A comparison of the performance of the 3-D super-ensemble and an ensemble Kalman filter for short-range regional ocean prediction

Tellus, Series A: Dynamic Meteorology and Oceanography

Volumn 66, Issue 1, 2014, Pages 21640-

  Mourre, Baptiste ^a,c   Chiggiato, Jacopo ^b  

^a Centre for Maritime Research and Experimentation (CMRE)   (Italy)

^b CNR   (Italy)

^c SOCIB   (Spain)

Author keywords

3 D super ensemble; Data assimilation; Ensemble Kalman filter; Ligurian Sea; Operational oceanography; Regional ocean prediction; Underwater gliders

Indexed keywords

ACCURACY ASSESSMENT; ALGORITHM; CLIMATOLOGY; DATA ASSIMILATION; ENSEMBLE FORECASTING; ERROR ANALYSIS; KALMAN FILTER; OCEANOGRAPHY; PREDICTION; SALINITY; SEA SURFACE TEMPERATURE; THREE-DIMENSIONAL MODELING; DATA SET;

LIGURIAN SEA; MEDITERRANEAN SEA;

EID: 84894504892     PISSN: 02806495     EISSN: 16000870     Source Type: Journal    
DOI: 10.3402/tellusa.v66.21640     Document Type: Article

References (35)

