Regional climatemodelling 107A good place to look for further evidence is in the record of cli-
mates of the past, presented in Chapter 4. Correlation between the
Milankovitch cycles in the Earth’s orbital parameters and the cycles
of climate change over the past half million years (see Figures 4.4 and
5.19) provides strong evidence to substantiate the Earth’s orbital varia-
tions as the main factor responsible for the triggering of climate change.
The nature of the feedbacks which control the very different amplitudes
of response to the three orbital variations still need to be understood.
Some 60±10% of the variance in the record of global average tem-
perature from paleontological sources over the past million years occurs
close to frequencies identified in the Milankovitch theory. The exis-
tence of this surprising amount of regularity suggests that the climate
system is not strongly chaotic so far as these large changes are con-
cerned, but responds in a largely predictable way to the Milankovitch
forcing.
This Milankovitch forcing arises from changes in the distribution
of solar radiation over the Earth because of variations in the Earth’s
orbit. Changes in climate as a result of the increase of greenhouse gases
are also driven by changes in the radiative regime at the top of the
atmosphere. These changes are not dissimilar in kind (although different
in distribution) fromthe changes that provide the Milankovitch forcing.
It can be argued therefore that the increases in greenhouse gases will
also result in a largely predictable response.
Regional climate modelling
The simulations we have so far described in this chapter are with global
circulation models (GCM) that typically possess a horizontal resolu-
tion (grid size) of around 300 km – the size being limited primarily by
the availability of computer power. Weather and climate on scales large
compared with the grid size are described reasonably well. However, at
scales comparable with the grid size, described as the regional scale,^23
the results fromglobal models possess serious limitations. The effects
of forcings and circulations that exist on the regional scale need to be
properly represented. For instance, patterns of precipitation depend crit-
ically on the major variations in orography and surface characteristics
that occur on this scale (see Figure 5.24). Patterns generated by a global
model therefore will be a poor representation of what actually occurs on
the regional scale.
To overcome these limitations regional modelling techniques have
been developed.^24 That most readily applicable to climate simulation
and prediction is theRegional Climate Model(RCM). A model covering
an appropriate region at a horizontal resolution of say 25 or 50 km can