pycontrails.models.dry_advection.DryAdvection

class pycontrails.models.dry_advection.DryAdvection(met=None, params=None, **params_kwargs)

Bases: Model

Simulate “dry advection” of an emissions plume with an elliptical cross section.

The model simulates both horizontal and vertical advection of a weightless plume without any sedimentation effects. Unlike Cocip, humidity is not considered, and radiative forcing is not simulated. The model is therefore useful simulating plume advection and dispersion itself.

Added in version 0.46.0.

This model has two distinct modes of operation:

• Pointwise only: If azimuth is None, then the model will only advect

  points without any wind shear effects. This mode is useful for testing the advection algorithm itself, and for simulating the evolution of a single point.

• Wind shear effects: If azimuth is not None, then the model will

  advect points with wind shear effects. At each time step, the model will evolve the plume geometry according to diffusion and wind shear effects. This mode is also used in CocipGrid and Cocip.

Parameters:

• met (MetDataset) – Meteorological data.

• params (dict[str, Any]) – Model parameters. See DryAdvectionParams for details.

• **kwargs (Any) – Additional parameters passed as keyword arguments.

__init__(met=None, params=None, **params_kwargs)

Methods

__init__([met, params])
downselect_met()	Downselect met domain to the max/min bounds of source.
ecmwf_met_variables()	Return an ECMWF-specific list of required meteorology variables.
eval([source])	Simulate dry advection (no sedimentation) of arbitrary points.
generic_met_variables()	Return a model-agnostic list of required meteorology variables.
get_data_param(other, key[, default, set_attr])	Get data from other source-compatible object with default set by model parameter key.
get_source_param(key[, default, set_attr])	Get source data with default set by parameter key.
gfs_met_variables()	Return a GFS-specific list of required meteorology variables.
require_met()	Ensure that met is a MetDataset.
require_source_type(type_)	Ensure that source is type_.
set_source([source])	Attach original or copy of input source to source.
set_source_met([optional, variable])	Ensure or interpolate each required met_variables on source .
transfer_met_source_attrs([source])	Transfer met source metadata from met to source.
update_params([params])	Update model parameters on params.

Attributes

met	Meteorology data
params	Instantiated model parameters, in dictionary form
source	Data evaluated in model
hash	Generate a unique hash for model instance.
interp_kwargs	Shortcut to create interpolation arguments from params.
long_name
met_required	Require meteorology is not None on __init__()
met_variables	Required meteorology pressure level variables.
name
processed_met_variables	Set of required parameters if processing already complete on met input.
optional_met_variables	Optional meteorology variables

default_params

alias of DryAdvectionParams

downselect_met()

Downselect met domain to the max/min bounds of source.

Override this method if special handling is needed in met down-selection.

• source must be defined before calling downselect_met().

• This method copies and re-assigns met using met.copy() to avoid side-effects.

Raises:

• ValueError – Raised if source is not defined. Raised if source is not a GeoVectorDataset.

• TypeError – Raised if met is not a MetDataset.

classmethod ecmwf_met_variables()

Return an ECMWF-specific list of required meteorology variables.

Returns:

tuple[MetVariable] – List of ECMWF-specific variants of required variables

eval(source=None, **params)

Simulate dry advection (no sedimentation) of arbitrary points.

Like Cocip, this model adds a “waypoint” column to the source.

Parameters:

• source (GeoVectorDataset | None) – Arbitrary points to advect. A Flight instance is not treated any differently than a GeoVectorDataset. In particular, the user must explicitly set flight["azimuth"] = flight.segment_azimuth() if they want to use wind shear effects for a flight. In the current implementation, any existing meteorological variables in the source are ignored. The source will be interpolated against the met dataset.

• **params (Any) – Overwrite model parameters defined in __init__.

Returns:

GeoVectorDataset – Advected points.

classmethod generic_met_variables()

Return a model-agnostic list of required meteorology variables.

Returns:

tuple[MetVariable] – List of model-agnostic variants of required variables

get_data_param(other, key, default=<object object>, *, set_attr=True)

Get data from other source-compatible object with default set by model parameter key.

Retrieves data with the following hierarchy:

1. other.data[key]. Returns np.ndarray | xr.DataArray.

2. other.attrs[key]

3. params[key]

4. default

In case 3., the value of params[key] is attached to other.attrs[key] unless set_attr is set to False.

Parameters:

• key (str) – Key to retrieve

• default (Any, optional) – Default value if key is not found.

• set_attr (bool, optional) – If True (default), set source.attrs[key] to params[key] if found. This allows for better post model evaluation tracking.

Returns:

Any – Value(s) found for key in other data, other attrs, or model params

Raises:

KeyError – Raises KeyError if key is not found in any location and default is not provided.

See also

get_source_param, pycontrails.core.vector.GeoVectorDataset.get_data_or_attr

get_source_param(key, default=<object object>, *, set_attr=True)

Get source data with default set by parameter key.

Retrieves data with the following hierarchy:

1. source.data[key]. Returns np.ndarray | xr.DataArray.

2. source.attrs[key]

3. params[key]

4. default

In case 3., the value of params[key] is attached to source.attrs[key] unless set_attr is set to False.

