There are now a greater number of global coupled atmosphere-ocean models and
a number of them have been run for multi-century time-scales. This has substantially
improved the basis for estimating long time-scale natural unforced variability.
There are still severe limitations in the ability of such models to represent
the full complexity of observed variability and the conclusions drawn here about
changes in variability must be viewed in the light of these shortcomings (Chapter
Some new studies have reinforced results reported in the SAR. These are:
- The future mean Pacific climate base state could more resemble an El Niño-like
state (i.e., a slackened west to east SST gradient with associated eastward
shifts of precipitation). Whilst this is shown in several studies, it is not
true of all.
- Enhanced interannual variability of daily precipitation in the Asian summer
monsoon. The changes in monsoon strength depend on the details of the forcing
scenario and model.
Some new results have challenged the conclusions drawn in earlier reports,
- Little change or a decrease in ENSO variability. More recently, increases
in ENSO variability have been found in some models where it has been attributed
to increases in the strength of the thermocline. Decadal and longer time-scale
variability complicates assessment of future changes in individual ENSO event
amplitude and frequency. Assessment of such possible changes remains quite
difficult. The changes in both the mean and variability of ENSO are still
Finally there are areas where there is no clear indication of possible changes
or no consensus on model predictions:
- Although many models show an El Niño-like change in the mean state
of tropical Pacific SSTs, the cause is uncertain. In some models it has been
related to changes in cloud forcing and/or changes in the evaporative damping
of the east-west SST gradient, but the result remains model-dependent. For
such an El Niño-like climate change, future seasonal precipitation
extremes associated with a given ENSO would be more intense due to the warmer
mean base state.
- There is still a lack of consistency in the analysis techniques used for
studying circulation statistics (such as the AO, NAO and AAO) and it is likely
that this is part of the reason for the lack of consensus from the models
in predictions of changes in such events.
- The possibility that climate change may be expressed as a change in the
frequency or structure of naturally occuring modes of low-frequency variability
has been raised. If true, this implies that GCMs must be able to simulate
such regime transitions to accurately predict the response of the system to
climate forcing. This capability has not yet been widely tested in climate
models. A few studies have shown increasingly positive trends in the indices
of the NAO/AO or the AAO in simulations with increased greenhouse gases, although
this is not true in all models, and the magnitude and character of the changes
varies across models.