melodies_monet.util.sat_l2_swath_utility_tempo

Python utility for TEMPO use.

Functions

`apply_weights_mod2tempo_hcho`(obsobj, modobj)	Apply the scattering weights and air mass factors according to Cooper et.
`apply_weights_mod2tempo_hcho_hydrostatic`(...)	Apply the scattering weights and air mass factors according to Cooper et.
`apply_weights_mod2tempo_no2`(obsobj, modobj)	Apply the scattering weights and air mass factors according to Cooper et.
`apply_weights_mod2tempo_no2_hydrostatic`(...)	Apply the scattering weights and air mass factors according to Cooper et.
`back_to_modgrid`(paireddict, modobj[, ...])	Grids object in sat-space to modgrid.
`back_to_modgrid_multiscan`(paireddict, modobj)	Grids object in sat-space to modgrid.
`calc_altitude_from_thickness`(dz_m)	Calculate layer altitude above ground
`calc_dz_m_from_altitude`(altitude)	Calculates dz_m from altitude AGL (in m).
`calc_grid_corners`(ds[, lat, lon])	Adds latitude and longitude bounds inplace.
`calc_partialcolumn`(modobj[, var])	Calculates the partial column of a species from its concentration.
`interp_vertical_mod2swath`(obsobj, modobj[, ...])	Interpolates model vertical layers to TEMPO vertical layers
`is_nonpairable`(obsobj, k, modobj)	Discards inplace granules from obsobj that do not match modobj's domain, or granules that are all NaN.
`read_paired_gridded_tempo_model`(path)	Reads in paired gridded tempo and model data
`read_paired_swath`(path)	Read in paired swath data
`regrid_and_apply_weights`(obsobj, modobj[, ...])	Does the complete process of regridding and applying scattering weights.
`save_paired_swath`(moddict[, path])	Saves each swath individually
`select_by_keys`(data_names[, period])	Selects data containing the same scan or day.
`speedup_regridding`(dset[, variables])	Makes modobj latitude and longitude C_contiguous, which speeds up regridding.
`tempo_interp_mod2swath`(obsobj, modobj[, ...])	Interpolate model to satellite swath/swaths

melodies_monet.util.sat_l2_swath_utility_tempo.apply_weights_mod2tempo_hcho(obsobj, modobj, species='HCHO')

Apply the scattering weights and air mass factors according to Cooper et. al, 2020, doi: https://doi.org/10.5194/acp-20-7231-2020

Parameters:

obsobj (xr.Dataset) – TEMPO data, including pressure and scattering weights
modobj (xr.Dataset) – Model data, already interpolated to TEMPO grid

Returns:

xr.DataArray – A xr.DataArray containing the NO2 model data after applying the air mass factors and scattering weights

melodies_monet.util.sat_l2_swath_utility_tempo.apply_weights_mod2tempo_hcho_hydrostatic(obsobj, modobj, species='HCHO')

Apply the scattering weights and air mass factors according to Cooper et. al, 2020, doi: https://doi.org/10.5194/acp-20-7231-2020, assuming the hydrostatic equation. It does not require temperature nor geometric layer thickness.

Parameters:

obsobj (xr.Dataset) – TEMPO data, including pressure and scattering weights
modobj (xr.Dataset) – Model data, already interpolated to TEMPO grid

Returns:

xr.DataArray – A xr.DataArray containing the NO2 model data after applying the air mass factors and scattering weights

melodies_monet.util.sat_l2_swath_utility_tempo.apply_weights_mod2tempo_no2(obsobj, modobj, species='NO2', column_type='tropospheric')

Apply the scattering weights and air mass factors according to Cooper et. al, 2020, doi: https://doi.org/10.5194/acp-20-7231-2020

Parameters:

obsobj (xr.Dataset) – TEMPO data, including pressure and scattering weights
modobj (xr.Dataset) – Model data, already interpolated to TEMPO grid
column_type (str) – Whether the “tropospheric” or “total” column should be used for the calculation

Returns:

xr.DataArray – A xr.DataArray containing the NO2 model data after applying the air mass factors and scattering weights

melodies_monet.util.sat_l2_swath_utility_tempo.apply_weights_mod2tempo_no2_hydrostatic(obsobj, modobj, species='NO2')

Apply the scattering weights and air mass factors according to Cooper et. al, 2020, doi: https://doi.org/10.5194/acp-20-7231-2020, assuming the hydrostatic equation. It does not require temperature nor geometric layer thickness.

