pycontrails.models.accf.ACCFParams¶

class pycontrails.models.accf.ACCFParams(copy_source=True, interpolation_method='linear', interpolation_bounds_error=False, interpolation_fill_value=nan, interpolation_localize=False, interpolation_use_indices=False, interpolation_q_method=None, verify_met=True, downselect_met=True, met_longitude_buffer=(0.0, 0.0), met_latitude_buffer=(0.0, 0.0), met_level_buffer=(0.0, 0.0), met_time_buffer=(np.timedelta64(0, 'h'), np.timedelta64(0, 'h')), lat_bound=None, lon_bound=None, efficacy=True, efficacy_option='lee_2021', accf_v='V1.0', ch4_scaling=1.0, co2_scaling=1.0, cont_scaling=1.0, h2o_scaling=1.0, o3_scaling=1.0, forecast_step=None, sep_ri_rw=False, climate_indicator='ATR', horizontal_resolution=None, emission_scenario='pulse', time_horizon=20, pfca='PCFA-ISSR', merged=True, issr_rhi_threshold=0.9, issr_temp_threshold=235, sac_ei_h2o=1.25, sac_q=43000000.0, sac_eta=0.3, nox_ei='TTV', PMO=False, unit_K_per_kg_fuel=False)¶

Bases: ModelParams

Default ACCF model parameters.

See config-user.yml definition at https://github.com/dlr-pa/climaccf

__init__(copy_source=True, interpolation_method='linear', interpolation_bounds_error=False, interpolation_fill_value=nan, interpolation_localize=False, interpolation_use_indices=False, interpolation_q_method=None, verify_met=True, downselect_met=True, met_longitude_buffer=(0.0, 0.0), met_latitude_buffer=(0.0, 0.0), met_level_buffer=(0.0, 0.0), met_time_buffer=(np.timedelta64(0, 'h'), np.timedelta64(0, 'h')), lat_bound=None, lon_bound=None, efficacy=True, efficacy_option='lee_2021', accf_v='V1.0', ch4_scaling=1.0, co2_scaling=1.0, cont_scaling=1.0, h2o_scaling=1.0, o3_scaling=1.0, forecast_step=None, sep_ri_rw=False, climate_indicator='ATR', horizontal_resolution=None, emission_scenario='pulse', time_horizon=20, pfca='PCFA-ISSR', merged=True, issr_rhi_threshold=0.9, issr_temp_threshold=235, sac_ei_h2o=1.25, sac_q=43000000.0, sac_eta=0.3, nox_ei='TTV', PMO=False, unit_K_per_kg_fuel=False)¶

Methods

`__init__`([copy_source, ...])
`as_dict`()	Convert object to dictionary.

Attributes

`PMO`
`accf_v`
`ch4_scaling`
`climate_indicator`
`co2_scaling`
`cont_scaling`
`copy_source`	Copy input `source` data on eval
`downselect_met`	Downselect input MetDataset` to region around `source`.
`efficacy`
`efficacy_option`
`emission_scenario`
`forecast_step`
`h2o_scaling`
`horizontal_resolution`	The horizontal resolution of the meteorological data in degrees.
`interpolation_bounds_error`	If True, points lying outside interpolation will raise an error
`interpolation_fill_value`	Used for outside interpolation value if `interpolation_bounds_error` is False
`interpolation_localize`	Experimental.
`interpolation_method`	Interpolation method.
`interpolation_q_method`	Experimental.
`interpolation_use_indices`	Experimental.
`issr_rhi_threshold`	RHI Threshold
`issr_temp_threshold`
`lat_bound`
`lon_bound`
`merged`
`met_latitude_buffer`	Met latitude buffer for input to `Flight.downselect_met()`, in WGS84 coordinates.
`met_level_buffer`	Met level buffer for input to `Flight.downselect_met()`, in [\(hPa\)].
`met_longitude_buffer`	Met longitude buffer for input to `Flight.downselect_met()`, in WGS84 coordinates.
`met_time_buffer`	Met time buffer for input to `Flight.downselect_met()` Only applies when `downselect_met` is True.
`nox_ei`
`o3_scaling`
`pfca`
`sac_ei_h2o`
`sac_eta`
`sac_q`
`sep_ri_rw`
`time_horizon`
`unit_K_per_kg_fuel`
`verify_met`	Call `_verify_met()` on model instantiation.

PMO = False¶

accf_v = 'V1.0'¶

as_dict()¶

Convert object to dictionary.

We use this method instead of dataclasses.asdict to use a shallow/unrecursive copy. This will return values as Any instead of dict.

Returns:: dict[str, Any] – Dictionary version of self.

ch4_scaling = 1.0¶

climate_indicator = 'ATR'¶

co2_scaling = 1.0¶

cont_scaling = 1.0¶

copy_source = True¶: Copy input source data on eval

downselect_met = True¶: Downselect input MetDataset` to region around source.

efficacy = True¶

efficacy_option = 'lee_2021'¶

emission_scenario = 'pulse'¶

forecast_step = None¶

h2o_scaling = 1.0¶

horizontal_resolution = None¶: The horizontal resolution of the meteorological data in degrees. If None, it will be inferred from the met dataset for MetDataset source, otherwise it will be set to 0.5.

interpolation_bounds_error = False¶: If True, points lying outside interpolation will raise an error

interpolation_fill_value = nan¶: Used for outside interpolation value if interpolation_bounds_error is False

interpolation_localize = False¶: Experimental. See pycontrails.core.interpolation.

interpolation_method = 'linear'¶: Interpolation method. Supported methods include “linear”, “nearest”, “slinear”, “cubic”, and “quintic”. See scipy.interpolate.RegularGridInterpolator for the description of each method. Not all methods are supported by all met grids. For example, the “cubic” method requires at least 4 points per dimension.

interpolation_q_method = None¶: Experimental. Alternative interpolation method to account for specific humidity lapse rate bias. Must be one of None, "cubic-spline", or "log-q-log-p". If None, no special interpolation is used for specific humidity. The "cubic-spline" method applies a custom stretching of the met interpolation table to account for the specific humidity lapse rate bias. The "log-q-log-p" method interpolates in the log of specific humidity and pressure, then converts back to specific humidity. Only used by models calling to interpolate_met().

interpolation_use_indices = False¶: Experimental. See pycontrails.core.interpolation.

issr_rhi_threshold = 0.9¶: RHI Threshold

issr_temp_threshold = 235¶

lat_bound = None¶

lon_bound = None¶

merged = True¶

met_latitude_buffer = (0.0, 0.0)¶: Met latitude buffer for input to Flight.downselect_met(), in WGS84 coordinates. Only applies when downselect_met is True.

met_level_buffer = (0.0, 0.0)¶: Met level buffer for input to Flight.downselect_met(), in [\(hPa\)]. Only applies when downselect_met is True.

met_longitude_buffer = (0.0, 0.0)¶: Met longitude buffer for input to Flight.downselect_met(), in WGS84 coordinates. Only applies when downselect_met is True.

met_time_buffer = (np.timedelta64(0,'h'), np.timedelta64(0,'h'))¶: Met time buffer for input to Flight.downselect_met() Only applies when downselect_met is True.

nox_ei = 'TTV'¶

o3_scaling = 1.0¶

pfca = 'PCFA-ISSR'¶

sac_ei_h2o = 1.25¶

sac_eta = 0.3¶

sac_q = 43000000.0¶

sep_ri_rw = False¶

time_horizon = 20¶

unit_K_per_kg_fuel = False¶

verify_met = True¶: Call _verify_met() on model instantiation.