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Application of the probabilistic collocation method for an uncertainty analysis of a simple ocean model

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dc.contributor Webster, Mort David.
dc.contributor Tatang, Menner A.
dc.contributor McRae, Gregory J.
dc.date 2003-10-24T14:57:58Z
dc.date 2003-10-24T14:57:58Z
dc.date 1996-01
dc.date.accessioned 2013-10-09T02:31:48Z
dc.date.available 2013-10-09T02:31:48Z
dc.date.issued 2013-10-09
dc.identifier no. 4
dc.identifier http://mit.edu/globalchange/www/abstracts.html#a4
dc.identifier http://hdl.handle.net/1721.1/3643
dc.identifier.uri http://koha.mediu.edu.my:8181/xmlui/handle/1721
dc.description This paper presents the probabilistic collocation method as a computationally efficient method for performing uncertainty analysis on large complex models such as those used in global climate change research. The collocation method is explained, and then the results of its application to a box model of ocean thermohaline circulation are presented. A comparison of the results of the collocation method with a traditional Monte Carlo simulation show that the collocation method gives a better approximation for the probability density function of the model's response with less than 20 model runs as compared with a Monte Carlo simulation of 5000 model runs.
dc.description Includes bibliographical references (p. 21).
dc.description Abstract in HTML and technical report in HTML and PDF available on the Massachusetts Institute of Technology Joint Program on the Science and Policy of Global Change website (http://mit.edu/globalchange/www/).
dc.format 21 p.
dc.format 87395 bytes
dc.format application/pdf
dc.language eng
dc.publisher MIT Joint Program on the Science and Policy of Global Change
dc.relation Report no. 4
dc.subject QC981.8.C5 M58 no.4
dc.title Application of the probabilistic collocation method for an uncertainty analysis of a simple ocean model


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