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  • 1
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    Decorrelation scales for Arctic Ocean hydrogpraphy - Part I: Amerasian Basin (2018)
    COPERNICUS GESELLSCHAFT MBH
    In:  EPIC3Ocean Science, COPERNICUS GESELLSCHAFT MBH, 14, pp. 161-185, ISSN: 1812-0784
    Details
    Publication Date: 2018-03-06
    Description: Any use of observational data for data assimilation requires adequate information of their representativeness in space and time. This is particularly important for sparse, non-synoptic data, which comprise the bulk of oceanic in situ observations in the Arctic. To quantify spatial and temporal scales of temperature and salinity variations, we estimate the autocorrelation function and associated decorrelation scales for the Amerasian Basin of the Arctic Ocean. For this purpose, we compile historical measurements from 1980 to 2015. Assuming spatial and temporal homogeneity of the decorrelation scale in the basin interior (abyssal plain area), we calculate autocorrelations as a function of spatial distance and temporal lag. The examination of the functional form of autocorrelation in each depth range reveals that the autocorrelation is well described by a Gaussian function in space and time. We derive decorrelation scales of 150–200 km in space and 100–300 days in time. These scales are directly applicable to quantify the representation error, which is essential for use of ocean in situ measurements in data assimilation. We also describe how the estimated autocorrelation function and decorrelation scale should be applied for cost function calculation in a data assimilation system.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , isiRev
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  • 2
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    Arctic pathways of Pacific Water: Arctic Ocean Model Intercomparison experiments (2016)
    Wiley
    In:  EPIC3Journal of Geophysical Research-Oceans, Wiley, 121(1), pp. 27-59, ISSN: 0148-0227
    Details
    Publication Date: 2016-11-23
    Description: Pacific Water (PW) enters the Arctic Ocean through Bering Strait and brings heat, fresh water and nutrients from the northern Bering Sea. The circulation of PW in the central Arctic Ocean is only partially understood due to the lack of observations. In this paper pathways of PW are investigated using simulations with six state-of-the art regional and global Ocean General Circulation Models (OGCMs). In the simulations PW is tracked by a passive tracer, released in Bering Strait. Simulated PW water spreads from the Bering Strait region in three major branches. One of them starts in the Barrow Canyon, bringing PW along continental slope of Alaska into the Canadian Straits and then into Baffin Bay. The other initiates in the vicinity of the Herald Canyon and transports PW along the continental slope of the East-Siberian Sea into the transpolar drift, and then through Fram Strait and the Greenland Sea. The third branch begins near the Herald Shoal and the central Chukchi shelf and brings PW waters into the Beaufort Gyre. Models suggest that the spread of PW through the Arctic Ocean depends on the atmospheric circulation. In the models the wind, acting via Ekman pumping, drives the seasonal and interannual variability of PW in the Canadian Basin of the Arctic Ocean. The wind effects the simulated PW pathways by changing vertical shear of the relative vorticity of the ocean flow in the Canada Basin. This article is protected by copyright. All rights reserved.
    Repository Name: EPIC Alfred Wegener Institut
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  • 3
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    A comparison between gradient descent and stochastic approaches for parameter optimization of a sea ice model (2013)
    COPERNICUS GESELLSCHAFT MBH
    In:  EPIC3Ocean Science, COPERNICUS GESELLSCHAFT MBH, 9(4), pp. 609-630, ISSN: 1812-0784
    Details
    Publication Date: 2019-07-16
    Description: Two types of optimization methods were applied to a parameter optimization problem in a coupled ocean--sea ice model of the Arctic, and applicability and efficiency of the respective methods were examined. One optimization utilizes a finite difference (FD) method based on a traditional gradient descent approach, while the other adopts a micro-genetic algorithm (\unit{\mu}GA) as an example of a stochastic approach. The opt\imizations were performed by minimizing a cost function composed of model--data misfit of ice concentration, ice drift velocity and ice thickness. A series of optimizations were conducted that differ in the model formulation (``smoothed code'' versus standard code) with respect to the FD method and in the population size and number of possibilities with respect to the \unit{\mu}GA method. The FD method fails to estimate optimal parameters due to the ill-shaped nature of the cost function caused by the strong non-linearity of the system, whereas the genetic algorithms can effectively estimate near optimal parameters. The results of the study indicate that the sophisticated stochastic approach (\unit{\mu}GA) is of practical use for parameter optimization of a coupled ocean--sea ice model with a medium-sized horizontal resolution of 50\,km\,$\times$\,50\,km as used in this study.
