Path Delays in the Neutral Atmosphere - Atmospheric Effects in Space Geodesy - page 84

Ta b l e 2 Availability of pressure values from local recordings at the sites, from numerical weather
models (e.g. the hydrostatic zenith delays from ECMWF data as provided by the Vienna University
of Technology), and from the empirical model GPT
Pressure Local recordings Grid values GPT

Availability At sites All (by interpolation) All

Time span Per observation Since 1994 Unlimited

5 ◦ Spatial resolution Per site 2 . 0x2 . Spherical harmonics (9/9)

Time resolution Per observation 6 h Annual

height factor) at five latitude bands which are symmetric w.r.t. the equator (similar
to the Niell Mapping Functions (Niell 1996 )). Input parameters for GPT are station
latitude, longitude, height and the day of the year, which is similar to the Global
Mapping Functions (GMF; Böhm et al. 2006a ) as both, GPT and GMF, are based on
spherical harmonics up to degree and order 9.
Table 2 summarizes some properties of the pressure values (or zenith hydrosta-
tic delays) from different sources. Unfortunately, local pressure measurements are
usually not available, in particular at GNSS stations. Thus, to get consistent values
of a priori zenith hydrostatic delays for global GNSS networks it is preferable to
take these values from numerical weather models. For example, the Department of
Geodesy and Geoinformation (GEO) at the Vienna University of Technology pro-
vides zenith hydrostatic delays calculated from ECMWF data. These are provided
on global grids (2

0 ◦ ) and with a temporal resolution of 6 h starting in
1994 (Böhm et al. 2009a ). For scientific purposes also forecast values are made avail-
able so that they can be used for real-time applications without significant loss of
accuracy (Böhm et al. 2009b ). Empirical models like GPT are always available for
all time epochs, but the spatial resolution is limited as it is represented by spherical
harmonics up to degree and order 9 (

5 ◦ . times 2 .

20 ◦ in latitude/longitude), respectively. The
model only includes an annual variation with the zero phase set to 28 January, so
it cannot capture short-term and sub-annual weather phenomena. As an example,
Fig. 5 shows pressure values at station O'Higgins in Antarctica. It is evident that
empirical models like the model by Berg ( 1948 ) or GPT cannot describe the short
term pressure variations and that the model by Berg ( 1948 ) is offset by about 20 hPa.
We have also compared and validated the empirical models Berg and GPT with
pressure values from the ECMWF on global grids (10 ◦

≈

5 ◦ in
longitude) (Böhm et al. 2009a ). The comparison was performed for the year 2005
and the temporal resolution was 10 days (i.e. one global grid was taken every 10 days
and consequently 36 grids were used for the statistics). An error in the pressure of
1 hPa corresponds (at sea level) to approximately a 2.3 mm error in the L h . This error
will result in an error in the position—especially the vertical component - estimated
with a space geodetic technique. In Sect. 4.2 a rule of thumb relating the error in the
delay to the error in the vertical coordinate is presented, from this we find that 3 hPa
(7 mm zenith delay error) correspond to 1 mm station height difference. It was found
that the Berg model has large deficiencies especially around Antarctica, resulting in

in latitude times 12 .