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Understanding climatic controls on sea-ice transport pathways in the Arctic Ocean

Published online by Cambridge University Press:  14 September 2017

Andrey Proshutinsky
Affiliation:
Institute of Marine Science, University of Alaska Fairbanks, P.O. Box 757220, Fairbanks, AK 99775−7220, U.S.A.
Mark Johnson
Affiliation:
Institute of Marine Science, University of Alaska Fairbanks, P.O. Box 757220, Fairbanks, AK 99775−7220, U.S.A.
Tatiana Proshutinsky
Affiliation:
Institute of Marine Science, University of Alaska Fairbanks, P.O. Box 757220, Fairbanks, AK 99775−7220, U.S.A.
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Abstract

The primary goal of this paper is to demonstrate the dependence of Arctic Ocean sea-ice transport pathways on climate variations. We build our analysis on the results of Proshutinsky and Johnson (1997), Johnson and others (1999), Polyakov and others (1999) and Proshutinsky and others (1999), where we have shown that wind-driven ice motion and upper ocean circulation alternate between anticyclonic and cyclonic states. Shifts between regimes occur at 5−7 year intervals, resulting in a 10−15 year period. The anticyclonic circulation regime has been observed in our model results for 1946−52,1958−62,1972−79,1984−88 and 1998−present. The cyclonic circulation regime prevailed during 1953−57,1963−71,1980−83 and 1989−97. The regime shifts are fundamentally important to understanding the Arctic’s general circulation and particularly useful for estimating pollution transport by sea ice and surface waters. It is important to pollution studies to understand which circulation regime prevails. Initially, we simulate trajectories of a non-reactive, conservative soluble tracer. Results from this research demonstrate realistic potential flow pathlines and we describe how those pathlines change in response to climate forcing. These results can be used to aid current and future scenario risk assessments and may provide management agencies with the tools to determine where risks from contaminants might exist.

Information

Type
Sea-Ice and Climate Variability: Modelling
Copyright
Copyright © the Author(s) [year] 2001
Figure 0

Fig. 1.Results of the EOF analysis of SSHS simulated for the period 1946−97. upper panel shows the first mode pattern of the ssh anomaly (cm) and represents 43% of the anomaly variance. the lower panel shows ssh gradients (yellow and red bars) as defined by proshutinsky and johnson (1997), and time series of the first eof mode of ssh extension coefficient (blue and red lines). blue line depicts annual mean value, and red lines shows 5 year running-mean data.

Figure 1

Fig. 2.Water-marker trajectories originating in bering strait for the periods of anticyclonic (left column) and cyclonic (right column) circulation regimes.

Figure 2

Fig. 3.Ice-marker trajectories originating in bering strait for the periods of anticyclonic (left column) and cyclonic (right column) circulation regimes.

Figure 3

Fig. 4.Ice-marker trajectories originating in ob river for the periods of anticyclonic (left column) and cyclonic (right column) circulation regimes.