Application of an Ensemble Optimal Interpolation in a North/Baltic Sea model: Assimilating temperature and salinity profiles

Ocean Modelling

Volumn 40, Issue 3-4, 2011, Pages 227-245

  Fu, Weiwei ^a   She, Jun ^a   Zhuang, Shiyu ^a  

^a DANISH METEOROLOGICAL INSTITUTE   (Denmark)

Author keywords

Assimilation; EnOI; Temperature and salinity profiles; The North Sea and Baltic Sea

Indexed keywords

ASSIMILATION; BACKGROUND-ERROR COVARIANCES; COARSE-RESOLUTION MODEL; ENOI; INITIAL STATE; KATTEGAT; NORTH SEA; OCEAN FORECASTS; OPERATIONAL FORECASTING; OPTIMAL INTERPOLATION; ROOT MEAN SQUARE DIFFERENCES; SEA MODEL; SEA SURFACE TEMPERATURES; SKAGERRAK; SPATIAL CORRELATIONS; STATE VECTOR; TIDE GAUGE DATA;

ATMOSPHERIC TEMPERATURE; EXPERIMENTS; FORECASTING; INTERPOLATION; OPTIMIZATION; SEA LEVEL;

SALINITY MEASUREMENT;

ANNUAL CYCLE; DATA ASSIMILATION; ENSEMBLE FORECASTING; INTERPOLATION; NUMERICAL MODEL; SALINITY; SEA LEVEL; SEA SURFACE TEMPERATURE; SPATIAL ANALYSIS; TEMPERATURE PROFILE;

ATLANTIC OCEAN; BALTIC SEA; KATTEGAT; NORTH SEA; SKAGERRAK;

EID: 80054110213     PISSN: 14635003     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ocemod.2011.09.004     Document Type: Article

References (38)

