Tuesday, 15 January 2002: 2:59 PM
How Well Can Ensemble Perturbations Explain Forecast Errors?
Ensemble forecast products from both NCEP and ECMWF are evaluated.
To study how much the forecast errors can be explained by the ensemble
perturbations, we compare the structures of forecast errors and the first
10 individual ensemble perturbations. For different forecast lead times,
the correlations between the forecast errors and the individual ensemble
perturbations are computed. In addition, the optimally combined perturbations
of the first 10 ensemble perturbations are computed and also compared with
the forecast errors. The structures of the residual vectors between
the optimally combined vectors and forecast errors are analyzed
to identify those dominant structures which cannot be explained by the
ensemble perturbations. The dependence of correlations on the number of
ensembles is studied for different lead times by using data from both
It is found that the performances of both ensemble forecast systems are
similar globally in most cases, with NCEP ensembles having slightly advantages during the
first 2 days in some cases. But after about 2 days, ECMWF ensembles have higher correlations
in some cases. For longer lead times, the correlations from both
systems are converging, indicating that both forecast errors and singular
vectors are converging to the dominant Lyapunov vector. In tropic region,
NCEP ensembles perform than better ECMEF's in most cases.