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    Independent Component Analysis of Climate Data: A New Look at EOF Rotation 

    Source: Journal of Climate:;2009:;volume( 022 ):;issue: 011:;page 2797
    Author(s): Hannachi, A.; Unkel, S.; Trendafilov, N. T.; Jolliffe, I. T.
    Publisher: American Meteorological Society
    Abstract: The complexity inherent in climate data makes it necessary to introduce more than one statistical tool to the researcher to gain insight into the climate system. Empirical orthogonal function (EOF) analysis is one of the ...
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    Two Extra Components in the Brier Score Decomposition 

    Source: Weather and Forecasting:;2008:;volume( 023 ):;issue: 004:;page 752
    Author(s): Stephenson, D. B.; Coelho, C. A. S.; Jolliffe, I. T.
    Publisher: American Meteorological Society
    Abstract: The Brier score is widely used for the verification of probability forecasts. It also forms the basis of other frequently used probability scores such as the rank probability score. By conditioning (stratifying) on the ...
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    Revised “LEPS” Scores for Assessing Climate Model Simulations and Long-Range Forecasts 

    Source: Journal of Climate:;1996:;volume( 009 ):;issue: 001:;page 34
    Author(s): Potts, J. M.; Folland, C. K.; Jolliffe, I. T.; Sexton, D.
    Publisher: American Meteorological Society
    Abstract: The most commonly used measures for verifying forecasts or simulators of continuous variables are root-mean-squared error (rmse) and anomaly correlation. Some disadvantages of these measures are demonstrated. Existing ...
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