1. Barth A., Alvera-Azcárate A., Rixen M., Beckers J.-M. Two-way nested model of mesoscale circulation features in the Ligurian Sea. Prog. Oceanogr. 2005, 66:171-189.
2. Barth A., Alvera-Azcárate A., Beckers J.M., Rixen M., Vandenbulcke L. Multigrid state vector for data assimilation in a two-way nested model of the Ligurian Sea. J. Mar. Syst. 2007, 65(1-4):41-59.
3. Berg, P. 2003. MIKE 3, Estuarine and Coastal Hydraulics and Oceanography, Hydrodynamic Module, Hydrostatic Version. DHI Software. DHI Water & Environment.
4. Buch, E., Elken, J., Gajewsk, J., Håkansson, B., Kahma, K., Soetje, K. 2006. Present Status of the Baltic Operational Oceanographic System. In: European Operational Oceanography: Present and Future, EuroGOOS Office, Sweden, and European Commission, Belgium, pp. 276-280.
5. Canuto V.M., Howard A., Cheng Y., Dubovikov M.S. Ocean turbulence. Part II: Vertical diffusivities of momentum, heat, salt, mass, and passive scalars. J. Phys. Oceanogr. 2002, 32:240-264.
6. Chen D., Omstedt A. Climate-induced variability of sea level in Stockholm: influence of air temperature and atmospheric circulation. Adv. Atmos. Sci. 2005, 22(5):655-664.
7. Cossarini G., Lermusiaux P.F.J., Solidoro C. Lagoon of Venice ecosystem: seasonal dynamics and environmental guidance with uncertainty analyses and error subspace data assimilation. J. Geophys. Res. 2009, 114:C06026. 10.1029/2008JC005080.
8. Counillon F., Bertino L. Ensemble optimal interpolation: multivariate properties in the Gulf of Mexico. Tellus 2009, 61A:296-308.
9. Counillon F., Bertino L. High-resolution ensemble forecasting for the Gulf of Mexico eddies and fronts. Ocean Dyn. 2009, 59:83-95. 10.1007/s10236-008-0167-0.
10. Di Lorenzo E., Moore A.M., Arango H.G., Cornuelle B.D., Miller A.J., Powell B., Chua B.S., Bennett A.F. Weak and strong constraint data assimilation in the inverse Regional Ocean Modeling System (ROMS): development and application for a baroclinic coastal upwelling system. Ocean Modell. 2007, 16(3-4):160-187. 10.1016/j.ocemod.2006.08.002.
11. Dick, S., Kleine, E., Mueller-Navarra, S.H., Kleine, H., Komo, H. 2001. The Operational Circulation Model of BSH (BSHcmod) model description and validation. Berichte des BSH 29/2001, Bundesamt fur Seeschifffart und Hydrographie, pp. 48.
12. Emery W.J., Thomson R.E. Data Analysis Methods in Physical Oceanography 2001, Elsevier, (pp. 392-402). second ed.
13. Evensen G. The ensemble Kalman filter: theoretical formulation and practical implementation. Ocean Dyn. 2003, 53:343-367.
14. Fu W.W., Zhu J., Yan C.X., Liu H.L. Toward a global ocean data assimilation system based on Ensemble Optimum Interpolation: altimetry data assimilation experiment. Ocean Dyn. 2009, 59(4):587-602.
15. Gustafsson B. Interaction between Baltic Sea and North Sea. Ger. J. Hydrography 1997, 492(3):165-183.
16. Haley P.J., Lermusiaux P.F.J., Robinson A.R., Leslie W.G., Logutov O., et al. Forecasting and reanalysis in the Monterey Bay/California current region for the autonomous ocean sampling network-II experiment. Deep Sea Res. Part II 2009, 56:127-148. (ISSN 0967-0645). 10.1016/j.dsr2.2008.08.010.
17. Hamill T.M., Whitaker J.S., Snyder C. Distance-dependent filtering of background error covariance estimates in an ensemble Kalman filter. Mon. Weather Rev. 2001, 129:2776-2790.
18. Houtekamer P.L., Mitchell H.L. A sequential ensemble Kalman filter for atmospheric data assimilation. Mon. Weather Rev. 2001, 129:123-137.
19. Høyer J.L., She J. Optimal interpolation of sea surface temperature for the North Sea and Baltic Sea. J. Mar. Sys. 2007, 65(1-4):176-189.
20. Jacobson F. Hydrographic investigation of the Northern Kattegat front. Cont. Shelf Res. 1997, 17:533-554.
21. Kurapov A.L., Egbert G.D., Miller R.N., Allen J.S. Data assimilation in a Baroclinic coastal ocean model: ensemble statistics and comparison of methods. Mon. Weather Rev. 2002, 130:1009-1025. 10.1175/1520-0493(2002).
22. Kurapov A.L., Egbert G.D., Allen J.S., Miller R.N. Representer-based variational data assimilation in a nonlinear model of nearshore circulation. J. Geophys. Res. 2007, 112:C11019.
23. Larsen J., Høyer J.L., She J. Validation of a hybrid optimal interpolation and Kalman filter scheme for sea surface temperature assimilation. J. Mar. Syst. 2007, 65:122-133.
24. Lermusiaux P.F.J. Adaptive modeling, adaptive data assimilation and adaptive sampling. Physica D 2007, 230:172-196.
25. Liu Ye, Zhu Jiang, She Jun, Zhuang Shiyu, Jidong Gao Impacts of assimilating ocean profile observations using a bottom-topography-following recursive filter on ocean forecasting in North Sea/Baltic Sea. Ocean Modell. 2009, 26(2-3):75-87. 10.1016/j.ocemod.2009.06.005.
26. Oke P., Schiller A., Griffin D., Brassington G. Ensemble data assimilation for an eddy-resolving ocean model of the Australian region. QJR Meteorol. Soc. 2005, 131:3301-33311.
27. Oke P., Sakov P., Corney S. Impacts of localisation in the EnKF and EnOI: experiments with a small model. Ocean Dyn. 2007, 57:32-45.
28. Oke P.R., Brassington G.B., Griffin D.A., Schiller A. The Bluelink ocean data assimilation system (BODAS). Ocean Modell. 2008, 21:46-70.
29. Pemberton, P. 2006. Validation of a one year simulation of the Baltic Sea with optimised boundary conditions, improved bathymetry and data assimilation. In: European Operational Oceanography: Present and Future, EuroGOOS Office, Sweden, and European Commission, Belgium, pp. 526-530.
30. Plag H.-P., Tsimplis M.N. Temporal variability of the seasonal sea-level cycle in the North Sea and Baltic Sea in relation to climate variability. Global Planet. Change 1999, 20(2-3):173-203.
31. Raschke E., et al. BALTEX (Baltic Sea Experiment): a European contribution to investigate the energy and water cycle over a large drainage basin. Bull. Amer. Met. Soc. 2001, 82(11):2389-2413.
32. Rodhe J. On the dynamics of the large-scale circulation of the Skagerrak. J. Sea Res. 1996, 35:9-21.
33. She, J., Berg, P., Høyer, J.L., Larsen, J., Nielsen, J.W. 2006. On operational three dimensional hydrodynamic model validation. In: Proceedings of EuroGOOS 4th Conference, pp. 519-526.
34. She J., Berg P., Berg J. Bathymetry impacts on water exchange modeling through the Danish Straits. J. Mar. Syst. 2007, 65:450-459.
35. She J., Høyer J.L., Larsen J. Assessment of sea surface temperature observational networks in the Baltic Sea and North Sea. J. Mar. Syst. 2007, 65:314-335.
36. Umlauf L., Burchard H., Hutter K. Extending the k-omega turbulence model towards oceanic applications. Ocean Modell. 2003, 5:195-218.
37. Xie J., Zhu J. Ensemble optimal interpolation schemes for assimilating Argo profiles into a hybrid coordinate ocean model. Ocean Modell. 2010, 33:283-298.
38. Zhang W.G., Wilkin J.L., Arango H.G. Towards an integrated observation and modeling system in the New York Bight using variational methods. Part I: 4DVAR data assimilation. Ocean Modell. 2010, 35(3):119-133. 10.1016/j.ocemod.2010.08.003.