• Fix memory bottleneck in CocipGrid simulation by avoiding expensive call to pd.concat.

  • Require oldest-supported-numpy for python 3.12. Remove logic for numpy 1.26.0rc1 in the pyproject.toml build system.


This release updates the Poll-Schumann (PS) aircraft performance model to version 2.0. It also includes a number of bug fixes and internal improvements.


  • Add convenience Fleet.resample_and_fill.

  • Update the PS model aircraft-engine parameters.

  • Improve PS model accuracy in fuel consumption estimates.

  • Improve PS model accuracy in overall propulsive efficiency estimates.

  • Include additional guardrails in the PS model to constrain the operational limits of different aircraft-engine types, i.e., the maximum permitted Mach number by altitude, maximum available thrust coefficient, maximum lift coefficient, and maximum allowable aircraft mass.


  • Update polygon algorithm to use shapely.Polygon instead of shapely.LinearRing for contours with at least 4 vertices.

  • Fix Fleet.to_flight_list to avoid duplicating global attributes on the child Flight instances.

  • Add __slots__ to GeoVectorDataset, Flight, and Fleet. The base VectorDataset class already uses __slots__.

  • Add Fleet.copy method.

  • Improve Fleet.__init__ implementation.

  • Ensure source parameter is mutated in CocipGrid.eval when the model parameter copy_source=False.



  • Generalize met.shift_longitude() to translate longitude coordinates onto any domain bounds.

  • Add VectorDataset.to_dict() methods to output Vector data as dictionary. This method enables Flight.to_dict() objects to be serialized for input to the Contrails API.

  • Add VectorDataset.from_dict() class method to create VectorDataset class from dictionary.

  • Support more time formats, including timezone aware times, in VectorDataset creation. All timezone aware `”time”`` coordinates are converted to UTC and stripped of timezone identifier.


  • Fix issue in the wake_vortex.max_downward_displacement function in which float32 dtypes were promoted to float64 dtypes in certain cases.

  • Ignore empty vectors in VectorDataset.sum.


  • Set frozen=True on the MetVariable dataclass.

  • Test against python 3.12 in the GitHub Actions CI. Use python 3.12 the docs and doctest workflows.


This release includes a number of breaking changes and new features. If upgrading from a previous version of pycontrails, please read the changelog carefully. Open an issue if you experience problems.

Breaking changes#

  • When running Cocip and other pycontrails models, the met and rad parameter must now contain predefined metadata attributes provider, dataset, and product describing the met source. An error will now be raised in Cocip if these attributes are not present.

  • Deprecate passing arbitrary kwargs into the MetDataArray constructor.

  • No longer convert accumulated radiation data to average instantaneous data in ERA5 and HRES interfaces. This logic is now handled downstream by the model (e.g., Cocip). This change allows for more flexibility in the rad data passed into the model and avoids unnecessary computation in the MetDataSource interfaces.

  • Add new MetDataSource.set_met_source_metadata abstract method. This should be called within the implementing class open_metdataset method.

  • No longer take a finite difference in the time dimension for HRES radiation data. This is now also handled natively in Cocip.

  • No longer convert relative humidity from a percentage to a fraction in ERA5 and HRES interfaces.

  • Require the HRES stream parameter to be one of ["oper", "enfo"]. Require the field_type parameter to be one of ["fc", "pf", "cf", "an"].

  • Remove the steps and step_offset properties in the GFSForecast interface. Now the timesteps attribute is the only source of truth for determining AWS S3 keys. Change the filename method to take in a datatime timestep instead of an int step. No longer assign the first step radiation data to the zeroth step.

  • Change the return type of ISSR.eval, SAC.eval, and PCR.eval from MetDataArray to MetDataset. This is more consistent with the return type of other pycontrails models and more closely mirrors the behavior of vector models. Set output attrs metadata on the global MetDataset instead of the individual MetDataArray in each case.


  • Rewrite parts of the pycontrails.core.datalib module for higher performance and readability.

  • Add optional attrs and attrs_kwargs parameters to MetDataset constructor. This allows the user to customize the attributes on the underlying xarray.Dataset object. This update makes MetDataset more consistent with VectorDataset.

