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  • 1
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    Sea Ice Rheology Experiment (SIREx): 2. Evaluating Linear Kinematic Features in High‐Resolution Sea Ice Simulations (2022)
    Details
    Publication Date: 2022-09-22
    Description: Simulating sea ice drift and deformation in the Arctic Ocean is still a challenge because of the multiscale interaction of sea ice floes that compose the Arctic Sea ice cover. The Sea Ice Rheology Experiment (SIREx) is a model intercomparison project of the Forum of Arctic Modeling and Observational Synthesis (FAMOS). In SIREx, skill metrics are designed to evaluate different recently suggested approaches for modeling linear kinematic features (LKFs) to provide guidance for modeling small‐scale deformation. These LKFs are narrow bands of localized deformation that can be observed in satellite images and also form in high resolution sea ice simulations. In this contribution, spatial and temporal properties of LKFs are assessed in 36 simulations of state‐of‐the‐art sea ice models and compared to deformation features derived from the RADARSAT Geophysical Processor System. All simulations produce LKFs, but only very few models realistically simulate at least some statistics of LKF properties such as densities, lengths, or growth rates. All SIREx models overestimate the angle of fracture between conjugate pairs of LKFs and LKF lifetimes pointing to inaccurate model physics. The temporal and spatial resolution of a simulation and the spatial resolution of atmospheric boundary condition affect simulated LKFs as much as the model's sea ice rheology and numerics. Only in very high resolution simulations (≤2 km) the concentration and thickness anomalies along LKFs are large enough to affect air‐ice‐ocean interaction processes.
    Description: Plain Language Summary: Winds and ocean currents continuously move and deform the sea ice cover of the Arctic Ocean. The deformation eventually breaks an initially closed ice cover into many individual floes, piles up floes, and creates open water. The distribution of ice floes and open water between them is important for climate research, because ice reflects more light and energy back to the atmosphere than open water, so that less ice and more open water leads to warmer oceans. Current climate models cannot simulate sea ice as individual floes. Instead, a variety of methods is used to represent the movement and deformation of the sea ice cover. The Sea Ice Rheology Experiment (SIREx) compares these different methods and assesses the deformation of sea ice in 36 numerical simulations. We identify and track deformation features in the ice cover, which are distinct narrow areas where the ice is breaking or piling up. Comparing specific spatial and temporal properties of these features, for example, the different amounts of fractured ice in specific regions, or the duration of individual deformation events, to satellite observations provides information about the realism of the simulations. From this comparison, we can learn how to improve sea ice models for more realistic simulations of sea ice deformation.
    Description: Key Points: All models simulate linear kinematic features (LKFs), but none accurately reproduces all LKF statistics. Resolved LKFs are affected strongest by spatial and temporal resolution of model grid and atmospheric forcing and rheology. Accurate scaling of deformation rates is a proxy only for realistic LKF numbers but not for any other LKF static.
    Description: DOE
    Description: HYCOM NOPP
    Description: Innovation Fund Denmark and the Horizon 2020 Framework Programme of the European Union
    Description: National centre for Climate Research, SALIENSEAS, ERA4CS
    Description: German Helmholtz Climate Initiative REKLIM (Regional Climate Change)
    Description: Gouvernement du Canada, Natural Sciences and Engineering Research Council of Canada (NSERC) http://dx.doi.org/10.13039/501100000038
    Description: Environment and Climate Change Canada Grants & Contributions program
    Description: Office of Naval Research Arctic and Global Prediction program
    Description: U.S. Department of Energy Regional and Global Model Analysis program
    Description: National Science Foundation Arctic System Science program
    Description: Deutsche Forschungsgemeinschaft (DFG) http://dx.doi.org/10.13039/501100001659
    Description: https://zenodo.org/communities/sirex
    Keywords: ddc:550.285
    Language: English
    Type: doc-type:article
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    CITATION GEO-LEO
  • 2
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    Lagrangian ocean analysis: fundamentals and practices (2018)
    Elsevier
    In:  Ocean Modelling, 121 . pp. 49-75.
