Regridding

GCPy currently supports regridding of data from:

GEOS-Chem Classic restart files
GEOS-Chem Classic diagnostic files
GCHP restart files
GCHP diagnostic files
HEMCO restart files
HEMCO diagnostic files
As well as any netCDF file adhering to COARDS or CF conventions.

Regridding is supported across any horizontal resolution and any grid type available in GEOS-Chem, including lat/lon (global or non-global), global standard cubed-sphere, and global stretched-grid. GCPy also supports arbitrary vertical regridding across different vertical resolutions.

Regridding with GCPy is currently undergoing an overhaul. As of the current release, regridding is split into two different categories:

Regridding between lat-lon grids using regridding weights computed on the fly by GCPy, and
Regridding either lat-lon or cubed-sphere using regridding weights computed as a preprocessing step.

The latter method may be used for creating GCHP standard grid and stretched grid restart files from either GCHP or GEOS-Chem Classic restart files.

Using Online Regridding Weights

You can regrid existing GEOS-Chem restart or diagnostic files using GCPy function gcpy.file_regrid(). This function can called directly from the command line or from within a Python script, as shown in the (examples) below.

Note

For regridding to or from GCHP stretched-grid restart files, we recommend using the offline regridding weights method.

For a list of input arguments, see gcpy.file_regrid() in the API reference section.

Examples

Regrid a 4x5 GEOS-Chem Classic restart or diagnostic file to a GEOS-Chem Classic 2x2.5 file:

$ conda activate gcpy_env
(gcpy_env) $ python -m gcpy.file_regrid   \
  --filein         /path/to/file_4x5.nc4  \
  --dim_format_in  classic                \
  --fileout        /path/to/file_2x25.nc4 \
  --ll_res_out     2x2.5                  \
  --dim_format_out classic

Regrid a 4x5 GEOS-Chem Classic restart or diagnostic file to a GCHP C24 restart file:

$ conda activate gcpy_env
(gcpy_env) $ python -m gcpy.file_regrid   \
  --filein         /path/to/file_4x5.nc4  \
  --dim_format_in  classic                \
  --fileout        /path/to/file_c24.nc4  \
  --cs_res_out     24                     \
  --dim_format_out checkpoint

Regrid a GCHP C48 restart file to a GCHP stretched grid C48 restart file. The stretch parameters are:

stretch-factor: 5
target-longitude: -72
target-latitude: 41

$ conda activate gcpy_env
(gcpy_env) $ python -m gcpy.file_regrid      \
  --filein         /path/to/file_c48.nc4     \
  --dim_format_in  checkpoint                \
  --fileout        /path/to/file_c48_sg.nc4  \
  --cs_res_out     48                        \
  --dim_format_out checkpoint                \
  --sg_params_out  5 -72 41

Regrid the GCHP stretched grid C48 restart file from Example 3 above to a GCHP C24 diagnostic file.

$ conda activate gcpy_env
(gcpy_env) $ python -m gcpy.file_regrid      \
  --filein         /path/to/file_c48_sg.nc4  \
  --sg_params_in   5 -72 41                  \
  --dim_format_in  checkpoint                \
  --fileout        /path/to/file_c24.nc4     \
  --cs_res_out     24                        \
  --dim_format_out diagnostic

Same example as above, but implemented within a Python script rather than from the comamnd line.

from gcpy.file_regrid import file_regrid

file_regrid(
  "/path/to/file_c48_sg.nc4",   # filein
  "/path/to/file_c24.nc4",      # fileout
  "checkpoint",                 # dim_format_in
  "diagnostic",                 # dim_format_out
  sg_params_in=[5, -72, 41],
  cs_res_out=24,
)

Using Offline Regridding Weights

This approach requires generating regridding weights using python packages gridspec and sparselt, which are included with the GCPy Python environment.

Regridding with GCPy, gridspec and sparselt is a three stage process:

Create grid specifications for the source and target grids using gridspec.
Create regridding weights for the transformation using ESMF_RegridWeightGen.
Run the regridding operation using the gcpy.regrid_restart_file() submodule of GCPy.

Example 1: Standard Lat-Lon to Cubed-Sphere Regridding

This example will show regridding a GC-Classic 4x5 restart file to a GCHP c24 restart file.

Activate your GCPy environment.

