melodies_monet.util.sat_l2_swath_utility_tropomi

Python utility for TROPOMI use.

Functions

apply_averaging_kernel(modobj, obsobj, sat_type)	Applies the averaging kernel and calculates the column
apply_averaging_kernel_co(mod_p_cols, obsobj)	Applies the averaging kernel for TROPOMI total column CO and calculates the column.
apply_averaging_kernel_hcho(mod_p_cols, obsobj)	Applies the averaging kernel for TROPOMI HCHO and calculates the column.
apply_averaging_kernel_no2(mod_p_cols, obsobj)	Applies the averaging kernel for TROPOMI NO2 and calculates the column
back_to_structured_grid(paired_object, ...)	Reformats the output dictionary to a structured grid.
crop_obsobj(obsobj, modobj)	Subselects the observations depending on the model domain.
interp_horizontal_mod2sat(obsobj, modobj[, ...])	Interpolates model horizontally to satellite
interp_vertical_mod2swath(obsobj, modobj[, ...])	Interpolates model vertical layers to TROPOMI vertical layers
regrid_and_apply_ak(obsobj_dict, modobj, ...)	Regrids and applies AK to multiple swaths.
select_swaths_overlapping_model(obsobj, modobj)	Selects the swaths overlapping with the model domain.
tropomi_mol_m2_to_molec_cm2(column_data)	Converts column data from mol/m2 to molec/cm2
within_model_domain(obsobj, bounds)	Checks if any of the observations are within the model domain.

melodies_monet.util.sat_l2_swath_utility_tropomi.apply_averaging_kernel(modobj, obsobj, sat_type, varname=None, averaging_kernel_params=None)

Applies the averaging kernel and calculates the column

Parameters:

• modobj (xr.Dataset) – DataArray containing the model information. It has to be previously regridded to satellite space.

• obsobj (xr.Dataset) – Dataset containing all the observational data, including the variables related to the averaging kernel.

• sat_type (str) – string of satellite type. Currently, tropomi_l2_no2, tropomi_l2_hcho and tropomi_l2_co are supported

• averaging_kernel_params (dict[str, str]) – dictionary containing the keys “averaging_kernel” and “tropospheric_averaging_kernel_calc” plus, optionally, “airmass_factor_total” and “airmass_factor_troposphere”.

Returns:

xr.DataArray – DataArray containing the model columns after applying the averaging kernel.

melodies_monet.util.sat_l2_swath_utility_tropomi.apply_averaging_kernel_co(mod_p_cols, obsobj, varname=None, averaging_kernel_params=None)

Applies the averaging kernel for TROPOMI total column CO and calculates the column. It is in the User Guide.

Parameters:

• mod_p_cols (xr.DataArray) – DataArray containing the model HCHO partial columns. It has to be previously regridded to satellite space.

• obsobj (xr.Dataset) – Dataset containing all the observational data, including the variables related to the averaging kernel.

• averaging_kernel_params (dict[str, str]) – Dict containing the averaging kernel params

Returns:

xr.DataArray – DataArray containing the model columns after applying the averaging kernel.

melodies_monet.util.sat_l2_swath_utility_tropomi.apply_averaging_kernel_hcho(mod_p_cols, obsobj, varname=None, averaging_kernel_params=None)

Applies the averaging kernel for TROPOMI HCHO and calculates the column. It is in the ATBD documentation, instead of the user guide.

Parameters:

• mod_p_cols (xr.DataArray) – DataArray containing the model HCHO partial columns. It has to be previously regridded to satellite space.

• obsobj (xr.Dataset) – Dataset containing all the observational data, including the variables related to the averaging kernel.

• averaging_kernel_params (dict[str, str]) – dictionary containing the keys “averaging_kernel” and “tropospheric_averaging_kernel_calc” plus, optionally, “airmass_factor_total” and “airmass_factor_troposphere”.

Returns:

xr.DataArray – DataArray containing the model columns after applying the averaging kernel.

melodies_monet.util.sat_l2_swath_utility_tropomi.apply_averaging_kernel_no2(mod_p_cols, obsobj, averaging_kernel_params=None)

Applies the averaging kernel for TROPOMI NO2 and calculates the column

Parameters:

• mod_p_cols (xr.DataArray) – DataArray containing the model NO2 partial columns. It has to be previously regridded to satellite space.

• obsobj (xr.Dataset) – Dataset containing all the observational data, including the variables related to the averaging kernel.

