Several operational centers routinely issue seasonal forecasts of Earth’s climate using coupled ocean-atmosphere models, which require near-real-time knowledge of the state of the global ocean. This paper reviews existing ocean analysis efforts aimed at initializing seasonal forecasts. We show that ocean data assimilation improves the skill of seasonal forecasts in many cases, although its impact can be overshadowed by errors in the coupled models. The current practice, known as “uncoupled” initialization, has the advantage of better knowledge of atmospheric forcing fluxes, but it has the shortcoming of potential initialization shock. In recent years, the idea of obtaining truly “coupled” initialization, where the different components of the coupled system are well balanced, has stimulated several research activities that will be reviewed in light of their application to seasonal forecasts.

Balmaseda, M.A., O.J. Alves, A. Arribas, T. Awaji, D.W. Behringer, N. Ferry, Y. Fujii, T. Lee, M. Rienecker, T. Rosati, and D. Stammer. 2009. Ocean initialization for seasonal forecasts. Oceanography 22(3):154–159, https://doi.org/10.5670/oceanog.2009.73.

Alves, O., M. Balmaseda, D Anderson, and T. Stockdale. 2004. Sensitivity of dynamical seasonal forecasts to ocean initial conditions. Quarterly Journal of the Royal Meteorological Society 130:647–668.

Alves, O., and C. Robert. 2005. Tropical Pacific ocean model error covariances from Monte Carlo simulations. Quarterly Journal of the Royal Meteorological Society 131:3,643–3,658.

Balmaseda, M.A., A. Vidard, and D. Anderson. 2008a. The ECMWF ORA-S3 ocean analysis system. Monthly Weather Review 136:3,018–3,034.

Balmaseda, M.A., O. Alves, A. Arribas, T. Awaji, D. Behringer, N. Ferry, Y. Fujii, T. Lee, M. Rienecker, T. Rosati, and D. Stammer. 2008b. Ocean initialization for seasonal forecasting. Invited paper presented at the Final GODAE Symposium, Nice, France, November 12–15, 2008. Abstract available online at: http://www.godae.org/5.5-MB-abstract.html (accessed May 20, 2009).

Balmaseda, M.A., and D. Anderson. 2009. Impact of initialization strategies and observations on seasonal forecast skill. Geophysical Research Letters 36, L01701, doi:10.1029/2008GL035561.

Behringer, D.W. 2007. The Global Ocean Data Assimilation System at NCEP. Paper presented at the 11^th Symposium on Integrated Observing and Assimilation Systems for Atmosphere, Oceans, and Land Surface, AMS 87th Annual Meeting, San Antonio, Texas.

Burgers, G., M. Balmaseda, F. Vossepoel, G.J. van Oldenborgh, and P.J. van Leeuwen. 2002. Balanced ocean-data assimilation near the equator. Journal of Physical Oceanography 32:2,509–2,519.

Cazes-Boezio, G., D. Menemenlis, and C.R. Mechoso. 2008. Impact of ECCO ocean-state estimates on the initialization of seasonal climate forecasts. Journal of Climate 21:1,929–1,947.

Dommenget, D., and D. Stammer. 2004. Assessing ENSO simulations and predictions using adjoint ocean state estimation. Journal of Climate 17:4,301–4,315.

Fujii, Y., S. Matsumoto, M. Kamachi, and S. Ishizaki. In press. Estimation of the equatorial Pacific salinity field using ocean data assimilation system. Advances in Geosciences.

Fujii, Y., T. Yasuda, S. Matsumoto, M. Kamachi, and K. Ando. 2008. Observing system evaluation (OSE) using the El Niño forecasting system in Japan Meteorological Agency. Paper presented at the fall meeting of the Oceanographic Society of Japan (in Japanese).

Fukumori, I. 2002. A partitioned Kalman filter and smoother. Monthly Weather Review 130:1,370–1,383.

Keppenne, C.L., M.M. Rienecker, J.P. Jacob, and R. Kovach. 2008. Error covariance modeling in the GMAO ocean ensemble Kalman filter. Monthly Weather Review 136:2,964–2,982, doi:10.1175/2007MWR2243.1.

Martin, M.J., A. Hines, and M.J. Bell. 2007. Data assimilation in the FOAM operational short-range ocean forecasting system: A description of the scheme and its impact. Quarterly Journal of the Royal Meteorological Society 133:981–995.

Oke, P.R., M.A. Balmaseda, M. Benkiran, J.A. Cummings, E. Dombrowsky, Y. Fujii, S. Guinehut, G. Larnicol, P.-Y. Le Traon, and M.J. Martin. 2009. Observing system evaluations using GODAE systems. Oceanography 22(3):144–153.

Pham, D.T., J. Verron, and M.C. Roubaud. 1998. A singular evolutive extended Kalman filter for data assimilation in oceanography. Journal of Marine Systems 16:323–340.

Sugiura, N., T. Awaji, S. Masuda, T. Mochizuki, T. Toyoda, T. Miyama, H. Igarashi, and Y. Ishikawa. 2008. Development of a 4-dimensional variational coupled data assimilation system for enhanced analysis and prediction of seasonal to interannual climate variations. Journal of Geophysical Research 113, C10017, doi:10.1029/2008JC004741.

Troccoli, A., M. Balmaseda, J. Segschneider, J. Vialard, D. Anderson, K. Haines, T. Stockdale, F. Vitart, and A.D. Fox. 2002. Salinity adjustments in the presence of temperature data assimilation. Monthly Weather Review 130:89–102.

Usui, N., S. Ishizaki, Y. Fujii, H. Tsujino, T. Yasuda, and M. Kamachi. 2006. Meteorological Research Institute Multivariate Ocean Variational Estimation (MOVE) System: Some early results. Advances in Space Research 37:806–822.

Yang, S., C.C. Keppenne, M. Rienecker, and E. Kalnay. In press. Application of coupled bred vectors to seasonal-to-interannual forecasting and ocean data assimilation. Journal of Climate.

Zhang, S., M.J. Harrison, A. Rosati, and A. Wittenberg. 2007. System design and evaluation of coupled ensemble data assimilation for global oceanic studies. Monthly Weather Review 135:3,541–3,564.

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.