Climatic Change

, Volume 79, Issue 1–2, pp 31–63 | Cite as

Challenges posed by and approaches to the study of seasonal-to-decadal climate variability

  • Cornelia Schwierz
  • Christof Appenzeller
  • Huw C. Davies
  • Mark A. Liniger
  • Wolfgang Müller
  • Thomas F. Stocker
  • Masakazu Yoshimori
Original Article


The tasks of providing multi-decadal climate projections and seasonal plus sub-seasonal climate predictions are of significant societal interest and pose major scientific challenges. An outline is presented of the challenges posed by, and the approaches adopted to, tracing the possible evolution of the climate system on these various time-scales. First an overview is provided of the nature of the climate system’s natural internal variations and the uncertainty arising from the complexity and non-linearity of the system. Thereafter consideration is given sequentially to the range of extant approaches adopted to study and derive multi-decadal climate projections, seasonal predictions, and significant sub-seasonal weather phenomena. For each of these three time-scales novel results are presented that indicate the nature (and limitations) of the models used to forecast the evolution, and illustrate the techniques adopted to reduce or cope with the forecast uncertainty. In particular, the contributions (i) appear to exemplify that in simple climate models uncertainties in radiative forcing outweigh uncertainties associated with ocean models, (ii) examine forecast skills for a state-of-the-art seasonal prediction system, and (iii) suggest that long-lived weather phenomena can help shape intra-seasonal climate variability. Finally, it is argued, that co-consideration of all these scales can enhance our understanding of the challenges associated with uncertainties in climate prediction.


Climate Sensitivity North Atlantic Oscillation North Atlantic Oscillation Index Skill Score Multimodel Ensemble 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Science+Business Media, Inc. 2006

Authors and Affiliations

  • Cornelia Schwierz
    • 1
  • Christof Appenzeller
    • 2
  • Huw C. Davies
    • 1
  • Mark A. Liniger
    • 2
  • Wolfgang Müller
    • 2
    • 3
  • Thomas F. Stocker
    • 4
  • Masakazu Yoshimori
    • 4
    • 5
  1. 1.Institute for Atmospheric and Climate ScienceETH ZürichSwitzerland
  2. 2.Federal Office of Meteorology and Climatology (MeteoSwiss)MeteoSwissSwitzerland
  3. 3.MPI for MeteorologyHamburgGermany
  4. 4.Climate and Environmental Physics, Physics InstituteUniversity of BernBernSwitzerland
  5. 5.Center for Environmental PredictionRutgers UniversityRutgersUSA

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