geodezyx.athmo package

Submodules

geodezyx.athmo.athmo module

Created on Tue Jul 9 09:23:54 2019

@author: Chaiyaporn Kitpracha

geodezyx.athmo.athmo.PWV_conversion(zwd, Tm)

This function convert from Zenith Wet delay to Precipitate Water Vapor (PWV)

Parameters:

• zwd – Zenith wet delay in meters

• Tm – Mean temperature of troposphere

Returns:

• PWV – Precipitate Water Vapor in mm

• Sources

• ———-

• Solution and Constant k2’ k3 from Atmospheric effects in Space Geodesy Chapter 3.

geodezyx.athmo.athmo.Tm_bevis(Ts)

This function determines mean temperature based on surface temperature using Bevis equation

Parameters:

Ts – Surface temperature in Kelvin

Returns:

• Tm – Mean temperature in Kevlin

• Sources

• ———-

• Atmospheric effects in Space Geodesy Chapter 3.

geodezyx.athmo.athmo.calc_stand_ties(epoc, lat_ref, h_ref, h_rov, p0, t0, e0, unit='mm')

Determine standard atmospheric ties with analytical equation from Teke et al. (2011)

Parameters:

epoc :

time in Python datetime

lat_ref :

Latitude of Ref. station

h_ref :

Height of Ref. station

h_rov :

Height of Rov. station

p0:

Pressure of Ref. station in hPa

t0:

Temperature in C of Ref. station

e0:

Water vapor pressure of Ref. station in hPa

unit :

in meters (m) or milimeters (mm)

Return:

ties :

Standard ties of total delay in milimeters or meters

geodezyx.athmo.athmo.calc_stand_ties_gpt3(epoc, lat_ref, lon_ref, h_ref, lat_rov, lon_rov, h_rov, grid, unit='mm')

Determine standard atmospheric ties from meteological information from GPT3 with analytical equation from Teke et al. (2011)

Parameters:

epoc :

time in Python datetime

lat_ref :

Latitude of Ref. station

lat_rov :

Latitude of Rov. station

h_ref :

Height of Ref. station

h_rov :

Height of Rov. station

grid_file :

meteological grid file

unit :

in meters (m) or milimeters (mm)

Return:

ties :

Standard ties of total delay in milimeters or meters

geodezyx.athmo.athmo.gpt2_5(mjd, lat, lon, HELL, IT, VEC)

(c) Department of Geodesy and Geoinformation, Vienna University of Technology, 2013

The copyright in this document is vested in the Department of Geodesy and Geoinformation (GEO), Vienna University of Technology, Austria. This document may only be reproduced in whole or in part, or stored in a retrieval system, or transmitted in any form, or by any means electronic, mechanical, photocopying or otherwise, either with the prior permission of GEO or in accordance with the terms of ESTEC Contract No. 4000107329/12/NL/LvH. —

This subroutine determines pressure, temperature, temperature lapse rate, mean temperature of the water vapor, water vapour pressure, hydrostatic and wet mapping function coefficients ah and aw, water vapour decrease factor and geoid undulation for specific sites near the Earth surface. It is based on a 5 x 5 degree external grid file (‘gpt2_5.grd’) with mean values as well as sine and cosine amplitudes for the annual and semiannual variation of the coefficients.

The hydrostatic mapping function coefficients have to be used with the height dependent Vienna Mapping Function 1 (vmf_ht.f) because the coefficients refer to zero height.

