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  • 1
    Dissertations
    Dissertations
    Rapid climate changes in the Arctic region of Svalbard : processes, implications and representativeness for the broader Arctic (2019)
    Potsdam : Universität Potsdam
    Details Availability
    Call number: AWI A4-20-93991
    Description / Table of Contents: Over the last decades, the Arctic regions of the earth have warmed at a rate 2–3 times faster than the global average– a phenomenon called Arctic Amplification. A complex, non-linear interplay of physical processes and unique pecularities in the Arctic climate system is responsible for this, but the relative role of individual processes remains to be debated. This thesis focuses on the climate change and related processes on Svalbard, an archipelago in the North Atlantic sector of the Arctic, which is shown to be a "hotspot" for the amplified recent warming during winter. In this highly dynamical region, both oceanic and atmospheric large-scale transports of heat and moisture interfere with spatially inhomogenous surface conditions, and the corresponding energy exchange strongly shapes the atmospheric boundary layer. In the first part, Pan-Svalbard gradients in the surface air temperature (SAT) and sea ice extent (SIE) in the fjords are quantified and characterized. This analysis is based on observational data from meteorological stations, operational sea ice charts, and hydrographic observations from the adjacent ocean, which cover the 1980–2016 period. [...]
    Type of Medium: Dissertations
    Pages: xv, 123 Seiten , Illustrationen, Diagramme
    URL: http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-445542
    URL: https://doi.org/10.25932/publishup-44554
    URN: urn:nbn:de:kobv:517-opus4-445542
    DOI: 10.25932/publishup-44554
    Language: English
    Note: Dissertation, Universität Potsdam, 2020 , CONTENTS 1 Introduction 1.1 Context: A rapidly changing Arctic 1.1.1 Documentation of recent changes in the Arctic 1.1.2 Research relevance 1.1.3 Objective: Svalbard as a hotspot for climate change 1.2 Physical Background 1.2.1 Radiation and surface energy balance 1.2.2 Peculiarities of the Arctic climate system 1.2.3 Role of atmospheric circulation 1.3 The regional setup on Svalbard 2 data and methods 2.1 Data description 2.1.1 Era-Interim atmospheric reanalysis 2.1.2 Svalbard Station Meteorology 2.1.3 Sea Ice Extent 2.1.4 Ocean data products 2.1.5 FLEXTRA Trajectories 2.2 Statistical Methods 2.2.1 Trend estimation 2.2.2 Correlation 2.2.3 Coefficient of Determination 3 state of surface climate parameters: pan-svalbard differences 3.1 Motivation 3.2 Surface air temperature 3.2.1 Annual cycle 3.2.2 Annual temperature range 3.2.3 Long-term trends 3.3 Fjord Sea Ice coverage 3.3.1 Climatology 3.3.2 Sea ice cover trends 3.3.3 Regional classification across Svalbard 3.3.4 Drivers of regional differences 3.4 Discussion and Conclusion 3.5 Current state of climate projections for the Svalbard region 4 Air mass back trajectories 4.1 Methodology 4.2 Winter 4.2.1 Source Regions of Ny-Ålesund Air 4.2.2 Circulation changes 4.2.3 Quantification of Advective Warming 4.3 Summer 4.3.1 Source Regions of Ny-Ålesund Air 4.3.2 Circulation changes 4.3.3 Quantification of advective cooling 4.3.4 Observational Case Study: May/June 2017 4.4 Discussion and Conclusion 5 Changing drivers of the arctic near surface temperature budget 5.1 Winter 5.2 Summer 5.3 Summary 6 Summary and conclusion A Details on calculations A.1 SLP composite Index A.2 Derivation of coefficient of determination A.3 Temperature effect of changing source regions over time B Supplementary figures Bibliography
    Location: AWI Reading room
    Branch Library: AWI Library
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  • 2
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    Meteorological conditions during the ACLOUD/PASCAL field campaign near Svalbard in early summer 2017 (2018)
    Copernicus
    Details
    Publication Date: 2018-12-18
    Description: The two concerted field campaigns, Arctic CLoud Observations Using airborne measurements during polar Day (ACLOUD) and the Physical feedbacks of Arctic planetary boundary level Sea ice, Cloud and AerosoL (PASCAL), took place near Svalbard from 23 May to 26 June 2017. They were focused on studying Arctic mixed-phase clouds and involved observations from two airplanes (ACLOUD), an icebreaker (PASCAL) and a tethered balloon, as well as ground-based stations. Here, we present the synoptic development during the 35-day period of the campaigns, using near-surface and upper-air meteorological observations, as well as operational satellite, analysis, and reanalysis data. Over the campaign period, short-term synoptic variability was substantial, dominating over the seasonal cycle. During the first campaign week, cold and dry Arctic air from the north persisted, with a distinct but seasonally unusual cold air outbreak. Cloudy conditions with mostly low-level clouds prevailed. The subsequent 2 weeks were characterized by warm and moist maritime air from the south and east, which included two events of warm air advection. These synoptical disturbances caused lower cloud cover fractions and higher-reaching cloud systems. In the final 2 weeks, adiabatically warmed air from the west dominated, with cloud properties strongly varying within the range of the two other periods. Results presented here provide synoptic information needed to analyze and interpret data of upcoming studies from ACLOUD/PASCAL, while also offering unprecedented measurements in a sparsely observed region.
