A simple method for estimating variations in the predictability of ENSO
Article first published online: 2 SEP 2004
Copyright 2004 by the American Geophysical Union.
Geophysical Research Letters
Volume 31, Issue 17, September 2004
How to Cite
2004), A simple method for estimating variations in the predictability of ENSO, Geophys. Res. Lett., 31, L17205, doi:10.1029/2004GL020673., , and (
- Issue published online: 2 SEP 2004
- Article first published online: 2 SEP 2004
- Manuscript Accepted: 10 AUG 2004
- Manuscript Received: 3 JUN 2004
 Using a linear stochastic dynamical system, we further develop a recently proposed criteria of measuring variations in the predictability of ENSO. It is found that model predictability is intrinsically related to how the initial signal variance (ISV) projects on to its eigenmode space. When the ISV is large, the corresponding prediction is found to be reliable, whereas when the ISV is small, the prediction is likely to be less reliable. This finding was validated by results from a more realistic model prediction system for the period 1964–1998. A comparison of model skill and ISV for prediction made with and without data assimilation reveals that the role of data assimilation in improving model predictability may be mainly due to a further increase of ISV. Furthermore, model skill may result mainly from a few successful predictions associated with large ISV.