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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. en_US
dc.contributor Tatang, Menner A. en_US
dc.contributor McRae, Gregory J. en_US
dc.date.accessioned 2003-10-24T14:57:58Z
dc.date.available 2003-10-24T14:57:58Z
dc.date.issued 1996-01 en_US
dc.identifier.other no. 4 en_US
dc.identifier.uri http://mit.edu/globalchange/www/abstracts.html#a4 en_US
dc.identifier.uri http://hdl.handle.net/1721.1/3643
dc.description Includes bibliographical references (p. 21). en_US
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/). en_US
dc.description.abstract 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. en_US
dc.format.extent 21 p. en_US
dc.format.extent 87395 bytes
dc.format.mimetype application/pdf
dc.language.iso eng en_US
dc.publisher MIT Joint Program on the Science and Policy of Global Change en_US
dc.relation.ispartofseries Report no. 4 en_US
dc.subject.lcc QC981.8.C5 M58 no.4 en_US
dc.title Application of the probabilistic collocation method for an uncertainty analysis of a simple ocean model en_US


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