    Print ISSN: 1680-7316
    Electronic ISSN: 1680-7324
    Topics: Geosciences
    Published by Copernicus on behalf of European Geosciences Union.
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  • 3
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    Contribution of Atmospheric Advection to the Amplified Winter Warming in the Arctic North Atlantic Region (2017)
    Hindawi
    Details
    Publication Date: 2017-01-01
    Description: Arctic Amplification of climate warming is caused by various feedback processes in the atmosphere-ocean-ice system and yields the strongest temperature increase during winter in the Arctic North Atlantic region. In our study, we attempt to quantify the advective contribution to the observed atmospheric warming in the Svalbard area. Based on radiosonde measurements from Ny-Ålesund, a strong dependence of the tropospheric temperature on the synoptic flow direction is revealed. Using FLEXTRA backward trajectories, an increase of advection from the lower latitude Atlantic region towards Ny-Ålesund is found that is attributed to a change in atmospheric circulation patterns. We find that about one-quarter (0.45 K per decade) of the observed atmospheric winter near surface warming trend in the North Atlantic region of the Arctic (2 K per decade) is due to increased advection of warm and moist air from the lower latitude Atlantic region, affecting the entire troposphere.
    Print ISSN: 1687-9309
    Electronic ISSN: 1687-9317
    Topics: Geosciences , Physics
    Published by Hindawi
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  • 4
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    Synoptic development during the ACLOUD/PASCAL field campaign near Svalbard in spring 2017 (2018)
    Copernicus
    Details
    Publication Date: 2018-05-23
    Description: The two concerted field campaigns Arctic CLoud Observations Using airborne measurements during polar Day (ACLOUD) and the Physical feedbacks of Arctic planetary boundary level Sea ice, Cloud and AerosoL (PASCAL) took place near Svalbard from 23 May to 26 June 2017. They were focused on studying Arctic mixed-phase clouds and involved observations from two airplanes (ACLOUD), an icebreaker (PASCAL), as well as surface-based stations, a tethered balloon, and satellites. Here, we present the synoptic development during the 35 day period of the campaigns, using classical near-surface and upper-air meteorological observations, as well as operational satellite and model data. Over the campaign period, short-term synoptic variability was substantial, dominating over the long-term background effect of Arctic amplification. During the first campaign week, cold and dry Arctic air from the north persisted, with a distinct but seasonally unusual cold air outbreak. Cloudy conditions with mostly low-level clouds prevailed. The subsequent two weeks were characterized by warm and moist maritime air from the south and east, which included two warm air advections. These synoptical disturbances caused lower cloud cover fractions and higher-reaching cloud systems. In the final two weeks, adiabatically warmed westerly air dominated, with a strongly varying cloud distribution in between the two other periods. Results presented here provide synoptic information needed to analyze and interpret data of upcoming studies from ACLOUD/PASCAL, while also offering unprecedented measurements in a sparsely observed region.
    Electronic ISSN: 1680-7375
    Topics: Geosciences
    Published by Copernicus on behalf of European Geosciences Union.
