903300701; P5_216_AFLUX_2019_1903310801; P5_216_AFLUX_2019_1904010901; P5_216_AFLUX_2019_1904031002; P5_216_AFLUX_2019_1904041101; P5_216_AFLUX_2019_1904061202; P5_216_AFLUX_2019_1904071301; P5_216_AFLUX_2019_1904081401; P5_216_AFLUX_2019_1904111501; Polar 5; POLAR 5; remote sensing; RF02; RF03; RF04; RF05; RF06; RF07; RF08; RF09; RF10; RF11; RF12; RF13; RF14; RF15; Svalbard; water vapor
    Type: Dataset
    Format: text/tab-separated-values, 14 data points
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