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  • PANGAEA  (18)
  • AGU (American Geophysical Union)  (4)
  • INT GLACIOL SOC  (2)
  • American Geophysical Union (AGU)  (1)
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Keywords
  • 1
    Publication Date: 2015-03-10
    Description: This study was motivated by a strong warming signal seen in mooring-based and oceanographic survey data collected in 2004 in the Eurasian Basin of the Arctic Ocean. The source of this and earlier Arctic Ocean changes lies in interactions between polar and sub-polar basins. Evidence suggests such changes are abrupt, or pulse-like, taking the form of propagating anomalies that can be traced to higher-latitudes. For example, an anomaly found in 2004 in the eastern Eurasian Basin took ∼1.5 years to propagate from the Norwegian Sea to the Fram Strait region, and additional ∼4.5–5 years to reach the Laptev Sea slope. While the causes of the observed changes will require further investigation, our conclusions are consistent with prevailing ideas suggesting the Arctic Ocean is in transition towards a new, warmer state.
    Type: Article , PeerReviewed
    Format: text
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  • 2
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    AGU (American Geophysical Union) | Wiley
    In:  Geophysical Research Letters, 42 (15). pp. 6454-6461.
    Publication Date: 2017-04-10
    Description: We use surface air temperature to evaluate the decadal forecast skill of the fully coupled Max Planck Institut Earth System Model (MPI-ESM) initialized using only surface wind stress applied to the ocean component of the model (Modini: Model initialization by partially coupled spin-up). Our analysis shows that the greenhouse gas forcing alone results in a significant forecast skill on the 2–5 and 6–9 year range even for uninitialized hindcasts. For the first forecast year, the forecast skill of Modini is generally comparable with previous initialization procedures applied to MPI-ESM. But only Modini is able to generate a significant skill (correlation) in the tropical Pacific for a 2–5 year (and to a lesser extent for a 6–9 year) hindcast. Modini is also better able to capture the observed hiatus in global warming in hindcast mode than the other methods. Finally, we present forecasts for 2015 and the average of years 2016–2019 and 2020–2024, predicting an end to the hiatus.
    Type: Article , PeerReviewed
    Format: text
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  • 3
    Publication Date: 2022-02-18
    Description: A simple polynya flux model driven by standard atmospheric forcing is used to investigate the ice formation that took place during an exceptionally strong and consistent western New Siberian (WNS) polynya event in 2004 in the Laptev Sea. Whether formation rates are high enough to erode the stratification of the water column beneath is examined by adding the brine released during the 2004 polynya event to the average winter density stratification of the water body, preconditioned by summers with a cyclonic atmospheric forcing (comparatively weakly stratified water column). Beforehand, the model performance is tested through a simulation of a well-documented event in April 2008. Neglecting the replenishment of water masses by advection into the polynya area, we find the probability for the occurrence of density-driven convection down to the bottom to be low. Our findings can be explained by the distinct vertical density gradient that characterizes the area of the WNS polynya and the apparent lack of extreme events in the eastern Laptev Sea. The simple approach is expected to be sufficiently rigorous, since the simulated event is exceptionally strong and consistent, the ice production and salt rejection rates are likely to be overestimated, and the amount of salt rejected is distrusted over a comparatively weakly stratified water column. We conclude that the observed erosion of the halocline and formation of vertically mixed water layers during a WNS polynya event is therefore predominantly related to wind- and tidally driven turbulent mixing processes.
    Type: Article , PeerReviewed
    Format: text
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  • 4
    Publication Date: 2024-01-07
    Description: Drift is a prominent parameter characterizing the Arctic sea ice cover that has a deep impact on the climate system. Hence it is a key issue to both the remote sensing as well as the modeling community, to provide reliable sea ice drift fields. This study focuses on the comparison of sea ice drift results from different sea ice‐ocean coupled models and the validation with observational data in the period 1979–2001. The models all take part in the Arctic Ocean Model Intercomparison Project (AOMIP) and the observations are mainly based on satellite imagery. According to speed distributions, one class of models has a mode at drift speeds around 3 cm s −1 and a short tail toward higher speeds. Another class shows a more even frequency distribution with large probability of drift speeds of 10 to 20 cm s −1 . Observations clearly agree better with the first class of model results. Reasons for these differences are manifold and lie in discrepancies of wind stress forcing as well as sea ice model characteristics and sea ice‐ocean coupling. Moreover, we investigated the drift patterns of anticyclonic and cyclonic wind‐driven regimes. The models are capable of producing realistic drift pattern variability. The winter of 1994/1995 stands out because of its maximum in Fram Strait ice export. Although export estimates of some models agree with observations, the corresponding inner Arctic drift pattern is not reproduced. The reason for this is found in the wind‐forcing as well as in differences in ocean velocities.
