Conclusions:
Characteristics of bred vectors of CZ model:
o Bred vectors
have larger growth rate and more coherent spatial ENSO-like
structure between events.
o Bred vectors of CZ model have the largest growth rate in
the summer
season => “spring barrier”.
Application
in data assimilation:
o The ENSO forecast errors can be reduced as much as 30% when bred vectors are removed
from initial errors.
o
Within data assimilation cycles, this reduction of errors would accumulate to an even a larger
value.
Application
in ensemble forecasts:
o The ensemble forecasts with a pair of
“positive/negative” bred vectors
improve the skill significantly.
o “Spring
Barrier” is much less noticeable.