  • Add three new properties provider_attr, dataset_attr, and product_attr to MetDataset. These properties give metadata describing the underlying meterological data source.

  • Add new Model.transfer_met_source_attrs method for more consistent handling of met source metadata on the source parameter passed into Model.eval.

  • No longer require geopotential data when computing tau_cirrus. If neither geopotential nor geopotential_height are available, geopotential is approximated from the geometric height. No longer require geopotential on the met parameter in Cocip or CocipGrid.

  • Remove the Cocip shift_radiation_time parameter. This is now inferred directly from the rad metadata. An error is raised if the necessary metadata is not present.

  • Allow Cocip to run with both instantaneous (W m-2) and accumulated (J m-2) radiation data.

  • Allow Cocip to run with accumulated ECMWF HRES radiation data.


  • Correct radiation unit in the ACCF wrapper model [#64]. Both instantaneous (W m-2) and accumulated (J m-2) radiation data are now supported, and the ACCF wrapper will handle each appropriately.

  • Avoid unnecessary writing and reading of temporary files in ERA5.cache_dataset and HRES.cache_dataset.

  • Fix timestep resolution bug in GFSForecast. When the grid parameter is 0.5 or 1.0, forecasts are only available every 3 hours. Previously, the timesteps property would define an hourly timestep.


  • Include name parameter in MetDataArray constructor.

  • Make the coordinates.slice_domain function slightly more performant by explicitly dropping nan values from the request parameter.

  • Round unwieldy floating point numbers in GeoVectorDataset._display_attrs.

  • Remove the ecmwflibs package from the ecmwf optional dependencies.

  • Add NPY to ruff rules.

  • Add convenience MetDataset.standardize_variables method.

  • Remove the p_settings attribute on the ACCF interface. This is now constructed internally within ACCF.eval. Replace the ACCF._update_accf_config method with a _get_accf_config function.



  • Strengthen correct_fuel_flow in the PSmodel to account for descent conditions.

  • Clip the denominator computed in pycontrails.physics.jet.equivalent_fuel_flow_rate_at_cruise.

  • Ensure the token used within GitHub workflows has the fewest privileges required. Set top-level permissions to none in each workflow file. Remove unnecessary permissions previously used in the google-github-actions/auth action.

  • Fix bug in radiative_forcing.effective_tau_contrail identified in #99.

  • Fix the unit for vertical_velocity in geo.advect_level.

  • Fix bug appearing in Flight._geodesic_interpolation in which a single initial large gap was not interpolated with a geodesic path.


  • Add FlightPhase to the pycontrails namespace.



  • New experimental GOES interface for downloading and visualizing GOES-16 satellite imagery.

  • Add new GOES example notebook highlighting the interface.

  • Build python 3.12 wheels for Linux, macOS, and Windows on release. This is in addition to the existing python 3.9, 3.10, and 3.11 wheels.


  • Use the experimental version number parameter E in pycontrails.ecmwf.hres.get_forecast_filename. Update the logic involved in setting the dissemination data stream indicator S.

  • Change the behavior of _altitude_interpolation method that is called within resample_and_fill. Step climbs are now placed in the middle of long flight segments. Descents continue to occur at the end of segments.


  • Provide consistent ModuleNotFoundError messages when optional dependencies are not installed.

  • Move the synthetic_flight module into the pycontrails.ext namespace.



  • Fix bug in PSGrid in which the met data was assumed to be already loaded into memory. This caused errors when running PSGrid with a MetDataset source.

  • Fix bug (#86) in which Cocip.eval loses the source fuel type. Instead of instantiating a new Flight or Fleet instance with the default fuel type, the Cocip._bundle_results method now overwrites the attribute with the bundled predictions.

  • Avoid a memory explosion when running Cocip on a large non-dask-backed met parameter. Previously the tau_cirrus computation would be performed in memory over the entire met dataset.

  • Replace datetime.utcfromtimestamp (deprecated in python 3.12) with datetime.fromtimestamp.

  • Explicitly support python 3.12 in the pyproject.toml build system.