    Type: Article , PeerReviewed
    Format: text
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  • 5
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    PANGAEA
    In:  Supplement to: Hunkeler, Priska A; Hoppmann, Mario; Hendricks, Stefan; Kalscheuer, Thomas; Gerdes, Rüdiger (2016): A glimpse beneath Antarctic landfast sea ice: platelet-layer volume from multi-frequency electromagnetic induction sounding. Geophysical Research Letters, 43(1), 222-231, https://doi.org/10.1002/2015GL065074
    Publication Date: 2023-03-16
    Description: Ice shelves strongly impact coastal Antarctic sea-ice and the associated ecosystem through the formation of a sub-sea-ice platelet layer. Although progress has been made in determining and understanding its spatio-temporal variability based on point measurements, an investigation of this phenomenon on a larger scale remains a challenge due to logistical constraints and a lack of suitable methodology. In this study, we applied a laterally-constrained Marquardt-Levenberg inversion to a unique multi-frequency electromagnetic (EM) induction sounding dataset obtained on the landfast sea ice of Atka Bay, eastern Weddell Sea, in 2012. In addition to consistent fast-ice thickness and -conductivities along 〉 100 km transects; we present the first comprehensive, high resolution platelet-layer thickness and -conductivity dataset recorded on Antarctic sea ice. The reliability of the algorithm was confirmed by using synthetic data, and the inverted platelet-layer thicknesses agreed within the data uncertainty to drill-hole measurements. Ice-volume fractions were calculated from platelet-layer conductivities, revealing that an older and thicker platelet layer is denser and more compacted than a loosely attached, young platelet layer. The overall platelet-layer volume below Atka Bay fast ice suggests that the contribution of ocean/ice-shelf interaction to sea-ice volume in this region is even higher than previously thought. This study also implies that multi-frequency EM induction sounding is an effective approach in determining platelet layer volume on a larger scale than previously feasible. When applied to airborne multi-frequency EM, this method could provide a step towards an Antarctic-wide quantification of ocean/ice-shelf interaction.
    Keywords: AWI_SeaIce; Sea Ice Physics @ AWI
    Type: Dataset
    Format: application/zip, 13 datasets
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  • 6
    Publication Date: 2023-11-24
    Keywords: ANT-Land_2012; Atka_Bay_Transect_1c; Atka Bay; AWI_SeaIce; ICESUR; Ice survey; Identification; LATITUDE; LONGITUDE; NEUMAYER III; Platelet-layer conductivity; Platelet-layer thickness; Root mean square error; Sea ice conductivity; Sea Ice Physics @ AWI; Sea ice thickness; Validation flag/comment
    Type: Dataset
    Format: text/tab-separated-values, 11494 data points
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  • 7
    Publication Date: 2023-11-24
    Keywords: ANT-Land_2012; Atka_Bay_Transect_3b; Atka Bay; AWI_SeaIce; ICESUR; Ice survey; Identification; LATITUDE; LONGITUDE; NEUMAYER III; Platelet-layer conductivity; Platelet-layer thickness; Root mean square error; Sea ice conductivity; Sea Ice Physics @ AWI; Sea ice thickness; Validation flag/comment
    Type: Dataset
    Format: text/tab-separated-values, 13048 data points
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  • 8
    Publication Date: 2023-11-24
    Keywords: ANT-Land_2012; Atka_Bay_Transect_2b; Atka Bay; AWI_SeaIce; ICESUR; Ice survey; Identification; LATITUDE; LONGITUDE; NEUMAYER III; Platelet-layer conductivity; Platelet-layer thickness; Root mean square error; Sea ice conductivity; Sea Ice Physics @ AWI; Sea ice thickness; Validation flag/comment
    Type: Dataset
    Format: text/tab-separated-values, 21973 data points
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  • 9
    Publication Date: 2023-11-24
    Keywords: ANT-Land_2012; Atka_Bay_Transect_4b; Atka Bay; AWI_SeaIce; ICESUR; Ice survey; Identification; LATITUDE; LONGITUDE; NEUMAYER III; Platelet-layer conductivity; Platelet-layer thickness; Root mean square error; Sea ice conductivity; Sea Ice Physics @ AWI; Sea ice thickness; Validation flag/comment
    Type: Dataset
    Format: text/tab-separated-values, 16716 data points
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  • 10
    Publication Date: 2023-11-24
    Keywords: ANT-Land_2012; Atka_Bay_Transect_6; Atka Bay; AWI_SeaIce; ICESUR; Ice survey; Identification; LATITUDE; LONGITUDE; NEUMAYER III; Platelet-layer conductivity; Platelet-layer thickness; Root mean square error; Sea ice conductivity; Sea Ice Physics @ AWI; Sea ice thickness; Validation flag/comment
    Type: Dataset
    Format: text/tab-separated-values, 16254 data points
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