compute

• Calculates tidal elevations at points and times

  • Can use OTIS format tidal solutions provided by Ohio State University and ESR

  • Can use Global Tide Model (GOT) solutions provided by Richard Ray at GSFC

  • Can use Finite Element Solution (FES) models provided by AVISO

• Calculates tidal currents at points and times

  • Can use OTIS format tidal solutions provided by Ohio State University and ESR

  • Can use Finite Element Solution (FES) models provided by AVISO

• Calculates long-period equilibrium tides (LPET) at points and times

  • Uses the summation of fifteen tidal spectral lines from Cartwright and Edden, (1973)

• Calculates radial pole load tides (LPT) at points and times

  • Following IERS Convention (2010) guidelines

• Calculates radial ocean pole load tides (OPT) at points and times

  • Following IERS Convention (2010) guidelines

• Calculates radial solid earth tides (SET) at points and times

  • Following IERS Convention (2010) guidelines

Calling Sequence

import pyTMD
tide_h = pyTMD.compute.tide_elevations(x, y, delta_time,
    DIRECTORY=DIRECTORY, MODEL=MODEL, EPOCH=(2000,1,1,0,0,0),
    EPSG=3031, TYPE='drift')
tide_uv = pyTMD.compute.tide_currents(x, y, delta_time,
    DIRECTORY=DIRECTORY, MODEL=MODEL, EPOCH=(2000,1,1,0,0,0),
    EPSG=3031, TYPE='drift')

Source code

pyTMD.compute.corrections(x: ndarray, y: ndarray, delta_time: ndarray, CORRECTION: str = 'ocean', **kwargs)

Wrapper function to compute tide corrections at points and times

Parameters

x: np.ndarray

x-coordinates in projection EPSG

y: np.ndarray

y-coordinates in projection EPSG

delta_time: np.ndarray

seconds since EPOCH or datetime array

CORRECTION: str, default ‘ocean’

Correction type to compute

• 'ocean': ocean tide from model constituents

• 'load': load tide from model constituents

• 'LPET': long-period equilibrium tide

• 'LPT': solid earth load pole tide

• 'OPT': ocean pole tide

• 'SET': solid earth tide

**kwargs: dict

keyword arguments for correction functions

Returns

values: np.ndarray

tidal correction at coordinates and time in meters

pyTMD.compute.tide_elevations(x: ndarray, y: ndarray, delta_time: ndarray, DIRECTORY: str | pathlib.Path | None = None, MODEL: str | None = None, ATLAS_FORMAT: str = 'netcdf', GZIP: bool = False, DEFINITION_FILE: str | pathlib.Path | None = None, EPSG: str | int = 3031, EPOCH: list | tuple = (2000, 1, 1, 0, 0, 0), TYPE: str | None = 'drift', TIME: str = 'UTC', METHOD: str = 'spline', EXTRAPOLATE: bool = False, CUTOFF: int | float = 10.0, INFER_MINOR: bool = True, APPLY_FLEXURE: bool = False, FILL_VALUE: float = nan, **kwargs)

Compute ocean or load tides at points and times from model constituents

Parameters

x: np.ndarray

x-coordinates in projection EPSG

y: np.ndarray

y-coordinates in projection EPSG

delta_time: np.ndarray

seconds since EPOCH or datetime array

DIRECTORY: str or NoneType, default None

working data directory for tide models

MODEL: str or NoneType, default None

Tide model to use in correction

ATLAS_FORMAT: str, default ‘netcdf’

ATLAS tide model format

• 'OTIS'

• 'netcdf'

GZIP: bool, default False

Tide model files are gzip compressed

DEFINITION_FILE: str or NoneType, default None

Tide model definition file for use

EPSG: int, default: 3031 (Polar Stereographic South, WGS84)

Input coordinate system

EPOCH: tuple, default (2000,1,1,0,0,0)

Time period for calculating delta times

TYPE: str or NoneType, default ‘drift’