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  • 5
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    The observed recent surface air temperature development across Svalbard and concurring footprints in local sea ice cover (2020)
    Wiley
    Details
    Publication Date: 2020-02-22
    Print ISSN: 0899-8418
    Electronic ISSN: 1097-0088
    Topics: Geosciences , Physics
    Published by Wiley
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  • 6
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    Tropische Instabilitätswellen und Vermischungsprozesse in der oberen Wassersäule des östlichen tropischen Atlantiks (2012)
    In:  (Bachelor thesis), Christian-Albrechts-Universität Kiel, Kiel, Germany, 29 pp
    Details
    Publication Date: 2013-04-19
    Keywords: Course of study: BSc Physics of the Earth System
    Type: Thesis , NonPeerReviewed
    Format: text
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  • 7
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    Global teleconnections associated with diabatic heating due to local rainfall events (2015)
    In:  (Master thesis), Christian-Albrechts-Universität Kiel, Kiel, Germany, 71 pp
    Details
    Publication Date: 2016-09-12
    Keywords: Course of study: MSc Climate Physics
    Type: Thesis , NonPeerReviewed
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  • 8
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    The unexpected smoke layer in the High Arctic winter stratosphere during MOSAiC 2019–2020 (2021)
    Copernicus
    Details
    Publication Date: 2021-10-22
    Description: During the 1-year MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate) expedition, the German icebreaker Polarstern drifted through Arctic Ocean ice from October 2019 to May 2020, mainly at latitudes between 85 and 88.5∘ N. A multiwavelength polarization Raman lidar was operated on board the research vessel and continuously monitored aerosol and cloud layers up to a height of 30 km. During our mission, we expected to observe a thin residual volcanic aerosol layer in the stratosphere, originating from the Raikoke volcanic eruption in June 2019, with an aerosol optical thickness (AOT) of 0.005–0.01 at 500 nm over the North Pole area during the winter season. However, the highlight of our measurements was the detection of a persistent, 10 km deep aerosol layer in the upper troposphere and lower stratosphere (UTLS), from about 7–8 to 17–18 km height, with clear and unambiguous wildfire smoke signatures up to 12 km and an order of magnitude higher AOT of around 0.1 in the autumn of 2019. Case studies are presented to explain the specific optical fingerprints of aged wildfire smoke in detail. The pronounced aerosol layer was present throughout the winter half-year until the strong polar vortex began to collapse in late April 2020. We hypothesize that the detected smoke originated from extraordinarily intense and long-lasting wildfires in central and eastern Siberia in July and August 2019 and may have reached the tropopause layer by the self-lifting process. In this article, we summarize the main findings of our 7-month smoke observations and characterize the aerosol in terms of geometrical, optical, and microphysical properties. The UTLS AOT at 532 nm ranged from 0.05–0.12 in October–November 2019 and 0.03–0.06 during the main winter season. The Raikoke aerosol fraction was estimated to always be lower than 15 %. We assume that the volcanic aerosol was above the smoke layer (above 13 km height). As an unambiguous sign of the dominance of smoke in the main aerosol layer from 7–13 km height, the particle extinction-to-backscatter ratio (lidar ratio) at 355 nm was found to be much lower than at 532 nm, with mean values of 55 and 85 sr, respectively. The 355–532 nm Ångström exponent of around 0.65 also clearly indicated the presence of smoke aerosol. For the first time, we show a distinct view of the aerosol layering features in the High Arctic from the surface up to 30 km height during the winter half-year. Finally, we provide a vertically resolved view on the late winter and early spring conditions regarding ozone depletion, smoke occurrence, and polar stratospheric cloud formation. The latter will largely stimulate research on a potential impact of the unexpected stratospheric aerosol perturbation on the record-breaking ozone depletion in the Arctic in spring 2020.
    Print ISSN: 1680-7316
    Electronic ISSN: 1680-7324
    Topics: Geosciences
    Published by Copernicus on behalf of European Geosciences Union.
