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Figure 9.3 Sea-level
pressure patterns showing
the spatial structure of the
Southern Oscillation for
(a) ALO, (b) AO, (c) AL and
(d) A. See text for definition
of symbols. Contour interval
is 1mb. (Adapted from Lau
and Bua
1998
)
(a)
(b)
Spatial scale of SOI, ALO
Spatial scale of SOI, AO
90
N
90
N
60
N
60
N
30
N
30
N
EQ
EQ
30
S
30
S
60
S
60
S
0
60
E
120
E
180
120
W 0
W0
0
60
E
120
E
180
120
W 0
W0
(c)
(d)
Spatial scale of SOI, AL
Spatial scale of SOI, A
90
N
90
N
60
N
60
N
30
N
30
N
EQ
EQ
30
S
60
S
30
S
60
S
0
60
E
120
E
180
120
W 0
W0
0
60
E
120
E
180
120
W 0
W0
Exp-IV (A in Figure
9.3d
) suggest that there is an intrinsic inverse variation
of the tropical and extra-tropical atmospheres even in the absence of any
anomalous SST forcings.
If the objective is to examine the impact of a particular land surface
anomaly, such as snow cover, as a climate forcing, then it is possible to run
a new set of experiments in which the land and ocean forcing conditions can
be reversed. The design of the numerical experiments using climate models
will depend on the objectives of the experiments, and on the hypotheses being
tested.
9.2.4 Ensemble simulations
Given that atmospheric variations have a large chaotic component, it is
possible that even when forced by a specified lower boundary anomaly
such as SST, the atmosphere may respond differently depending on the initial
conditions. Often, the real climatic signals are obscured by the large varia-
bility due to internal dynamics of the atmosphere. Ensemble forecasts have
commonly been used in numerical long-range weather forecasts since the late
1980s to extend the lead time for useful forecasts and to evaluate the skill of
the forecasts using some measure of the spread among the ensemble members
(Hoffman and Kalnay
1983
; Palmer
1993
; Tracton et al.
1993
). To increase
the signal-to-noise ratio and to extend predictability, ensemble approaches
are increasingly being used in long-term climate simulations and projections
(Shukla et al.
2000
; Kawamura et al.
1998
). Typically, an ensemble climate
simulation calls for a set of control experiments and a set of anomalous
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