Input data type

• None: determined from input variable dimensions

• 'drift': drift buoys or satellite/airborne altimetry

• 'grid': spatial grids or images

• 'time series': time series at a single point

TIME: str, default ‘UTC’

Time type if need to compute leap seconds to convert to UTC

• 'GPS': leap seconds needed

• 'LORAN': leap seconds needed (LORAN = GPS + 9 seconds)

• 'TAI': leap seconds needed (TAI = GPS + 19 seconds)

• 'UTC': no leap seconds needed

• 'datetime': numpy datatime array in UTC

METHOD: str

Interpolation method

• `bilinear`: quick bilinear interpolation

• `spline`: scipy bivariate spline interpolation

• `linear`, `nearest`: scipy regular grid interpolations

EXTRAPOLATE: bool, default False

Extrapolate with nearest-neighbors

CUTOFF: int or float, default 10.0

Extrapolation cutoff in kilometers

Set to np.inf to extrapolate for all points

INFER_MINOR: bool, default True

Infer the height values for minor tidal constituents

APPLY_FLEXURE: bool, default False

Apply ice flexure scaling factor to height values

Only valid for models containing flexure fields

FILL_VALUE: float, default np.nan

Output invalid value

Returns

tide: np.ndarray

tidal elevation at coordinates and time in meters

pyTMD.compute.tide_currents(x: ndarray, y: ndarray, delta_time: ndarray, DIRECTORY: str | pathlib.Path | None = None, MODEL: str | None = None, ATLAS_FORMAT: str = 'netcdf', GZIP: bool = False, DEFINITION_FILE: str | pathlib.Path | None = None, EPSG: str | int = 3031, EPOCH: list | tuple = (2000, 1, 1, 0, 0, 0), TYPE: str | None = 'drift', TIME: str = 'UTC', METHOD: str = 'spline', EXTRAPOLATE: bool = False, CUTOFF: int | float = 10.0, INFER_MINOR: bool = True, FILL_VALUE: float = nan, **kwargs)

Compute ocean tide currents at points and times from model constituents

Parameters

x: np.ndarray

x-coordinates in projection EPSG

y: np.ndarray

y-coordinates in projection EPSG

delta_time: np.ndarray

seconds since EPOCH or datetime array

DIRECTORY: str or NoneType, default None

working data directory for tide models

MODEL: str or NoneType, default None

Tide model to use in correction

ATLAS_FORMAT: str, default ‘netcdf’

ATLAS tide model format

• 'OTIS'

• 'netcdf'

GZIP: bool, default False

Tide model files are gzip compressed

DEFINITION_FILE: str or NoneType, default None

Tide model definition file for use

EPSG: int, default: 3031 (Polar Stereographic South, WGS84)

Input coordinate system

EPOCH: tuple, default (2000,1,1,0,0,0)

Time period for calculating delta times

TYPE: str or NoneType, default ‘drift’

Input data type

• None: determined from input variable dimensions

• 'drift': drift buoys or satellite/airborne altimetry

• 'grid': spatial grids or images

• 'time series': time series at a single point

TIME: str, default ‘UTC’

Time type if need to compute leap seconds to convert to UTC

• 'GPS': leap seconds needed

• 'LORAN': leap seconds needed (LORAN = GPS + 9 seconds)

• 'TAI': leap seconds needed (TAI = GPS + 19 seconds)

• 'UTC': no leap seconds needed

• 'datetime': numpy datatime array in UTC

METHOD: str

Interpolation method

• `bilinear`: quick bilinear interpolation

• `spline`: scipy bivariate spline interpolation

• `linear`, `nearest`: scipy regular grid interpolations

EXTRAPOLATE: bool, default False

Extrapolate with nearest-neighbors

CUTOFF: int or float, default 10.0

Extrapolation cutoff in kilometers

Set to np.inf to extrapolate for all points

INFER_MINOR: bool, default True

Infer the height values for minor tidal constituents

FILL_VALUE: float, default np.nan

Output invalid value

Returns

tide: dict

tidal currents at coordinates and times

pyTMD.compute.LPET_elevations(x: ndarray, y: ndarray, delta_time: ndarray, EPSG: str | int = 3031, EPOCH: list | tuple = (2000, 1, 1, 0, 0, 0), TYPE: str | None = 'drift', TIME: str = 'UTC', **kwargs)