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  • 9
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    Radiosonde measurements in 2019-12 during MOSAiC Legs PS122/1 and PS122/2 (level 3 data) (2022)
    PANGAEA
    Details
    Publication Date: 2023-06-27
    Description: This Level 3 dataset of radiosondes launched during the MOSAiC expedition has been processed by the Global Climate Observing System (GCOS) Reference Upper-Air Network (GRUAN) algorithm for RS41 radiosonde data. The GRUAN processing is based on the extensive characterisation of the sensor properties to produce a traceable reference data product which is free of manufacturer-dependent effects. Uncertainty values are provided for all measured parameters at all height levels. It should be noted that all provided height information is obtained from the GPS measurement. Close to buildings and metal surfaces (such as RV Polarstern) GPS signals are often very noisy, resulting in artifacts in the vertical elevation coordinate close to the surface. In the atmospheric boundary layer, it is therefore recommended to rely on height calculations based on pressure. Please note that the TAB-delimited ascii format data present only a subset of parameters. The complete GRUAN-processed data are available in the linked netCDF files.
    Keywords: ALTITUDE; Altitude, uncertainty; Arctic; Arctic Ocean; Ascent rate; Ascent rate, uncertainty; DATE/TIME; Day-Night indicator; Dew/frost point; Dew/frost point, uncertainty; Event label; GCOS Reference Upper-Air Network; Geoid difference; GNSS receiver mounted on radiosonde RS41; GRUAN; Height, uncertainty; Height above sea level; Horizon correction angle; Humidity, relative; Humidity, relative, uncertainty; humidity profile; LATITUDE; Latitude, uncertainty; LONGITUDE; Longitude, uncertainty; MOSAiC; MOSAiC20192020; Multidisciplinary drifting Observatory for the Study of Arctic Climate; Polarstern; Pressure, at given altitude; Pressure, at given altitude, uncertainty; 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_9-100; PS122/1_9-101; PS122/1_9-102; PS122/1_9-105; PS122/1_9-106; PS122/1_99-46; PS122/1_99-47; PS122/2; 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_18-11; PS122/2_18-12; PS122/2_18-13; PS122/2_18-20; PS122/2_18-21; PS122/2_18-22; RADIO; Radiosonde; Radiosonde, Vaisala, RS41; radiosondes; Solar azimuth angle; Solar elevation angle; Temperature, air; Temperature, air, uncertainty; temperature profiles; upper air profiles; Water vapour content, integrated; Water vapour content, integrated, uncertainty; Water vapour mixing ratio; Water vapour mixing ratio, uncertainty; Water vapour partial pressure; Water vapour partial pressure, uncertainty; Water vapour saturation pressure; Water vapour saturation pressure, uncertainty; Wind direction; Wind direction, uncertainty; Wind speed; Wind speed, uncertainty
    Type: Dataset
    Format: text/tab-separated-values, 22932933 data points
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  • 10
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    Radiosonde measurements in 2019-10 during MOSAiC Leg PS122/1 (level 2 data) (2021)
    PANGAEA
    In:  Alfred Wegener Institute - Research Unit Potsdam
    Details
    Publication Date: 2023-06-27
    Description: This is a Level 2 dataset of radiosondes launched during the MOSAiC expedition. The balloon-borne radiosondes measured temperature, pressure, relative humidity and wind from board R/V Polarstern to about 30 km height, commonly four times daily during the entire expedition period. The objective of Level 2 is to provide the user community with a usable data product before the final processed product is completed. Quality control for appropriate physical ranges has been applied. However, it should be noted that potential inconsistencies in the physical data in particular in the lowermost part of the profiles are not corrected. This regards e.g. GPS altitude close to the surface and wind direction at latitudes 〉89° N.
    Keywords: ALTITUDE; Arctic; Arctic Ocean; AWI_Meteo; Calculated from GPS; DATE/TIME; Elapsed time; Event label; GPS receiver mounted on radiosonde RS41; Height, geometric; Humidity, relative; integrated from pressure and temperature; LATITUDE; LONGITUDE; Meteorological Long-Term Observations @ AWI; MOSAiC; MOSAiC20192020; Multidisciplinary drifting Observatory for the Study of Arctic Climate; Polarstern; Pressure, at given altitude; PS122/1; 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_2-142; 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_2-160; 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_5-37; PS122/1_5-6; PS122/1_5-7; RADIO; Radiosonde; Radiosonde, Vaisala, RS41; radiosondes; Temperature, air; temperature profiles; upper air profiles; Wind direction; Wind speed
    Type: Dataset
    Format: text/tab-separated-values, 5115478 data points
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