  • Add compute_tau_cirrus_in_model_init parameter to CocipParams. This controls whether to compute the cirrus optical depth in Cocip.__init__ or Cocip.eval. When set to "auto" (the default), the tau_cirrus is computed in Cocip.__init__ if and only if the met parameter is dask-backed.

  • Change data requirements for the EmpiricalGrid aircraft performance model.

  • Consolidate ERA5.cache_dataset and HRES.cache_dataset onto common ECMWFAPI.cache_dataset method. Previously the child implementations were identical.

  • No longer require the pyproj package as a dependency. This is now an optional dependency, and can be installed with pip install pycontrails[pyproj].


Implement a Poll-Schumann (PSGrid) theoretical aircraft performance over a grid.

Breaking changes#

  • Move the pycontrails.models.aircraft_performance module to pycontrails.core.aircraft_performance.

  • Rename PSModel -> PSFlight.


  • Use the instance fuel attribute in the Fleet.to_flight_list method. Previously, the default JetA fuel was always used.

  • Ensure the Fleet.fuel attribute is inferred from the underlying sequence of flights in the Fleet.from_seq method.


  • Implement the PSGrid model. For a given aircraft type and position, this model computes optimal aircraft performance at cruise conditions. In particular, this model can be used to estimate fuel flow, engine efficiency, and aircraft mass at cruise. In particular, the PSGrid model can now be used in conjunction with CocipGrid to simulate contrail formation over a grid.

  • Refactor the Emissions model so that Emissions.eval runs with source: GeoVectorDataset. Previously, the eval method required a Flight instance for the source parameter. This change allows the Emissions model to run more seamlessly as a sub-model of a gridded model (ie, CocipGrid),

  • No longer require pycontrails-bada to import or run the CocipGrid model. Instead, the CocipGridParams.aircraft_performance parameter can be set to any AircraftPerformanceGrid instance. This allows the CocipGrid model to run with any aircraft performance model that implements the AircraftPerformanceGrid interface.

  • Add experimental EmpiricalAircraftPerformanceGrid model.

  • Add convenience GeoVectorDataset.T_isa method to compute the ISA temperature at each point.


  • Add optional climb_descend_at_end parameter to the Flight.resample_and_fill method. If True, the climb or descent will be placed at the end of each segment rather than the start.

  • Define AircraftPerformanceGridParams, AircraftPerformanceGrid, and AircraftPerformanceGridData abstract interfaces for gridded aircraft performance models.

  • Add set_attr parameter to Models.get_source_param.

  • Better handle source, source.attrs, and params customizations in CocipGrid.

  • Include additional classes and functions in the pycontrails.models.emissions module.

  • Hardcode the paths to the static data files used in the Emissions and PSFlight models. Previously these were configurable by model parameters.

  • Add altitude_ft parameter to the GeoVectorDataset constructor. Warn if at least two of altitude_ft, altitude, and level are provided.

  • Allow instantiation of Model instances with params: ModelParams. Previously, the params parameter was required to be a dict. The current implementation checks that the params parameter is either a dict or has type default_params on the Model class.


Support “dry advection” simulation.


  • Add new DryAdvection model to simulate sediment-free advection of an aircraft’s exhaust plume. This model is experimental and may change in future releases. By default, the current implementation simulates plume geometry as a cylinder with an elliptical cross section (the same geometry assumed in CoCiP). Wind shear perturbs the ellipse azimuth, width, and depth over the plume evolution. The DryAdvection model may also be used to simulate advection without wind-shear effects by setting the model parameters azimuth, width, and depth to None.

  • Add new Dry Advection example notebook highlighting the new DryAdvection model and comparing it to the Cocip model.

  • Add optional fill_value parameter to VectorDataset.sum.


  • (#80) Fix unit error in wake_vortex.turbulent_kinetic_energy_dissipation_rate. This fix affects the estimate of wake vortex max downward displacement and slightly changes Cocip predictions.

  • Change the implementation of Flight.resample_and_fill so that lat-lon interpolation is linear in time. Previously, the timestamp associated to a waypoint was floored according to the resampling frequency without updating the position accordingly. This caused errors in segment calculations (e.g., true airspeed).