    Details
    Publication Date: 2021-02-08
    Description: Highlights: • Lagrangian ocean analysis is a powerful way to analyse the output of ocean circulation models • We present a review of the Kinematic framework, available tools, and applications of Lagrangian ocean analysis • While there are unresolved questions, the framework is robust enough to be used widely in ocean modelling Abstract: Lagrangian analysis is a powerful way to analyse the output of ocean circulation models and other ocean velocity data such as from altimetry. In the Lagrangian approach, large sets of virtual particles are integrated within the three-dimensional, time-evolving velocity fields. Over several decades, a variety of tools and methods for this purpose have emerged. Here, we review the state of the art in the field of Lagrangian analysis of ocean velocity data, starting from a fundamental kinematic framework and with a focus on large-scale open ocean applications. Beyond the use of explicit velocity fields, we consider the influence of unresolved physics and dynamics on particle trajectories. We comprehensively list and discuss the tools currently available for tracking virtual particles. We then showcase some of the innovative applications of trajectory data, and conclude with some open questions and an outlook. The overall goal of this review paper is to reconcile some of the different techniques and methods in Lagrangian ocean analysis, while recognising the rich diversity of codes that have and continue to emerge, and the challenges of the coming age of petascale computing.
    Type: Article , PeerReviewed
    Format: text
    DOI: 10.1016/j.ocemod.2017.11.008
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    OceanRep: Article in a Scientific Journal - peer-reviewed
  • 3
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    An assessment of the Arctic Ocean in a suite of interannual CORE-II simulations. Part III: Hydrography and fluxes (2016)
    Elsevier
    In:  Ocean Modelling, 100 . pp. 141-161.
    Details
    Publication Date: 2019-06-28
    Description: Highlights: • We compare the simulated Arctic Ocean in 15 global ocean–sea ice models. • There is a large spread in temperature bias in the Arctic Ocean between the models. • Warm bias models have a strong temperature anomaly of inflow of Atlantic Water. • Dense outflows formed on Arctic shelves are not captured accurately in the models. In this paper we compare the simulated Arctic Ocean in 15 global ocean-sea ice models in the framework of the Coordinated Ocean-ice Reference Experiments, phase II (CORE-II). Most of these models are the ocean and sea-ice components of the coupled climate models used in the Coupled Model Intercomparison Project Phase 5 (CMIP5) experiments. We mainly focus on the hydrography of the Arctic interior, the state of Atlantic Water layer and heat and volume transports at the gateways of the Davis Strait, the Bering Strait, the Fram Strait and the Barents Sea Opening. We found that there is a large spread in temperature in the Arctic Ocean between the models, and generally large differences compared to the observed temperature at intermediate depths. Warm bias models have a strong temperature anomaly of inflow of the Atlantic Water entering the Arctic Ocean through the Fram Strait. Another process that is not represented accurately in the CORE-II models is the formation of cold and dense water, originating on the eastern shelves. In the cold bias models, excessive cold water forms in the Barents Sea and spreads into the Arctic Ocean through the St. Anna Through. There is a large spread in the simulated mean heat and volume transports through the Fram Strait and the Barents Sea Opening. The models agree more on the decadal variability, to a large degree dictated by the common atmospheric forcing. We conclude that the CORE-II model study helps us to understand the crucial biases in the Arctic Ocean. The current coarse resolution state-of-the-art ocean models need to be improved in accurate representation of the Atlantic Water inflow into the Arctic and density currents coming from the shelves.
    Type: Article , PeerReviewed , info:eu-repo/semantics/article
    Format: text
    DOI: 10.1016/j.ocemod.2016.02.004
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    OceanRep: Article in a Scientific Journal - peer-reviewed
  • 4
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    SKIM, a Candidate Satellite Mission Exploring Global Ocean Currents and Waves (2019)
    Frontiers
    In:  Frontiers in Marine Science, 6 (Art.Nr. 209).
