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dc.contributor.supervisorRasmussen, Peter (Civil Engineering)en_US
dc.contributor.authorEvans, Andrea Marie
dc.date.accessioned2013-11-26T13:20:19Z
dc.date.available2013-11-26T13:20:19Z
dc.date.issued2013-11-26
dc.identifier.urihttp://hdl.handle.net/1993/22276
dc.description.abstractThe Canadian Precipitation Analysis (CaPA) generates gridded precipitation data outputs based on the assimilation of both observation and climate model data. CaPA outputs are highly valuable to modelling efforts dependent on precipitation inputs, and as such the quality of CaPA outputs is crucial. Two improvements to CaPA were investigated: reducing transformation bias though correction against moving-window averaged CaPA output that avoids transformation, and enhancing semivariograms through anisotropy and convection considerations. Accounting for convection in the semivariogram proved ineffectual, while the bias correction technique and anisotropic semivariograms both reduced bias and improved related metrics. No methods improved the Equitable Threat Score. If implemented separately, the bias correction or anisotropic semivariogram approaches will yield targeted benefits for CaPA users, particularly for applications focused on extreme precipitation values. Improvements were not so comprehensive as to warrant adoption in the operational CaPA configuration, although availability in experimental versions is recommended.en_US
dc.language.isoengen_US
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectbiasen_US
dc.subjectsemivariogramen_US
dc.subjectprecipitationen_US
dc.subjectanisotropyen_US
dc.titleInvestigation of enhancements to two fundamental components of the statistical interpolation method used by the Canadian Precipitation Analysis (CaPA)en_US
dc.typeinfo:eu-repo/semantics/masterThesis
dc.typemaster thesisen_US
dc.degree.disciplineCivil Engineeringen_US
dc.contributor.examiningcommitteeStadnyk, Tricia (Civil Engineering) Acar, Elif (Statistics)en_US
dc.degree.levelMaster of Science (M.Sc.)en_US
dc.description.noteFebruary 2014en_US


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