Impact of assimilating ocean velocity observations inferred from lagrangian drifter data using the NCOM-4DVAR

Matthew J. Carrier, Hans Ngodock, Scott Smith, Gregg Jacobs, Philip Muscarella, Tamay Ozgokmen, Brian Haus, Bruce Lipphardt

Research output: Contribution to journalArticle

24 Scopus citations

Abstract

Eulerian velocity fields are derived from 300 drifters released in the Gulf of Mexico by The Consortium for Advanced Research on Transport of Hydrocarbon in the Environment (CARTHE) during the summer 2012 Grand Lagrangian Deployment (GLAD) experiment. These data are directly assimilated into the Navy Coastal Ocean Model (NCOM) four-dimensional variational data assimilation (4DVAR) analysis system in a series of experiments to investigate their impact on the model circulation. The NCOM-4DVAR is a newly developed tool for data analysis, formulated for weak-constraint data assimilation based on the indirect representer method. The assimilation experiments take advantage of this velocity data along with other available data sources from in situ and satellite measurements of surface and subsurface temperature and salinity. Three different experiments are done: (i) A nonassimilative NCOM free run, (ii) an assimilative NCOM run that utilizes temperature and salinity observations, and (iii) an assimilative NCOM run that uses temperature and salinity observations as well as the GLAD velocity observations. The resulting analyses and subsequent forecasts are compared to assimilated and future GLAD velocity and temperature/salinity observations to determine the performance of each experiment and the impact of the GLAD data on the analysis and the forecast. It is shown that the NCOM-4DVARis able to fit the observations not only in the analysis step, but also in the subsequent forecast. It is also found that the GLAD velocity data greatly improves the characterization of the circulation, with the forecast showing a better fit to future GLAD observations than those experiments without the velocity data included.

Original languageEnglish (US)
Pages (from-to)1509-1524
Number of pages16
JournalMonthly Weather Review
Volume142
Issue number4
DOIs
StatePublished - Apr 2014

Keywords

  • Inverse methods
  • Model initialization
  • Numerical analysis/modeling
  • Ocean models
  • Variational analysis

ASJC Scopus subject areas

  • Atmospheric Science

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