Editorial Type:
Article
Article Type:
Research Article

Sea Level Assimilation Experiments in the Tropical Pacific

J. O. S. Alves European Centre for Medium-Range Weather Forecasts, Reading, Berkshire, United Kingdom

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K. Haines Department of Meteorology, University of Edinburgh, Edinburgh, United Kingdom

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D. L. T. Anderson European Centre for Medium-Range Weather Forecasts, Reading, Berkshire, United Kingdom

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Print Publication:
01 Feb 2001
DOI:
https://doi.org/10.1175/1520-0485(2001)031<0305:SLAEIT>2.0.CO;2
Page(s):
305–323
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Abstract

Idealized twin experiments with the HOPE ocean model have been used to study the ability of sea level data assimilation to correct for errors in a model simulation of the tropical Pacific, using the Cooper and Haines method to project the surface height increments below the surface. This work should be seen in the context of the development of the comprehensive real-time ocean analysis system used at ECMWF for seasonal forecasting, which currently assimilates only thermal data.

Errors in the model simulation from two sources are studied: those present in the initial state and those generated by errors in the surface forcing during the simulation. In the former, the assimilation of sea level data improves the convergence of the model toward its twin. Without assimilation convergence occurs more slowly on the equator, compared to an experiment using only correct surface forcing. With forcing errors present the sea level assimilation still significantly reduces the errors almost everywhere. An exception was in the central equatorial Pacific where assimilation of sea level did not correct the errors. This is mainly due to this region responding rapidly to errors in wind stress forcing and also to relatively large freshwater flux errors imposed here. These lead to errors in the mixed layer salinity, which the Cooper and Haines scheme is not designed to correct. It is argued that surface salinity analyses would strongly complement sea level assimilation here.

Corresponding author address: J. O. S. Alves, Bureau of Meteorology Research Centre, GPO Box 1289K, Melbourne, Vic 3001, Australia.

Email: o.alves@bom.gov.au

Abstract

Idealized twin experiments with the HOPE ocean model have been used to study the ability of sea level data assimilation to correct for errors in a model simulation of the tropical Pacific, using the Cooper and Haines method to project the surface height increments below the surface. This work should be seen in the context of the development of the comprehensive real-time ocean analysis system used at ECMWF for seasonal forecasting, which currently assimilates only thermal data.

Errors in the model simulation from two sources are studied: those present in the initial state and those generated by errors in the surface forcing during the simulation. In the former, the assimilation of sea level data improves the convergence of the model toward its twin. Without assimilation convergence occurs more slowly on the equator, compared to an experiment using only correct surface forcing. With forcing errors present the sea level assimilation still significantly reduces the errors almost everywhere. An exception was in the central equatorial Pacific where assimilation of sea level did not correct the errors. This is mainly due to this region responding rapidly to errors in wind stress forcing and also to relatively large freshwater flux errors imposed here. These lead to errors in the mixed layer salinity, which the Cooper and Haines scheme is not designed to correct. It is argued that surface salinity analyses would strongly complement sea level assimilation here.

Corresponding author address: J. O. S. Alves, Bureau of Meteorology Research Centre, GPO Box 1289K, Melbourne, Vic 3001, Australia.

Email: o.alves@bom.gov.au

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  • Alves, J. O. S., D. L. T. Anderson, T. N. Stockdale, M. A. Balmaseda, and J. Segschneider, 1999: Sensitivity of ENSO forecasts to ocean initial conditions. Proc. Int. Symp. TRIANGLE 98, Kyoto, Japan, JAMSTEC, 21–30.

  • Anderson, D. L. T., J. Sheinbaum, and K. Haines, 1996: Data assimilation in ocean models. Rep. Prog. Phys.,59, 1209–1266.

  • Berry, P. J., and J. C. Marshall, 1989: Ocean modelling studies in support of altimetry. Dyn. Atmos. Oceans,13, 269–300.

  • Carton, J. A., B. S. Giese, X. Cao, and L. Miller, 1996: Impact of altimeter, thermistor, and expendable bathythermograph data on retrospective analyses of the tropical Pacific Ocean. J. Geophys. Res.,101 (C6), 14 147–14 159.

  • Cooper, M., and K. Haines, 1996: Altimetric assimilation with water property conservation. J. Geophys. Res.,101 (C1), 1059–1077.

  • De Mey, P., and A. R. Robinson, 1987: Assimilation of altimeter eddy fields in a limited-area quasi-geostrophic model. J. Phys. Oceanogr.,17, 2280–2293.

  • Drakopoulos, P. G., K. Haines, and P. Wu, 1997: Altimetric assimilation in a Mediterranean general circulation model. J. Geophys. Res.,102 (C5), 10 509–10 523.