  • Add optional keep_original_index parameter to the Flight.resample_and_fill method. If True, the time original index is preserved in the output in addition to the new time index obtained by resampling.

  • Improve docstrings in wake_vortex module

  • Rename wake_vortex functions to remove get_ prefix at the start of each function name.

  • Add pytest command line parameter --regenerate-results to regenerate static test fixture results. Automate in make recipe make pytest-regenerate-results.

  • Update handling of GeoVectorDataset.required_keys the GeoVectorDataset constructor. Add class variable GeoVectorDataset.vertical_keys for handing the vertical dimension.

  • Rename CocipParam.max_contrail_depth -> CocipParam.max_depth.

  • Add units.dt_to_seconds function to convert np.timedelta64 to float seconds.

  • Rename thermo.p_dz -> thermo.pressure_dz.


Add experimental support for simulating radiative effects due to contrail-contrail overlap.


  • Support simulating contrail contrail overlap when running the Cocip model with a Fleet source. The contrail_contrail_overlapping and dz_overlap_m parameters govern the overlap calculation. This mode of calculation is still experimental and may change in future releases.

  • Rewrite the pycontrails.models.cocip.output modules into a single pycontrails.cocip.output_formats module. The new module supports flight waypoint summary statistics, contrail waypoints summary statistics, gridded outputs, and time-slice outputs.

  • Add new GeoVectorDataset.to_lon_lat_grid method. This method can be thought of as a partial inverse to the MetDataset.to_vector method. The current implementation is brittle and may be revised in a future release.


  • Extend Models.set_source_met to allow interpolation_q_method="cubic-spline" when working with MetDataset source (ie, so-called gridded models). Previously a NotImplementedError was raised.

  • Ensure the Flight.copy implementation works with Fleet instances as well.

  • Avoid looping over keys twice in VectorDataset.broadcast_attrs. This is a slight performance enhancement.

  • Fix Fleet signature for compatibility with Flight.

  • Fix a few hard-coded assumptions in broadcasting aircraft performance and emissions when running Cocip with a Fleet source. The previous implementation did not consider the possibility of aircraft performance variables on and Flight.attrs separately.


  • Add optional raise_error parameter to the VectorDataset.broadcast_attrs method.

  • Update Fleet internals.



  • Narrow type hints on the ABC AircraftPerformance model. The AircraftPerformance.eval method requires a Flight object for the source parameter.

  • In PSFlight.eval, explicitly set any aircraft performance data at waypoints with zero true airspeed to np.nan. This avoids numpy RuntimeWarnings without affecting the results.

  • Fix corner-case in the polygon.buffer_and_clean function in which the polygon created by buffering the opencv contour is not valid. Now a second attempt to buffer the polygon is made with a smaller buffer distance.

  • Ignore RuntimeError raised in scipy.optimize.newton if the maximum number of iterations is reached before convergence. This is a workaround for occasional false positive convergence warnings. The pycontrails use-case may be related to this GitHub issue.

  • Update the Models.__init__ warnings when humidity_scaling is not provided. The previous warning provided an outdated code example.

  • Ensure the interpolation_q_method used in a parent model is passed into the humidity_scaling child model in the Models.__init__ method. If the two interpolation_q_method values are different, a warning is issued. This could be extended to other model parameters in the future.


  • Enable ExponentialBoostLatitudeCorrectionHumidityScaling humidity scaling for the model parameter interpolation_q_method="cubic_spline".

  • Add GFS notebook example.

Breaking changes#

  • Remove ExponentialBoostLatitudeCorrectionHumidityScalingParams. These parameters are now hard-coded in the ExponentialBoostLatitudeCorrectionHumidityScaling model.


Breaking changes#

  • By default, call xr.open_mfdataset with lock=False in the MetDataSource.open_dataset method. This helps alleviate a dask threading issue similar to this GitHub issue.


  • Support MetDataset source in the HistogramMatching humidity scaling model. Previously only GeoVectorDataset sources were explicitly supported.

  • Replace np.gradient with dask.array.gradient in the tau_cirrus module. This ensures that the computation is done lazily for dask-backed arrays.