Example 1 (Vienna, 2 August 2012, with time variation):

dmjd = 56141.d0 dlat(1) = 48.20d0*pi/180.d0 dlon(1) = 16.37d0*pi/180.d0 hell(1) = 156.d0 nstat = 1 it = 0

output: p = 1002.56 hPa T = 22.12 deg Celsius dT = -6.53 deg / km Tm = 281.11 K e = 16.72 hPa ah = 0.0012647 aw = 0.0005726 la = 2.6964 undu = 44.06 m

Example 2 (Vienna, 2 August 2012, without time variation, i.e. constant values):

dmjd = 56141.d0 dlat(1) = 48.20d0*pi/180.d0 dlon(1) = 16.37d0*pi/180.d0 hell(1) = 156.d0 nstat = 1 it = 1

output: p = 1003.49 hPa T = 11.95 deg Celsius dT = -5.47 deg / km Tm = 273.00 K e = 10.23 hPa ah = 0.0012395 aw = 0.0005560 la = 2.6649 undu = 44.06 m

Klemens Lagler, 2 August 2012 Johannes Boehm, 6 August 2012, revision Klemens Lagler, 21 August 2012, epoch change to January 1 2000 Johannes Boehm, 23 August 2012, adding possibility to determine constant field Johannes Boehm, 27 December 2012, reference added Johannes Boehm, 10 January 2013, correction for dlat = -90 degrees

(problem found by Changyong He)

Johannes Boehm, 21 May 2013, bug with dmjd removed (input parameter dmjd was replaced unintentionally; problem found by Dennis Ferguson) Gregory Pain, 17 June 2013, adding water vapour decrease factor la Gregory Pain, 01 July 2013, adding mean temperature Tm Gregory Pain, 30 July 2013, changing the method to calculate the water vapor partial pressure (e) Gregory Pain, 31 July 2013, correction for (dlat = -90 degrees, dlon = 360 degrees) Johannes Boehm, 27 December 2013, copyright notice added Johannes Boehm, 25 August 2014, reference changed to Boehm et al. in GPS Solutions

Source

J. Böhm, G. Möller, M. Schindelegger, G. Pain, R. Weber, Development of an improved blind model for slant delays in the troposphere (GPT2w), GPS Solutions, 2014, doi:10.1007/s10291-014-0403-7

Notes

Modified for Python by: Chaiyaporn Kitpracha

Parameters:

mjd:

modified Julian date (scalar, only one epoch per call is possible)

lat:

ellipsoidal latitude in degrees

lon:

longitude in degrees

HELL:

ellipsoidal height in m

IT:

case 1: no time variation but static quantities

case 0: with time variation (annual and semiannual terms)

VEC:

GPT2 grid data in numpy array size 5 x 5 degree (‘gpt2_5.grd’)

Returns:

p:

pressure in hPa

T:

temperature in degrees Celsius

dT:

temperature lapse rate in degrees per km

e:

water vapour pressure in hPa

undu:

geoid undulation in m

geodezyx.athmo.athmo.gpt3(dtin, lat, lon, h_ell, C, it=0)

This subroutine determines pressure, temperature, temperature lapse rate, mean temperature of the water vapor, water vapour pressure, hydrostatic and wet mapping function coefficients ah and aw, water vapour decrease factor, geoid undulation and empirical tropospheric gradients for specific sites near the earth’s surface. It is based on a 5 x 5 degree external grid file (‘gpt3_5.grd’) with mean values as well as sine and cosine amplitudes for the annual and semiannual variation of the coefficients.

Parameters:

dtin :

datatime in Python datetime object

lat:

ellipsoidal latitude in radians [-pi/2:+pi/2]

lon:

longitude in radians [-pi:pi] or [0:2pi]

h_ell:

ellipsoidal height in m

it:

case 1 no time variation but static quantities, case 0 with time variation (annual and semiannual terms)

Returns:

p:

pressure in hPa

T:

temperature in degrees Celsius

dT:

temperature lapse rate in degrees per km

Tm:

mean temperature weighted with the water vapor in degrees Kelvin

e:

water vapour pressure in hPa

ah:

hydrostatic mapping function coefficient at zero height (VMF3)

aw:

wet mapping function coefficient (VMF3)

la:

water vapour decrease factor

undu:

geoid undulation in m

Gn_h:

hydrostatic north gradient in m

Ge_h:

hydrostatic east gradient in m

Gn_w:

wet north gradient in m

Ge_w:

wet east gradient in m

Notes

Modified for Python by Chaiyaporn Kitpracha

Source

(c) Department of Geodesy and Geoinformation, Vienna University of Technology, 2017

