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dc.contributor.authorSlivinski, Laura  Concept link
dc.contributor.authorPratt, Lawrence J.  Concept link
dc.contributor.authorRypina, Irina I.  Concept link
dc.contributor.authorOrescanin, Mara M.  Concept link
dc.contributor.authorRaubenheimer, Britt  Concept link
dc.contributor.authorMacMahan, Jamie  Concept link
dc.contributor.authorElgar, Steve  Concept link
dc.date.accessioned2017-06-09T18:31:30Z
dc.date.issued2017-04
dc.identifier.urihttps://hdl.handle.net/1912/9030
dc.description© The Author(s), 2017. This is the author's version of the work. It is posted here under a nonexclusive, irrevocable, paid-up, worldwide license granted to WHOI. It is made available for personal use, not for redistribution. The definitive version was published in Ocean Modelling 113 (2017): 131-144, doi:10.1016/j.ocemod.2017.04.001.en_US
dc.description.abstractNumerical models of ocean circulation often depend on parameters that must be tuned to match either results from laboratory experiments or field observations. This study demonstrates that an initial, suboptimal estimate of a parameter in a model of a small bay can be improved by assimilating observations of trajectories of passive drifters. The parameter of interest is the Manning's n coefficient of friction in a small inlet of the bay, which had been tuned to match velocity observations from 2011. In 2013, the geometry of the inlet had changed, and the friction parameter was no longer optimal. Results from synthetic experiments demonstrate that assimilation of drifter trajectories improves the estimate of n, both when the drifters are located in the same region as the parameter of interest and when the drifters are located in a different region of the bay. Real drifter trajectories from field experiments in 2013 also are assimilated, and results are compared with velocity observations. When the real drifters are located away from the region of interest, the results depend on the time interval (with respect to the full available trajectories) over which assimilation is performed. When the drifters are in the same region as the parameter of interest, the value of n estimated with assimilation yields improved estimates of velocity throughout the bay.en_US
dc.description.sponsorshipThis work was supported by: Department of Defense Multidisciplinary University Research Initiative (MURI) [grant N000141110087], administered by the Office of Naval Research; the National Science Foundation (NSF); the National Oceanic and Atmospheric Administration (NOAA); NOAA's Climate Program Office; the Department of Energy's Office for Science (BER); and the Assistant Secretary of Defense (Research & Development).en_US
dc.language.isoen_USen_US
dc.relation.urihttps://doi.org/10.1016/j.ocemod.2017.04.001
dc.subjectData assimilationen_US
dc.subjectModellingen_US
dc.subjectDrag coefficienten_US
dc.subjectDriftersen_US
dc.subjectTidal inletsen_US
dc.titleAssimilating Lagrangian data for parameter estimation in a multiple-inlet systemen_US
dc.typePreprinten_US


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