Hey,
Suppose we have additional data (they say we have it in here) for
the interpolation, how can i do that in a proper way? What kind of
interpolation is e.g. SCAT2GRID using? We need to know whether it
is taking into account the roughness, surface relief, statistical
linking between surface and variable, etc., dont we?
Someone suggested me to have a look at the method that Parry &
Carter, 1998 says (Parry, M. and T. Carter. 1998. Climate Impact
And Adaptation Assessment. London: Earthscan Publications Ltd.).
Have you heard of this?
Regards, Peter
On Thu, Jun 4, 2009 at 9:52 PM, Ryo Furue <furue@xxxxxxxxxx> wrote:
Hi Peter,
| it is not putting more information into the grid, but interpolates
| to a smoother one.
|
| I need an interpolation method which uses a surface and
interpolates
| the data onto it: suppose i have a data set which highest surface
| point for Hungary is around 400 metres. On a smoother resolution of
| a model the highest surface point is at 800 metres. And during the
| process an intelligent interpolation should take into account that
| the surface is not that same as it was in the coarse resolution
| data.
From your description, I can tell what result you want.
But, I can't tell what additional data you have.
Suppose we have a gridded topography map at a resolution
of 0.1 x 0.1. In it, the highest point of Hungary is 400m,
say. Can we convert it to a 0.01 x 0.01 map in which the
maximum altitude of Hungary is 800m? How do we know "800m"
is the desirable value? How do we know where that altitude
(800m) is located? We need an additional set of data
to modify the 0.1 x 0.1 topography.
To proceed, let me assume that you have some additional data
points:
lon lat altitude [m]
19.00 47.53 800
87.63 29.69 8848
37.36 -3.07 5891.8
. . . . . . . . . . .
You could convert your original 0.1 x 0.1 gridded data
into "station" data (scattered data), mix it with the
additional datapoints above, and regrid it, using
one of the SCAT2GRID functions.
This method may be highly inefficient. I hope there are
better ones.
Regards,
Ryo