polar_motion

  • Predicts ocean and load pole tides

Source code

pyTMD.predict.load_pole_tide(t: ndarray, XYZ: Dataset, deltat: float = 0.0, gamma_0: float = 9.80665, omega: float = 7.2921151467e-05, h2: float = 0.6207, l2: float = 0.0836, convention: str = '2018')[source]

Estimate load pole tide displacements in Cartesian coordinates [56]

Parameters:
t: np.ndarray

Days relative to 1992-01-01T00:00:00

XYZ: xarray.Dataset

Dataset with cartesian coordinates

deltat: float or np.ndarray, default 0.0

Time correction for converting to Ephemeris Time (days)

gamma_0: float, default 9.80665

Normal gravity (m s-2)

omega: float, default 7.2921151467e-5

Earth’s rotation rate (radians/second)

h2: float, default 0.6207

Degree-2 Love number of vertical displacement

l2: float, default 0.0836

Degree-2 Love (Shida) number of horizontal displacement

convention: str, default ‘2018’

IERS Mean or Secular Pole Convention

  • '2003'

  • '2010'

  • '2015'

  • '2018'

Returns:
dxt: xr.Dataset

Load pole tide displacements (meters)

pyTMD.predict.ocean_pole_tide(t: ndarray, UXYZ: Dataset, deltat: float = 0.0, gamma_0: float = 9.780325, a_axis: float = 6378136.3, GM: float = 398600441800000.0, omega: float = 7.2921151467e-05, rho_w: float = 1025.0, g2: complex = 0.687 + 0.0036j, convention: str = '2018')[source]

Estimate ocean pole tide displacements in Cartesian coordinates [14, 15, 56]

Parameters:
t: np.ndarray

Days relative to 1992-01-01T00:00:00

UXYZ: xarray.Dataset

Ocean pole tide values from Desai (2002)

deltat: float or np.ndarray, default 0.0

Time correction for converting to Ephemeris Time (days)

a_axis: float, default 6378136.3

Semi-major axis of the Earth (meters)

gamma_0: float, default 9.780325

Normal gravity (m s-2)

GM: float, default 3.986004418e14

Geocentric gravitational constant (m3 s-2)

omega: float, default 7.2921151467e-5

Earth’s rotation rate (radians/second)

rho_w: float, default 1025.0

Density of sea water (kg m-3)

g2: complex, default 0.6870 + 0.0036j

Degree-2 Love number tilt factor (1 + k2 - h2)

convention: str, default ‘2018’

IERS Mean or Secular Pole Convention

  • '2003'

  • '2010'

  • '2015'

  • '2018'

Returns:
dxt: xr.Dataset

Ocean pole tide displacements (meters)

pyTMD.predict.earth_orientation(t: ndarray, deltat: float | ndarray = 0.0)[source]

Compute the variations in earth rotation caused by diurnal and semidiurnal tides [28, 64]

Parameters:
t: np.ndarray

Days relative to 1992-01-01T00:00:00

deltat: float or np.ndarray, default 0.0

Time correction for converting to Ephemeris Time (days)

Returns:
ds: xr.Dataset

Dataset containing:

  • dX: anomaly in polar motion in X (arcseconds)

  • dY: anomaly in polar motion in Y (arcseconds)

  • dUT: anomaly in UT1-TAI (seconds)

pyTMD.predict.length_of_day(t: ndarray, deltat: float | ndarray = 0.0)[source]

Compute the variations in earth rotation caused by long-period (zonal) tides [63]

Parameters:
t: np.ndarray

Days relative to 1992-01-01T00:00:00

deltat: float or np.ndarray, default 0.0

Time correction for converting to Ephemeris Time (days)

Returns:
ds: xr.Dataset

Dataset containing:

  • dUT: anomaly in UT1-TAI (seconds)

  • dLOD: excess LOD (seconds per day)

  • period: period of constituent (days)