$ conda activate gcpy_env  # Or whatever your environment's name is

Create a lat-lon source grid specification using gridspec-create.
```
$ gridspec-create latlon --pole-centered --half-polar 46 72
```
This will produce 1 file: regular_lat_lon_46x72.nc.
Create a target grid specification using gridspec-create.
```
$ gridspec-create gcs 24
```
This will produce 7 files: c24_gridspec.nc and c24.tile[1-6].nc

Create the regridding weights for the regridding transformation (46x72 to C24) using ESMF_RegridWeightGen.

$ ESMF_RegridWeightGen                   \
  --source      regular_lat_lon_46x72.nc \
  --destination c24_gridspec.nc          \
  --method      conserve                 \
  --weight      46x72_to_c24_weights.nc

This will produce a log file, PET0.RegridWeightGen.Log, and our regridding weights, 46x72_to_c24_weights.nc

Use the grid weights produced in previous steps to complete the regridding.
```
$ python -m gcpy.regrid_restart_file          \
  GEOSChem.Restart.20190701_0000z.nc4         \
  46x72_to_c24_weights.nc                     \
  GEOSChem.Restart.20190701_0000z.c24_old.nc4
```
(Click on gcpy.regrid_restart_file() for a list of input and output arguments to the function.)

In this example (lat-lon to cubed-sphere) we need to use a GEOS-Chem Classic restart file as the file to be regridded and a GCHP restart file as the template file.

Note

The resolution of the template file does not matter as long as it contains all of the variables and attributes that you wish to include in the regridded restart file.

After running gcpy.regrid_restart_file(), a single restart file named new_restart_file.nc will be created. You can rename this file and use it to initialize your GCHP C24 simulation.
Deactivate your GCPy environment when finished.
```
$ conda deactivate
```

Example 2: Standard Cubed-Sphere to Cubed-Sphere Regridding

We will use the example of regridding the out-of-the-box GEOSChem.Restart.20190701_0000z.c48.nc4 restart file from C48 to C60 to demonstrate the standard cubed-sphere regridding process:

Activate your GCPy environment.

$ conda activate gcpy_env  # Or whatever your environment's name is

Create a source grid specification using gridspec-create.
```
$ gridspec-create gcs 48
```
This will produce 7 files: c48_gridspec.nc and c48.tile[1-6].nc
Create a target grid specification using gridspec-create.
```
$ gridspec-create gcs 60
```
Again, this will produce 7 files: c60_gridspec.nc and c60.tile[1-6].nc

Create the regridding weights for the regridding transformation (C48 to C60) using ESMF_RegridWeightGen.

$ ESMF_RegridWeightGen               \
  --source      c48_gridspec.nc      \
  --destination c60_gridspec.nc      \
  --method      conserve             \
  --weight      c48_to_c60_weights.nc

This will produce a log file, PET0.RegridWeightGen.Log, and our regridding weights, c48_to_c60_weights.nc

Use the grid weights produced in earlier steps to complete the regridding.
```
$ python -m gcpy.regrid_restart_file      \
  GEOSChem.Restart.20190701_0000z.c48.nc4 \
  c48_to_c60_weights.nc                   \
  GEOSChem.Restart.20190701_0000z.c48.nc4
```
(Click on gcpy.regrid_restart_file() to see its input and output arguments.)

Because we are regridding from one cubed-sphere grid to another cubed-sphere grid, we can use the file to be regridded as the template file.

After running gcpy.regrid_restart_file(), a single restart file named new_restart_file.nc will be created. You can rename this file as you wish and use it for your GCHP C60 simulation.
Deactivate your GCPy environment when you have finished.
```
$ conda deactivate
```

Example 3: Standard to Stretched Cubed-Sphere Regridding

This example regrids the out-of-the-box c48 restart file (GEOSChem.Restart.20190701_0000z.c48.nc4) from a standard cubed-sphere grid to a stretched grid. The base resolution will remain the same at c48. The regridded file will have a stretch factor of 4.0 over Bermuda which means a regional grid resolution of c196 (4 times 48) in that area.

Activate your GCPy environment:

$ conda activate gcpy_env  # Or whatever your environment's name is

Create a source grid specification using gridspec-create.
```
$ gridspec-create gcs 48
```
This will produce 7 files: c48_gridspec.nc and c48.tile[1-6].nc
Create a target grid specification using gridspec-create. This will be for the stretched grid.
```
$ gridspec-create sgcs 48 -s 4.0 -t 32.0 -64.0
```
Here, the -s option denotes the stretch factor and the -t option denotes the latitude / longitude of the centre point of the grid stretch.

Again, this will produce 7 files: c48_..._gridspec.nc and c48_..._tile[1-6].nc, where ... denotes randomly generated characters. Be sure to look for these since you will need them in the next step.

