Oceanography The Official Magazine of
The Oceanography Society
Volume 27 Issue 03

View Issue TOC
Volume 27, No. 3
Pages 32 - 43

OpenAccess

US Navy Operational Global Ocean and Arctic Ice Prediction Systems

By E. Joseph Metzger , Ole Martin Smedstad , Prasad G. Thoppil, Harley E. Hurlburt , James A. Cummings, Alan J. Wallcraft, Luis Zamudio , Deborah S. Franklin, Pamela G. Posey, Michael W. Phelps, Patrick J. Hogan, Frank L. Bub, and Chris J. DeHaan 
Jump to
Article Abstract Citation References Copyright & Usage
Article Abstract

The US Navy’s operational global ocean nowcast/forecast system is presently comprised of the 0.08° HYbrid Coordinate Ocean Model (HYCOM) and the Navy Coupled Ocean Data Assimilation (NCODA). Its high horizontal resolution and adaptive vertical coordinate system make it capable of producing nowcasts (current state) and forecasts of oceanic “weather,” which includes three-dimensional ocean temperature, salinity, and current structure; surface mixed layer depth; and the location of mesoscale features such as eddies, meandering currents, and fronts. It runs daily at the Naval Oceanographic Office and provides seven-day forecasts that support fleet operations, provide boundary conditions to higher resolution regional models, and are available to the community. Using a data-assimilative hindcast and series of 14-day forecasts for 2012, the system is shown to have forecast skill of the oceanic mesoscale out to about 10 days for the Gulf Stream region and to 14+ days for the global ocean and other selected subregions. Forecast skill is sensitive to the type of atmospheric forcing (i.e., operational vs. analysis quality). Subsurface temperature bias is small (< 0.25°C) and root mean square error peaks at the depth range of the mixed layer and thermocline. Coupled to the Community Ice CodE (CICE) on the same grid, the HYCOM/CICE/NCODA system (initially restricted to the Arctic) provides sea ice nowcasts and forecasts. Ice edge location errors are improved from the previous sea ice prediction system but are limited in part by the accuracy of the satellite observations it assimilates.

Citation

Metzger, E.J., O.M. Smedstad, P.G. Thoppil, H.E. Hurlburt, J.A. Cummings, A.J. Wallcraft, L. Zamudio, D.S. Franklin, P.G. Posey, M.W. Phelps, P.J. Hogan, F.L. Bub, and C.J. DeHaan. 2014. US Navy operational global ocean and Arctic ice prediction systems. Oceanography 27(3):32–43, https://doi.org/10.5670/oceanog.2014.66.

