Prediction-skill variability in atmospheric and oceanic models
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Authors
Chu, Peter C.
Ivanov, Leonid, M.
Subjects
prediction-skill variability
atmospheric models
oceanic modeling
atmospheric models
oceanic modeling
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Date of Issue
2003-09-05
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Max Planck Institute for Meteorology
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Abstract
Various numerical atmospheric and oceanic models have been developed in the past several decades. a fundamental questions arises: Can we determine which model prpovides "the best prediction"? To answer this question, full knowledge of the prediction error statistics of each model is needed. Due to high structural complexity and high dimensionality of the error phase space, establishment of such statistics is difficult. Usually the Gaussian distribution is assumed for the error statistics for simplicity. However, it might not be true for regional ocean models.
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This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.