Earthquakes

This module contains functions relating to the processing and representation of earthquakes.

disstans.earthquakes.okada_displacement(station_lla, eq_catalog_row)[source]

For a single station and a single row from the earthquake catalog as defined by okada_prior(), calculate the estimated displacement.

Parameters
Return type

ndarray

Returns

3D displacement in mm.

disstans.earthquakes.okada_prior(network, catalog_path, target_timeseries=None, target_model=None, target_model_regularize=False, no_pbar=False, catalog_prior_kw_args={})[source]

Given a catalog of earthquakes (including moment tensors), calculate an approximate displacement for each of the stations in the network.

If target_timeseries and target_model are passed, the function adds step models to the respective station’s timeseries and models.

Parameters

  • network (Network) – Network instance whose stations should be used.

  • catalog_path (str) – File name of the earthquake catalog to load. Currently, only the Japanese NIED’s F-net earthquake mechanism catalog format is supported.

  • target_timeseries (Optional[str], default: None) – Name of the timeseries to add the model to.

  • target_model (Optional[str], default: None) – Name of the earthquake model added to target_timeseries. Has to be passed if target_timeseries is passed.

  • target_model_regularize (bool, default: False) – Whether to mark the model for regularization or not.

  • no_pbar (bool, default: False) – Suppress the progress bar with True.

  • catalog_prior_kw_args (dict, default: {}) – A dictionary fine-tuning the displacement calculation and modeling, see defaults for explanations and defaults.

Return type

dict[str, list]

Returns

Dictionary of that maps the station names to a list of steptimes.

Notes

This function uses Okada’s [okada92] dislocation calculation subroutines coded in Fortran and wrapped by the Python package okada_wrapper.

The catalog format needs to have the following named columns: Date,Origin_Time(JST),Latitude(°),Longitude(°),JMA_Depth(km),JMA_Magnitude(Mj), Region_Name,Strike,Dip,Rake,Mo(Nm),MT_Depth(km),MT_Magnitude(Mw),Var._Red., mxx,mxy,mxz,myy,myz,mzz,Unit(Nm),Number_of_Stations

The keywords in catalog_prior_kw_args are:

Keyword

Units

Description

mu

GPa

Shear modulus μ of the elastic half space

alpha

-

Medium constant α=(λ+μ)/(λ+2μ), where λ is the first Lamé parameter and μ the second one (shear modulus)

threshold

mm

Minimum amount of calculated displacement that a station needs to surpass in order for a step to be added to the model.

References

okada92

Okada, Y. (1992). Internal deformation due to shear and tensile faults in a half-space. Bulletin of the Seismological Society of America, 82(2), 1018–1040.

disstans.earthquakes.empirical_prior(network, catalog_path, target_timeseries=None, target_model=None, target_model_regularize=False, do_add=True)[source]

Given a catalog of earthquakes, compute whether a station is expected to see a step with the following empirical formula (used by the Geodesy group at UNR, see unr_steps):

\[d < 10^{\text{M}_\text{w} / 2 - 0.8} ~\text{km}\]

where \(d\) is the distance between the earthquake and the station and \(\text{M}_\text{w}\) is the moment magnitude.

If target_timeseries and target_model are passed, the function adds step models to the respective station’s timeseries and models.

Parameters

  • network (Network) – Network instance whose stations should be used.

  • catalog_path (str) – File name of the earthquake catalog to load. Currently, only the Japanese NIED’s F-net earthquake mechanism catalog format is supported.

  • target_timeseries (Optional[str], default: None) – Name of the timeseries to add the model to.

  • target_model (Optional[str], default: None) – Name of the earthquake model added to target_timeseries. Has to be passed if target_timeseries is passed.

  • target_model_regularize (bool, default: False) – Whether to mark the model for regularization or not.

Return type

dict[str, list]

Returns

Dictionary of that maps the station names to a list of steptimes.