References
    Anonymous. 1976. Ocean forecasting. Eos, Transactions American Geophysical Union 58(5):279–281, https://doi.org/10.1029/EO058i005p00279-02.
  1. Arbic, B.K., J.G. Richman, J.F. Shriver, P.G. Timko, E.J. Metzger, and A.J. Wallcraft. 2012. Global modeling of internal tides within an eddying ocean general circulation model. Oceanography 25(2):20–29, https://doi.org/10.5670/oceanog.2012.38.
  2. Bleck, R. 2002. An oceanic general circulation model framed in hybrid isopycnic-Cartesian coordinates. Ocean Modelling 4:55–88, https://doi.org/10.1016/S1463-5003(01)00012-9.
  3. Bloom, S.C., L.L. Takacs, A.M. da Silva, and D. Ledvina. 1996. Data assimilation using incremental analysis updates. Monthly Weather Review 124:1,256–1,271, https://doi.org/10.1175/1520-0493(1996)124<1256:DAUIAU>2.0.CO;2.
  4. Chassignet, E.P., H.E. Hurlburt, E.J. Metzger, O.M. Smedstad, J.A. Cummings, G.R. Halliwell, R. Bleck, R. Baraille, A.J. Wallcraft, C. Lozano, and others. 2009. US GODAE: Global ocean prediction with the HYbrid Coordinate Ocean Model (HYCOM). Oceanography 22(2):64–75, https://doi.org/10.5670/oceanog.2009.39.
  5. Chassignet, E.P., H.E. Hurlburt, O.M. Smedstad, G.R. Halliwell, P.J. Hogan, A.J. Wallcraft, R. Baraille, and R. Bleck. 2007. The HYCOM (HYbrid Coordinate Ocean Model) data assimilative system. Journal of Marine Systems 65:60–83, https://doi.org/10.1016/j.jmarsys.2005.09.016.
  6. Chassignet, E.P., L.T. Smith, G.R. Halliwell, and R. Bleck. 2003. North Atlantic simulations with the HYbrid Coordinate Ocean Model (HYCOM): Impact of the vertical coordinate choice, reference pressure, and thermobaricity. Journal of Physical Oceanography 33:2,504–2,526, https://doi.org/10.1175/1520-0485(2003)033<2504:NASWTH>2.0.CO;2.
  7. Cummings, J.A., and O.M. Smedstad. 2013. Variational data assimilation for the global ocean. Pp. 303–343 in Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications (Vol. II). S.K. Park and L. Xu, eds, Springer-Verlag, Berlin Heidelberg, https://doi.org/10.1007/978-3-642- 35088-7_13.
  8. Dombrowsky, E., L. Bertino, G.B. Brassington, E.P. Chassignet, F. Davidson, H.E. Hurlburt, M. Kamachi, T. Lee, M.J. Martin, S. Mei, and others. 2009. GODAE systems in operation. Oceanography 22(3):80–95, https://doi.org/10.5670/oceanog.2009.68.
  9. Eleuterio, D.P., and S. Sandgathe. 2012. The Earth System Prediction Capability program. Pp. 1–3 in Proceedings of OCEANS 12. MTS/IEEE, October 14–19, 2012. Hampton Roads, Virginia, https://doi.org/10.1109/OCEANS.2012.6404895.
  10. Fox, D.N., W.J. Teague, C.N. Barron, M.R. Carnes, and C.M. Lee. 2002. The Modular Ocean Data Assimilation System (MODAS). Journal of Atmospheric and Oceanic Technology 19:240–252, https://doi.org/10.1175/1520-0426(2002)019<0240:TMODAS>2.0.CO;2.
  11. Halliwell, G.R. 2004. Evaluation of vertical coordinate and vertical mixing algorithms in the HYbrid Coordinate Ocean Model (HYCOM). Ocean Modelling 7(3–4):285–322, https://doi.org/10.1016/j.ocemod.2003.10.002.
  12. Helber, R.W., T.L. Townsend, C.N. Barron, J.M. Dastugue, and M.R. Carnes. 2013. Validation Test Report for the Improved Synthetic Ocean Profile (ISOP) System: Part I. Synthetic Profile Methods and Algorithm. NRL Memorandum Report NRL/MR/7320—13-9364, http://www7320.nrlssc.navy.mil/pubs/2013/helber1-2013.pdf (accessed March 22, 2014)
  13. Hill, C., C. DeLuca, V. Balaji, M. Suarez, and A. da Silva. 2004. The architecture of the Earth System Modeling Framework. Computing in Science & Engineering. 6:18–28, https://doi.org/10.1109/MCISE.2004.1255817.
  14. Hunke, E.C., and W. Lipscomb. 2008. CICE: The Los Alamos Sea Ice Model: Documentation and Software User’s Manual, Version 4.0. Technical Report LA-CC-06-012, Los Alamos National Laboratory, Los Alamos, NM.
  15. Hurlburt, H.E., G.B. Brassington, Y. Drillet, M. Kamachi, M. Benkiran, R. Bourdalle-Badie, E.P. Chassignet, G.A. Jacobs, O. Le Galloudec, J.-M. Lellouche, and others. 2009. High resolution global and basin-scale ocean analyses and forecasts. Oceanography 22(3):110–127, https://doi.org/10.5670/oceanog.2009.70.
  16. Hurlburt, H.E., E.P. Chassignet, J.A. Cummings, A.B. Kara, E.J. Metzger, J.F. Shriver, O.M. Smedstad, A.J. Wallcraft, and C.N. Barron. 2008. Eddy-resolving global ocean prediction. Pp. 353–381 in Ocean Modeling in an Eddying Regime. M. Hecht and H. Hasumi, eds, Geophysical Monograph 177, American Geophysical Union, Washington, DC, https://doi.org/10.1029/177GM21.
