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  • 1
    Publication Date: 2022-05-25
    Description: Author Posting. © The Author(s), 2010. This is the author's version of the work. It is posted here by permission of Elsevier B.V. for personal use, not for redistribution. The definitive version was published in Ocean Modelling 35 (2010): 134-145, doi:10.1016/j.ocemod.2010.06.006.
    Description: As part of an effort to build an integrated observation and modeling system for the New York Bight, this study explores observing system design using a representer-based method. The Representer of a single observation describes the covariance between the observed quantity and ocean state at all locations at any time. It is related closely to the influence of the observation on control variable correction in a 4D Variational data assimilation system. We prove that these properties hold for the combination of representers that is associated with an arithmetic function of model variables or a group of observations. The representer-based method is used here to identify which of a set of proposed tracks for an autonomous coastal glider is better for predicting horizontal salt flux within the Hudson Shelf Valley in a 2-day forecast period. Twin experiments confirm the result. The system is also used to compare different observation strategies. We show that a glider that traverses a regular transect influences a larger area than a continuously profiling mooring, but the mooring carries stronger influence at the observation location. The representer analysis shows how the information provided by observations extends toward the dynamically upstream and how increasing the duration of the analysis window captures more dynamical connections and expands the area of influence of the observations in data assimilation. Overall, the study demonstrates that the representer methodology can quantitatively contrast different observational strategies and determine spatial patterns and temporal extent of the influence of observations, both of which are helpful for evaluating the design of observation networks.
    Description: This work was funded by National Science Foundation grant OCE-0238957.
    Keywords: Representer ; Adjoint ; Observing system design ; Adaptive sampling ; Observation influence ; New York Bight
    Repository Name: Woods Hole Open Access Server
    Type: Preprint
    Format: application/pdf
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  • 2
    Publication Date: 2022-05-25
    Description: Author Posting. © The Author(s), 2010. This is the author's version of the work. It is posted here by permission of Elsevier B.V. for personal use, not for redistribution. The definitive version was published in Ocean Modelling 35 (2010): 119-133, doi:10.1016/j.ocemod.2010.08.003.
    Description: Four-dimensional Variational data assimilation (4DVAR) in the Regional Ocean Modeling System (ROMS) is used to produce a best-estimate analysis of ocean circulation in the New York Bight during spring 2006 by assimilating observations collected by a variety of instruments during an intensive field program. An incremental approach is applied in an overlapped cycling system with 3-day data assimilation window to adjust model initial conditions. The model-observation mismatch for all observed variables is reduced substantially. Comparisons between model forecast and independent observations show improved forecast skill for about 15 days for temperature and salinity, and 2 to 3 days for velocity. Tests assimilating only certain subsets of the data indicate that assimilating satellite sea surface temperature improves the forecast of surface and subsurface temperature but worsens the salinity forecast. Assimilating in situ temperature and salinity from gliders improves the salinity forecast but has little effect on temperature. Assimilating HF-radar surface current data improves the velocity forecast by 1-2 days yet worsens the forecast of subsurface temperature. During some time periods the convergence for velocity is poor as a result of the data assimilation system being unable to reduce errors in the applied winds because surface forcing is not among the control variables. This study demonstrates the capability of 4DVAR data assimilation system to reduce model-observation mismatch and improve forecasts in the coastal ocean, and highlights the value of accurate meteorological forcing.
    Description: This work was funded by National Science Foundation grant OCE-0238957.
    Keywords: Data assimilation ; 4DVAR ; ROMS ; Ocean prediction ; New York Bight ; River plume
    Repository Name: Woods Hole Open Access Server
    Type: Preprint
    Format: application/pdf
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