pycontrails.physics.geo¶
Tools for spherical geometry, solar radiation, and wind advection.
Functions
|
Calculate the latitude of a particle after time |
|
Calculate the pressure level of a particle after time |
|
Calculate the longitude of a particle after time dt caused by advection due to wind. |
|
Calculate angle relative to true north for set of coordinates. |
|
Calculate rectangular direction from spherical azimuth. |
|
Calculate the cosine of the solar zenith angle. |
|
Calculate the days elapsed since the start of the reference year. |
|
Calculate surface area in the provided spatial bounding box. |
|
Calculate coordinates along forward azimuth. |
|
Calculate surface area that is covered by each pixel in a longitude-latitude grid. |
|
Calculate haversine distance between points in (lons0, lats0) and (lons1, lats1). |
|
Calculate the hours elapsed since the start of day (00:00:00 UTC). |
|
Calculate angle with longitudinal axis for sequence of segments. |
Calculate correction to the solar hour angle due to Earth's orbital location. |
|
|
Calculate the orbital position of Earth to a reference point set at the start of year. |
|
Calculate the angle between coordinate segments and the longitudinal axis. |
|
Calculate the angle between coordinate segments and true north. |
|
Calculate haversine distance between consecutive points along path. |
|
Calculate the segment length between coordinates by assuming a great circle distance. |
|
Calculate the solar electromagnetic radiation per unit area from orbital position. |
|
Calculate the solar declination angle from the orbital position in radians (theta_rad). |
|
Calculate the instantaneous theoretical solar direct radiation (SDR). |
|
Calculate the sun's East to West angular displacement around the polar axis. |
|
Construct rectangular spatial bounding box from a set of waypoints. |
- pycontrails.physics.geo.advect_latitude(latitude, v_wind, dt)¶
Calculate the latitude of a particle after time
dt
caused by advection due to wind.Note
It is possible for advected latitude values to lie outside of the WGS84 domain
[-90, 90]
. InCocip
models, latitude values close to the poles create an end of life condition, thereby avoiding this issue. In practice, such situations are very rare.These polar divergence issues could also be addressed by reflecting the longitude values 180 degrees via a spherical equivalence such as
(lon, lat) ~ (lon + 180, 180 - lat)
. This approach is not currently taken.- Parameters:
latitude (
ArrayLike
) – Original latitude, [\(\deg\)]v_wind (
ArrayLike
) – Wind speed in the latitudinal direction, [\(m s^{-1}\)]dt (
numpy.ndarray
) – Advection time delta
- Returns:
ArrayLike
– New latitude value, [\(\deg\)]
- pycontrails.physics.geo.advect_level(level, vertical_velocity, rho_air, terminal_fall_speed, dt)¶
Calculate the pressure level of a particle after time
dt
.This function calculates the new pressure level of a particle as a result of vertical advection caused by the vertical velocity and terminal fall speed.
- Parameters:
level (
ArrayLike
) – Pressure level, [\(hPa\)]vertical_velocity (
ArrayLike
) – Vertical velocity, [\(Pa s^{-1}\)]rho_air (
ArrayLike | float
) – Air density, [\(kg m^{-3}\)]terminal_fall_speed (
ArrayLike | float
) – Terminal fall speed of the particle, [\(m s^{-1}\)]dt (
npt.NDArray[np.timedelta64] | np.timedelta64
) – Time delta for each waypoint
- Returns:
ArrayLike
– New pressure level, [\(hPa\)]
- pycontrails.physics.geo.advect_longitude(longitude, latitude, u_wind, dt)¶
Calculate the longitude of a particle after time dt caused by advection due to wind.
Automatically wrap over the antimeridian if necessary.
- Parameters:
longitude (
ArrayLike
) – Original longitude, [\(\deg\)]latitude (
ArrayLike
) – Original latitude, [\(\deg\)]u_wind (
ArrayLike
) – Wind speed in the longitudinal direction, [\(m s^{-1}\)]dt (
numpy.ndarray
) – Advection timestep
- Returns:
ArrayLike
– New longitude value, [\(\deg\)]
- pycontrails.physics.geo.azimuth(lons0, lats0, lons1, lats1)¶
Calculate angle relative to true north for set of coordinates.