Parameters:

• key (str) – Key to retrieve

• default (Any, optional) – Default value if key is not found.

• set_attr (bool, optional) – If True (default), set source.attrs[key] to params[key] if found. This allows for better post model evaluation tracking.

Returns:

Any – Value(s) found for key in source data, source attrs, or model params

Raises:

KeyError – Raises KeyError if key is not found in any location and default is not provided.

See also

get_data_param, pycontrails.core.vector.GeoVectorDataset.get_data_or_attr

classmethod gfs_met_variables()

Return a GFS-specific list of required meteorology variables.

Returns:

tuple[MetVariable] – List of GFS-specific variants of required variables

property hash

Generate a unique hash for model instance.

Returns:

str – Unique hash for model instance (sha1)

property interp_kwargs

Shortcut to create interpolation arguments from params.

The output of this is useful for passing to interpolate_met().

Returns:

dict[str, Any] – Dictionary with keys

• ”method”

• ”bounds_error”

• ”fill_value”

• ”localize”

• ”use_indices”

• ”q_method”

as determined by params.

long_name = 'Emission plume advection without sedimentation'

met

Meteorology data

met_required = True

Require meteorology is not None on __init__()

met_variables = (MetVariable(short_name='t', standard_name='air_temperature', long_name='Air Temperature', level_type='isobaricInhPa', ecmwf_id=130, grib1_id=11, grib2_id=(0, 0, 0), units='K', amip='ta', description='Air temperature is the bulk temperature of the air, not the surface (skin) temperature.'), MetVariable(short_name='u', standard_name='eastward_wind', long_name='Eastward Wind', level_type='isobaricInhPa', ecmwf_id=131, grib1_id=33, grib2_id=(0, 2, 2), units='m s**-1', amip='ua', description='"Eastward" indicates a vector component which is positive when directed eastward (negative westward). Wind is defined as a two-dimensional (horizontal) air velocity vector, with no vertical component.'), MetVariable(short_name='v', standard_name='northward_wind', long_name='Northward Wind', level_type='isobaricInhPa', ecmwf_id=132, grib1_id=34, grib2_id=(0, 2, 3), units='m s**-1', amip='va', description='"Northward" indicates a vector component which is positive when directed northward (negative southward). Wind is defined as a two-dimensional (horizontal) air velocity vector, with no vertical component.'), MetVariable(short_name='w', standard_name='lagrangian_tendency_of_air_pressure', long_name='Vertical Velocity (omega)', level_type='isobaricInhPa', ecmwf_id=135, grib1_id=39, grib2_id=(0, 2, 8), units='Pa s**-1', amip='wap', description='The Lagrangian tendency of air pressure, often called "omega", plays the role of the upward component of air velocity when air pressure is being used as the vertical coordinate. If the vertical air velocity is upwards, it is negative when expressed as a tendency of air pressure; downwards is positive. Air pressure is the force per unit area which would be exerted when the moving gas molecules of which the air is composed strike a theoretical surface of any orientation.'))

Required meteorology pressure level variables. Each element in the list is a MetVariable or a tuple[MetVariable]. If element is a tuple[MetVariable], the variable depends on the data source and the tuple must include entries for a model-agnostic variable, an ECMWF-specific variable, and a GFS-specific variable. Only one of the three variable in the tuple is required for model evaluation.

name = 'dry_advection'

optional_met_variables

Optional meteorology variables

params

Instantiated model parameters, in dictionary form

processed_met_variables

Set of required parameters if processing already complete on met input.

require_met()

Ensure that met is a MetDataset.

Returns:

MetDataset – Returns reference to met. This is helpful for type narrowing met when meteorology is required.

Raises:

ValueError – Raises when met is None.

require_source_type(type_)

Ensure that source is type_.

Returns:

_Source – Returns reference to source. This is helpful for type narrowing source to specific type(s).

Raises:

ValueError – Raises when source is not _type_.

set_source(source=None)

Attach original or copy of input source to source.

Parameters:

source (MetDataset | GeoVectorDataset | Flight | Iterable[Flight] | None) – Parameter source passed in eval(). If None, an empty MetDataset with coordinates like met is set to source.

See also

eval

set_source_met(optional=False, variable=None)

Ensure or interpolate each required met_variables on source .

For each variable in met_variables, check source for data variable with the same name.

For GeoVectorDataset sources, try to interpolate met if variable does not exist.

For MetDataset sources, try to get data from met if variable does not exist.

Parameters:

• optional (bool, optional) – Include optional_met_variables

• variable (MetVariable | Sequence[MetVariable] | None, optional) – MetVariable to set, from met_variables. If None, set all variables in met_variables and optional_met_variables if optional is True.

Raises:

• ValueError – Variable does not exist and source is a MetDataset.

• KeyError – Variable not found in source or met.

source

Data evaluated in model

transfer_met_source_attrs(source=None)

Transfer met source metadata from met to source.

update_params(params=None, **params_kwargs)

Update model parameters on params.

Parameters:

• params (dict[str, Any], optional) – Model parameters to update, as dictionary. Defaults to {}

• **params_kwargs (Any) – Override keys in params with keyword arguments.