On Feb 9, 9:28*pm, Liam Steele wrote:
I know this forum is populated by various people with meteorology
backgrounds, so thought I'd ask here first...

For my PhD I am assimilating data into a general circulation model. Now
what I want to do is compare the assimilation result (a simple lat-lon
plot of whatever) with a lat-lon plot of the observations.

I can simply subtract one from the other to get a difference plot, but I
was wondering if there was a statistical way to compare the 'fit'
between two 2D plots? The model calculates the average rms error over
all lat-lon points, but this isn't very helpful, as one particularly bad
gridpoint can skew the whole result.

If you can give any helpful advice I shall endeavor to mention you in
the acknowledgements of my thesis. )

Many thanks,

--
Liam (Milton Keynes)http://physics.open.ac.uk/~lsteele/

Why not treat the assimilated version as a forecast? You can
construct various forecast scores averaged over spatial zones. We
often use ROCs but it depends what you want to test. Anything you
might do with a time series i.e. sequence of forecasts you can use
for a single event over space. You could use this to test the
improvement between different assimilation methods and different
assimilation starting points. I have no direct experience of working
in assimilation schemes but we look for skill in much that we do.

There is a good page on verification here.

http://www.cawcr.gov.au/projects/verification/


Andy