  17. Hurlburt, H.E., E.J. Metzger, J.G. Richman, E.P. Chassignet, Y. Drillet, M.W. Hecht, O. Le Galloudec, J.F. Shriver, X. Xu, and L. Zamudio. 2011. Dynamical evaluation of ocean models using the Gulf Stream as an example. Pp. 545–609 in Operational Oceanography in the 21st Century. A. Schiller and G.B. Brassington, eds, Springer Science+Business Media B.V., https://doi.org/10.1007/978-94-007-0332-2_21.
  18. Lellouche, J.-M., O.L. Galloudec, M. Drévillon, C. Régnier, E. Greiner, G. Garric, N. Ferry, C. Desportes, C.E. Testu, C. Bricaud, and others. 2013. Evaluation of global monitoring and forecasting at Mercator Océan. Ocean Science 9:57–81, https://doi.org/10.5194/os-9-57-2013.
  19. Mehra, A., and I. Rivin. 2010. A real time ocean forecast system in the North Atlantic Ocean. Terrestrial, Atmospheric and Oceanic Sciences 21:211–228, https://doi.org/10.3319/TAO.2009.04.16.01(IWNOP).
  20. Metzger, E.J., B.C. Ruston, J.D. Dykes, T.R. Whitcomb, A.J. Wallcraft, L.F. Smedstad, S. Chen, and J. Chen. 2014. Operational Implementation Design for the Earth System Prediction Capability (ESPC): A First-Look. NRL Memorandum Report NRL/MR/7320—13-9498, 27 pp, http://www7320.nrlssc.navy.mil/pubs/2014/metzger1-2014.pdf (accessed March 22, 2014).
  21. Metzger, E.J., O.M. Smedstad, P.G. Thoppil, H.E. Hurlburt, A.J. Wallcraft, D.S. Franklin, J.F. Shriver, and L.F. Smedstad. 2008. Validation Test Report for the Global Ocean Prediction System V3.0 – 1/12° HYCOM/NCODA: Phase I. NRL Memorandum Report NRL/MR/7320—08-9148, 85 pp., http://www7320.nrlssc.navy.mil/pubs/2008/metzger-2008.pdf (accessed March 22, 2014).
  22. Metzger, E.J., O.M. Smedstad, P.G. Thoppil, H.E. Hurlburt, D.S. Franklin, G. Peggion, J.F. Shriver, and A.J. Wallcraft. 2010. Validation Test Report for the Global Ocean Forecast System V3.0 – 1/12° HYCOM/NCODA: Phase II. NRL Memorandum Report NRL/MR/7320—10-9236, 76 pp., http://www7320.nrlssc.navy.mil/pubs/2010/metzger1-2010.pdf (accessed March 22, 2014).
  23. Murphy, A.H., and E.S. Epstein. 1989. Skill scores and correlation coefficients in model verification. Monthly Weather Review 117:572–581, https://doi.org/10.1175/1520-0493(1989)117<0572:SSACCI>2.0.CO;2.
  24. Murray, R.J. 1996. Explicit generation of orthogonal grids for ocean models. Journal of Computational Physics 126:251–273, https://doi.org/10.1006/jcph.1996.0136.
  25. National Snow and Ice Data Center. 2013. “State of the Cryosphere: Is the Cryosphere Sending Signals about Climate Change? SOTC: Sea Ice,” http://nsidc.org/cryosphere/sotc/sea_ice.html (accessed April 1, 2014).
  26. Ocean Prediction Workshop. 1986. A status and prospectus report on the scientific basis and the Navy’s needs. Proceedings of the Ocean Prediction Workshop, Phase I: April 1986, Phase II: November 1986. Cambridge, Massachusetts and Long Beach, Mississippi.
  27. Posey, P.G., E.J. Metzger, A.J. Wallcraft, R.H. Preller, O.M. Smedstad, M.W. Phelps. 2010. Validation of the 1/12° Arctic Cap Nowcast/Forecast System (ACNFS). NRL Memorandum Report NRL/MR/7320—10-9287, 61 pp., http://www7320.nrlssc.navy.mil/pubs/2010/posey1-2010.pdf (accessed March 22, 2014).
  28. Preller, R.H., P.G. Posey, W. Maslowski, D. Stark, and T.T.C. Pham. 2002. Navy sea ice prediction systems. Oceanography 15(1):44–56, https://doi.org/10.5670/oceanog.2002.35.
  29. Rhodes, R.C., H.E. Hurlburt, A.J. Wallcraft, C.N. Barron, P.J. Martin, O.M. Smedstad, S.L. Cross, E.J. Metzger, J.F. Shriver, A.B. Kara, and D.S. Ko. 2002. Navy real-time global modeling systems. Oceanography 15(1):29–43, https://doi.org/10.5670/oceanog.2002.34.
  30. Smith, N.R. 2000. The Global Ocean Data Assimilation Experiment. Advances in Space Research 25:1,089–1,098, https://doi.org/10.1016/S0273-1177(99)00868-6.
  31. Smith, N.R. 2006. Perspective from the Global Ocean Data Assimilation Experiment. Pp. 1–18 in Ocean Weather Forecasting: An Integrated View of Oceanography. E.P. Chassignet and J. Verron, eds, Springer, Netherlands.
Copyright & Usage

This is an open access article made available under the terms of the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution, and reproduction in any medium or format as long as users cite the materials appropriately, provide a link to the Creative Commons license, and indicate the changes that were made to the original content. Images, animations, videos, or other third-party material used in articles are included in the Creative Commons license unless indicated otherwise in a credit line to the material. If the material is not included in the article’s Creative Commons license, users will need to obtain permission directly from the license holder to reproduce the material.