Re: using sea ice concentration as forcing


Subject: Re: using sea ice concentration as forcing
From: David Noone (dcn@gps.caltech.edu)
Date: Wed Nov 28 2001 - 16:55:18 MST


> > Now I want to do some simulations with CCM3.10, using sea ice
> > concentration as input data, which means I don't want the model to
> > calculate sea ice, but let it run under the force of sea ice. Now
> > the question is how I can input the sea ice file?

<snip>

> 3) Locate the Oro= .... AND other variables.
<snip>
> 6) Take the time variant boundary dataset (if I remember on the
> spot correctly): Apply the same Ascii procedure.
>
> Set at the appropriate data-points the temperature to -1.8.

<snip>

Be careful to recognize that using the DOM, ORO sets only the mask, and
not the concentration per se. In fact, CCM3.6 does not include a
parameterisation to consider the open water fraction of the ice pack.
Instead, the oro=2 (for sea ice) flag says "this ocean grid box is
covered in sea ice with a concentration of 100% and a thickness (sicthk)
of 2 meters". So in fact, it doesn't "calculate" the sea ice, it just
reads in temperature from the boundary data set and sets it as ice if
it's cold enough (flagged as ts < tsice, as Peter mentions in his step
6). I suppose you would define this mask based on your concentration
data.

To include the concentration itself, you will need to modify the source
to take account of both the ice covered part and the open water parts of
the ocean grid boxes. The easiest way might be you will need to call
BOTH flxoce and flxsice for the ice covered points, and weight the
resulting fluxes by the open water and ice covered fraction). While this
could be a trivial modification, you might also have to play around with
the ice thicknesses (when the concentration is, say, 15% you probably
don't expect it to be 2 meters thick). In this case you will need to
carry two extra time varying datasets with the appropriate interpolation
in the "advnce" routine (see sstini and sstint). This type of change
will alter the polar simulation, particularly the seasonality.

Cheers,

David

-- 

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