CarbonMonitor/netcdf CarbonMonitor/netcdf

CarbonMonitor/netcdf CarbonMonitor/netcdf#

Description#

Carbon Monitor near-real-time gridded emission data.

Reads Carbon Monitor’s gridded emissions, mapped onto its 8 native sectors (Agriculture, Energy, Industrial, Transportation, Residential/Commercial/ Other, Solvents, Waste, International Shipping). Each sector is remapped to its corresponding TNO GNFR category to apply an hourly time profile read from the GNFR profile CSVs.

Unlike most other flux plugins in this package, the horizontal domain is not read from a reference file: it is a synthetic, configurable regular lon/lat grid defined purely from the lon_min/lon_max/lat_min/lat_max/ nlon/nlat input arguments.

Writing is not implemented for this plugin.

YAML arguments#

The following arguments are used to configure the plugin. pyCIF will return an exception at the initialization if mandatory arguments are not specified, or if any argument does not fit accepted values or type:

Optional arguments#

dir : str, optional, default “”

Path to the corresponding component. This value is used if not provided in parameters

file : str, optional, default “”

File format in the given directory. This value is used if not provided in parameters

varname : str, optional, default “”

Variable name to use to read data filesinstead of the parameter name if different to the parameter name

file_freq : str, optional, default “1M”

The time frequency at which data files are available.

split_freq : str, optional

Re-bucket this tracer’s fetched dates/files onto a fixed pandas-frequency grid (e.g. '1D', '1MS', '1YS'), independently of the native frequency the files were found at (file_freq). This fixes the sub-simulation boundaries that fromcontrol inherits for this tracer. For minimal memory usage, match it to the consuming model’s own periodicity: a finer value costs an extra time_interpolation bridge for no memory benefit, while a coarser value keeps the tracer’s data resident in memory across every one of the model’s sub-simulations it spans. See the ‘Splitting the temporal grid’ section on the observation operator page for the full mechanism and worked examples.

dir_profiles : str, optional, default False

Directory where the time and vertical profiles are files should be: TNO_height-distribution_GNFR.csv, timeprofiles-month-in-year_GNFR.csv, timeprofiles-day-in-week_GNFR.csv, timeprofiles-hour-in-day_GNFR.csv

cat_select : , optional, default [0, 1, 2, 3, 4, 5, 6, 7]

List of Carbon Monitor categories to use (in 0:7 range). By Default all categories are used

dummy_arg : str, optional, default “let’s say it’s not mandatory”

document here the argument

lon_min : float, optional, default -180

Minimum longitude

lon_max : float, optional, default 180

Maximum longitude

lat_min : float, optional, default -90

Minimum latitude

lat_max : float, optional, default 90

Maximum latgitude

nlon : int, optional, default 90

Number of grid cells in the zonal direction

nlat : int, optional, default 45

Number of grid cells in the meridional direction

nlev : int, optional, default 1

Number of levels in the data

average_value : float, optional, default 1

Average value for the generation of random values

YAML template#

Please find below a template for a YAML configuration:

 1flux:
 2  plugin:
 3    name: CarbonMonitor
 4    version: netcdf
 5    type: flux
 6
 7  # Optional arguments
 8  dir: XXXXX  # str
 9  file: XXXXX  # str
10  varname: XXXXX  # str
11  file_freq: XXXXX  # str
12  split_freq: XXXXX  # str
13  dir_profiles: XXXXX  # str
14  cat_select: XXXXX  # 
15  dummy_arg: XXXXX  # str
16  lon_min: XXXXX  # float
17  lon_max: XXXXX  # float
18  lat_min: XXXXX  # float
19  lat_max: XXXXX  # float
20  nlon: XXXXX  # int
21  nlat: XXXXX  # int
22  nlev: XXXXX  # int
23  average_value: XXXXX  # float

See also

API reference (functions & code)