summary: I'd appreciate advice regarding tools and methods for
transforming netCDF gridded values from an unprojected global 3D
spatial "grid" to a projected 3D grid with different horizontal and
vertical resolution, or pointers to other resources to consult.
details:
I have output from a global atmospheric model that I'd like to use as
initial and boundary conditions for a regional model. The global input
netCDF has dimensions=2.5° lon x 1.875° lat x 56 vertical levels. The
regional model runs over North America using a 12-km grid projected
Lambert Comformal Conic (LCC), with 34 vertical levels. Since its top
height is less than that of the global input, the extents of the output
domain are fully contained within the input domain.
Each box or voxel defined by the global input grid contains an estimate
for the N2O concentration for that volume. From those I want to compute
the concentrations for each output gridbox volume. I'd appreciate your
recommendations for tools that can do this. The best tool I've seen so
far is R package=gstat, but (IIUC)
- gstat expects projected input. I'm not sure if I can work around that
for this usecase.
- as the name implies, 'gstat' is doing geostatistics, e.g., variogram-
and covariance-based modeling. I'm not sure either how to setup the
distance weighting for my scenario, and, frankly, I remain unconvinced
that a statistical approach is necessary for this application (though
it may be a sufficient or the best-available approach). This may be
due to my statistical ignorance, however.
your assistance is appreciated, Tom Roche <Tom_Roche@xxxxxxxxx>
