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Validation and Operational Implementation of the Navy Coastal Ocean Model Four Dimensional Variational Data Assimilation System (NCOM 4DVAR) in the Okinawa Trough

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Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications (Vol. III)

Abstract

The Navy Coastal Ocean Model Four-Dimensional Variational Assimilation (NCOM 4DVAR ) system is an analysis software package that is designed to supplement the current capability of the operational analysis/prediction system known as the Relocatable Navy Coupled Ocean Model (Relo NCOM ) system. The present assimilation component of Relo NCOM employs the Navy Coupled Ocean Data Assimilation Three-Dimensional Variational Assimilation (NCODA 3DVAR) system to process and assimilate observations. The NCOM 4DVAR, on the other hand, uses a representer based 4DVAR method and has been found to improve the forecast-skill for several regional applications. This chapter presents the results of validation experiments performed in the Okinawa Trough. The analysis and resulting forecast skill of the two assimilation methods within Relo NCOM (NCOM 4DVAR and NCODA 3DVAR ) are compared, and the operational implementation of NCOM 4DVAR is examined to verify that it satisfies operational constraints. The metrics used to validate the NCOM 4DVAR system include: computational efficiency, scalability, robustness, and the prediction accuracy of temperature, sea surface height, and sonic layer depth through NCOM 4DVAR and NCODA 3DVAR analyses. Forecast skill metrics are computed using surface observations of temperature, salinity and sea surface height, and profile observations from gliders and AXBTs (aerial expendable bathythermograph). Overall, the validation reveals that NCOM 4DVAR has lower root mean square errors for both analyses and forecasts than the operational NCODA 3DVAR system.

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References

  • Barron CN, Kara AB, Martin PJ, Rhodes RC, Smedstad LF (2006) Formulation, implementation, and examination of vertical coordinate choices in the global Navy Coastal Ocean Model (NCOM). Ocean Modell 11:347–375. doi:10.1016/j.ocemod.2005.01.004

    Article  Google Scholar 

  • Barron CN, Kara AB, Rhodes RC, Rowley C, Shriver JF (2007) Validation test report for the 1/8° Global Navy Coastal Ocean Model Nowcast/Forecast System. NRL Tech Report NRL/MR/7320–07-9019. Naval Research Laboratory, Stennis Space Center, MS

    Google Scholar 

  • Bennet AF (1992) Inverse methods in physical oceanography. Cambridge University Press, New York 347 pp

    Book  Google Scholar 

  • Bennett AF (2002) Inverse modeling of the ocean and atmosphere. Cambridge University Press, New York 234 pp

    Book  Google Scholar 

  • Blumberg AF, Mellor GL (1983) Diagnostic and prognostic numerical circulation studies of the South Atlantic Bight. J Geophys Res 88:4579–4592

    Article  Google Scholar 

  • Blumberg AF, Mellor GL (1987) A description of a three-dimensional coastal ocean circulation model. In: Heaps N (ed) Three-dimensional coastal ocean models. American Union, New York, N.Y., 208 pp

    Google Scholar 

  • Carrier MJ, Ngodock H (2010) Background-error correlation model based on implicit solution of a diffusion equation. Ocean Modell 35:45–53

    Article  Google Scholar 

  • Carrier M, Ngodock H, Smith S, Jacobs G, Muscarella P, Ozgokmen T, Haus B, Lipphardt B (2014) Impact of assimilating ocean velocity observations inferred from Lagrangian drifter data using the NCOM 4DVAR. Mon Weather Rev 142:1509–1524

    Article  Google Scholar 

  • Chua BS, Bennett AF (2001) An inverse ocean modeling system. Ocean Modell 3:137–165

    Article  Google Scholar 

  • Courtier P (1997) Dual formulation of four-dimensional variational assimilation. Q J R Meteorol Soc 123:2449–2461

    Article  Google Scholar 

  • Cummings JA (2005) Operational multivariate ocean data assimilation. Q J R Meteorol Soc 131:3583–3604