    Repository Name: EPIC Alfred Wegener Institut
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  • 4
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    Sensitivity of simulated Arctic sea ice to realistic ice thickness distributions and snow parameterizations (2014)
    Wiley
    In:  EPIC3Journal of Geophysical Research: Oceans, Wiley, 119(1), pp. 559-571, ISSN: 0148-0227
    Details
    Publication Date: 2017-10-17
    Description: Sea ice and snow on sea ice to a large extent determine the surface heat budget in the Arctic Ocean. In spite of the advances in modeling sea-ice thermodynamics, a good number of models still rely on simple parameterizations of the thermodynamics of ice and snow. Based on simulations with an Arctic sea-ice model coupled to an ocean general circulation model, we analyzed the impact of changing two sea-ice parameterizations: (1) the prescribed ice thickness distribution (ITD) for surface heat budget calculations, and (2) the description of the snow layer. For the former, we prescribed a realistic ITD derived from airborne electromagnetic induction sounding measurements. For the latter, two different types of parameterizations were tested: (1) snow thickness independent of the sea-ice thickness below, and (2) a distribution proportional to the prescribed ITD. Our results show that changing the ITD from seven uniform categories to fifteen nonuniform categories derived from field measurements, and distributing the snow layer according to the ITD, leads to an increase in average Arctic-wide ice thickness by 0.56 m and an increase by 1 m in the Canadian Arctic Archipelago and Canadian Basin. This increase is found to be a direct consequence of 524 km3 extra thermodynamic growth during the months of ice formation (January, February, and March). Our results emphasize that these parameterizations are a key factor in sea-ice modeling to improve the representation of the sea-ice energy balance.
    Repository Name: EPIC Alfred Wegener Institut
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  • 5
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    An intercomparison of Arctic ice drift products to deduce uncertainty estimates (2014)
    Wiley
    In:  EPIC3Journal of Geophysical Research: Oceans, Wiley, 119(8), pp. 4887-4921, ISSN: 0148-0227
    Details
    Publication Date: 2015-02-24
    Description: An intercomparison of four low-resolution remotely sensed ice-drift products in the Arctic Ocean is presented. The purpose of the study is to examine the uncertainty in space and time of these different drift products. The comparison is based on monthly mean ice drifts from October 2002 to December 2006. The ice drifts were also compared with available buoy data. The result shows that the differences of the drift vectors are not spatially uniform, but are covariant with ice concentration and thickness. In high (low) ice-concentration areas, the differences are small (large), and in thick (thin) ice-thickness areas, the differences are small (large). A comparison with the drift deduced from buoys reveals that the error of the drift speed depends on the magnitude of the drift speed: larger drift speeds have larger errors. Based on the intercomparison of the products and comparison with buoy data, uncertainties of the monthly mean drift are estimated. The estimated uncertainty maps reasonably reflect the difference between the products in relation to ice concentration and the bias from the buoy drift in relation to drift speed. Examinations of distinctive features of Arctic sea ice motion demonstrate that the transpolar drift speed differs among the products by 13% (0.32 cm s−1) on average, and ice drift curl in the Amerasian Basin differs by up to 24% (3.3 × 104 m2 s−1). These uncertainties should be taken into account if these products are used, particularly for model validation and data assimilation within the Arctic.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , isiRev , info:eu-repo/semantics/article
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