  • Ezer, T., and G. L. Mellor, 1994: Continuous assimilation of GEOSAT altimeter data into a three-dimensional primitive equation Gulf Stream model. J. Phys. Oceanogr.,24, 832–847.

  • Fisher, M., M. Latif, M. Flugel, and M. Ji, 1997: On the benefit of sea level assimilation in the tropical Pacific. Mon. Wea. Rev.,125, 819–829.

  • Haines, K., 1991: A direct method for assimilating sea surface height data into ocean models with adjustments to the deep circulation. J. Phys. Oceanogr.,21, 843–868.

  • Holland, W. R., and P. Malanotte-Rizzoli, 1989: Assimilation of altimeter data into an ocean model: Space verses time resolution studies. J. Phys. Oceanogr.,19, 1507–1534.

  • Hurlburt, H. E., 1986: Dynamic transfer of simulated altimeter data into subsurface information by a numerical ocean model. J. Geophys. Res.,91, 2372–2400.

  • Ji, M., and A. Leetmaa, 1997: Impact of data assimilation on ocean initialization and El Niño prediction. Mon. Wea. Rev.,125, 742–753.

  • ——, ——, and J. Derber, 1995: An ocean analysis system for seasonal to interannual climate studies. Mon. Wea. Rev.,123, 460–481.

  • —— R. W. Reynolds, and D. Behringer, 2000: Use of TOPEX/Poseidon sea level data for ocean analyses and ENSO prediction:Some early results. J. Climate,13, 216–231.

  • Latif, M., T. Stockdale, J. Wolff, F. Burgers, E. Maier-Reimer, M. Junge, K. Arpe, and L. Bengtsson, 1994: Climatology and variability in the ECHO coupled GCM. Tellus,46A, 351–366.

  • ——, D. Anderson, T. Barnett, M. Cane, R. Kleeman, J. O’Brien, A. Rosati, and E. K. Schneider, 1998: TOGA review paper: Predictability and prediction. J. Geophys. Res.,103 (C7), 14 375–14 393.

  • Le Traon, P.-Y., F. Nadal, and N. Ducet, 1998: An improved mapping method of multi-satellite altimeter data. J. Atmos. Oceanic Technol.,15, 522–534.

  • Mellor, G. L., and T. Ezer, 1991: A Gulf Stream model and an altimetry assimilation scheme. J. Geophys. Res.,96, 8779–8795.

  • Oschlies, A., and J. Willebrand, 1996: Assimilation Geosat of altimeter data into an eddy-resolving primitive equation model of the North Atlantic Ocean. J. Geophys. Res.,101 (C6), 14 175–14 190.

  • Reynolds, R. W., 1988: A real-time global sea surface temperature analyses. J. Climate,1, 75–86.

  • Segschneider, J., D. Anderson, and T. Stockdale, 2000: Toward the use of altimetry for operational seasonal forecasting. J. Climate,13, 3115–3138.

  • Stockdale, T. N., D. L. T. Anderson, J. O. S. Alves, and M. A. Balmaseda, 1998: Global seasonal rainfall forecasts using a coupled ocean–atmosphere model. Nature,392, 370–373.

  • Trenberth, K. E., 1998: Development and forecasts of the 1997/98 El Niño: CLIVAR scientific issues. Exchanges: Newsletter of the Climate Variability and Predictability Program (CLIVAR), published by the Internatinal CLIVAR Project Office, Max-Planck-Institut für Meteorologie, Hamburg, Germany, 11 pp. [Available from Max-Planck-Institut für Meteorologie, Bundesstr. 55, D-20146 Hamburg, Germany.].

  • Verron, J., L. Gourdeau, D. T. Pham, R. Murtugudde, and A. J. Busalacchi, 1999: An extended Kalman filter to assimilate satellite altimeter data into a nonlinear numerical model of the tropical Pacific Ocean: Method and validation. J. Geophys. Res.,104 (C3), 5441–5458.

  • Vossepoel, F. C., and D. W. Behringer, 2000: Impact of sea level assimilation on salinity variability in the western equatorial Pacific. J. Phys. Oceanogr.,30, 1706–1721.

  • Weaver, A. T., and D. L. T. Anderson, 1997: Variational assimilation of altimeter data in a multilayer model of the tropical Pacific Ocean. J. Phys. Oceanogr.,27, 664–682.

  • Wolff, J., E. Maier-Reimer, and S. Legutke, 1997: The Hamburg Ocean Primitive Equation Model. Deutsches KlimaRechenZentrum Tech. Rep. 98 pp. [Available from Max-Planck-Institut für Meteorologie, Bundesstr. 55, D-20146 Hamburg, German.].

  • Woodgate, R. A., and P. D. Killworth, 1996: The problem of the barotropic mode in deriving pressure from density by using vertical normal modes. J. Geophys. Res.,101 (C2), 3762–3768.

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