Tropical Atlantic SST Prediction with Coupled Ocean–Atmosphere GCMs

Timothy N. Stockdale ECMWF, Shinfield Park, Reading, United Kingdom

Search for other papers by Timothy N. Stockdale in
Current site
Google Scholar
PubMed
Close
,
Magdalena A. Balmaseda ECMWF, Shinfield Park, Reading, United Kingdom

Search for other papers by Magdalena A. Balmaseda in
Current site
Google Scholar
PubMed
Close
, and
Arthur Vidard ECMWF, Shinfield Park, Reading, United Kingdom

Search for other papers by Arthur Vidard in
Current site
Google Scholar
PubMed
Close
Restricted access

Abstract

Variations in tropical Atlantic SST are an important factor in seasonal forecasts in the region and beyond. An analysis is given of the capabilities of the latest generation of coupled GCM seasonal forecast systems to predict tropical Atlantic SST anomalies. Skill above that of persistence is demonstrated in both the northern tropical and equatorial Atlantic, but not farther south. The inability of the coupled models to correctly represent the mean seasonal cycle is a major problem in attempts to forecast equatorial SST anomalies in the boreal summer. Even when forced with observed SST, atmosphere models have significant failings in this area. The quality of ocean initial conditions for coupled model forecasts is also a cause for concern, and the adequacy of the near-equatorial ocean observing system is in doubt. A multimodel approach improves forecast skill only modestly, and large errors remain in the southern tropical Atlantic. There is still much scope for improving forecasts of tropical Atlantic SST.

Corresponding author address: Dr. T. Stockdale, ECMWF, Shinfield Park, Reading RG2 9AX, United Kingdom. Email: T.Stockdale@ecmwf.int

Abstract

Variations in tropical Atlantic SST are an important factor in seasonal forecasts in the region and beyond. An analysis is given of the capabilities of the latest generation of coupled GCM seasonal forecast systems to predict tropical Atlantic SST anomalies. Skill above that of persistence is demonstrated in both the northern tropical and equatorial Atlantic, but not farther south. The inability of the coupled models to correctly represent the mean seasonal cycle is a major problem in attempts to forecast equatorial SST anomalies in the boreal summer. Even when forced with observed SST, atmosphere models have significant failings in this area. The quality of ocean initial conditions for coupled model forecasts is also a cause for concern, and the adequacy of the near-equatorial ocean observing system is in doubt. A multimodel approach improves forecast skill only modestly, and large errors remain in the southern tropical Atlantic. There is still much scope for improving forecasts of tropical Atlantic SST.

Corresponding author address: Dr. T. Stockdale, ECMWF, Shinfield Park, Reading RG2 9AX, United Kingdom. Email: T.Stockdale@ecmwf.int

Save
  • Alves, O., M. Balmaseda, D. Anderson, and T. Stockdale, 2004: Sensitivity of dynamical seasonal forecasts to ocean initial conditions. Quart. J. Roy. Meteor. Soc., 130 , 647668.

    • Search Google Scholar
    • Export Citation
  • Anderson, D., and Coauthors, 2003: Comparison of the ECMWF seasonal forecast systems 1 and 2, including the relative performance for the 1997/8 El Nino. ECMWF Tech. Memo. 404, 95 pp. [Available online at www.ecmwf.int/publications.].

  • Balmaseda, M. A., 2003: Ocean data assimilation for seasonal forecasts. Proc. ECMWF Seminar on Recent Developments in Data Assimilation for Atmosphere and Ocean, Reading, United Kingdom, ECMWF, 301–326. [Available online at www.ecmwf.int/publications.].

  • Bell, M. J., M. J. Martin, and N. K. Nichols, 2004: Assimilation of data into an ocean model with systematic errors near the equator. Quart. J. Roy. Meteor. Soc., 130 , 873893.

    • Search Google Scholar
    • Export Citation
  • Burgers, G., M. A. Balmaseda, F. C. Vossepoel, G. J. van Oldenborgh, and P. J. van Leeuwen, 2002: Balanced ocean data assimilation near the equator. J. Phys. Oceanogr., 32 , 25092519.

    • Search Google Scholar
    • Export Citation
  • Carton, J. A., X. Cao, B. S. Giese, and A. M. Da Silva, 1996: Decadal and interannual SST variability in the tropical Atlantic Ocean. J. Phys. Oceanogr., 26 , 11651175.