  • Round to 6 digits in the polygon.determine_buffer function. This avoid unnecessary warnings for rounding errors.

  • Fix type hint for opencv-python


  • Take more care with float and int types in the contrail_properties module. Prefer np.clip to np.where or np.maximum for clipping values.

  • Support air_temperature in CocipGrid verbose formation outputs.

  • Remove pytest-timeout dev dependency.


Support for the Poll-Schumann aircraft performance model.


  • Implement a basic working version of the Poll-Schumann (PS) aircraft performance model. This is experimental and may undergo revision in future releases. The PS Model currently supports the following 53 aircraft types:

    • A30B

    • A306

    • A310

    • A313

    • A318

    • A319

    • A320

    • A321

    • A332

    • A333

    • A342

    • A343

    • A345

    • A346

    • A359

    • A388

    • B712

    • B732

    • B733

    • B734

    • B735

    • B736

    • B737

    • B738

    • B739

    • B742

    • B743

    • B744

    • B748

    • B752

    • B753

    • B762

    • B763

    • B764

    • B77L

    • B772

    • B77W

    • B773

    • B788

    • B789

    • E135

    • E145

    • E170

    • E195

    • MD82

    • MD83

    • GLF5

    • CRJ9

    • DC93

    • RJ1H

    • B722

    • A20N

    • A21N

    The “gridded” version of this model is not yet implemented. This will be added in a future release.

  • Improve the runtime of instantiating the Emissions model by a factor of 10-15x. This translates to a time savings of several hundred milliseconds on modern hardware. This improvement is achieved by more efficient parsing of the underlying static data and by deferring the construction of the interpolation artifacts until they are needed.

  • Automatically use a default engine type from the aircraft type in the Emissions model if an engine_uid parameter is not included on the source. This itself is configurable via the use_default_engine_uid parameter on the Emissions model. The default mappings from aircraft types to engines is included in pycontrails/models/emissions/static/default-engine-uids.csv.

Breaking changes#

  • Remove the Aircraft dataclass from Flight instantiation. Any code previously using this should instead directly pass additional attrs to the Flight constructor.

  • The load_factor is now required in AircraftPerformance models. The global DEFAULT_LOAD_FACTOR constant in pycontrails.models.aircraft_performance provides a reasonable default. This is currently set to 0.7.

  • Use a takeoff_mass parameter in AircraftPerformance models if provided in the source.attrs data.

  • No longer use a reference mass ref_mass in AircraftPerformance models. This is replaced by the takeoff_mass parameter if provided, or calculated from operating empty operating mass, max payload mass, total fuel consumption mass, reserve fuel mass, and the load factor.


  • Remove the fuel parameter from the Emissions model. This is inferred directly from the source parameter in Emissions.eval.

  • Fix edge cases in the jet.reserve_fuel_requirements implementation. The previous version would return nan for some combinations of fuel_flow and segment_phase variables.

  • Fix a spelling mistake: units.kelvin_to_celcius -> units.kelvin_to_celsius.


  • Use ruff in place of pydocstyle for linting docstrings.

  • Use ruff in place of isort for sorting imports.

  • Update the AircraftPerformance template based on the patterns used in the new PSFlight class. This may change again in the future.


Support experimental interpolation against gridded specific humidity. Add new data-driven humidity scaling models.


  • Add new experimental interpolation_q_method field to the ModelParams data class. This parameter controls the interpolation methodology when interpolation against gridded specific humidity. The possible values are:

    • None: Interpolate linearly against specific humidity. This is the default behavior and is the same as the previous behavior.

    • "cubic-spline": Apply cubic-spline scaling to the interpolation table vertical coordinate before interpolating linearly against specific humidity.

    • "log-q-log-p": Interpolate in the log-log domain against specific humidity and pressure.

    This interpolation parameter is used when calling pycontrails.core.models.interpolate_met. It can also be used directly with the new lower-level pycontrails.core.models.interpolate_gridded_specific_humidity function.

  • Add new experimental HistogramMatching humidity scaling model to match RHi values against IAGOS observations. The previous HistogramMatchingWithEckel scaling is still available when working with ERA5 ensemble members.

