Toward the Use of Altimetry for Operational Seasonal Forecasting

J. Segschneider European Centre for Medium-Range Weather Forecasts, Shinfield Park, Reading, United Kingdom

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

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T. N. Stockdale European Centre for Medium-Range Weather Forecasts, Shinfield Park, Reading, United Kingdom

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Abstract

The TOPEX/Poseidon and ERS-1/2 satellites have now been observing sea level anomalies for a continuous time span of more than 6 yr. These sea level observations are first compared with tide gauge data and then assimilated into an ocean model that is used to initialize coupled ocean–atmosphere forecasts with a lead time of 6 months. Ocean analyses in which altimeter data are assimilated are compared with those from a no-assimilation experiment and with analyses in which subsurface temperature observations are assimilated. Analyses with altimeter data show variations of upper-ocean heat content similar to analyses using subsurface observations, whereas the ocean model has large errors when no data are assimilated. However, obtaining good results from the assimilation of altimeter data is not straightforward: it is essential to add a good mean sea level to the observed anomalies, to filter the sea level observations appropriately, to start the analyses from realistic initial temperature and salinity fields, and to assign appropriate weights for the analyzed increments.

To assess the impact of altimeter data assimilation on the coupled system, ensemble hindcasts are initialized from ocean analyses in which either no data, subsurface temperatures, or sea level observations were assimilated. For each kind of ocean analysis, a five-member ensemble is started every 3 months from January 1993 to October 1997, adding up to 100 forecasts for each type. The predicted SST anomalies for the equatorial Pacific are intercompared between the experiments and against observations. The predicted anomalies are on average closer to observed values when forecasts are initialized from the ocean analysis using altimeter data than when initialized from the no-assimilation ocean analysis, and forecast errors appear to be only slightly larger than for forecasts initialized from ocean analyses using subsurface temperatures. However, even based on 100 coupled forecasts, the distinction between the two experiments that benefit from data assimilation is barely statistically significant. The verification should still be considered preliminary, because the period covered by the forecasts is only 5 yr, which is too short properly to sample ENSO variability. It is, nonetheless, encouraging that altimeter assimilation can improve the forecast skill to a level comparable to that obtained from using Tropical Ocean Atmosphere–expendable bathythermograph data.

Corresponding author address: Dr. Joachim Segschneider, European Centre for Medium-Range Weather Forecasts, Shinfield Park, Reading RG2 9AX, United Kingdom.

Email: j.segschneider&commat⊇mwf.int

Abstract

The TOPEX/Poseidon and ERS-1/2 satellites have now been observing sea level anomalies for a continuous time span of more than 6 yr. These sea level observations are first compared with tide gauge data and then assimilated into an ocean model that is used to initialize coupled ocean–atmosphere forecasts with a lead time of 6 months. Ocean analyses in which altimeter data are assimilated are compared with those from a no-assimilation experiment and with analyses in which subsurface temperature observations are assimilated. Analyses with altimeter data show variations of upper-ocean heat content similar to analyses using subsurface observations, whereas the ocean model has large errors when no data are assimilated. However, obtaining good results from the assimilation of altimeter data is not straightforward: it is essential to add a good mean sea level to the observed anomalies, to filter the sea level observations appropriately, to start the analyses from realistic initial temperature and salinity fields, and to assign appropriate weights for the analyzed increments.

To assess the impact of altimeter data assimilation on the coupled system, ensemble hindcasts are initialized from ocean analyses in which either no data, subsurface temperatures, or sea level observations were assimilated. For each kind of ocean analysis, a five-member ensemble is started every 3 months from January 1993 to October 1997, adding up to 100 forecasts for each type. The predicted SST anomalies for the equatorial Pacific are intercompared between the experiments and against observations. The predicted anomalies are on average closer to observed values when forecasts are initialized from the ocean analysis using altimeter data than when initialized from the no-assimilation ocean analysis, and forecast errors appear to be only slightly larger than for forecasts initialized from ocean analyses using subsurface temperatures. However, even based on 100 coupled forecasts, the distinction between the two experiments that benefit from data assimilation is barely statistically significant. The verification should still be considered preliminary, because the period covered by the forecasts is only 5 yr, which is too short properly to sample ENSO variability. It is, nonetheless, encouraging that altimeter assimilation can improve the forecast skill to a level comparable to that obtained from using Tropical Ocean Atmosphere–expendable bathythermograph data.

Corresponding author address: Dr. Joachim Segschneider, European Centre for Medium-Range Weather Forecasts, Shinfield Park, Reading RG2 9AX, United Kingdom.

Email: j.segschneider&commat⊇mwf.int

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  • Alves, J. O. S., K. Haines, and D. L. T. Anderson, 2000: Sea level assimilation experiments in the tropical Pacific. J. Phys. Oceanogr., in press.

  • 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, 14147–14159.

  • Chambers, D. P., R. H. Stewart, and B. D. Tapley, 1998: Measuring heat storage changes in the equatorial Pacific: A comparison between TOPEX altimetry and Tropical Atmosphere–Ocean buoys. J. Geophys. Res.,103, 18591–18597.