    Article  Google Scholar 

  • Cummings JA (2011) Ocean data quality control. In: Schiller A, Brassington G (eds) Operational oceanography in the 21st century. Springer, pp 91–122. doi:10.1007/978-94-007-0332-2_4

  • Fox DN, Barron CN, Carnes MR, Booda M, Peggion G, Gurley JV (2002) The modular ocean data assimilation system. Oceanography 15:22–28

    Article  Google Scholar 

  • Helber RW, Barron CN, Carnes MR, Zingarelli RA (2008) Evaluating the sonic layer depth relative to the mixed layer depth. J Geophys Res 113. doi:10.1029/2007JC004595

  • Hodur RM (1997) The naval research laboratory’s coupled ocean/atmosphere mesoscale prediction system (COAMPS). Mon Weather Rev 125:1414–1430

    Article  Google Scholar 

  • Hogan TF, Liu M, Ridout JA, Peng MS, Whitcomb TR, Ruston BC, Reynolds CA, Eckermann SD, Moskaitis JR, Baker NL, McCormack JP, Viner KC, McLay JG, Flatau MK, Xu L, Chen C, Chang SW (2014) The navy global environmental model. Oceanography 27(3):116–125

    Article  Google Scholar 

  • Jacobs GA, Barron CN, Fox DN, Whitmer KR, Klingenberger S, May D, Blaha JP (2002) Operational altimeter sea level products. Oceanography 15(1):13–21

    Article  Google Scholar 

  • Large WG, McWilliams JC, Doney SC (1994) Oceanic vertical mixing: a review and a model with a nonlocal boundary layer parameterization. Rev Geophys 32:363–403

    Article  Google Scholar 

  • Martin PJ, Peggion G, Yip KJ (1998) A comparison of several coastal ocean models. NRL Report NRL/FR/7322-97-9692, Naval Research Laboratory, Stennis Space Center, MS

    Google Scholar 

  • Martin P (2000) Description of the Navy Coastal Ocean Model Version 1.0. NRL report NRL/FR/7322-00-9961, Naval Research Laboratory, Stennis Space Center, MS

    Google Scholar 

  • Martin PJ, Barron CN, Smedstad LF, Wallcraft AJ, Rhodes RC, Campbell TJ, Rowley C, Carroll SN (2008) Software design description for the Navy Coastal Ocean Model Version 4.0. NRL Report NRL/MR/7320-08-9149, Naval Research Laboratory, Stennis Space Center, MS

    Google Scholar 

  • Mellor GL, Yamada T (1982) Development of a turbulence closure model for geophysical fluid problems. Rev Geophys Space Phys 20:851–875

    Article  Google Scholar 

  • Metzger EJ, Smedstad OM, Thoppil PG, Hurlburt HE, Cummings JA, Wallcraft AJ, Zamudio L, Franklin DS, Posey PG, Phelps MW, Hogan PJ, Bub FL, Dehaan CJ (2014) US Navy operational global ocean and arctic ice prediction systems. Oceanography 27(3). http://dx.doi.org/10.5670/oceanog.2014.66

  • Ngodock HE (2005) Efficient implementation of covariance multiplication for data assimilation with the representer method. Ocean Modell 8(3):237–251

    Article  Google Scholar 

  • Ngodock HE, Carrier M (2014a) A 4DVAR system for the Navy Coastal Ocean Model Part I: System description and assimilation of synthetic observations in Monterey Bay. Mon Weather Rev 142. doi:10.1175/MWR-D-13-00221

  • Ngodock HE, Carrier M (2014b) A 4DVAR system for the Navy Coastal Ocean Model Part II: strong and weak constraints assimilation experiments with real observations in the Monterey Bay. Mon Weather Rev 142. doi:10.1175/MWR-D-13-00220

  • Ngodock HE, Carrier M, Souopgui I, Smith S, Martin P, Muscarella P, Jacobs G (2015) On the direct assimilation of along-track sea surface height observations into a free-surface ocean model using a weak constraints four dimensional variational (4DVAR) method. Q J R Meotorol Soc (in press). doi:10.1002/qj.2721

