[MITgcm-devel] (not so) funny things happen in seaice_lsr and pickups
Jinlun Zhang
zhang at apl.washington.edu
Wed Feb 18 11:42:34 EST 2009
Martin,
Have you tried LSR on B-grid with the bug fixed, just for a comparison?
Good luck, Jinlun
Martin Losch wrote:
> Hi all,
>
> just to let you know that we are experiencing problems with the LSR
> sea ice solver on the C-grid: At unpredictable points of the
> integration, it appears to become instable and blows up. I have not
> been able to isolate this in all cases, because a small issue with
> pickups hampers this:
>
> Apparently, starting from pickup is NOT exact. We have tried the
> famous 2+2=4 test with our 8CPU job on our SX8 (cc to Olaf, who's been
> mostly involved in this) and found no difference between the cg2d
> output (and other output). However, when we run an experiment for a
> longer time, the same test fails, e.g., 2160+2160 != 4320 (we can
> provide plots if required). I assume that this is expected, because
> double precision is not more than double precisioin and in the cg2d
> output (and other monitor output) there are always only 15 digits, and
> we don't know about the 16th one, correct? Anyway, this tiny pickup
> issue hinders me from approaching the point of model crash with
> pickups, because after starting from a pickup, the model integrate
> beyond the problem and crashes (sometimes) at a much later time. This
> is to say, that the problem in seaice_lsr (the problem only appears
> when the C-LSR solver is used) very sensitive; the code crashes
> without any warning from one time step to the other. A while ago, in a
> different case I was able to get close enough the point of crashing to
> do some diagnostics, but its almost impossible to identify, why the
> model explodes. I am assuming that for random pathological cases one
> or more matrix entries are nearly zero, which then prevents the solver
> from converging.
>
> Any comments? Any similar experience?
>
> I run this code in so many different configurations, and I have these
> problems only very seldom/randomly, so I am a little at a loss where I
> should continue looking, so any hint is appreciated.
>
> Martin
>
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