- Parameters:
lons0 (
npt.NDArray[np.float64]
) – Longitude values of initial endpoints, [\(\deg\)].lats0 (
npt.NDArray[np.float64]
) – Latitude values of initial endpoints, [\(\deg\)].lons1 (
npt.NDArray[np.float64]
) – Longitude values of terminal endpoints, [\(\deg\)].lats1 (
npt.NDArray[np.float64]
) – Latitude values of terminal endpoints, [\(\deg\)].
References
- Returns:
npt.NDArray[np.float64]
– Azimuth relative to true north (\(0\deg\)), [\(\deg\)]
See also
- pycontrails.physics.geo.azimuth_to_direction(azimuth_, latitude)¶
Calculate rectangular direction from spherical azimuth.
This implementation uses the equation
cos(latitude) / tan(azimuth) = sin_a / cos_a
to solve for sin_a and cos_a.
- Parameters:
azimuth_ (
npt.NDArray[np.float64]
) – Angle measured clockwise from true north, [\(\deg\)]latitude (
npt.NDArray[np.float64]
) – Latitude value of the point, [\(\deg\)]
- Returns:
tuple[npt.NDArray[np.float64]
,npt.NDArray[np.float64]]
– A tuple of sine and cosine values.
- pycontrails.physics.geo.cosine_solar_zenith_angle(longitude, latitude, time, theta_rad)¶
Calculate the cosine of the solar zenith angle.
Return (\(\cos(\theta)\)), where \(\theta\) is the angle between the sun and the vertical direction.
- Parameters:
longitude (
ArrayLike
) – Longitude, [\(\deg\)]latitude (
ArrayLike
) – Latitude, [\(\deg\)]time (
ArrayLike
) – Time, formatted asnp.datetime64
theta_rad (
ArrayLike
) – Orbital position, [\(rad\)]. Output oforbital_position()
.
- Returns:
ArrayLike
– Cosine of the solar zenith angle
References
- pycontrails.physics.geo.days_since_reference_year(time, ref_year=2000)¶
Calculate the days elapsed since the start of the reference year.
- Parameters:
- Returns:
ArrayLike
– Days elapsed since the reference year. Outputdtype
isnp.float64
.- Raises:
RuntimeError – Raises when reference year is greater than the time of time element
- pycontrails.physics.geo.domain_surface_area(spatial_bbox=(-180.0, -90.0, 180.0, 90.0), spatial_grid_res=0.5)¶
Calculate surface area in the provided spatial bounding box.
- pycontrails.physics.geo.forward_azimuth(lons, lats, az, dist)¶
Calculate coordinates along forward azimuth.
This function is identical to the pyproj.Geod.fwd method when working on a spherical earth. Both signatures are also identical. This implementation is generally more performant.
- Parameters:
lons (
npt.NDArray[np.float64]
) – Array of longitude values.lats (
npt.NDArray[np.float64]
) – Array of latitude values.az (
npt.NDArray[np.float64] | float
) – Azimuth, measured in [\(\deg\)].dist (
npt.NDArray[np.float64] | float
) – Distance [\(m\)] between initial longitude latitude values and point to be computed.
- Returns:
tuple[npt.NDArray[np.float64]
,npt.NDArray[np.float64]]
– Tuple of longitude latitude arrays.
See also
:meth:pyproj.Geod.fwd
- pycontrails.physics.geo.grid_surface_area(longitude, latitude)¶
Calculate surface area that is covered by each pixel in a longitude-latitude grid.
- Parameters:
longitude (
npt.NDArray[np.float64]
) – Longitude coordinates in a longitude-latitude grid, [\(\deg\)]. Must be in ascending order.latitude (
npt.NDArray[np.float64]
) – Latitude coordinates in a longitude-latitude grid, [\(\deg\)]. Must be in ascending order.
- Returns:
xarray.DataArray
– Surface area of each pixel in a longitude-latitude grid, [\(m^{2}\)]
References
- pycontrails.physics.geo.haversine(lons0, lats0, lons1, lats1)¶
Calculate haversine distance between points in (lons0, lats0) and (lons1, lats1).