  • Add new tutorial discussing the new specific humidity interpolation methodology.

Breaking changes#

  • Add an optional q_method parameter to the pycontrails.core.models.interpolate_met function. The default value None agrees with the previous behavior.

  • Change function signatures in the module for consistency. The interp_kwargs parameter is now unpacked in the calc_timestep_meterology signature. Rename kwargs to interp_kwargs where appropriate.

  • Remove the cache_size parameter in MetDataset.from_zarr. Previously this parameter allowed the user to wrap the Zarr store in a LRUCacheStore to improve performance. Changes to Zarr internals have broken this approach. Custom Zarr patterns should now be handled outside of pycontrails.


  • Recompute and extend quantiles for histogram matching humidity scaling. Quantiles are now available for each combination of q_method and the following ERA5 data products: reanalysis and ensemble members 0-9. This data is available as a parquet file and is packaged with pycontrails.

  • Fix the precomputed Eckel coefficients. Previous values where computed for different interpolation assumptions and were not correct for the default interpolation method.

  • Clip the scaled humidity values computed by the humidity_scaling.eckel_scaling function to ensure that they are non-negative. Previously, both relative and specific humidity values arising from Eckel scaling could be negative.

  • Handle edge case of all NaN values in the T_critical_sac function in the module.

  • Avoid extraneous copy when calling VectorDataset.sum.

  • Officially support numpy v1.25.0.

  • Set a pytest-timeout limit for tests in tests/unit/ to avoid hanging tests.

  • Add forecast_step parameter to the ACCF model.


  • Refactor auxillary functions used by HistogramMatchingWithEckel to better isolated histogram matching from Eckel scaling.

  • Refactor intersect_met method in pycontrails.core.models to handle experimental q_method parameter.

  • Include a q_method field in Model.interp_kwargs.

  • Include precomputed humidity lapse rate values in the new pycontrails.core.models._load_spline function.

  • Move the module into its own subdirectory within pycontrails/models.


Re-release of v0.42.1.



  • Add new HistogramMatchingWithEckel experimental humidity scaling model. This is still a work in progress.

  • Add new Flight.fit_altitude method which uses piecewise linear fitting to smooth a flight profile.

  • Add new pycontrails.core.flightplan module for parsing ATC flight plans between string and dictionary representations.

  • Add new airports and flightplan examples.

Breaking changes#

  • No longer attach empty fields “sdr”, “rsr”, “olr”, “rf_sw”, “rf_lw”, “rf_net” onto the source parameter in Cocip.eval when the flight doesn’t generate any persistent contrails.

  • Remove params humidity_scaling, rhi_adj_uncertainty, and rhi_boost_exponent_uncertainty from CocipUncertaintyParams.

  • Change the default value for parallel from True to False in xr.open_mfdataset. This can be overridden by setting the xr_kwargs parameter in ERA5.open_metdataset.


  • Fix a unit test ( that occasionally hangs. There may be another test in that suffers from the same issue.

  • Fix issue encountered in Cocip.eval when concatenating contrails with inconsistent values for _out_of_bounds. This is only relevant when running the model with the experimental parameter interpolation_use_indices=True.

  • Add a Fleet.max_distance_gap property. The previous property on the Flight class was not applicable to Fleet instances.

  • Fix warning in Flight class to correctly suggest adding kwarg drop_duplicated_times.

  • Fix an issue in the VectorDataset constructor with a data parameter of type pd.DataFrame. Previously, time data was rewritten to the underlying DataFrame. This could cause copy-on-write issues if the DataFrame was a view of another DataFrame. This is now avoided.


  • When possible, replace type hints np.ndarray -> np.typing.NDArray[np.float_] in the cocip, cocip_params, cocip_uncertainty, radiative_forcing, and wake_vortex modules.

  • Slight performance enhancements in the radiative_forcing module.

  • Change the default value of u_wind and v_wind from None to 0 in Flight.segment_true_airspeed. This makes more sense semantically.


Phase 1 of the Spire datalib, which contains functions to identify unique flight trajectories from the raw Spire ADS-B data.