  • Rosmond TE (1992) The design and testing of the Navy Operational Global Atmospheric Prediction System. Weather Forecast 7:262–272

    Article  Google Scholar 

  • Rosmond TE, Teixeria J, Peng M, Hogan TF, Pauley R (2002) Navy Operational Global Atmospheric Prediction System (NOGAPS): forcing for ocean models. Oceanography 15:99–106

    Article  Google Scholar 

  • Rowley C (2010) Validation test report for the Relo system. NRL Report NRL/MR/7320-10-9216, Naval Research Laboratory, Stennis Space Center, MS

    Google Scholar 

  • Smagorinsky J (1963) General circulation experiments with the primitive equations. I: The basic experiment. Mon Weather Rev 91:99–164

    Article  Google Scholar 

  • Smith SR, Cummings JA, Rowley C, Chu P, Shriver J, Helber R, Spence P, Carroll S, Smedstad OM (2012) Validation test report for the Navy Coupled Ocean Data Assimilation 3D Variational Analysis (NCODA-VAR) System, Version 3.43. NRL Memorandum Report NRL/MR/7320-11-9363, Naval Research Laboratory, Stennis Space Center, MS

    Google Scholar 

  • Smith SR, Carrier MJ, Ngodock HE, Shriver J, Muscarella P (2015) Validation testing report for the Navy Coastal Ocean Model Four-Dimensional Variational Assimilation (NCOM 4DVAR) System, Version 1.0. NRL Memorandum Report NRL/MR/732-14-9574, Naval Research Laboratory, Stennis Space Center, MS

    Google Scholar 

  • Weaver A, Courtier P (2001) Correlation modeling on the sphere using a generalized diffusion Equation. Q J R Meteorol Soc 127:1815–1846

    Article  Google Scholar 

  • Yaremchuk M, Carrier M, Smith S, Jacobs G (2013) Background error correlation modeling with diffusion operators. In: Park SK, Xu L (eds) Data assimilation for atmospheric, oceanic and hydrologic applications, vol 2. Springer, Berlin, Heidelberg. doi:10.1007/978-3-642-35088-7_15

  • Yu P, Kurapov AL, Egbert GD, Allen JS, Kosro AP (2012) Variational assimilation of HF radar surface currents in a coastal ocean model off Oregon. Ocean Modell 49–50:86–104

    Article  Google Scholar 

Download references

Acknowledgements

The authors were supported by the NRL 6.4 NCOM 4DVAR Rapid Transition Project (projects 4727-04 and 4727-14), which was managed by both Space and Naval Warfare Systems Command under program element 063207N and the Office of Naval Research under program element 0602435N. Numerical simulations were performed at the DoD Supercomputing Resource Center (DSRC) with grants of computer time from the HPCMP Variational Assimilation High Performance Computing (HPC) subproject.

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Authors and Affiliations

  1. Stennis Space Center, Naval Research Laboratory, Bay St. Louis, MS, USA

    Scott Smith, Hans Ngodock, Matthew Carrier, Jay Shriver & Philip Muscarella

  2. Stennis Space Center, University of Southern Mississippi, Hattiesburg, MS, USA

    Innocent Souopgui

Authors
  1. Scott Smith
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  2. Hans Ngodock
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  3. Matthew Carrier
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  4. Jay Shriver
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  5. Philip Muscarella
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  6. Innocent Souopgui
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Correspondence to Scott Smith .

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Editors and Affiliations

  1. Environmental Science and Engineering, Ewha Womans University, Seoul, Korea (Republic of)

    Seon Ki Park

  2. Marine Meteorology Division, Naval Research Laboratory, Monterey, California, USA

    Liang Xu

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Smith, S., Ngodock, H., Carrier, M., Shriver, J., Muscarella, P., Souopgui, I. (2017). Validation and Operational Implementation of the Navy Coastal Ocean Model Four Dimensional Variational Data Assimilation System (NCOM 4DVAR) in the Okinawa Trough. In: Park, S., Xu, L. (eds) Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications (Vol. III). Springer, Cham. https://doi.org/10.1007/978-3-319-43415-5_18

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