1. Alvarez, A., Chiggiato, J. and Mourre, B. 2013. Under the sea: rapid characterization of restricted marine environments. IEEE Robot. Autom. Mag. 20(3), 42-49.
2. Bonavita, M. and Torrisi, L. 2005. Impact of a variational objective analysis scheme on a regional area numerical model: the Italian air force weather service experience. Meteorol. Atmos. Phys. 88, 39-52.
3. Bonavita, M., Torrisi, L. and Marcucci, F. 2010. Ensemble data assimilation with the CNMCA regional forecasting system. Q. J. Roy. Meteorol. Soc. 136(646), 132-145.
4. Brasseur, P., Bahurel, P., Bertino, L., Birol, F., Brankart, J.-M. and co-authors. 2005. Data assimilation in operational ocean forecasting systems: the MERCATOR and MERSEA developments. Q. J. Roy. Meteorol. Soc. 131, 3561-3582.
5. Buongiorno Nardelli, B., Tronconi, C., Pisano, A. and Santoleri, R. 2013. High and ultra-high resolution processing of satellite Sea Surface Temperature data over Southern European Seas in the framework of MyOcean project. Rem. Sens. Environ. 129, 116.
6. Burgers, G., Van Leeuwen, P. J. and Evensen, G. 1998. Analysis scheme in the ensemble Kalman filter. Mon. Weather Rev. 126, 1719-1724.
7. Chao, Y., Li, Z., Farrara, J., McWilliams, J. C., Bellingham, J., Capet, X. and co-authors. 2009. Development, implementation and evaluation of a data-assimilative ocean forecasting system off the central California coast. Deep-Sea Res II. 56, 100-126.
8. Doblas-Reyes, F., Hagedorn, R. and Palmer, T. N. 2005. The rationale behind the success of multi-model ensembles in seasonal forecasting-II. Calibration and combination. Tellus A. 57, 234-252.
9. Dombrowsky, E., Bertino, L., Brassington, G. B., Chassignet, E. P., Davidson, F. and co-authors. 2009. GODAE systems in operation. Oceanography. 22(3), 8095.
10. Dowell, D. C., Zhang, F., Wicker, L. J., Snyder, C. and Crook, N. A. 2004. Wind and temperature retrievals in the 17 May 1981 Arcadia, Oklahoma, supercell: ensemble Kalman filter experiments. Mon. Weather Rev. 132, 19822005.
11. Evensen, G. 2003. The ensemble Kalman filter: theoretical formulation and practical implementation. Ocean Dynam. 53, 343-367.
12. Haidvogel, D. B., Arango, H., Budgell, W. P., Cornuelle, B. D., Curchitser, E. and co-authors. 2008. Ocean forecasting in terrain-following coordinates: formulation and skill assessment of the Regional Ocean Modeling System. J. Comput. Phys. 227, 3595-3624.
13. Houtekamer, P. L., Mitchell, H. L. and Deng, X. 2009. Model error representation in an operational ensemble Kalman filter. Mon. Weather Rev. 137, 2126-2143.
14. Jolliff, J. K., Kindle, J. C., Shulman, I., Penta, B., Friedrichs, M. and co-authors. 2009. Summary diagrams for coupled hydrodynamic-ecosystem model skill assessment. J. Mar. Syst. 76, 64-82.
15. Keppenne, C. L., Rienecker, M., Kurkowski, N. P. and Adamec, D. A. 2005. Ensemble Kalman filter assimilation of temperature and altimeter data with bias correction and application to seasonal prediction. Nonlinear Processes Geophys. 12, 491-503.
16. Krishnamurti, T. N., Kishtawal, C. M., LaRow, T. E., Bachiochi, D. R., Zhang, Z. and co-authors. 1999. Improved weather and seasonal climate forecasts from multimodel superensemble. Science. 285(5433), 1548-1550.
17. Leeuwenburgh, O. 2007. Validation of an EnKF system for OGCM initialization assimilating temperature, salinity, and surface height measurements. Mon. Weather Rev. 135, 125-139.
18. Lenartz, F., Mourre, B., Barth, A., Beckers, J.-M., Vandenbulcke, L. and co-authors. 2010. Enhanced ocean temperature forecast skills through 3-D super-ensemble multi-model fusion. Geophys. Res. Lett. 37(19), L19606.
19. Logutov, O. G. and Robinson, A. R. 2005. Multimodel fusion, error parameter estimation. Q. J. Roy. Meteorol. Soc. 131, 3397-3408.
20. Marchesiello, P., McWilliams, J. C. and Shchepetkin, A. 2001. Open boundary conditions for long-term integration of regional oceanic models. Ocean Model. 3, 1-20.
21. Marta-Almeida, M., Pereira, J. and Cirano, M. 2011. Development of a pilot Brazilian regional operational ocean forecast system, REMO-OOF. J. Oper. Oceanogr. 4(2), 3-15.
22. MEDAR Group. 2002. MEDATLAS 2002, Mediterranean and Black Sea database of temperature salinity and bio-chemical parameters and climatological atlas, IFREMER edition (4 CDRoms).
23. Mourre, B. and Alvarez, A. 2012. Benefit assessment of glider adaptive sampling in the Ligurian Sea. Deep Sea Res. Part I Oceanogr. Res. Pap. 68, 68-78.
24. Mourre, B., Chiggiato, J., Lenartz, F. and Rixen, M. 2012. Uncertainty forecast from 3-D super-ensemble multi-model combination: validation and calibration. Ocean Dynam. 62(2), 283-294.
25. Murphy, A. H. 1995. The coefficients of correlation and determination as measures of performance in forecast verification. Weather Forecast. 10, 681-688.
26. Oke, P. R., Brassington, G. B., Griffin, D. A. and Schiller, A. 2008. The Bluelink ocean data assimilation system (BODAS). Ocean Model. 21, 46-70.
27. Pinardi, N. and Coppini, G. 2010. Operational oceanography in the Mediterranean Sea: the second stage of development. Ocean Sci. 6, 263-267.
28. Raftery, A. E., Gneiting, T., Balabdaoui, F. and Polakowski, M. 2005. Using Bayesian model averaging to calibrate forecast ensembles. Mon. Weather Rev. 133, 1155-1174.
29. Rixen, M., Book, J. W., Carta, A., Grandi, V., Gualdesi, L. and co-authors. 2009. Improved ocean prediction skill and reduced uncertainty in the coastal region from multimodel superensembles. J. Mar. Syst. 78, S282-S289.
30. Sakov, P., Counillon, F., Bertino, L., Lisaeter, K. A., Oke, P. R. and co-authors. 2012. TOPAZ4: an ocean-sea ice data assimilation system for the North Atlantic and Arctic. Ocean Sci. 8, 633-656.
31. Sakov, P., Evensen, G. and Bertino, L. 2010. Asynchronous data assimilation with the EnKF. Tellus. 62, 24-29.
32. Schroeder, K., Chiggiato, J., Haza, A. C., Griffa, A., Özgökmen, T. M. and co-authors. 2012. Targeted Lagrangian sampling of submesoscale dispersion at a coastal frontal zone. Geophys. Res. Lett. 39, L11608.
33. Shchepetkin, A. F. and McWilliams, J. C. 2005. The Regional Oceanic Modeling System (ROMS): a split explicit, free-surface, topography-following-coordinate oceanic model. Ocean Model. 9, 347-404.
34. Wang, X., Chao, Y., Thompson, D. R., Chien, S. A., Farrara, J. and co-authors. 2013. Multi-model ensemble forecasting and glider path planning in the Mid-Atlantic Bight. Continent. Shelf Res. 63, S223-S234.
35. Zodiatis, G., Lardner, R., Hayes, D. R., Georgiou, G., Sofianos, S. and co-authors. 2008. Operational ocean forecasting in the Eastern Mediterranean: implementation and evaluation. Ocean Sci. 4(1), 31-47.