cc: wg1-ar4-ch06@joss.ucar.edu
date: Wed, 12 Jan 2005 16:04:23 +0100
from: Stefan Rahmstorf <rahmstorf@pik-potsdam.de>
subject: Re: [Wg1-ar4-ch06] Bullet points for the executive summary for
to: David Rind <drind@giss.nasa.gov>

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Dear David,

now we're talking science; that's good. I appreciate that for 
atmospheric dynamics, the effects you are talking about are the 
first-order effects. How well any attempts to parameterise these effects 
work has to be judged by the results, e.g., the comparison of a 
parameterisation with data and with results from more comprehensive 
models. How well, for example, a model like CLIMBER2 performs in this 
respect is documented in the published literature. The results for 
large-scale features (e.g., zonal averages and the like), which we are 
aiming for, lie generally within the range of GCM simulations. And this 
is not the result (as is a common prejudice amongst the GCM friends) of 
some illegitimate "tuning" practise - this is all discussed in detail in 
the papers. If a scientist like Peter Stone didn't succeed, I have all 
the more respect for my Russian colleagues who were more successful in 
tackling this problem (it also took them most of their career).
The next question then is to what accuracy you need to resolve a 
specific process to study a particular problem. If you want to study how 
a tsunami spreads, you can obviously forget about all the atmospheric 
dynamics, as it plays no role. This is not a climate problem of course, 
but I would argue that there are also many climate problems in which 
atmospheric dynamics is not the prime mechanism, and for which you don't 
need to resolve atmospheric dynamics except that you need to get some 
very basic feedbacks and responses (e.g., how Hadley cells shift and 
change in strength), which a parameterised version can give you to an 
acceptable level of accuracy. If that was not the case, EMICs would be 
useless, of course.

Cheers, Stefan

-- 
Stefan Rahmstorf
www.ozean-klima.de
www.realclimate.org

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