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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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    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
    Type: Article , isiRev
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  • 3
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    Arctic Ocean basin liquid freshwater storage trend 1992–2012 (2014)
    John Wiley & Sons
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    Publication Date: 2022-05-26
    Description: Author Posting. © American Geophysical Union, 2014. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Geophysical Research Letters 41 (2014): 961-968, doi:10.1002/2013GL058121.
    Description: Freshwater in the Arctic Ocean plays an important role in the regional ocean circulation, sea ice, and global climate. From salinity observed by a variety of platforms, we are able, for the first time, to estimate a statistically reliable liquid freshwater trend from monthly gridded fields over all upper Arctic Ocean basins. From 1992 to 2012 this trend was 600±300 km3 yr−1. A numerical model agrees very well with the observed freshwater changes. A decrease in salinity made up about two thirds of the freshwater trend and a thickening of the upper layer up to one third. The Arctic Ocean Oscillation index, a measure for the regional wind stress curl, correlated well with our freshwater time series. No clear relation to Arctic Oscillation or Arctic Dipole indices could be found. Following other observational studies, an increased Bering Strait freshwater import to the Arctic Ocean, a decreased Davis Strait export, and enhanced net sea ice melt could have played an important role in the freshwater trend we observed.
    Description: This work was supported by the cooperative project 03F0605E, funded by the German Federal Ministry for Education and Research (BMBF), and by the European Union Sixth Framework Programme project DAMOCLES, contract 018509GOCE.
    Description: 2014-08-12
    Keywords: Arctic ; Liquid freshwater ; Observation ; Model
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 4
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    Arctic pathways of Pacific Water : Arctic Ocean Model Intercomparison experiments (2016)
    John Wiley & Sons
    Details
    Publication Date: 2022-05-26
    Description: © The Author(s), 2016. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Journal of Geophysical Research: Oceans 121 (2016): 27–59, doi:10.1002/2015JC011299.
    Description: Pacific Water (PW) enters the Arctic Ocean through Bering Strait and brings in 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 spreads from the Bering Strait region in three major branches. One of them starts in the Barrow Canyon, bringing PW along the continental slope of Alaska into the Canadian Straits and then into Baffin Bay. The second begins 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 into the Beaufort Gyre. 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 affects the simulated PW pathways by changing the vertical shear of the relative vorticity of the ocean flow in the Canada Basin.
    Description: National Science Foundation (NSF). Grant Numbers: PLR-0806306 , PLR-85653100 , PLR-82486400 , PLR-1313614; NASA Advanced Supercomputing (NAS) Division; JPL Supercomputing and Visualization Facility (SVF) Grant Numbers: ARC-0806306 , ARC-85653100 , ARC-82486400; Russian Foundation of Basic Research; Ministry of the Education and Science of the Russian Federation; UK Natural Environment Research Council Grant Number: NE/I028947/
    Keywords: Arctic Ocean ; Beaufort Gyre ; Pacific Water ; Ocean dynamics ; Wind forcing
    Repository Name: Woods Hole Open Access Server
    Type: Article
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