ESSAY: Model interpretation of climate signals: an application to the Asian monsoon climate - The Global Climate System: Patterns, Processes, and Teleconnections - page 304

Figure 9.7 Pattern
correlation of ensemble
anomalies of each model
over the ENSO-monsoon
domain (y-axis) vs. that of
the corresponding
climatology (x-axis) for the
1997 summer (open circle)
and 1997-8 winter (dark
circle) seasons. (b) As in (a),
except for the normalized
rms.

(a) (b)

1

1.8

CMAP

DJF9798 Composite
DJF97/98 each model
JJA97 Composite
JJA97 each model

1.6

1.4

0.8

1.2

1

0.6

0.8

0.6

0.4 0.4

0.4 0.6 0.8 1 0.4 0.6 0.8 1

Climatology

1.2 1.4 1.6 1.8

Climatology

anomalies in the Indo-Pacific region. This is expected, because the all-model
mean is derived from a large number (in this case, for 10 models and 10 members
per ensemble, 10 10 ¼ 100) of model realizations, while the observation is just
a one-time realization of the real system. In all, the multi-model ensemble mean
provides a simulation with more reliability and skill comparable to the top
performing models. Other more sophisticated ensemble means, such as the
super-ensemble procedure, can produce simulations with skills that exceed all
the individual models (Krishnamurti et al. 2000 ).
Another important finding of MMIP is that models which can simulate a
realistic climatology generally have better skill in simulating interannual
variability. Figure 9.7a shows scatter plots of the climatological pattern corre-
lation vs. the anomaly pattern correlation of rainfall of the models with respect
to observations over the Indo-Pacific region. Figure 9.7b shows the same, but
for R rms . The climatological quantity is a measure of how good the models are
in simulating the annual cycle, and the anomaly, of how well the models
simulate interannual variability. Prediction skills are based on the ability of
the models to simulate the interannual anomalies above and beyond those
provided by the climatology. The positive slope of the regression lines in
Figure 9.7a and b suggests that a good simulation of climatology generally
implies a good simulation of the interannual anomaly. A model that has a good
climatology is an indication that the physical and dynamical processes are well
represented, and therefore provides some assurance that the model may be used
for climate anomaly predictions on interannual or longer time scales.

9.3.3 Response to 1997-8 ENSO
Intercomparison of the simulations of the impact of the 1997-8 El Ni˜o
indicates that AGCMs generally simulate reasonably well the eastward shift