Compute long-period equilibrium tidal elevations at points and times

Parameters

x: np.ndarray

x-coordinates in projection EPSG

y: np.ndarray

y-coordinates in projection EPSG

delta_time: np.ndarray

seconds since EPOCH or datetime array

EPSG: int, default: 3031 (Polar Stereographic South, WGS84)

Input coordinate system

EPOCH: tuple, default (2000,1,1,0,0,0)

Time period for calculating delta times

TYPE: str or NoneType, default ‘drift’

Input data type

• None: determined from input variable dimensions

• 'drift': drift buoys or satellite/airborne altimetry

• 'grid': spatial grids or images

• 'time series': time series at a single point

TIME: str, default ‘UTC’

Time type if need to compute leap seconds to convert to UTC

• 'GPS': leap seconds needed

• 'LORAN': leap seconds needed (LORAN = GPS + 9 seconds)

• 'TAI': leap seconds needed (TAI = GPS + 19 seconds)

• 'UTC': no leap seconds needed

• 'datetime': numpy datatime array in UTC

FILL_VALUE: float, default np.nan

Output invalid value

Returns

tide_lpe: np.ndarray

long-period equilibrium tide at coordinates and time in meters

pyTMD.compute.LPT_displacements(x: ndarray, y: ndarray, delta_time: ndarray, h: float | numpy.ndarray = 0.0, EPSG: str | int = 3031, EPOCH: list | tuple = (2000, 1, 1, 0, 0, 0), TYPE: str | None = 'drift', TIME: str = 'UTC', ELLIPSOID: str = 'WGS84', CONVENTION: str = '2018', FILL_VALUE: float = nan, **kwargs)

Compute radial load pole tide displacements at points and times following IERS Convention (2010) guidelines

Parameters

x: np.ndarray

x-coordinates in projection EPSG

y: np.ndarray

y-coordinates in projection EPSG

delta_time: np.ndarray

seconds since EPOCH or datetime array

h: float or np.ndarray, default 0.0

height coordinates in meters

EPSG: int, default: 3031 (Polar Stereographic South, WGS84)

Input coordinate system

EPOCH: tuple, default (2000,1,1,0,0,0)

Time period for calculating delta times

TYPE: str or NoneType, default ‘drift’

Input data type

• None: determined from input variable dimensions

• 'drift': drift buoys or satellite/airborne altimetry

• 'grid': spatial grids or images

• 'time series': time series at a single point

TIME: str, default ‘UTC’

Time type if need to compute leap seconds to convert to UTC

• 'GPS': leap seconds needed

• 'LORAN': leap seconds needed (LORAN = GPS + 9 seconds)

• 'TAI': leap seconds needed (TAI = GPS + 19 seconds)

• 'UTC': no leap seconds needed

• 'datetime': numpy datatime array in UTC

ELLIPSOID: str, default ‘WGS84’

Ellipsoid for calculating Earth parameters

CONVENTION: str, default ‘2018’

IERS Mean or Secular Pole Convention

• '2003'

• '2010'

• '2015'

• '2018'

FILL_VALUE: float, default np.nan

Output invalid value

Returns

Srad: np.ndarray

solid earth pole tide at coordinates and time in meters

pyTMD.compute.OPT_displacements(x: ndarray, y: ndarray, delta_time: ndarray, h: float | numpy.ndarray = 0.0, EPSG: str | int = 3031, EPOCH: list | tuple = (2000, 1, 1, 0, 0, 0), TYPE: str | None = 'drift', TIME: str = 'UTC', ELLIPSOID: str = 'WGS84', CONVENTION: str = '2018', METHOD: str = 'spline', FILL_VALUE: float = nan, **kwargs)

