AirNow and CAM-chem

First we need to import the driver.

from melodies_monet import driver

Please install h5py to open files from the Amazon S3 servers.
Please install h5netcdf to open files from the Amazon S3 servers.

# Needed if you want to make changes to `melodies_monet` and don't want to restart kernel:
%load_ext autoreload

%autoreload 2

Initiate the analysis class

Now lets create an instance of the melodies_monet.driver analysis class. It consists of 4 main parts: model instances, observation instances, a paired instance of both. This will allow us to move things around the plotting function for spatial and overlays and more complex plots.

an = driver.analysis()
an

analysis(
    control='control.yaml',
    control_dict=None,
    models={},
    obs={},
    paired={},
    start_time=None,
    end_time=None,
    download_maps=True,
    output_dir=None,
    debug=False,
)

Control File

Read in the required yaml control file that sets up all the definitions of what we want to pair and plot.

an.control = 'control_camchem.yaml'
an.read_control()
an.control_dict

Show code cell output Hide code cell output

{'analysis': {'start_time': '2019-09-01-00:00:00',
  'end_time': '2019-09-09-00:00:00',
  'output_dir': './output/camchem',
  'download_maps': False,
  'debug': False},
 'model': {'cam-chem': {'files': 'example:camchem:fv',
   'mod_type': 'cesm_fv',
   'radius_of_influence': 150000.0,
   'mapping': {'airnow': {'O3': 'OZONE'}},
   'projection': 'None',
   'plot_kwargs': {'color': 'dodgerblue', 'marker': '+', 'linestyle': '-.'}}},
 'obs': {'airnow': {'use_airnow': True,
   'filename': 'example:airnow:2019-09',
   'obs_type': 'pt_sfc',
   'variables': {'PM2.5': {'unit_scale': 1,
     'unit_scale_method': '*',
     'nan_value': -1.0,
     'ylabel_plot': 'PM2.5 (ug/m3)',
     'ty_scale': 2.0,
     'vmin_plot': 0.0,
     'vmax_plot': 22.0,
     'vdiff_plot': 15.0,
     'nlevels_plot': 23},
    'OZONE': {'unit_scale': 1,
     'unit_scale_method': '*',
     'nan_value': -1.0,
     'ylabel_plot': 'Ozone (ppbv)',
     'vmin_plot': 15.0,
     'vmax_plot': 55.0,
     'vdiff_plot': 20.0,
     'nlevels_plot': 21}}}},
 'plots': {'plot_grp1': {'type': 'timeseries',
   'fig_kwargs': {'figsize': [12, 6]},
   'default_plot_kwargs': {'linewidth': 2.0, 'markersize': 10.0},
   'text_kwargs': {'fontsize': 18.0},
   'domain_type': ['all', 'epa_region'],
   'domain_name': ['CONUS', 'R1'],
   'data': ['airnow_cam-chem'],
   'data_proc': {'rem_obs_nan': True,
    'ts_select_time': 'time',
    'ts_avg_window': 'H',
    'set_axis': False}},
  'plot_grp2': {'type': 'taylor',
   'fig_kwargs': {'figsize': [8, 8]},
   'default_plot_kwargs': {'linewidth': 2.0, 'markersize': 10.0},
   'text_kwargs': {'fontsize': 16.0},
   'domain_type': ['all', 'epa_region'],
   'domain_name': ['CONUS', 'R1'],
   'data': ['airnow_cam-chem'],
   'data_proc': {'rem_obs_nan': True, 'set_axis': True}},
  'plot_grp3': {'type': 'spatial_bias',
   'fig_kwargs': {'states': True, 'figsize': [10, 5]},
   'text_kwargs': {'fontsize': 16.0},
   'domain_type': ['all', 'epa_region'],
   'domain_name': ['CONUS', 'R1'],
   'data': ['airnow_cam-chem'],
   'data_proc': {'rem_obs_nan': True, 'set_axis': True}},
  'plot_grp4': {'type': 'spatial_overlay',
   'fig_kwargs': {'states': True, 'figsize': [10, 5]},
   'text_kwargs': {'fontsize': 16.0},
   'domain_type': ['all', 'epa_region'],
   'domain_name': ['CONUS', 'R1'],
   'data': ['airnow_cam-chem'],
   'data_proc': {'rem_obs_nan': True, 'set_axis': True}},
  'plot_grp5': {'type': 'boxplot',
   'fig_kwargs': {'figsize': [8, 6]},
   'text_kwargs': {'fontsize': 20.0},
   'domain_type': ['all', 'epa_region'],
   'domain_name': ['CONUS', 'R1'],
   'data': ['airnow_cam-chem'],
   'data_proc': {'rem_obs_nan': True, 'set_axis': False}}}}