Create the regridding weights for the regridding transformation (C48 to C48-stretched) using ESMF_RegridWeightGen, replacing c48_..._gridspec.nc with the actual name of the file created in the previous step. An example is shown below.

$ ESMF_RegridWeightGen                              \
  --source      c48_gridspec.nc                     \
  --destination c48_s4d00_tdtdqp9ktebm5_gridspec.nc \
  --method      conserve                            \
  --weight      c48_to_c48_stretched_weights.nc

This will produce a log file, PET0.RegridWeightGen.Log, and our regridding weights, c48_to_c48_stretched_weights.nc

Use the grid weights produced in earlier steps to complete the regridding.
```
$ python -m gcpy.regrid_restart_file       \
   --stretched-grid                        \
   --stretch-factor 4.0                    \
   --target-latitude 32.0                  \
   --target-longitude -64.0                \
   GEOSChem.Restart.20190701_0000z.c48.nc4 \
   c48_to_c48_stretched_weights.nc         \
   GEOSChem.Restart.20190701_0000z.c48.nc4
```
(Click on gcpy.regrid_restart_file() to see its input and output arguments.)

Because we are regridding from one cubed-sphere grid to another cubed-sphere grid, we can use the file to be regridded as the template file.

This will produce a single file, new_restart_file.nc, regridded from C48 standard to C48 stretched with a stretch factor of 4.0 over 32.0N, -64.0E, that you can rename and use as you please.
Tip

It is generally a good idea to rename the file to include the grid resolution, stretch factor, and target lat/lon for easy reference. You can copy it somewhere to keep long-term and link to it from the GCHP Restarts subdirectory in the run directory.
```
$ mv new_restart_file.nc GEOSChem.Restart.20190701_0000z.c120.s4_32N_64E.nc
```
You can also easily reference the file’s stretch parameters by looking at the global attributes in the file. When using the file as a restart file in GCHP make sure that you use the exact same parameters in both the file’s global attributes and GCHP configuration file setCommonRunSettings.sh.
Deactivate your GCPy environment when you have finished.
```
$ conda deactivate
```

Regridding for Plotting in GCPy

When plotting in GCPy (e.g. through gcpy.plot.compare_single_level() or gcpy.plot.compare_zonal_mean()), the vast majority of regridding is handled internally. You can optionally request a specific horizontal comparison resolution in gcpy.plot.compare_single_level() and gcpy.plot.compare_zonal_mean(). Note that all regridding in these plotting functions only applies to the comparison panels (not the top two panels which show data directly from each dataset). There are only two scenarios where you will need to pass extra information to GCPy to help it determine grids and to regrid when plotting.

Pass stretched-grid file paths

Stretched-grid parameters cannot currently be automatically determined from grid coordinates. If you are plotting stretched-grid data in gcpy.plot.compare_single_level() or gcpy.plot.compare_zonal_mean() (even if regridding to another format), you need to use the sg_ref_path or sg_dev_path arguments to pass the path of your original stretched-grid restart file to GCPy. If using gcpy.plot.single_panel(), pass the file path using sg_path. Stretched-grid restart files created using GCPy contain the specified stretch factor, target longitude, and target latitude in their metadata. Currently, output files from stretched-grid runs of GCHP do not contain any metadata that specifies the stretched-grid used.

Pass vertical grid parameters for non-72/47-level grids

GCPy automatically handles regridding between different vertical grids when plotting except when you pass a dataset that is not on the typical 72-level or 47-level vertical grids. If using a different vertical grid, you will need to pass the corresponding grid parameters using the ref_vert_params or dev_vert_params keyword arguments.

Automatic regridding decision process

When you do not specify a horizontal comparison resolution using the cmpres argument in gcpy.plot.compare_single_level() and gcpy.plot.compare_zonal_mean(), GCPy follows several steps to determine what comparison resolution it should use:

If both input grids are lat/lon, use the highest resolution between them (don’t regrid if they are the same resolution).
Else if one grid is lat/lon and the other is cubed-sphere (standard or stretched-grid), use a 1x1.25 lat/lon grid.
Else if both grids are cubed-sphere and you are plotting zonal means, use a 1x1.25 lat/lon grid.
Else if both grids are standard cubed-sphere, use the highest resolution between them (don’t regrid if they are the same resolution).
Else if one or more grids is a stretched-grid, use the grid of the ref dataset.

For differing vertical grids, the smaller vertical grid is currently used for comparisons.