  • Add a pycontrails.core.airport module to read and process the global airport database, which can be used to identify the nearest airport to a given coordinate.

  • Add a pycontrails.datalib.spire.clean function to remove and address erroneous waypoints in the raw Spire ADS-B data.

  • Add a pycontrails.datalib.spire.filter_altitude function to remove noise in cruise altitude.

  • Add a pycontrails.datalib.spire.identify_flights function to identify unique flight trajectories from ADS-B messages.

  • Add a pycontrails.datalib.spire.validate_trajectory function to check the validity of the identified trajectories from ADS-B messages.

  • Add a FlightPhase integer Enum in the flight module. This includes a new level_flight flight phase.


  • Add unit tests providing examples to identify unique flights.

  • Rename flight._dt_waypoints -> flight.segment_duration.

  • Move jet.rate_of_climb_descent -> flight.segment_rocd.

  • Move jet.identify_phase_of_flight -> flight.segment_phase.

  • Update FlightPhase to be a dictionary enumeration of flight phases.

  • Add references to traffic library.


Improve polygon algorithms.


  • Rewrite the polygon module to run computation with opencv in place of scikit-image for finding contours. This change improves the algorithm runtime and fixes some previous unstable behavior in finding nested contours. For an introduction to the methodology, see the OpenCV contour tutorial.

Breaking changes#

  • Completely rewrite the polygon module. Replace the “main” public function polygon.find_contours_to_depth with polygon.find_multipolygon. Replace the polygon.contour_to_lat_lon function with polygon.multipolygon_to_geojson. Return shapely objects when convenient to do so.

  • Convert continuous data to binary for polygon computation.

  • Remove parameters min_area_to_iterate and depth in the MetDataArray.to_polygon_feature method. The depth parameter has been replaced by the boolean interiors parameter. Add a properties parameter for adding properties to the Polygon and MultiPolygon features. The max_area and epsilon parameters are now expressed in terms of latitude-longitude degrees.


  • Add opencv-python-headless>=4.5 as an optional “vis” dependency. Some flavor of opencv is required for the updated polygon algorithms.




Support scipy 1.10, improve interpolation performance, and fix many windows issues.


  • Improve interpolation performance by cythonizing linear interpolation. This extends the approach taken in scipy 1.10. The pycontrails cython routines allow for both float64 and float32 grids via cython fused types (the current scipy implementation assumes float64). In addition, interpolation up to dimension 4 is supported (the scipy implementation supports dimension 1 and 2).

  • Officially support scipy 1.10.

  • Officially test on windows in the GitHub Actions CI.

  • Build custom wheels for python 3.9, 3.10, and 3.11 for the following platforms:

    • Linux (x86_64)

    • macOS (arm64 and x86_64)

    • Windows (x86_64)

Breaking changes#

  • Change MetDataset and MetDataArray conventions: underlying dimension coordinates are automatically promoted to float64.

  • Change how datetime arrays are converted to floating values for interpolation. The new approach introduces small differences compared with the previous implementation. These differences are significant enough to see relative differences in CoCiP predictions on the order of 1e-4.


  • Unit tests no longer raise errors when the pycontrails-bada package is not installed. Instead, some tests are skipped.

  • Fix many numpy casting issues encountered on windows.

  • Fix temp file issues encountered on windows.

  • Officially support changes in xarray 2023.04 and pandas 2.0.


  • Make the interpolation module more aligned with scipy 1.10 enhancements to the RegularGridInterpolator. In particular, grid coordinates now must be float64.

  • Use cibuildwheel to build wheels for Linux, macOS (arm64 and x86_64), and Windows on release in Github Actions. Allow this workflow to be triggered manually to test the release process without actually publishing to PyPI.

  • Simplify interpolation with pre-computed indices (invoked with the model parameter interpolation_use_indices) via a RGIArtifacts interface.

  • Overhaul much of the interpolation module to improve performance.

  • Slight performance enhancements to the met module.



  • Add geo.azimuth and geo.segment_azimuth functions to calculate the azimuth between coordinates. Azimuth is the angle between coordinates relative to true north on the interval [0, 360).


