summary: I'd appreciate advice regarding tools and methods for transforming data attributed to voxels in an unprojected global grid onto a projected 3D grid with different horizontal and vertical resolution (or pointers to other resources to consult).
details: ESMF defines well (if somewhat oddly) the general problem: http://www.earthsystemmodeling.org/esmf_releases/public/ESMF_5_2_0rp1/ESMF_refdoc/node3.html#SECTION03020000000000000000 > Regridding, also called remapping or interpolation [or resampling], is > the process of changing the grid that underlies data values while > preserving qualities of the original data. ESMF seems to provide excellent tools for doing 2D regridding (or interpolating data values from the cells/pixels of one 2D/horizontal spatial grid to another), as does GRASS::r.proj http://grass.osgeo.org/grass64/manuals/html64_user/r.proj.html though I have not used either, and am quite new to GRASS. (My current personal favorite regridding tool is the R package 'raster': see code @ https://github.com/TomRoche/GEIA_to_netCDF/ ) However I'm not seeing tools for "reboxing," or interpolating data values from the boxes/voxels of one 3D/horizontal+vertical spatial grid to another. Am I missing something? I _do_ see (thanks, Doug Newcomb) raster3D http://grass.osgeo.org/grass64/manuals/html64_user/raster3D.html but I don't see r3 API that does what I want: I have output from a global atmospheric model that I'd like to use as initial/boundary conditions for a regional model. This unprojected "global input" (from the perspective of this usecase) netCDF has dimensions=2.5° lon x 1.875° lat x 56 vertical levels. The regional model covers North America using a 12-km grid projected LCC (Lambert Conic Comformal), with 34 vertical levels: details @ https://github.com/TomRoche/cornbeltN2O/wiki/AQMEII-North-American-domain#wiki-EPA The top height of the "regional output" is less than that of the global input; i.e., the input domain fully contains the output domain, in all 3 dimensions. Each box/voxel of the global input grid contains an estimate of its N2O concentration. From those data I want to compute the concentrations for each output box. 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. Is there a conservative projection over North America to which I could safely transform values from lon-lat (essentially via cropping?) in order to input them to gstat? - as the name implies, 'gstat' is doing geostatistical (variogram- and covariance-based) modeling. I'm not sure either how to setup the distance weighting for my usecase. I'm also unconvinced that a statistical approach is necessary for this usecase, though it may be a sufficient, or the best-available, approach; furthermore my position may just be a prejudice due to my statistical ignorance. TIA, Tom Roche <[email protected]> _______________________________________________ grass-user mailing list [email protected] http://lists.osgeo.org/mailman/listinfo/grass-user