The copyright in this document is vested in the Department of Geodesy and Geoinformation (GEO), Vienna University of Technology, Austria. This document may only be reproduced in whole or in part, or stored in a retrieval system, or transmitted in any form, or by any means electronic, mechanical, photocopying or otherwise, either with the prior permission of GEO or in accordance with the terms of ESTEC Contract No. 4000107329/12/NL/LvH.

D. Landskron, J. Böhm (2018), VMF3/GPT3: Refined Discrete and Empirical Troposphere Mapping Functions, J Geod (2018) 92: 349., doi: 10.1007/s00190-017-1066-2. Download at: https://link.springer.com/content/pdf/10.1007%2Fs00190-017-1066-2.pdf

geodezyx.athmo.athmo.read_grid_gpt(grid_name, cols=64)

geodezyx.athmo.athmo.trop_saast(p, dlat, hell, t=0, e=0, mode='dry')

This subroutine determines the zenith total delay based on the equation by Saastamoinen (1972) as refined by Davis et al. (1985)

Parameters:

• p – pressure in hPa

• dlat – ellipsoidal latitude in radians

• t – temperature in Celcius

• e – water vapor pressure in hPa

• hell – ellipsoidal height in meters

• mode – dry, wet or total

Returns:

• res – zenith total delay in m (depend on mode)

• Source

• ———- – c Reference: Saastamoinen, J., Atmospheric correction for the troposphere and stratosphere in radio ranging of satellites. The use of artificial satellites for geodesy, Geophys. Monogr. Ser. 15, Amer. Geophys. Union, pp. 274-251, 1972. Davis, J.L, T.A. Herring, I.I. Shapiro, A.E.E. Rogers, and G. Elgered, Geodesy by Radio Interferometry: Effects of Atmospheric Modeling Errors on Estimates of Baseline Length, Radio Science, Vol. 20, No. 6, pp. 1593-1607, 1985.

geodezyx.athmo.athmo.vmf1(ah, aw, dt, dlat, zd)

This subroutine determines the VMF1 (Vienna Mapping Functions 1) for specific sites.

Parameters:

• ah – hydrostatic coefficient a

• aw – wet coefficient a

• dt – datetime in python datetime

• dlat – ellipsoidal latitude in radians

• zd – zenith distance in radians

Returns:

• vmf1h – hydrostatic mapping function

• vmf1w – wet mapping function

• Reference

• ———-

• Boehm, J., B. Werl, H. Schuh (2006), Troposphere mapping functions for GPS and very long baseline interferometry

• from European Centre for Medium-Range Weather Forecasts operational analysis data,

• J. Geoph. Res., Vol. 111, B02406, doi (10.1029/2005JB003629.)

Notes

Written by Johannes Boehm, 2005 October 2

Translated to python by Chaiyaporn Kitpracha

geodezyx.athmo.vmf1_compute module

Python translation of the VMF1G computation Fortran modules.

This module provides atmospheric delay computation functions for geodetic applications using Vienna Mapping Function 1 Gridded (VMF1G) data.

Translated from Fortran modules: - get_vmf1g_values.f90 - compute_vmf1g_values.f90 - get_orography.f90 - sd_vmf1_grid_elevation.f90 - sd_gmf.f90 - sd_gpt.f90 - jour_julien_ff.f90 - calend1.f90

Author: Translated to Python Original Fortran authors: FF, FR, Johannes Boehm

geodezyx.athmo.vmf1_compute.compute_vmf1g_values(data_dir: str, year: int, month: int, day: int, hh: int, min_val: int, sec: int, lat: float, lon: float, h: float, el: float) → Dict[str, float]

Main function to compute VMF1G atmospheric delay values.

