Climate Dynamics

, Volume 19, Issue 7, pp 619–632 | Cite as

Sensitivity of seasonal climate forecasts to persisted SST anomalies

  •  L. Goddard
  •  S. Mason


Most estimates of the skill of atmospheric general circulation models (AGCMs) for forecasting seasonal climate anomalies have been based on simulations with actual observed sea surface temperatures (SSTs) as lower boundary forcing. Similarly estimates of the climatological response characteristics of AGCMs used for seasonal-to-interannual climate prediction generally rest on historical simulations using "perfect" SST forecasts. This work examines the errors and biases introduced into the seasonal precipitation response of an AGCM forced with persisted SST anomalies, which are generally considered to constitute a good prediction of SST in the first three-month season. The added uncertainty introduced by the persisted SST anomalies weakens, and in some cases nullifies, the skill of atmospheric predictions that is possible given perfect SST forcing. The use of persisted SST anomalies also leads to changes in local signal-to-noise characteristics. Thus, it is argued that seasonal-to-interannual forecasts using AGCMs should be interpreted relative to historical runs that were subject to the same strategy of boundary forcing used in the current forecast in order to properly account for errors and biases introduced by the particular SST prediction strategy. Two case studies are examined to illustrate how the sensitivity of the climate response to predicted SSTs may be used as a diagnostic to suggest improvements to the predicted SSTs.


General Circulation Model Atmospheric General Circulation Model Climate Response Seasonal Climate Climate Forecast 
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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© Springer-Verlag 2002

Authors and Affiliations

  •  L. Goddard
    • 1
  •  S. Mason
    • 2
  1. 1.International Research Institute for Climate Prediction, Lamont-Doherty Earth Observatory, Columbia University, Route 9W, Palisades, NY 10964, USA
  2. 2.Climate Research Division, Scripps Institution of Oceanography, University of California San Diego, La Jolla, CA 92093-0230, USA

Personalised recommendations