    Details
    Publication Date: 2022-01-31
    Description: The Sea surface KInematics Multiscale monitoring (SKIM) satellite mission is designed to explore ocean surface current and waves. This includes tropical currents, notably the unknown patterns of divergence and their impact on the ocean heat budget near the Equator, monitoring of the emerging Arctic up to 82.5$(\circ)$N. SKIM will also make unprecedented direct measurements of strong currents, from boundary currents to the Antarctic circumpolar current, and their interaction with ocean waves with expected impacts on air-sea fluxes and extreme waves. For the first time, SKIM will directly measure the ocean surface current vector from space. The main instrument on SKIM is a Ka-band conically scanning, multi-beam Doppler radar altimeter/wave scatterometer that includes a state-of-the-art nadir beam comparable to the Poseidon-4 instrument on Sentinel 6. The well proven Doppler pulse-pair technique will give a surface drift velocity representative of the top two meters of the ocean, after subtracting a large wave-induced contribution. Horizontal velocity components will be obtained with an accuracy better than 7 cm/s for horizontal wavelengths larger than 80~km and time resolutions larger than 15 days, with a mean revisit time of 4 days for of 99\% of the global oceans. This will provide unique and innovative measurements that will further our understanding of the transports in the upper ocean layer, permanently distributing heat, carbon, plankton, and plastics. SKIM will also benefit from co-located measurements of water vapor, rain rate, sea ice concentration, and wind vectors provided by the European operational satellite MetOp-SG(B), allowing many joint analyses. SKIM is one of the two candidate satellite missions under development for ESA Earth Explorer 9. The other candidate is the Far infrared Radiation Understanding and Monitoring (FORUM). The final selection will be announced by September 2019, for a launch in the coming decade.
    Type: Article , PeerReviewed
    Format: text
    DOI: 10.3389/fmars.2019.00209
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    OceanRep: Article in a Scientific Journal - peer-reviewed
  • 5
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    Satellite-derived sea ice export and its impact on Arctic ice mass balance (2018)
    In:  EPIC3Polar 2018, Davos, Switzerland, 2018-06-2018-06
    Details
    Publication Date: 2018-12-06
    Description: Sea ice volume export is affecting the Arctic ice mass balance, and certainly the multiyear ice volume variability. Climate relevance is also given by the significant fresh water input into the North Atlantic, affecting the thermohaline circulation. The Fram Strait represents the main sea ice export gate in the Arctic. Here, we present the first estimates of winter sea ice volume export through the Fram Strait using CryoSat-2 sea ice thickness retrievals and three different drift products for the years 2010 to 2017. The export rates vary between 20 and 550 km3/month. We find that sea ice drift is the main driver of seasonal and interannual ice volume export variability. Moreover, 79% of the interannual variability can be explained by the relation to the North Atlantic Oscillation index (NAO). The seasonal trend, however, is driven by the mean ice thickness, associated with the thermodynamic ice growth, which is typically peaking in March. Considering Arctic winter multiyear ice volume changes, 50% of the seasonal variability can be explained by the ice volume export through the Fram Strait.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Conference , notRev
    Format: application/pdf
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    PAPER (OA)
  • 6
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    Satellite-observed drop of Arctic sea ice growth in winter 2015–2016 (2017)
    Wiley
    In:  EPIC3Geophysical Research Letters, Wiley, ISSN: 0094-8276
    Details
    Publication Date: 2017-09-25
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , isiRev
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    PAPER (OA)
  • 7
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    The Impact of Tides on Simulated Landfast Ice in a Pan-Arctic Ice-Ocean Model (2018)
    In:  EPIC3Journal of Geophysical Research: Oceans, 123, pp. 1-16, ISSN: 2169-9275
    Details
    Publication Date: 2018-11-19
    Description: The impact of tides on the simulated landfast ice cover is investigated. Pan-Arctic simulations are conducted with an ice-ocean (CICE-NEMO) model with a modified rheology and a grounding scheme. The reference experiment (without tides) indicates there is an overestimation of the extent of landfast ice in regions of strong tides such as the Gulf of Boothia, Prince Regent Inlet, and Lancaster Sound. The addition of tides in the simulation clearly leads to a decrease of the extent of landfast ice in some tidally active regions. This numerical experiment with tides is more in line with observations of landfast ice in all the regions studied. Thermodynamics and changes in grounding cannot explain the lower landfast ice area when tidal forcing is included. We rather demonstrate that this decrease in the landfast ice extent is dynamically driven by the increase of the ocean-ice stress due to the tides.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , isiRev
    Format: application/pdf
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  • 8
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    Arctic Ocean Response to Greenland Sea Wind Anomalies in a Suite of Model Simulations (2019)
