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Memorial University - Electronic Theses and Dissertations 4
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Document Description
TitleValidating and improving the Canadian coast guard search and rescue planning program (CANSARP) ocean drift theory
AuthorHillier, Lindsay E. (Lindsay Erin), 1984-
DescriptionThesis (M.Sc.)--Memorial University of Newfoundland, 2009. Environmental Science / Physics and Physical Oceanography
Paginationxiii, 98 leaves : ill., col. maps
SubjectCoastal surveillance--Canada--Computer simulation; Ocean currents--Canada--Computer simulation; Search and rescue operations--Canada;
Degree GrantorMemorial University of Newfoundland. Dept. of Environmental Science / Physics and Physical Oceanography
DisciplineEnvironmental Science / Physics and Physical Oceanography
NotesIncludes bibliographical references (leaves 95-98)
AbstractThe Canadian Coast Guard Search and Rescue Coordinator uses a software system to estimate the drift of targets in the ocean, and consequently determine a search area. Existing software applies a simple drift algorithm (MiniMax) that has been in use since World War II (Canadian Coast Guard/Department of Fisheries and Oceans Canada [CCG/DFO], 2000). -- The Coast Guard must be aware of the effectiveness of the drift prediction algorithm, and the efficiency of the environmental inputs used. This thesis determines the practicality of the available methods of MiniMax and the stochastic Monte Carlo approach. In addition, we explore the implementation of higher resolution ocean and sea current inputs. This both improves the current MiniMax algorithm and allows exploration of a modified Monte Carlo approach. -- Using an assembled database of drifting buoys in the North Atlantic Ocean, the accuracy of the MiniMax and the Norwegian Meteorological Office implementation of the Monte Carlo methods are evaluated. Results from the assessment indicate that present prediction methods in CANSARP underestimate actual drifts by 2 to 3 times the actual length. These results are used to determine where improvements must be made to the current algorithms and environmental inputs for eventual application to the search system.
Resource TypeElectronic thesis or dissertation
FormatImage/jpeg; Application/pdf
SourcePaper copy kept in the Centre for Newfoundland Studies, Memorial University Libraries
Local Identifiera2996758
RightsThe author retains copyright ownership and moral rights in this thesis. Neither the thesis nor substantial extracts from it may be printed or otherwise reproduced without the author's permission.
CollectionElectronic Theses and Dissertations
Scanning StatusCompleted
PDF File(12.70 MB) --
CONTENTdm file name176293.cpd