Handles coordinates crossing the antimeridian line (-180, 180).
- Parameters:
- Returns:
ArrayLike
– Distances between corresponding points. [\(m\)]
Notes
This formula does not take into account the non-spheroidal (ellipsoidal) shape of the Earth. Originally referenced from https://andrew.hedges.name/experiments/haversine/.
References
See also
sklearn.metrics.pairwise.haversine_distances()
Compute the Haversine distance
pyproj.Geod
Performs forward and inverse geodetic, or Great Circle, computations
- pycontrails.physics.geo.hours_since_start_of_day(time)¶
Calculate the hours elapsed since the start of day (00:00:00 UTC).
- pycontrails.physics.geo.longitudinal_angle(lons0, lats0, lons1, lats1)¶
Calculate angle with longitudinal axis for sequence of segments.
- Parameters:
lons0 (
npt.NDArray[np.float64]
) – Longitude values of initial endpoints, [\(\deg\)].lats0 (
npt.NDArray[np.float64]
) – Latitude values of initial endpoints, [\(\deg\)].lons1 (
npt.NDArray[np.float64]
) – Longitude values of terminal endpoints, [\(\deg\)].lats1 (
npt.NDArray[np.float64]
) – Latitude values of terminal endpoints, [\(\deg\)].
References
- Returns:
sin_a (
npt.NDArray[np.float64]
) – Sine values.cos_a (
npt.NDArray[np.float64]
) – Cosine values.
- pycontrails.physics.geo.orbital_correction_for_solar_hour_angle(theta_rad)¶
Calculate correction to the solar hour angle due to Earth’s orbital location.
- Parameters:
theta_rad (
ArrayLike
) – Orbital position, [\(rad\)]- Returns:
ArrayLike
– Correction to the solar hour angle as a result of Earth’s orbital location, [\(\deg\)]
References
Notes
Tested against [NOAA, n.d.]
- pycontrails.physics.geo.orbital_position(time)¶
Calculate the orbital position of Earth to a reference point set at the start of year.
- pycontrails.physics.geo.segment_angle(longitude, latitude)¶
Calculate the angle between coordinate segments and the longitudinal axis.
np.nan is added to the final value so the length of the output is the same as the inputs.
- Parameters:
longitude (
npt.NDArray[np.float64]
) – Longitude values, [\(\deg\)]latitude (
npt.NDArray[np.float64]
) – Latitude values, [\(\deg\)]
- Returns:
tuple[npt.NDArray[np.float64]
,npt.NDArray[np.float64]]
– sin(a), cos(a), wherea
is the angle between the segment and the longitudinal axis. Final entry of each array is set to np.nan.
References
Notes
(lon_2, lat_2) X /| / | / | / | / | / | / | (lon_1, lat_1) X -------> longitude (x-axis)
See also
- pycontrails.physics.geo.segment_azimuth(longitude, latitude)¶
Calculate the angle between coordinate segments and true north.
np.nan is added to the final value so the length of the output is the same as the inputs.
- Parameters:
longitude (
npt.NDArray[np.float64]
) – Longitude values, [\(\deg\)]latitude (
npt.NDArray[np.float64]
) – Latitude values, [\(\deg\)]
- Returns:
npt.NDArray[np.float64]
– Azimuth relative to true north (\(0\deg\)), [\(\deg\)] Final entry of each array is set to np.nan.
References
See also
- pycontrails.physics.geo.segment_haversine(longitude, latitude)¶
Calculate haversine distance between consecutive points along path.
- Parameters:
longitude (
npt.NDArray[np.float64]
) – 1D Longitude values with index corresponding to latitude inputs, [\(\deg\)]latitude (
npt.NDArray[np.float64]
) – 1D Latitude values with index corresponding to longitude inputs, [\(\deg\)]
- Returns:
npt.NDArray[np.float64]
– Haversine distance between (lat_i, lon_i) and (lat_i+1, lon_i+1), [\(m\)] The final entry of the output is set to nan.
See also
- pycontrails.physics.geo.segment_length(longitude, latitude, altitude)¶
Calculate the segment length between coordinates by assuming a great circle distance.