    In:  EPIC3Journal of Geophysical Research: Oceans, 124(8), pp. 6286-6322
    Details
    Publication Date: 2020-05-18
    Description: Abstract Multimodel Arctic Ocean "climate response function" experiments are analyzed in order to explore the effects of anomalous wind forcing over the Greenland Sea (GS) on poleward ocean heat transport, Atlantic Water (AW) pathways, and the extent of Arctic sea ice. Particular emphasis is placed on the sensitivity of the AW circulation to anomalously strong or weak GS winds in relation to natural variability, the latter manifested as part of the North Atlantic Oscillation. We find that anomalously strong (weak) GS wind forcing, comparable in strength to a strong positive (negative) North Atlantic Oscillation index, results in an intensification (weakening) of the poleward AW flow, extending from south of the North Atlantic Subpolar Gyre, through the Nordic Seas, and all the way into the Canadian Basin. Reconstructions made utilizing the calculated climate response functions explain ~50% of the simulated AW flow variance; this is the proportion of variability that can be explained by GS wind forcing. In the Barents and Kara Seas, there is a clear relationship between the wind-driven anomalous AW inflow and the sea ice extent. Most of the anomalous AW heat is lost to the atmosphere, and loss of sea ice in the Barents Sea results in even more heat loss to the atmosphere, and thus effective ocean cooling. Release of passive tracers in a subset of the suite of models reveals differences in circulation patterns and shows that the flow of AW in the Arctic Ocean is highly dependent on the wind stress in the Nordic Seas.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , isiRev
    Format: application/pdf
    Location Call Number Limitation Availability
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  • 9
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    An assessment of the Arctic Ocean in a suite of interannual CORE-II simulations. Part III: Hydrography and fluxes (2016)
    In:  EPIC3Ocean Modelling, 100, pp. 141-161, ISSN: 14635003
    Details
    Publication Date: 2016-04-15
    Description: In this paper we compare the simulated Arctic Ocean in 15 global ocean–sea ice models in the framework of the Coordinated Ocean-ice Reference Experiments, phase II (CORE-II). Most of these models are the ocean and sea-ice components of the coupled climate models used in the Coupled Model Intercomparison Project Phase 5 (CMIP5) experiments. We mainly focus on the hydrography of the Arctic interior, the state of Atlantic Water layer and heat and volume transports at the gateways of the Davis Strait, the Bering Strait, the Fram Strait and the Barents Sea Opening. We found that there is a large spread in temperature in the Arctic Ocean between the models, and generally large differences compared to the observed temperature at intermediate depths. Warm bias models have a strong temperature anomaly of inflow of the Atlantic Water entering the Arctic Ocean through the Fram Strait. Another process that is not represented accurately in the CORE-II models is the formation of cold and dense water, originating on the eastern shelves. In the cold bias models, excessive cold water forms in the Barents Sea and spreads into the Arctic Ocean through the St. Anna Through. There is a large spread in the simulated mean heat and volume transports through the Fram Strait and the Barents Sea Opening. The models agree more on the decadal variability, to a large degree dictated by the common atmospheric forcing. We conclude that the CORE-II model study helps us to understand the crucial biases in the Arctic Ocean. The current coarse resolution state-of-the-art ocean models need to be improved in accurate representation of the Atlantic Water inflow into the Arctic and density currents coming from the shelves.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , isiRev
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  • 10
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    Satellite-derived sea ice export and its impact on Arctic ice mass balance (2018)
    In:  EPIC3The Cryosphere, 12(9), pp. 3017-3032, ISSN: 1994-0424
    Details
    Publication Date: 2018-12-06
    Description: Sea ice volume export through the Fram Strait represents an important freshwater input to the North Atlantic, which could in turn modulate the intensity of the thermoha-line circulation. It also contributes significantly to variations in Arctic ice mass balance. We present the first estimates of winter sea ice volume export through the Fram Strait using CryoSat-2 sea ice thickness retrievals and three different ice drift products for the years 2010 to 2017. The monthly export varies between − 21 and −540 km 3. We find that ice drift variability is the main driver of annual and interannual ice volume export variability and that the interannual variations in the ice drift are driven by large-scale variability in the atmospheric circulation captured by the Arctic Oscillation and North Atlantic Oscillation indices. On shorter timescale, however, the seasonal cycle is also driven by the mean thickness of exported sea ice, typically peaking in March. Considering Arctic winter multi-year ice volume changes, 54 % of their variability can be explained by the variations in ice volume export through the Fram Strait.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , isiRev
    Format: application/pdf
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