  • Fix edge case in polygon algorithm by utilizing the fully_connected parameter in measure.find_contours. This update leads to slight changes in interior contours in some cases.

  • Fix hard-coded POSIX path in for windows compatibility.

  • Address PermissionError raised by shutil.copy when the destination file is open in another thread. The copy is skipped and a warning is logged.

  • Fix some unit tests in and for windows compatibility. There are still a few tests that fail on windows (unrelated to changes in this release) that will be fixed in v0.40.0.

  • Allow cachestore=None to skip caching in ERA5, HRES, and GFS interfaces. Previously a default DiskCacheStore was created even when cachestore=None. By default, caching is still enabled.


  • Clean up geo module docstrings.

  • Add Wikipedia reference for Azimuth.

  • Convert MetBase._load to from a class method to a function.



  • Fix docs/examples/CoCiP.ipynb example demonstrating aircraft performance integration

  • Fix unit test caused by breaking change in pyproj 3.5.0


  • Add additional Zenodo metadata

  • Execute notebook examples in Docs Action





  • Update links in the README.

  • Update the release guide to include a checklist of steps to follow when cutting a release.



  • Fix links in documentation website.

  • Deploy build to PyPI (in addition to Test PyPI) on release.





  • Add Apache-2 LICENSE and NOTICE files (#21)

  • Add CONTRIBUTING document

  • Update documentation website Includes install and develop guides, update citations and many other small improvements (#19).

  • Initiate the Github Discussion forum (#22).


  • Fix erroneous docstrings in (#25)


  • Add Github action to push to pypi on tag (#3)

  • Replace flake8 with ruff linter

  • Add nb-clean to pre-commit hooks for example notebooks

  • Add doc8 rst linter and pre-commit hook


Breaking changes#

  • Change default value of epsilon parameter in method MetDataArray.to_polygon_feature from 0.15 to 0.0.

  • Change the polygon simplification algorithm. The new implementation uses shapely.buffer and doesn’t try to preserve the topology of the simplified polygon. This change may result in slightly different polygon geometries.


  • Add depth parameter to MetDataArray.to_polygon_feature to control the depth of the contour searching.

  • Add experimental convex_hull parameter to MetDataArray.to_polygon_feature to control whether to take the convex hull of each contour.

  • Warn if iso_value is not specified in MetDataArray.to_polygon_feature.


  • Consolidate three redundant implementations of standardizing variables into a single met.standardize_variables.

  • Ensure simplified polygons returned by MetDataArray.to_polygon_feature are disjoint. While non-disjoint polygons don’t violate the GeoJSON spec, they can cause problems in some applications.



  • Add citations for ISA calculations

  • Abstract functionality to convert a Dataset or DataArray to longitude coordinates [-180, 180) into core.met.shift_longitude. Add tests for method.

  • Add auto-formatting checks to CI testing


ACCF integration updates


  • Fixes ability to evaluate ACCF model over a MetDataset grid by passing in tuple of (dims, data) when assigning data

  • Fixes minor issues with ACCF configuration and allows more configuration options

  • Updates example ACCF notebook with example of how to set configuration options when evaluating ACCFs over a grid



  • Include “rhi” and “iwc” variables in CocipGrid verbose outputs.


Breaking changes#

  • Update CoCiP unit test static results for breaking changes in tau cirrus calculation. The relative difference in pinned energy forcing values is less than 0.001%.


  • Fix geopotential height gradient calculation in the tau_cirrus module. When calculating finite differences along the vertical axis, the tau cirrus model previously divided the top and bottom differences by 2. To numerically approximate the derivative at the top and bottom levels, these differences should have actually been divided by 1. The calculation now uses np.gradient to calculate the derivative along the vertical axis, which handles this correctly.

  • Make tau cirrus calculation slightly more performant.

  • Include a warning in the suspect IFS._calc_geopotential implementation.


  • Remove _deprecated.tau_cirrus_alt. This function is now the default tau_cirrus calculation. The original tau_cirrus calculation is still available in the _deprecated module.

  • Run flake8 over test modules.