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Summary of Discussion Points
1. Systematic bias
The model behavior toward elongating ENSO events (both cold and warm) in
time has also been seen in the past in the CFS hindcasts. When the initial state is, say, cold, the CFS tends to persist it and
misses the transition to warm. The same problem occurs in the opposite
transition direction. Figure 5 from an analysis of CFS hindcasts shows how cold states
and warm states tend to be overly persistent.
2.
Cases exploration
Figure 6 shows
Hovermoeller diagrams of SST along the equator in the Pacific for a case
study of the 1983 event for two different models, namely, CCSM on the
left and CFS on the right. The CCSM hindcast ensembles have been run
from real ocean initial states (MOM3 ODA) initialized with AMIP atmosphere and land initial states in Jan 1983. The OISSTv2 was used as verification for both CFS and CCSM
and the systematic error of both models has been corrected, based on the cases in the set
(19 cases for CCSM and 25 cases for CFS).
The two models
each have 8 panels with the observed (verification) in the upper left,
the ensemble mean in the upper right and six individual ensemble members
below. (The CFS picked the first six members
from its hindcast set
of
15
members.).
This
figure indicates that in the 1983 case, the CCSM did a more creditable job of
predicting the transition not only by the ensemble mean but also by
individual members.
Figure 7 is the same as Figure 6, except for the
1997 case with Jan 1997 ocean initial state. The CCSM also did a fairly
good job, although it underestimated the amplitude and displayed the
characteristic excessive westward propagation of anomaly phase that is a
systematic behavior of CCSM in ENSO events.
Since the
six
CFS members selected
by the designated way could be underrepresented, an additional check of the latest 10 members ensemble
mean was
made and shown in Figure 8. Again, the forecast held on to the initial
cold anomaly too much and significantly delayed the onset of El Nino.
Figure 9 shows
the CCSM predicted the transition from cold to warm in the middle of
2006. This admittedly limited set of results suggests that the
multi-model approach could be invaluable for the purpose of providing better
information to forecasters whose concern is, say, six-month lead
forecasts of ENSO that are used as guidance for hurricane and/or drought
outlooks
3. Prediction obstacle
One should not fault
CFS for not predicting a transition at all times. The plume diagrams of
Figure 10 show that CFS did a fine job when the initial states passed
the spring predictability barrier for the four years of 82, 83, 97 and
98. However, the critical point of such prediction obstacle can occur
in any seasons (such as that between July and August as well as that
between November and December in 2006). Besides, forecasts of weak
events continue to be difficult by any verification scores that are a
signal to noise ratio measure.
The weak El Nino of
last summer could be just something with a name to blame the failed
hurricane forecast on. There is more to it as
other researches
indicated.
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