tropomi_l2

Read TROPOMI data into MELODIES-MONET

apply_quality_flag(variable, netcdf_tropomi)

Applies quality_flags inplace

Parameters:

Name	Type	Description	Default
variable	str	Variable containing the attribute qa_thersh_min.	required
netcdf_tropomi	Dataset	Dataset containing the netCDF4 tropomi file	required

Returns:

Type	Description
DataArray	DataArray with applied quality flag

Source code in monetio/sat/tropomi_l2.py

def apply_quality_flag(variable, netcdf_tropomi):
    """Applies quality_flags inplace

    Parameters
    ----------
    variable : str
        Variable containing the attribute qa_thersh_min.
    netcdf_tropomi : nc4.Dataset
        Dataset containing the netCDF4 tropomi file

    Returns
    -------
    xr.DataArray
        DataArray with applied quality flag
    """
    assert "quality_flag" in variable.attrs, f"quality_flag not in {variable.name}"
    assert ("qa_thresh_min" in variable.attrs) or ("qa_thresh_max" in variable.attrs), (
        f"Neither qa_thresh_min nor qa_thresh_max in {variable.name}"
    )
    qa = _add_variable(variable.attrs["quality_flag"], netcdf_tropomi)
    if "qa_thresh_min" in variable.attrs:
        variable = variable.where(qa >= variable.attrs["qa_thresh_min"])
    if "qa_thresh_max" in variable.attrs:
        variable = variable.where(qa <= variable.attrs["qa_thresh_max"])
    return variable

ensure_increasing_altitude(ds)

Ensures that the altitude is increasing (i.e, the pressure should decrease as z increases)

Parameters:

Name	Type	Description	Default
ds	Dataset	Dataset with the satellite data. If pressure is not included, nothing will be done.	required

Returns:

Type	Description
Dataset	Dataset with corrected pressure

Source code in monetio/sat/tropomi_l2.py

def ensure_increasing_altitude(ds):
    """Ensures that the altitude is increasing (i.e, the pressure should
    decrease as z increases)

    Parameters
    ----------
    ds : xr.Dataset
        Dataset with the satellite data. If pressure is not included,
        nothing will be done.

    Returns
    -------
    xr.Dataset
        Dataset with corrected pressure
    """
    if ("pres_pa_mid" not in ds) and ("pres_pa_int" not in ds):
        warnings.warn("Missing pressure information. Ignoring vertical directionality check")
        return ds
    vertical_dim = {"pres_pa_mid": "z", "pres_pa_int": "z_stagg"}
    for pres_var, vert_dim in vertical_dim.items():
        if (ds[pres_var].isel(time=0).isel(**{vert_dim: slice(0, 10)}).diff(dim="z") > 0).any():
            ds = ds.sel(**{vert_dim: slice(None, None, -1)})
    return ds

open_datasets(all_files, variable_dict)

Creates a dict containing all the datasets

Parameters:

Name	Type	Description	Default
all_files	(str, list[str])	String or list of strings containing all the files that should be opened. Wildcards are supported.	required
variable_dict	dict[str, dict]	Dictionary of dictionaries for each variable.	required

Returns:

Type	Description
dict[str, Dataset]	Dictionary with time reference as keys and xr.Dataset containing satellite information as values.

Source code in monetio/sat/tropomi_l2.py

def open_datasets(all_files, variable_dict):
    """Creates a dict containing all the datasets

    Parameters
    ----------
    all_files : str, list[str]
        String or list of strings containing all the files that should
        be opened. Wildcards are supported.
    variable_dict : dict[str, dict]
        Dictionary of dictionaries for each variable.

    Returns
    -------
    dict[str, xr.Dataset]
        Dictionary with time reference as keys and xr.Dataset containing
        satellite information as values.
    """

    if isinstance(all_files, str):
        datasets = sorted(glob.glob(all_files))
    elif isinstance(all_files, list):
        datasets = []
        for ds in all_files:
            datasets.extend(glob.glob(ds))
        datasets = sorted(datasets)
    ds_collection = {}
    for data in datasets:
        d = _open_one_dataset(data, variable_dict)
        # Select time coverage start as key, removing the trailing Z
        ds_collection[d.attrs["time_coverage_start"].replace("Z", "")] = d
    return ds_collection

open_var_no_format(variable, netcdf_dataset)

Opens only one variable from a netCDF4 dataset

Parameters:

Name	Type	Description	Default
variable	str	Variable name	required
netcdf_dataset	Dataset	nc4.Dataset with data to search	required

Returns:

Type	Description
Variable	The variable object that was searched for

Source code in monetio/sat/tropomi_l2.py

def open_var_no_format(variable, netcdf_dataset):
    """Opens only one variable from a netCDF4 dataset

    Parameters
    ----------
    variable : str
        Variable name
    netcdf_dataset : nc4.Dataset
        nc4.Dataset with data to search

    Returns
    -------
    Variable
        The variable object that was searched for
    """
    path = _walktree_search(variable, netcdf_dataset)
    # Robustly navigate path
    parts = path.strip("/").split("/")
    varname = parts[-1]
    group_path = "/".join(parts[:-1])
    return get_nc_var(netcdf_dataset, group_path, varname)