    • Search Google Scholar
    • Export Citation
  • Chang, P., L. Ji, and H. Li, 1997: A decadal climate variation in the tropical Atlantic Ocean from thermodynamic air–sea interactions. Nature, 385 , 516518.

    • Search Google Scholar
    • Export Citation
  • Chang, P., R. Saravanan, and L. Ji, 2003: Tropical Atlantic seasonal predictability: The roles of El Nino remote influence and thermodynamic air–sea feedback. Geophys. Res. Lett., 30 .1501, doi:10.1029/2002GL016119.

    • Search Google Scholar
    • Export Citation
  • Davey, M. K., and Coauthors, 2002: STOIC: A study of coupled model climatology and variability in tropical ocean regions. Climate Dyn., 18 , 403420.

    • Search Google Scholar
    • Export Citation
  • Dee, D. P., and A. M. Da Silva, 1998: Data assimilation in the presence of forecast bias. Quart. J. Roy. Meteor. Soc., 124 , 269295.

  • Florenchie, P., C. J. C. Reason, J. R. E. Lutjeharms, M. Rouault, C. Roy, and S. Masson, 2004: Evolution of interannual warm and cold events in the southeast Atlantic Ocean. J. Climate, 17 , 23182334.

    • Search Google Scholar
    • Export Citation
  • Haines, K., J. Blower, J-P. Drecourt, A. Vidard, C. Liu, I. Astin, and X. Zhou, 2006: Salinity assimilation using S(T) relationships. Mon. Wea. Rev., 134 , 759771.

    • Search Google Scholar
    • Export Citation
  • Huang, B., P. S. Schopf, and Z. Pan, 2002: The ENSO effect on the tropical Atlantic variability: A regionally coupled model study. Geophys. Res. Lett., 29 .2039, doi:10.1029/2002GL014872.

    • Search Google Scholar
    • Export Citation
  • Kushnir, Y., W. A. Robinson, P. Chang, and A. W. Robertson, 2006: The physical basis for predicting Atlantic sector seasonal-to-interannual climate variability. J. Climate, 19 , 59495970.

    • Search Google Scholar
    • Export Citation
  • Mathieu, P-P., R. T. Sutton, B. Dong, and M. Collins, 2004: Predictability of winter climate over the North Atlantic European region during ENSO events. J. Climate, 17 , 19531974.

    • Search Google Scholar
    • Export Citation
  • Palmer, T. N., and Coauthors, 2004: Development of a European Multimodel Ensemble System for Seasonal-to-Interannual Prediction (DEMETER). Bull. Amer. Meteor. Soc., 85 , 853872.

    • Search Google Scholar
    • Export Citation
  • Servain, J., 1991: Simple climatic indices for the tropical Atlantic Ocean and some applications. J. Geophys. Res., 96 , 1513715146.

  • Segschneider, J., M. Balmaseda, and D. L. T. Anderson, 2000: Anomalous temperature and salinity variations in the tropical Atlantic: Possible causes and implications for the use of altimeter data. Geophys. Res. Lett., 27 , 22812284.

    • Search Google Scholar
    • Export Citation
  • Troccoli, A., and Coauthors, 2002: Salinity adjustments in the presence of temperature data assimilation. Mon. Wea. Rev., 130 , 89102.

    • Search Google Scholar
    • Export Citation
  • Uppala, S. M., and Coauthors, 2005: The ERA-40 re-analysis. Quart. J. Roy. Meteor. Soc., 131 , 29613012.

  • Vialard, J., A. T. Weaver, D. L. T. Anderson, and P. Delecluse, 2003: Three- and four-dimensional variational assimilation with a general circulation model of the tropical Pacific Ocean. Part II: Physical validation. Mon. Wea. Rev., 131 , 13791395.

    • Search Google Scholar
    • Export Citation
  • Vidard, A., A. Piacentini, and F-X. Le Dimet, 2004: Variational data analysis with control of the forecast bias. Tellus, 56A , 177188.

    • Search Google Scholar
    • Export Citation
  • Vidard, A., D. L. T. Anderson, and M. Balmaseda, 2005: Impact of ocean observation systems on seasonal forecasts. ECMWF Tech. Memo. 460, 32 pp. [Available online at www.ecmwf.int/publications.].

  • Zebiak, S. E., 1993: Air–sea interaction in the equatorial Atlantic region. J. Climate, 6 , 15671586.

All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 575 160 8
PDF Downloads 407 106 11