There is a lot of evidence for abrupt climate change - by definition
change that is disproportionate to the forcing - a nonlinear response
that is a characteristic of complex systems.  There are several good
resources - the NRC document Abrupt Climate Change: Inevitable
Surprises I quoted in the beginning is a readable and accessable
resource.

As for the distinction between weather and climate.  I have quoted
this before also.

'The global coupled atmosphere–ocean–land–cryosphere system exhibits a
wide range of physical and dynamical phenomena with associated
physical, biological, and chemical feedbacks that collectively result
in a continuum of temporal and spatial variability. The traditional
boundaries between weather and climate are, therefore, somewhat
artificial.

The large-scale climate, for instance, determines the environment for
microscale (1 km or less) and mesoscale (from several kilometers to
several hundred kilometers) processes that govern weather and local
climate, and these small-scale processes likely have significant
impacts on the evolution of the large-scale circulation.

The accurate representation of this continuum of variability in
numerical models is, consequently, a challenging but essential goal.
Fundamental barriers to advancing weather and climate prediction on
time scales from days to years, as well as longstanding systematic
errors in weather and climate models, are partly attributable to our
limited understanding of and capability for simulating the complex,
multiscale interactions intrinsic to atmospheric, oceanic, and
cryospheric fluid motions.'

A UNIFIED MODELING APPROACH TO CLIMATE SYSTEM PREDICTION

by James Hurrell, Gerald A. Meehl, David Bader, Thomas L. Delworth ,
Ben Kirtman, and Bruce Wielicki:  BAMS December 2009 | 1819: DOI:
10.1175/2009BAMS2752.1

I don't know what to say about the last glacial max. Models with fixed
ice sheets can't possibly be used for modelling glacial
conditions.

On Feb 2, 4:35 am, Phil Hays <[email protected]> wrote:
> On Mon, 2010-02-01 at 02:48 -0800, Robert Indigo Ellison wrote:
> > But a metaphor for what?  I know that global warming is involved
> > somewhere but I can’t quite make the connection.
>
> ...
>
> > There is a need to think in terms of total systems - difficult as
> > there are so many gaps in understanding and lack of data - rather than
> > trying to isolate a specific factor in a causative chain.  It is
> > useful to think in terms of climate shifts rather than global warming
> > necessarily.  I think it is helpful to have some understanding of
> > complex systems theory - as a metatheory, an organising principle, for
> > ideas about abrupt climate change.
>
> The connection is that both airflow over a wing is chaotic and climate
> is chaotic, yet meaningful causal statements can be made about both.
>
> As far as I understand it: Climate is usually weakly chaotic. It is,
> after all, just the average of weather. So there is clearly a limit to
> the short term accuracy of predictions. However, there is a lot of
> evidence that climate is not usually strongly chaotic, and thus longer
> term predictions are more reliable.
>
> Airflow over wings is usually weakly chaotic. Even in ideal conditions,
> 99% of the surface of the wing of the Wright Flyer had chaotic flow, aka
> turbulent flow. And in cases flying in turbulent air, often the case
> near the ground, 100% of the air flow on any wing can be turbulent. Yet
> that doesn't mean that complex system theory is needed to design an
> aircraft, or to fly one.
>
> > Although there are climate models their veracity has not been
> > demonstrated – they are best described as plausible.  The only
> > reasonable confirmation is in comparison with an untuned reality. It's
> > not looking real good at the moment.
>
> As for today's weather, exactly how closely could a climate model
> predict this year's weather? Where is the boundary between climate and
> weather?
>
> As for untuned reality, the cross check between models and the Last
> Glacial Maximum seems to me to be a fair confirmation.
>
> --
> Phil Hays <[email protected]>

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