• averaging_kernel_params (dict[str, str]) – dictionary containing the keys “averaging_kernel” and “tropospheric_averaging_kernel_calc” plus, optionally, “airmass_factor_total” and “airmass_factor_troposphere”.

Returns:

xr.DataArray – DataArray containing the model columns after applying the averaging kernel.

melodies_monet.util.sat_l2_swath_utility_tropomi.back_to_structured_grid(paired_object, target_grid, is_global=False)

Reformats the output dictionary to a structured grid.

Parameters:

• paired_object (dict[str, xr.Dataset]) – Dictionary containing the same keys as the obs, and the model data in satellite space after applying the ak as values

• target_grid (xr.Dataset) – Dataset containing the target grid information.

• is_global (bool) – Whether periodic=True should be applied to the data

Returns:

xr.Dataset – Dataset containing the paired data in the structured grid.

melodies_monet.util.sat_l2_swath_utility_tropomi.crop_obsobj(obsobj, modobj)

Subselects the observations depending on the model domain.

Parameters:

• obsobj (xr.Dataset) – Dataset containing all the observational data.

• modobj (xr.Dataset) – Model dataset, as read in by MELODIES-MONET.

Returns:

xr.Dataset | None – Dataset with the observations outside the bounds discarded. If no observations are within the model domain, None is returned.

melodies_monet.util.sat_l2_swath_utility_tropomi.interp_horizontal_mod2sat(obsobj, modobj, method='bilinear', is_global=False, **kwargs)

Interpolates model horizontally to satellite

Parameters:

• obsobj (xr.Dataset) – xr.Dataset with a granule of the obsobj.

• modobj (xr.Dataset) – Dataset with satellite data as formatted by monetio, already interpolated to correct time.

• method (str) – Method of regridding, any method supported by xesmf should work.

• is_global (bool) – Whether the model is global. If True, xe.Regridder will be set to periodic=True

• **kwargs – Extra arguments to pass to xe.Regridder

Returns:

dict[np.datetime64, xr.Dataset] – Dictionary with model data in obsobj grid.

melodies_monet.util.sat_l2_swath_utility_tropomi.interp_vertical_mod2swath(obsobj, modobj, variables='NO2_col')

Interpolates model vertical layers to TROPOMI vertical layers

Parameters:

• modobj (xr.Dataset) – Model data (as provided by MONETIO)

• obsobj (xr.Dataset) – TROPOMI data (as provided by the reader). Must include pressure.

• variables (str | list[str]) – Variables to interpolate.

Returns:

xr.Dataset – Model data (interpolated to TROPOMI vertical layers)

melodies_monet.util.sat_l2_swath_utility_tropomi.regrid_and_apply_ak(obsobj_dict, modobj, start_time, end_time, mod_var='NO2', sat_var='nitrogendioxide_tropospheric_column', sat_type='tropomi_l2_no2', is_global=False)

Regrids and applies AK to multiple swaths.

Parameters:

• obsobj_dict (dict[np.datetime64, xr.Dataset]) – Dictionary containing observations

• modobj (xr.Dataset) – model dataset, as read in by MELODIES-MONET. Model should be already at overpass time

Returns:

dict[str, xr.Dataset] – Dictionary containing the same keys as the obs, and the model data in satellite space after applying the ak as values

melodies_monet.util.sat_l2_swath_utility_tropomi.select_swaths_overlapping_model(obsobj, modobj)

Selects the swaths overlapping with the model domain.

Parameters:

• obsobj (dict[str, xr.Dataset]) – Dictionary containing observations

• modobj (xr.Dataset) – Model dataset, as read in by MELODIES-MONET.

Returns:

dict[np.datetime64, xr.Dataset] – Dictionary containing the same keys as the obs, and the observations within the model domain as values.

melodies_monet.util.sat_l2_swath_utility_tropomi.tropomi_mol_m2_to_molec_cm2(column_data)

Converts column data from mol/m2 to molec/cm2

Parameters:

column_data (xr.DataArray) – DataArray containing the column data in mol/m2

Returns:

xr.DataArray – DataArray containing the column data in molec/cm2

melodies_monet.util.sat_l2_swath_utility_tropomi.within_model_domain(obsobj, bounds)

Checks if any of the observations are within the model domain.

Parameters:

• obsobj (xr.Dataset) – Dataset containing all the observational data.

• bounds (list[float]) – List containing the bounds in the order [min_lon, max_lon, min_lat, max_lat].

Returns:

bool – True if all observations are within the model domain, False otherwise.