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dc.contributorWebster, Mort David.en_US
dc.contributorTatang, Menner A.en_US
dc.contributorMcRae, Gregory J.en_US
dc.date.accessioned2003-10-24T14:57:58Z
dc.date.available2003-10-24T14:57:58Z
dc.date.issued1996-01en_US
dc.identifier.otherno. 4en_US
dc.identifier.urihttp://mit.edu/globalchange/www/abstracts.html#a4en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/3643
dc.descriptionIncludes bibliographical references (p. 21).en_US
dc.descriptionAbstract 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.abstractThis 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.extent21 p.en_US
dc.format.extent87395 bytes
dc.format.mimetypeapplication/pdf
dc.language.isoengen_US
dc.publisherMIT Joint Program on the Science and Policy of Global Changeen_US
dc.relation.ispartofseriesReport no. 4en_US
dc.subject.lccQC981.8.C5 M58 no.4en_US
dc.titleApplication of the probabilistic collocation method for an uncertainty analysis of a simple ocean modelen_US


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