378
DAVID ANDERSON ET AL
techniques for initializing coupled models combined with better models
suggest a busy time ahead.
Acknowledgements
The authors thank the members of the ECMWF analysis and medium
range and seasonal forecast groups for constructive discussions, and Graeme
Kelly and Federico Grazzini for providing figs 1 and 2 respectively. This
work was supported in part by ENACT EU-contract EVK2-2001-00077.
References
Anderson D.L.T., A. Hollingsworth, S. Uppala, and P. Worceshyn, 1991: A study of the use
of scatterometer data in the ECMWF Operational Analysis - Forecast model. Part II
Data impact. J. Geophys. Res., 96, C2, 2635-2649.
Andersson E., and H. Jarvinen, 1999: Variational quality control. Quart. J. Roy. Met. Soc.,
125, 697-722.
Alves O., M.A. Balmaseda, D.L.T. Anderson, and T. Stockdale, 2004: Sensitivity of
dynamical seasonal forecasts to ocean initial conditions. Quart. J. Roy. Met. Soc., 130,
647-668.
Balmaseda M.A., 2003: Ocean data assimilation for seasonal forecasts. In Recent
developments in data assimilation for atmosphere and ocean. Seminar Proceedings
ECMWF.
Bell M., M.J. Martin, and N.K.Nichols, 2004: Assimilation of data into an ocean model with
systematic errors near the equator. Quart. J. Roy. Met. Soc., 130, 873-893.
Burgers G., M.A. Balmaseda, F. Vossepoel, G.J van Oldenburgh, and P.J. van Leeuwen,
2002: Balanced ocean data assimilation near the equator. J. Phys. Ocean., 32, 2509-2519.
Courtier P., J-N Thepaut, and A. Hollingsworth, 1994: A strategy for operational
implementation of 4DVAR, using an incremental approach. Quart. J. Roy. Met. Soc., 120,
1367-1388.
Daley R., 1991: Atmospheric Data Analysis, Cambridge University Press, 457pp
moisture analysis. Mon. Wea. Rev., 128, 3268-3282.
Derber J., and F. Bouttier, 1998: A reformulation of the background error covariance in the
ECMWF global data assimilation system. Tellus 51A, 195-221.
Fisher M., 2005: On the equivalence between Kalman Smoothing and weak-constraint fourdimensional variational assimilation. Quart. J. Roy. Met. Soc., to appear. See also
ECMWF Tech Memo 447 available on line.
Haines K., J. Blower, J-P Drecourt, C. Liu, A. Vidard, I. Astin, and X. Zhou, 2005: Salinity
assimilation using S(T) relationships. Part 1: theory. Mon Wea. Rev., to appear.
Huddleston M.R., M.J. Bell, M.J. Martin, and N.K.Nichols, 2004: Assessment of wind stress
errors using bias-corrected ocean data assimilation. Quart. J. Roy. Met. Soc., 130, 853871.
Isaksen L., and A.C.M. Stoffelen, 2000: ERS scatterometer wind data impact on ECMWF's
tropical cyclone forecasts. IEEE Trans. Geosci. Remote Sens., 38, 4, 1,885-1,892.
Dee D.P., and A. Da Silva, 1998: Data assimilation in the presence of forecast bias. Quart.
J. Roy. Met. Soc., 124, A, 269-295.
Dee D.P., and R Todling, 2000: Data assimilation in the presence of forecast bias: the GEOS
DAVID ANDERSON ET AL
techniques for initializing coupled models combined with better models
suggest a busy time ahead.
Acknowledgements
The authors thank the members of the ECMWF analysis and medium
range and seasonal forecast groups for constructive discussions, and Graeme
Kelly and Federico Grazzini for providing figs 1 and 2 respectively. This
work was supported in part by ENACT EU-contract EVK2-2001-00077.
References
Anderson D.L.T., A. Hollingsworth, S. Uppala, and P. Worceshyn, 1991: A study of the use
of scatterometer data in the ECMWF Operational Analysis - Forecast model. Part II
Data impact. J. Geophys. Res., 96, C2, 2635-2649.
Andersson E., and H. Jarvinen, 1999: Variational quality control. Quart. J. Roy. Met. Soc.,
125, 697-722.
Alves O., M.A. Balmaseda, D.L.T. Anderson, and T. Stockdale, 2004: Sensitivity of
dynamical seasonal forecasts to ocean initial conditions. Quart. J. Roy. Met. Soc., 130,
647-668.
Balmaseda M.A., 2003: Ocean data assimilation for seasonal forecasts. In Recent
developments in data assimilation for atmosphere and ocean. Seminar Proceedings
ECMWF.
Bell M., M.J. Martin, and N.K.Nichols, 2004: Assimilation of data into an ocean model with
systematic errors near the equator. Quart. J. Roy. Met. Soc., 130, 873-893.
Burgers G., M.A. Balmaseda, F. Vossepoel, G.J van Oldenburgh, and P.J. van Leeuwen,
2002: Balanced ocean data assimilation near the equator. J. Phys. Ocean., 32, 2509-2519.
Courtier P., J-N Thepaut, and A. Hollingsworth, 1994: A strategy for operational
implementation of 4DVAR, using an incremental approach. Quart. J. Roy. Met. Soc., 120,
1367-1388.
Daley R., 1991: Atmospheric Data Analysis, Cambridge University Press, 457pp
moisture analysis. Mon. Wea. Rev., 128, 3268-3282.
Derber J., and F. Bouttier, 1998: A reformulation of the background error covariance in the
ECMWF global data assimilation system. Tellus 51A, 195-221.
Fisher M., 2005: On the equivalence between Kalman Smoothing and weak-constraint fourdimensional variational assimilation. Quart. J. Roy. Met. Soc., to appear. See also
ECMWF Tech Memo 447 available on line.
Haines K., J. Blower, J-P Drecourt, C. Liu, A. Vidard, I. Astin, and X. Zhou, 2005: Salinity
assimilation using S(T) relationships. Part 1: theory. Mon Wea. Rev., to appear.
Huddleston M.R., M.J. Bell, M.J. Martin, and N.K.Nichols, 2004: Assessment of wind stress
errors using bias-corrected ocean data assimilation. Quart. J. Roy. Met. Soc., 130, 853871.
Isaksen L., and A.C.M. Stoffelen, 2000: ERS scatterometer wind data impact on ECMWF's
tropical cyclone forecasts. IEEE Trans. Geosci. Remote Sens., 38, 4, 1,885-1,892.
Dee D.P., and A. Da Silva, 1998: Data assimilation in the presence of forecast bias. Quart.
J. Roy. Met. Soc., 124, A, 269-295.
Dee D.P., and R Todling, 2000: Data assimilation in the presence of forecast bias: the GEOS