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Chapter 19 - Operational seasonal prediction

Published online by Cambridge University Press:  03 December 2009

David L. T. Anderson
Affiliation:
European Centre for Medium-Range Weather Forecasts, Reading; Representing the ECMWF Seasonal Forecasting Section, Magdalena Balmaseda, Laura Ferranti, Tim Stockdale, Alberto; Troccoli, Kristian Mogensen, Arthur Vidard, Frederic Vitart
Tim Palmer
Affiliation:
European Centre for Medium-Range Weather Forecasts
Renate Hagedorn
Affiliation:
European Centre for Medium-Range Weather Forecasts
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Summary

At ECMWF, a seasonal forecast system has been operating for several years. This system is described and some results presented. The forecasts are made by fully coupled atmosphere ocean models covering the globe. A multimodel forecast system is also well advanced. This approach avoids to some degree the tendency for individual models to be too confident in their predictions. Model error is still a major issue and considerable effort is needed to improve the models.

Introduction

For several years now ECMWF has been running, operationally, a seasonal forecast suite. This consists of an ocean data assimilation system to provide initial conditions for the forecast, a fully coupled ocean–atmosphere model to create the forecast ensemble and a post-processing procedure to generate forecast products. This system is being generalised to include other coupled models and to produce multimodel products. In this chapter we will consider the various components of the forecasting system.

Weather forecasts have a limited forecast range on account of the chaotic nature of the atmosphere (see Lorenz, this volume); depending on what variable one seeks to predict and on what scale, the predictability horizon might be roughly ten days. Why then do we think we can predict climate months or even years ahead? The information on which the predictability of such long timescale processes is based cannot be simply atmospheric (Palmer and Anderson, 1994). The longer timescales come mainly from the ocean, which has a much larger heat capacity and slower dynamics than the atmosphere.

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Publisher: Cambridge University Press
Print publication year: 2006

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References

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  • Operational seasonal prediction
    • By David L. T. Anderson, European Centre for Medium-Range Weather Forecasts, Reading; Representing the ECMWF Seasonal Forecasting Section, Magdalena Balmaseda, Laura Ferranti, Tim Stockdale, Alberto; Troccoli, Kristian Mogensen, Arthur Vidard, Frederic Vitart
  • Edited by Tim Palmer, Renate Hagedorn
  • Book: Predictability of Weather and Climate
  • Online publication: 03 December 2009
  • Chapter DOI: https://doi.org/10.1017/CBO9780511617652.020
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  • Operational seasonal prediction
    • By David L. T. Anderson, European Centre for Medium-Range Weather Forecasts, Reading; Representing the ECMWF Seasonal Forecasting Section, Magdalena Balmaseda, Laura Ferranti, Tim Stockdale, Alberto; Troccoli, Kristian Mogensen, Arthur Vidard, Frederic Vitart
  • Edited by Tim Palmer, Renate Hagedorn
  • Book: Predictability of Weather and Climate
  • Online publication: 03 December 2009
  • Chapter DOI: https://doi.org/10.1017/CBO9780511617652.020
Available formats
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Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

  • Operational seasonal prediction
    • By David L. T. Anderson, European Centre for Medium-Range Weather Forecasts, Reading; Representing the ECMWF Seasonal Forecasting Section, Magdalena Balmaseda, Laura Ferranti, Tim Stockdale, Alberto; Troccoli, Kristian Mogensen, Arthur Vidard, Frederic Vitart
  • Edited by Tim Palmer, Renate Hagedorn
  • Book: Predictability of Weather and Climate
  • Online publication: 03 December 2009
  • Chapter DOI: https://doi.org/10.1017/CBO9780511617652.020
Available formats
×