Predictability of Ice Concentration in the High-Latitude North Atlantic from Statistical Analysis of SST (Sea Surface Temperature) and Ice Concentration Data.
A statistical analysis of 27 years of monthly averaged sea surface temperature (SST) and ice concentration data was conducted for 17 locations along the annual mean position of the marginal ice zone spanning the North Atlantic. Anomalies (differences from monthly means) of both variables were observ...
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Format: | Text |
Language: | English |
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1987
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Online Access: | http://www.dtic.mil/docs/citations/ADA186621 http://oai.dtic.mil/oai/oai?&verb=getRecord&metadataPrefix=html&identifier=ADA186621 |
Summary: | A statistical analysis of 27 years of monthly averaged sea surface temperature (SST) and ice concentration data was conducted for 17 locations along the annual mean position of the marginal ice zone spanning the North Atlantic. Anomalies (differences from monthly means) of both variables were observed to have spatial scales of 100s to 1000s of kms, temporal scales of 6 months to several years, and a strong regional dependence. Sea surface temperature autocorrelation values were in general higher than ice concentration autocorrelation values. Cross-correlations between the two variables were found to be highly significant in some regions and poor in others. The various correlation features appeared in plausible with respect to understood physical processes in each region. For example, the data for the northern Barents and Iceland Seas showed strong cross-correlations at lags extending to over nine months. The steady-state cold water temperatures and relatively weak currents in these regions enhanced persistence of both SST and ice concentration, allowing them to interact. By contrast, the Davis Strait area, a region of strong confluent currents of different temperatures and limited ice persistence, showed weak cross-correlation values. Statistical analyses of large, homogeneous data sets as conducted in this study appear to be superior to current thermodynamic models in their potential for long-range forecasts of ice concentration. |
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