scholarly journals Origins and Levels of Seasonal Forecast Skill for Sea Ice in Hudson Bay Using Canonical Correlation Analysis

2011 ◽  
Vol 24 (5) ◽  
pp. 1378-1395 ◽  
Author(s):  
Adrienne Tivy ◽  
Stephen E. L. Howell ◽  
Bea Alt ◽  
John J. Yackel ◽  
Thomas Carrieres

Abstract Canonical correlation analysis (CCA) is used to estimate the levels and sources of seasonal forecast skill for July ice concentration in Hudson Bay over the 1971–2005 period. July is an important transition month in the seasonal cycle of sea ice in Hudson Bay because it is the month when the sea ice clears enough to allow the first passage of ships to the Port of Churchill. Sea surface temperature (quasi global, North Atlantic, and North Pacific), Northern Hemisphere 500-mb geopotential height (z500), sea level pressure (SLP), and regional surface air temperature (SAT) are tested as predictors at 3-, 6-, and 9-month lead times. The model with the highest skill has three predictors—fall North Atlantic SST, fall z500, and fall SAT—and significant tercile forecast skill covering 61% of the Hudson Bay region. The highest skill for a single-predictor model is from fall North Atlantic SST (6-month lead). Fall SST explains 69% of the variance in July ice concentration in Hudson Bay and a possible atmospheric link that accounts for the lagged relationship is presented. CCA diagnostics suggest that changes in the subpolar North Atlantic gyre and the Atlantic multidecadal oscillation (AMO), reflected in sea surface temperature, precedes a deepening/weakening of the winter upper-air ridge northwest of Hudson Bay. Changes in the height of the ridge are reflected in the strength of the winter northwesterly winds over Hudson Bay that have a direct impact on the winter ice thickness distribution; anomalies in winter ice severity are later reflected in the pattern and timing of spring breakup. July ice concentration in Hudson Bay has declined by approximately 20% per decade between 1979 and 2007, and the hypothesized link to the AMO may help explain this significant loss of ice.

1985 ◽  
Vol 24 (02) ◽  
pp. 91-100 ◽  
Author(s):  
W. van Pelt ◽  
Ph. H. Quanjer ◽  
M. E. Wise ◽  
E. van der Burg ◽  
R. van der Lende

SummaryAs part of a population study on chronic lung disease in the Netherlands, an investigation is made of the relationship of both age and sex with indices describing the maximum expiratory flow-volume (MEFV) curve. To determine the relationship, non-linear canonical correlation was used as realized in the computer program CANALS, a combination of ordinary canonical correlation analysis (CCA) and non-linear transformations of the variables. This method enhances the generality of the relationship to be found and has the advantage of showing the relative importance of categories or ranges within a variable with respect to that relationship. The above is exemplified by describing the relationship of age and sex with variables concerning respiratory symptoms and smoking habits. The analysis of age and sex with MEFV curve indices shows that non-linear canonical correlation analysis is an efficient tool in analysing size and shape of the MEFV curve and can be used to derive parameters concerning the whole curve.


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