Load the model data

The driver will automatically loop through the “models” found in the model section of the control file and create model classes for each. Classes include the label, mapping information, and xarray object as well as the filenames. Note it can open multiple files easily by including wildcards. Here we are only opening one CAM-chem file.

an.open_models()

Downloading data from 'https://csl.noaa.gov/groups/csl4/modeldata/melodies-monet/data/example_model_data/cesmfv_example/CAM_chem_merra2_FCSD_1deg_QFED_world_201909-01-09_small_sfc.nc' to file 'C:\Users\zmoon\AppData\Local\pooch\pooch\Cache\f57b114fb465b23ee998209b50df7d9d-CAM_chem_merra2_FCSD_1deg_QFED_world_201909-01-09_small_sfc.nc'.

cam-chem
{'files': 'example:camchem:fv', 'mod_type': 'cesm_fv', 'radius_of_influence': 150000.0, 'mapping': {'airnow': {'O3': 'OZONE'}}, 'projection': 'None', 'plot_kwargs': {'color': 'dodgerblue', 'marker': '+', 'linestyle': '-.'}}
example:camchem:fv
**** Reading CESM model output...

an.models

{'cam-chem': model(
     model='cesm_fv',
     radius_of_influence=150000.0,
     mod_kwargs={},
     file_str='example:camchem:fv',
     label='cam-chem',
     obj=...,
     mapping={'airnow': {'O3': 'OZONE'}},
     label='cam-chem',
     ...
 )}

an.models['cam-chem'].obj

<xarray.Dataset>
Dimensions:  (time: 36, z: 1, lat: 192, lon: 288)
Coordinates:
  * lat      (lat) float64 -90.0 -89.06 -88.12 -87.17 ... 87.17 88.12 89.06 90.0
  * z        (z) float64 992.5
  * lon      (lon) float64 0.0 1.25 2.5 3.75 5.0 ... 355.0 356.2 357.5 358.8
  * time     (time) datetime64[ns] 2019-09-01T06:00:00 ... 2019-09-10
Data variables:
    O3       (time, z, lat, lon) float32 dask.array<chunksize=(36, 1, 192, 288), meta=np.ndarray>
    PM25     (time, z, lat, lon) float32 dask.array<chunksize=(36, 1, 192, 288), meta=np.ndarray>
Attributes:
    Conventions:       CF-1.0
    source:            CAM
    case:              fmerra.2.1003.FCSD.f09.qfedcmip.56L.001.branch02
    logname:           buchholz
    host:              cheyenne3
    initial_file:      /glade/p/cesmdata/cseg/inputdata/atm/cam/inic/fv/f.e20...
    topography_file:   /glade/p/cesmdata/cseg/inputdata/atm/cam/met/MERRA2/0....
    model_doi_url:     https://doi.org/10.5065/D67H1H0V
    time_period_freq:  hour_6
    history:           Mon Feb 28 16:25:23 2022: ncks -7 -L 1 --baa=4 --ppc d...
    NCO:               netCDF Operators version 5.0.6 (Homepage = http://nco....

# All the info in the model class can be called here.
print(an.models['cam-chem'].label)
print(an.models['cam-chem'].mapping)

cam-chem
{'airnow': {'O3': 'OZONE'}}

# All the info in the analysis class can also be called.
print(an.start_time)
print(an.end_time)
print(an.download_maps)

2019-09-01 00:00:00
2019-09-09 00:00:00
True

Generate plots

%%time

an.plotting()

10 Figures

Figure 1

Figure 2

Figure 3

Figure 4

Figure 5

Figure 6

Figure 7

Figure 8

Figure 9

Figure 10

AirNow and CAM-chem

Initiate the analysis class

Control File

Load the model data

Open Obs

Pair model and obs data

Generate plots