Parameters:

obsobj (xr.Dataset) – TEMPO data, including pressure and scattering weights
modobj (xr.Dataset) – Model data, already interpolated to TEMPO grid

Returns:

xr.DataArray – A xr.DataArray containing the NO2 model data after applying the air mass factors and scattering weights

melodies_monet.util.sat_l2_swath_utility_tempo.back_to_modgrid(paireddict, modobj, keys_to_merge='all', add_time=True, to_netcdf=False, path='Regridded_object_XYZ.nc', method='bilinear', grid_path=None)

Grids object in sat-space to modgrid. Designed to grid back to modgrid after applying the scattering weights and air mass factors. It is designed for a single scan.

Parameters:

paireddict (collections.OrderedDict[str, xr.Dataset]) – An OrderedDict with time_reference strings as keys.
modobj (xr.Dataset) – A modobj including the modgrid.
keys_to_merge (str | list[str]) – If ‘all’, all keys are assumed to be part of the same scan and merged. Else, only the keys provided are merged.
add_time (bool) – If True, add reference time as a coordinate for the scan. Can be useful to concatenate later if multiple scans are required.
to_netcdf (bool) – If True, save a netcdf with the paired data
path (str) – The base name to save the files if to_netcdf is True. XX will be replaced with the scan number and the reference time. If to_netcdf is False, this will be ignored.
method (str) – Method of regridding used by xESMF
grid_path (str) – If None, defaults to the model grid. Otherwise, the grid in path is used. If the method is conservative, lat_b and lon_b are required.

Returns:

xr.Dataset – Dataset with obj2grid regridded to modobj.

melodies_monet.util.sat_l2_swath_utility_tempo.back_to_modgrid_multiscan(paireddict, modobj, to_netcdf=False, path='Regridded_object_XYZ.nc', method='bilinear', grid_path=None)

Grids object in sat-space to modgrid. Designed to grid back to modgrid after applying the scattering weights and air mass factors. It is designed for multiple scans, and uses back_to_modgrid under the hood. Generally, back_to_modgrid should only be used if you can ensure that you are reading only one scan at a time.

Parameters:

paireddict (collections.OrderedDict[str, xr.Dataset]) – An OrderedDict with time_reference strings as keys.
modobj (xr.Dataset) – A modobj including the modgrid.
to_netcdf (bool) – If True, save a netcdf with the paired data
path (str) – The base name to save the files if to_netcdf is True. XX will be replaced with the first and list times. If to_netcdf is False, this will be ignored.
method (str) – Method of regridding used by xESMF

Returns:

xr.Dataset – Dataset with obj2grid regridded to modobj.

melodies_monet.util.sat_l2_swath_utility_tempo.calc_altitude_from_thickness(dz_m)

Calculate layer altitude above ground

Parameters:: data (xr.DataArray) – DataArray containing dz_m
Returns:: Model altitude in satellite space

melodies_monet.util.sat_l2_swath_utility_tempo.calc_dz_m_from_altitude(altitude)

Calculates dz_m from altitude AGL (in m).

Parameters:: altitude (xr.DataArray) – DataArray containing the layer interface altitude AGL at the interface.
Returns:: xr.DataArray – DataArray containing the layer thickness (dz_m) in m.

melodies_monet.util.sat_l2_swath_utility_tempo.calc_grid_corners(ds, lat='latitude', lon='longitude')

Adds latitude and longitude bounds inplace. If the grid is rectilinear, it should be quite precise. If it is curvilinear, is a rough estimate.

Parameters:

ds (xr.Dataset) – Dataset to which the latitude and longitude will be added.
lat (str) – name of the lat variable.
lon (str) – name of the lon variable.

Returns:

None

melodies_monet.util.sat_l2_swath_utility_tempo.calc_partialcolumn(modobj, var='NO2')

Calculates the partial column of a species from its concentration.

Parameters:

modobj (xr.Dataset) – Model data
var (str) – variable to calculate the partial column from

Returns:

xr.DataArray – DataArray containing the partial column of the species.

melodies_monet.util.sat_l2_swath_utility_tempo.interp_vertical_mod2swath(obsobj, modobj, variables='NO2_col')

Interpolates model vertical layers to TEMPO vertical layers

Parameters:

modobj (xr.Dataset) – Model data (as provided by MONETIO)
obsobj (xr.Dataset) – TEMPO data (as provided by MONETIO). Must include pressure.
variables (str | list[str]) – Variables to interpolate.

