Quantifying uncertainties in ocean preditions / Advances in Computational Oceanography
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Authors
Lermusiaux, Pierre, F.J.
Chiu, Ching-Sang
Gawarkiewicz, Glen G.
Abbot, Phil
Robinson, Allan R.
Miller, Robert N.
Haley, Patrick J.
Leslie, Wayne G.
Majumdar, Sharan J.
Pang, Alex
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Advisors
Date of Issue
2006-03
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Abstract
A multitude of physical and biological processes occur in the ocean over a wide
range of temporal and spatial scales. Many of these processes are nonlinear and
highly variable, and involve interactions across several scales and oceanic disciplines.
For example, sound propagation is infl uenced by physical and biological
properties of the water column and by the seabed. From observations and conservation
laws, ocean scientists formulate models that aim to explain and predict dynamics
of the sea. This formulation is intricate because it is challenging to observe
the ocean on a sustained basis and to transform basic laws into generic but usable
models. There are imperfections in both data and model estimates. It is important
to quantify such uncertainties to understand limitations and identify the research
needed to increase accuracies, which will lead to fundamental progress.
Type
Article
Description
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Department
Oceanography
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Format
Citation
Oceanography, Volume 19, Number 1, March 2006, pp. 93
Distribution Statement
Rights
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.