  • Chelton, D. B., and M. G. Schlax, 1994: The resolution capability of an irregularly sampled dataset: With application to Geosat altimeter data. J. Atmos. Oceanic Technol.,11, 534–550.

  • Chen, D., M. A. Cane, S. E. Zebiak, and A. Kaplan, 1998: The impact of sea level assimilation on the Lamont model prediction of the 1997/98 El Niño. Geophys. Res. Lett.,25, 2837–2840.

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

  • Fischer, M., M. Fl&uumlϵl, M. Ji, and M. Latif, 1997: The impact of data assimilation on ENSO simulations and predictions. Mon. Wea Rev.,125, 819–829.

  • Helland-Hansen, B., and F. Nansen, 1916: Temperature Variations of the North Atlantic and in the Atmosphere (in German). Videnskapsselskapets Skrivter. I. Mat.-Naturv. Klasse, Vol. 9, Kristiania, 341 pp.

  • Ji, M., D. W. Behringer, and A. Leetma, 1998: An improved coupled model for ENSO prediction and implications for ocean initialization. Part II: The coupled model. Mon. Wea. Rev.,126, 1022– 1034.

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

  • Le Traon, P. Y., P. Gaspar, F. Bouyssel, and H. Makhmara, 1995: Using TOPEX/Poseidon data to enhance ERS-1 orbit. J. Atmos. Oceanic Technol.,12, 161–170.

  • ——, F. Nadal, and N. Ducet, 1998: An improved mapping method of multisatellite altimeter data. J. Atmos. Oceanic Technol.,15, 522–534.

  • Levitus, S., and T. P. Boyer, 1994: Temperature. Vol. 4, World Ocean Atlas 1994, NOAA NESDIS, 129 pp.

  • ——, R. Burgett, and T. P. Boyer, 1994: Salinity. Vol. 3, World Ocean Atlas 1994, NOAA NESDIS, 111 pp.

  • McPhaden, M. J., 1995: The Tropical Atmosphere Ocean array is completed. Bull. Amer. Meteor. Soc.,76, 739–741.

  • Mitchum, G., 1994: Comparison of TOPEX sea surface heights and tide gauge sea levels. J. Geophys. Res.,99, 24541–24553.

  • Oschlies, A., and J. Willebrand, 1996: Assimilation of Geosat altimeter data into an eddy-resolving primitive equation model of the North Atlantic Ocean. J. Geophys. Res.,101, 14175–14190.

  • Reynolds, R. W., and T. M. Smith, 1995: A high-resolution global sea surface temperature climatology. J. Climate,8, 1571–1583.

  • Segschneider, J., J. Alves, D. L. T. Anderson, M. Balmaseda, and T. N. Stockdale, 1999: Assimilation of TOPEX/Poseidon data into a seasonal forecast system. Phys. Chem. Earth (A),24, 369– 374.

  • Smith, N. R., 1995: SIANAL—A statistical interpolation routine. Documentation, BMRC, Melbourne, Australia, 35 pp. [Available from BMRC, Box 1289K, Melbourne, Victoria 3001, Australia.].

  • ——, J. E. Blomley, and G. Meyers, 1991: A univariate statistical interpolation scheme for subsurface thermal analyses in the tropical oceans. Progress in Oceanography, Vol. 28. Pergamon Press, 219–256.

  • Stammer, D., and C. Wunsch, 1996: The determination of the large-scale circulation of the Pacific Ocean from satellite altimetry using model Green’s functions. J. Geophys. Res.,101 (C8), 18409–18432.

  • Stockdale, T. N., 1997: Coupled ocean–atmosphere forecasts in the presence of climate drift. Mon. Wea. Rev.,125, 809–818.

  • ——, D. L. T. Anderson, J. Alves, and M. Balmaseda, 1998: Seasonal rainfall forecasts with a coupled ocean–atmosphere model. Nature,392, 370–373.

  • Tapley, B. D., and Coauthors, 1996: The Joint Gravity Model 3. J. Geophys. Res.,101, 28029–28049.

  • Vialard, J., and P. Delecluse, 1998: An OGCM study for the TOGA decade. Part I: Role of salinity in the physics of the western Pacific fresh pool. J. Phys. Oceanogr.,28, 1071–1088.

  • Vossepoel, F. C., R. W. Reynolds, and L. Miller, 1999: Use of sea level observations to estimate salinity variability in the tropical Pacific. J. Atmos. Oceanic Technol.,16, 1401–1415.

  • 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. O., E. Maier-Reimer, and S. Legutke, 1997: The Hamburg Ocean Primitive Equation Model. Deutsches Klimarechenzentrum Tech. Rep. 13, Hamburg, Germany, 98 pp. [Available from DKRZ, Bundesstr. 55, D 20146 Hamburg, Germany.].

  • Wyrtki, K., 1985: Water displacements in the Pacific and the genesis of El Niño cycles. J. Geophys. Res.,90, 7129–7132.

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