Compute radial ocean pole tide displacements at points and times following IERS Convention (2010) guidelines

Parameters

x: np.ndarray

x-coordinates in projection EPSG

y: np.ndarray

y-coordinates in projection EPSG

delta_time: np.ndarray

seconds since EPOCH or datetime array

h: float or np.ndarray, default 0.0

height coordinates in meters

EPSG: int, default: 3031 (Polar Stereographic South, WGS84)

Input coordinate system

EPOCH: tuple, default (2000,1,1,0,0,0)

Time period for calculating delta times

TYPE: str or NoneType, default ‘drift’

Input data type

• None: determined from input variable dimensions

• 'drift': drift buoys or satellite/airborne altimetry

• 'grid': spatial grids or images

• 'time series': time series at a single point

TIME: str, default ‘UTC’

Time type if need to compute leap seconds to convert to UTC

• 'GPS': leap seconds needed

• 'LORAN': leap seconds needed (LORAN = GPS + 9 seconds)

• 'TAI': leap seconds needed (TAI = GPS + 19 seconds)

• 'UTC': no leap seconds needed

• 'datetime': numpy datatime array in UTC

ELLIPSOID: str, default ‘WGS84’

Ellipsoid for calculating Earth parameters

CONVENTION: str, default ‘2018’

IERS Mean or Secular Pole Convention

• '2003'

• '2010'

• '2015'

• '2018'

METHOD: str

Interpolation method

• `bilinear`: quick bilinear interpolation

• `spline`: scipy bivariate spline interpolation

• `linear`, `nearest`: scipy regular grid interpolations

FILL_VALUE: float, default np.nan

Output invalid value

Returns

Urad: np.ndarray

ocean pole tide at coordinates and time in meters

pyTMD.compute.SET_displacements(x: ndarray, y: ndarray, delta_time: ndarray, h: float | numpy.ndarray = 0.0, EPSG: str | int = 3031, EPOCH: list | tuple = (2000, 1, 1, 0, 0, 0), TYPE: str | None = 'drift', TIME: str = 'UTC', ELLIPSOID: str = 'WGS84', TIDE_SYSTEM='tide_free', EPHEMERIDES='approximate', **kwargs)

Compute solid earth tidal elevations at points and times following IERS Convention (2010) guidelines

Parameters

x: np.ndarray

x-coordinates in projection EPSG

y: np.ndarray

y-coordinates in projection EPSG

delta_time: np.ndarray

seconds since EPOCH or datetime array

h: float or np.ndarray, default 0.0

height coordinates in meters

EPSG: int, default: 3031 (Polar Stereographic South, WGS84)

Input coordinate system

EPOCH: tuple, default (2000,1,1,0,0,0)

Time period for calculating delta times

TYPE: str or NoneType, default ‘drift’

Input data type

• None: determined from input variable dimensions

• 'drift': drift buoys or satellite/airborne altimetry

• 'grid': spatial grids or images

• 'time series': time series at a single point

TIME: str, default ‘UTC’

Time type if need to compute leap seconds to convert to UTC

• 'GPS': leap seconds needed

• 'LORAN': leap seconds needed (LORAN = GPS + 9 seconds)

• 'TAI': leap seconds needed (TAI = GPS + 19 seconds)

• 'UTC': no leap seconds needed

• 'datetime': numpy datatime array in UTC

ELLIPSOID: str, default ‘WGS84’

Ellipsoid for calculating Earth parameters

TIDE_SYSTEM: str, default ‘tide_free’

Permanent tide system for the output solid Earth tide

• 'tide_free': no permanent direct and indirect tidal potentials

• 'mean_tide': permanent tidal potentials (direct and indirect)

EPHEMERIDES: str, default ‘approximate’

Ephemerides for calculating Earth parameters

• 'approximate': approximate lunisolar parameters

• 'JPL': computed from JPL ephmerides kernel

Returns

tide_se: np.ndarray

solid earth tide at coordinates and time in meters