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dc.contributor.advisorPierre F. J. Lermusiaux.en_US
dc.contributor.authorLandry, Jennifer Jacobsen_US
dc.contributor.otherWoods Hole Oceanographic Institution.en_US
dc.coverage.spatiala-ch---en_US
dc.date.accessioned2015-02-05T18:21:24Z
dc.date.available2015-02-05T18:21:24Z
dc.date.copyright2014en_US
dc.date.issued2014en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/93792
dc.descriptionThesis: S.M., Joint Program in Applied Ocean Science and Engineering (Massachusetts Institute of Technology, Department of Mechanical Engineering; and the Woods Hole Oceanographic Institution), 2014.en_US
dc.descriptionCataloged from PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (pages 79-81).en_US
dc.description.abstractThe ocean is a complex, constantly changing, highly dynamical system. Prediction capabilities are constantly being improved in order to better understand and forecast ocean properties for applications in science, industry, and maritime interests. Our overarching goal is to better predict the ocean environment in regions of complex topography with a continental shelf, shelfbreak, canyons and steep slopes using the MIT Multidisciplinary Simulation, Estimation and Assimilation Systems (MSEAS) primitive-equation ocean model. We did this by focusing on the complex region surrounding Taiwan, and the period of time immediately following the passage of Typhoon Morakot. This area and period were studied extensively as part of the intense observation period during August - September 2009 of the joint U.S. - Taiwan program Quantifying, Predicting, and Exploiting Uncertainty Department Research Initiative (QPE DRI). Typhoon Morakot brought an unprecedented amount of rainfall within a very short time period and in this research, we model and study the effects of this rainfall on Taiwan's coastal oceans as a result of river discharge. We do this through the use of a river discharge model and a bulk river-ocean mixing model. We complete a sensitivity study of the primitive-equation ocean model simulations to the different parameters of these models. By varying the shape, size, and depth of the bulk mixing model footprint, and examining the resulting impacts on ocean salinity forecasts, we are able to determine an optimal combination of salinity relaxation factors for highest accuracy.en_US
dc.description.statementofresponsibilityby Jennifer Jacobs Landry.en_US
dc.format.extent81 pagesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsM.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectJoint Program in Applied Ocean Science and Engineering.en_US
dc.subjectMechanical Engineering.en_US
dc.subjectWoods Hole Oceanographic Institution.en_US
dc.subject.lcshOcean-atmosphere interactionen_US
dc.subject.lcshNumerical weather forecastingen_US
dc.titleCoastal ocean variability off the coast of Taiwan in response to typhoon Morakot : river forcing, atmospheric forcing, and cold dome dynamicsen_US
dc.typeThesisen_US
dc.description.degreeS.M.en_US
dc.contributor.departmentJoint Program in Applied Ocean Physics and Engineeringen_US
dc.contributor.departmentWoods Hole Oceanographic Institutionen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Mechanical Engineering
dc.identifier.oclc890937435en_US


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