Returns:

xr.Dataset – Model data (interpolated to TEMPO vertical layers

melodies_monet.util.sat_l2_swath_utility_tempo.is_nonpairable(obsobj, k, modobj)

Discards inplace granules from obsobj that do not match modobj’s domain, or granules that are all NaN. If the domain is small, it can considerably speed up the regridding process.

Parameters:

obsobj (dict[str, xr.Dataset]) – tempo data
modobj (xr.Dataset) – model data

Returns:

collections.OrderedDict[str, xr.Dataset]

melodies_monet.util.sat_l2_swath_utility_tempo.read_paired_gridded_tempo_model(path)

Reads in paired gridded tempo and model data

Parameters:: path (str or globobject)
Returns:: xr.Dataset – combined dataset with paired tempo and gridded data.

melodies_monet.util.sat_l2_swath_utility_tempo.read_paired_swath(path)

Read in paired swath data

Parameters:: path (str or globobject)
Returns:: collections.OrderedDict[str, xr.Dataset] – OrderedDict with datasets containing every swath

melodies_monet.util.sat_l2_swath_utility_tempo.regrid_and_apply_weights(obsobj, modobj, pair=True, verbose=True, method='conservative', weights=None, species=['NO2'], tempo_sp='NO2')

Does the complete process of regridding and applying scattering weights.

Parameters:

obsobj (xr.Dataset | collections.OrderedDict) – TEMPO observations
modobj (xr.Dataset) – Model output
pair (boolean) – If True, returns paired data.
verbose (boolean) – If True, let’s the user know when each timestamp is being regridded. Only has an effect if the input is an OrderedDict
method (str) – Choose regridding method. Can be “conservative”, “conservative_normed”, “bilinear” or “patch”. Check xesmf documentation for details.
weights (None | str) – If present, a weightfile (as in “weights”) is applied
discard_useless (boolean) – If True, satellite granules that don’t match the model domain are not used.
tempo_sp (str) – NO2 for the NO2 product, HCHO for the HCHO product

Returns:

xr.Dataset | collections.OrderedDict – Model with regridded data. If obsobj is of type collections.OrderedDict, an OrderedDict is returned.

melodies_monet.util.sat_l2_swath_utility_tempo.save_paired_swath(moddict, path='Paired_swath_XYZ.nc')

Saves each swath individually

Parameters:

moddict (collections.OrderedDict[str, xr.Dataset]) – Ordered dict containing all of the paired model and swath.
path (str) – Path to save the swath. If XYZ is present, it will be replaced by the date, number of scan and number of granule.

Returns:

None

melodies_monet.util.sat_l2_swath_utility_tempo.select_by_keys(data_names, period='per_scan')

Selects data containing the same scan or day. It does so by file name, so it is important that the standard naming is not altered.

Parameters:

data_names (list[str]) – list containing the names of the files to select from.
selection_criteria (str) – str with the selection criteria. If “all”, the function does nothing. If “per_scan”, it will return a list of lists[str], with each inner list containing one complete scan. If “per_day”, it will return a list of lists[str], with each inner list containing one complete day.

Returns:

list[str] | list[list[str]] – A sorted list of strings if “all” is provided, a list[list[str]] if a different criteria is provided.

melodies_monet.util.sat_l2_swath_utility_tempo.speedup_regridding(dset, variables='all')

Makes modobj latitude and longitude C_contiguous, which speeds up regridding. It makes the changes inplace

Parameters:: dset (xr.Dataset) – Dataset containing latitude and longitude
Returns:: None

melodies_monet.util.sat_l2_swath_utility_tempo.tempo_interp_mod2swath(obsobj, modobj, method='conservative', weights=None)

Interpolate model to satellite swath/swaths

Parameters:

obsobj (xr.Dataset) – satellite with swath data.
modobj (xr.Dataset) – model data (with no2 col calculated)
method (str) – Choose regridding method. Can be “conservative”, “conservative_normed”, “bilinear” or “patch”. Check xesmf documentation for details.
weights (str) – Path to the weightfile. If present, the weights won’t be calculated again.

Returns:

xr.Dataset – Regridded model data at swath or swaths. If type is xr.Dataset, a single swath is returned. If type is collections.OrderedDict, it returns an OrderedDict in which each time represents the reference time of the swath.