Folks,

This is a good first start, but ...

I am a big believer in specifying some very simple idealized experiments in
that I think these are often the easiest to analyze and the most
illuminating regarding system behavior.

It is often good to change one thing at a time so that it is easy to analyze
how the system responds to different perturbations.

I think it is also good to recognize that different people are doing
simulations in different kinds of models that include different kinds of
processes, and these different kinds of models have utility for different
kinds of applications.

So, I think it would describe a suite of experiments:

1. Step function change in atmospheric CO2 concentration.
2. Step function change in solar constant (perhaps decrease).
3. Combined step function change in atmospheric CO2 concentration + solar
constant (= 1+2)
4. Step function change in specified aerosols distribution and
concentrations
5. Combined step function change in atmospheric CO2 concentration and
aerosol distribution and concentration (=1 + 4)
6. Unit pulse of stratospheric aerosol emissions
7. Step function change in stratospheric aerosol emissions (ie, continuous
emissions)
8. Combined step function change in atmospheric CO2 concentration and
aerosol emissions (=1+7)

Following these I would have the experiments described in the document that
Alan sent around. Groups could do as many of these as that are relatively
easy to do.

In analyzing the differences between the more complex runs, these simpler
runs will prove extremely useful. For example, it will show whether the
differences in the model response is due to model response to a specified
aerosol distribution or whether the difference is because the model produces
a different distribution from the same emissions.

This will also allow groups who are unable to do the full suite of runs to
at least do these simplified experiments to allow a common basis for
comparison of a broader range of models.

Also, a major piece missing from the document is the specification of what
model output is required.

Before going too far with this, I would consult with people from PCMDI who
were involved in analyzing AR4 results, and I would also consult with Jim
Orr who led the ocean carbon-cycle model intercomparison program (OCMIP).
One problem with C4MIP (the coupled carbon climate MIP) is that not enough
data was collected from each group to allow for adequate analysis of
results.

I believe that it is often the simplest simulations that teach you the most.


Best,

Ken





___________________________________________________
Ken Caldeira

Carnegie Institution Dept of Global Ecology
260 Panama Street, Stanford, CA 94305 USA

[email protected]
http://dge.stanford.edu/DGE/CIWDGE/labs/caldeiralab
+1 650 704 7212; fax: +1 650 462 5968




On Tue, Dec 8, 2009 at 1:46 AM, Alan Robock <[email protected]>wrote:

> Dear All,
>
> After extensive discussion of our original proposal by email and at a
> geoengineering workshop in Hamburg a week ago, I attach our final
> proposal for standardized geoengineering experiments.  As Atm. Research
> Letters will have a special geoengineering issue, we have written it for
> possible submission.
>
> In any case, I hope this will allow climate modeling groups and others
> to look at it and comment, and we welcome all such comments.
>
> Alan
>
> Alan Robock, Professor II
>   Director, Meteorology Undergraduate Program
>   Associate Director, Center for Environmental Prediction
> Department of Environmental Sciences        Phone: +1-732-932-9800 x6222
> Rutgers University                                  Fax: +1-732-932-8644
> 14 College Farm Road                   E-mail: [email protected]
> New Brunswick, NJ 08901-8551  USA      
> http://envsci.rutgers.edu/~robock<http://envsci.rutgers.edu/%7Erobock>
>
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