Parameters:

data_dirstr

Directory containing VMF1G data files

year, month, dayint

Calendar date

hh, min_val, secint

Time (hour, minute, second)

lat, lonfloat

Latitude and longitude in degrees

hfloat

Ellipsoidal height in meters

elfloat

Elevation angle in degrees

Returns:

dict : Dictionary containing computed atmospheric delay values

geodezyx.athmo.vmf1_compute.get_orography(orography_file: str, lat: float, lon: float) → ndarray

Get orographic heights for the 4 grid nodes surrounding a location.

Parameters:

orography_filestr

File containing orography data

lat, lonfloat

Latitude and longitude in degrees

Returns:

np.ndarray : Orographic heights for 4 grid nodes

geodezyx.athmo.vmf1_compute.get_vmf1g_values(data_dir: str, year: int, month: int, day: int, sec: float, lat: float, lon: float) → Dict[str, float | ndarray]

Get VMF1G values for a given location and time.

Parameters:

data_dirstr

Directory containing VMF1G data files

year, month, dayint

Calendar date

secfloat

Seconds since midnight

lat, lonfloat

Latitude and longitude in degrees

Returns:

dict : Dictionary containing VMF1G grid data and interpolation parameters

geodezyx.athmo.vmf1_compute.main()

Main function to run VMF1G computation from command line or interactive input.

geodezyx.athmo.vmf1_compute.sd_gmf(dmjd, dlat, dlon, dhgt, zd)

Python translation of sd_gmf subroutine Determines Global Mapping Functions GMF

Parameters:

dmjdfloat

modified julian date

dlatfloat

latitude in radians

dlonfloat

longitude in radians

dhgtfloat

height in m

zdfloat

zenith distance in radians

Returns:

gmfhfloat

hydrostatic mapping function

gmfwfloat

wet mapping function

geodezyx.athmo.vmf1_compute.sd_gmf_simple(dmjd: float, dlat: float, dlon: float, dhgt: float, zd: float) → Tuple[float, float]

Determine Global Mapping Functions (GMF).

Parameters:

dmjdfloat

Modified Julian date

dlatfloat

Latitude in radians

dlonfloat

Longitude in radians

dhgtfloat

Height in m

zdfloat

Zenith distance in radians

Returns:

tuple : (gmfh, gmfw) - hydrostatic and wet mapping functions

geodezyx.athmo.vmf1_compute.sd_gpt(dmjd, dlat, dlon, dhgt)

Python translation of sd_gpt subroutine Determines Global Pressure and Temperature

Parameters:

dmjdfloat

modified julian date

dlatfloat

latitude in radians

dlonfloat

longitude in radians

dhgtfloat

ellipsoidal height in m

Returns:

presfloat

pressure in hPa

tempfloat

temperature in Celsius

undufloat

Geoid undulation in m

geodezyx.athmo.vmf1_compute.sd_gpt_simple(dmjd: float, dlat: float, dlon: float, dhgt: float) → Tuple[float, float, float]

Determine Global Pressure and Temperature based on Spherical Harmonics.

Parameters:

dmjdfloat

Modified Julian date

dlatfloat

Latitude in radians

dlonfloat

Longitude in radians

dhgtfloat

Ellipsoidal height in m

Returns:

tuple : (pressure in hPa, temperature in Celsius, geoid undulation in m)

geodezyx.athmo.vmf1_compute.sd_vmf1_grid_elevation(ah: float, aw: float, dmjd: float, dlat: float, ht: float, zd: float) → Tuple[float, float]

Determine VMF1 (Vienna Mapping Functions 1) with height correction.

Parameters:

ahfloat

Hydrostatic coefficient a

awfloat

Wet coefficient a

dmjdfloat

Modified Julian date

dlatfloat

Latitude in radians

htfloat

Ellipsoidal height in meters

zdfloat

Zenith distance in radians

Returns:

tuple : (vmf1h, vmf1w) - hydrostatic and wet mapping functions