MICS to CMAQ

MICS.ipynb

A quick remind
If you are using different machines beyond google colab, different installation methods or versions of CDO could make "cdoo.remapycon" or "cdoo.gridarea" not working. The CDO version on Ubuntu with Colab is 1.9.3 and python3-CDO 1.3.5 here.

If you can't install old-version CDO like 1.9.3, the recent version of CDO I have tested is CDO 2.0.3 using conda.
Several changes to match original code with CDO 2.0.3

1. install cdo bundle:
   I suggest to create a new conda env for cdo so it won't have unexpected bugs happening for conda
   conda create -n cdo
   conda install -c conda-forge cdo python-cdo xarray

2. make sure you also install other required packages for running this gist.
   Pseudonetcdf
   pyproj

3. Now you don't have to use python-cdo interface, you can comment out like
   #import cdo
   #cdoo = cdo.Cdo(cdopath)

4. Change cdoo code
   change
   cdoo.remapycon(f'{dom}.grid', input=fluxpath, output=regridpath, returnCdf=False)
   to
   os.system(f'cdo remapycon,grid.{domain} {fluxpath} {regridpath}')

change
cdoo.gridarea(f'-O -remapnn,{dom}.grid -stdatm,0', options='-f nc', output=areapath, returnCdf=True)
to
os.system(f'cdo -O -f nc -gridarea -remapnn,grid.{domain} -stdatm,0 ../outputs/{domain}/flux_regrid/area.nc')

5. Instead of creating "Projection" variable in remapped files, newer version CDO like CDO 2.0.3 here will output "crs". You also need to change code
   if k in ('time', 'lat', 'lon', 'x', 'y', 'Projection')
   to
   if k in ('time', 'lat', 'lon', 'x', 'y', 'crs')

Dear @barronh ,

I'm using eta_levels in WRF :

1.000, 0.995, 0.985, 0.979, 0.973,
0.967, 0.960, 0.954, 0.949, 0.941,
0.934, 0.925, 0.917, 0.907, 0.897,
0.887, 0.878, 0.866, 0.855, 0.844,
0.832, 0.806, 0.778, 0.764, 0.749,
0.718, 0.687, 0.654, 0.623, 0.590,
0.559, 0.526, 0.495, 0.462, 0.431,
0.398, 0.367, 0.334, 0.304, 0.272,
0.244, 0.213, 0.187, 0.155, 0.120,
0.090, 0.065, 0.040, 0.015, 0.000

And I would like to make 17 vertically allocated emissions. Is it possible to allocate emissions on different vertical grid?

I know I should not simply interpolate the vertical fractions to my eta_levels. But, I don't know a mathematical keyword to obtain new fractions on the new vertical grid.

I've obtained the new fractions on my eta_levels by replacing layerfractions with :

layerfractions = pd.read_csv(io.StringIO("""L,SigmaTop,PPCB,PROT
1,0.995,0.00,0.06
2,0.985,0.066,0.26
3,0.979,0.067,0.34
4,0.973,0.067,0.34
5,0.967,0.1,0.0
6,0.960,0.1,0.0
7,0.954,0.1,0.0
8,0.949,0.05,0.0
9,0.941,0.05,0.0
10,0.934,0.05,0.0
11,0.925,0.05,0.0
12,0.917,0.05,0.0
13,0.907,0.05,0.0
14,0.897,0.05,0.0
15,0.887,0.05,0.0
16,0.878,0.05,0.0
17,0.866,0.05,0.0
"""), comment='#')

I distributed original fraction to new level properly, and the sum of fractions is 1.

I have one question regarding the area source of MICS-Asia RESIDENTIAL, TRANSPORT, and AGRICULTURE.
In [23], the area sources are allocated on the second vertical grids. But, the first vertical grid has also height (35m). So should be the area sources allocated on the first vertical grids?
Thank you.

I'm glad you figured it out.

You're right about the layers. When it was first made, I think that L was the index. In this version, however, the index is a zero-based value. You should change all of those to layerfractions.loc[0, '...'] = 1. I updated the notebook.

Thank you for response.