Requires coordinates to be in EPSG:4326. Lengths are calculated using both horizontal and vertical displacement of segments.
np.nan is added to the final value so the length of the output is the same as the inputs.
- Parameters:
longitude (
npt.NDArray[np.float64]
) – Longitude values, [\(\deg\)]latitude (
npt.NDArray[np.float64]
) – Latitude values, [\(\deg\)]altitude (
npt.NDArray[np.float64]
) – Altitude values, [\(m\)]
- Returns:
npt.NDArray[np.float64]
– Array of distances in [\(m\)] between coordinates. Final entry of each array is set to np.nan.
See also
- pycontrails.physics.geo.solar_constant(theta_rad)¶
Calculate the solar electromagnetic radiation per unit area from orbital position.
On average, the extraterrestrial irradiance is 1367 W/m**2 and varies by +- 3% as the Earth orbits the sun.
- Parameters:
theta_rad (
ArrayLike
) – Orbital position, [\(rad\)]. Useorbital_position()
to calculate the orbital position from time input.- Returns:
ArrayLike
– Solar constant, [\(W m^{-2}\)]
References
Notes
\(orbital_effect = (R_{av} / R)^{2}\) where \(R\) is the separation of Earth from the sun and \(R_{av}\) is the mean separation.
- pycontrails.physics.geo.solar_declination_angle(theta_rad)¶
Calculate the solar declination angle from the orbital position in radians (theta_rad).
The solar declination angle is the angle between the rays of the Sun and the plane of the Earth’s equator.
It has a range of between -23.5 (winter solstice) and +23.5 (summer solstice) degrees.
- Parameters:
theta_rad (
ArrayLike
) – Orbital position, [\(rad\)]. Output oforbital_position()
.- Returns:
ArrayLike
– Solar declination angle, [\(\deg\)]
References
Notes
Tested against [NOAA, n.d.]
- pycontrails.physics.geo.solar_direct_radiation(longitude, latitude, time, threshold_cos_sza=0.0)¶
Calculate the instantaneous theoretical solar direct radiation (SDR).
- Parameters:
longitude (
ArrayLike
) – Longitude, [\(\deg\)]latitude (
ArrayLike
) – Latitude, [\(\deg\)]time (
ArrayLike
) – Time, formatted asnp.datetime64
threshold_cos_sza (
float
, optional) – Set the SDR to 0 when thecosine_solar_zenith_angle()
is below a certain value. By default, set to 0.
- Returns:
ArrayLike
– Solar direct radiation of incoming radiation, [\(W m^{-2}\)]
References
- pycontrails.physics.geo.solar_hour_angle(longitude, time, theta_rad)¶
Calculate the sun’s East to West angular displacement around the polar axis.
The solar hour angle is an expression of time in angular measurements: the value of the hour angle is zero at noon, negative in the morning, and positive in the afternoon, increasing by 15 degrees per hour.
- Parameters:
longitude (
ArrayLike
) – Longitude, [\(\deg\)]time (
ArrayLike
) – ArrayLike ofnp.datetime64
timestheta_rad (
ArrayLike
) – Orbital position, [\(rad\)]. Output oforbital_position()
.
- Returns:
ArrayLike
– Solar hour angle, [\(\deg\)]
- pycontrails.physics.geo.spatial_bounding_box(longitude, latitude, buffer=1.0)¶
Construct rectangular spatial bounding box from a set of waypoints.
- Parameters:
longitude (
numpy.ndarray
) – 1D Longitude values with index corresponding to longitude inputs, [\(\deg\)]latitude (
numpy.ndarray
) – 1D Latitude values with index corresponding to latitude inputs, [\(\deg\)]buffer (
float
) – Add buffer to rectangular spatial bounding box, [\(\deg\)]
- Returns:
tuple[float
,float
,float
,float]
– Spatial bounding box,(lon_min, lat_min, lon_max, lat_max)
, [\(\deg\)]
Examples
>>> rng = np.random.default_rng(654321) >>> lon = rng.uniform(-180, 180, size=30) >>> lat = rng.uniform(-90, 90, size=30) >>> spatial_bounding_box(lon, lat) (np.float64(-168.0), np.float64(-77.0), np.float64(155.0), np.float64(82.0))