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Origins and Levels of Seasonal Forecast Skill for Sea Ice in Hudson Bay Using Canonical Correlation Analysis
Author(s) -
Adrienne Tivy,
Stephen Howell,
B T Alt,
John Yackel,
Thomas Carrieres
Publication year - 2011
Publication title -
journal of climate
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.315
H-Index - 287
eISSN - 1520-0442
pISSN - 0894-8755
DOI - 10.1175/2010jcli3527.1
Subject(s) - bay , geopotential height , climatology , sea ice , sea surface temperature , ocean gyre , north atlantic oscillation , geopotential , ridge , atlantic multidecadal oscillation , geology , oceanography , environmental science , arctic ice pack , northern hemisphere , pacific decadal oscillation , precipitation , geography , meteorology , paleontology , subtropics , fishery , biology
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 atmosp...

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