Journal of Global Positioning Systems (2007)
Vol.6, No.1: 74-79
An Evaluation of GNSS Radio Occultation Technology for Australian
Meteorology
Erjiang Fu, Kefei Zhang, Falin Wu, Xiaohua Xu and Kaye Marion
Surveying, Positioning and Navigation (SPAN) research group, RMIT University
Anthony Rea, Yuriy Kuleshov, and Gary Weymouth
Australian Bureau of Meteorology, Australia
Abstract. Earth atmospheric information has been
primarily observed by a global network of radiosonde
weather observation stations for global weather
forecasting and climatologic studies for many years.
However, the main disadvantage of this method is that it
can not sufficiently capture the complex dynamics of the
Earth’s atmosphere since its limited and heterogeneous
geographic distribution of launching stations. Since the
first low earth orbit (LEO) satellite equipped with a GPS
receiver was launched in early 1990s, there are more than
a dozen of GPS receivers onboard LEO satellites used for
Earth atmospheric observation. Recent research has
shown that the Global Navigation Satellite System
(GNSS) radio occultation (RO) derived atmospheric
profiles have great potentials to overcome many
limitations of existing atmospheric observation methods.
Constellation Observing Systems for Meteorology,
Ionosphere, and Climate (COSMIC) retrieved
atmospheric profiles are investigated using radiosonde
measurements at 42 collocated stations in the Australian
region. Statistical results show that the difference in
average temperature is about 0.05˚C with a standard
deviation of 1.52˚C and the difference in average pressure
is -1.06 hPa with a standard deviation of 0.91 hPa. This
research has also demonstrated that the GNSS RO
derived atmospheric profiles have good agreement with
the radiosonde observations.
Keywords. Radio Occultation, COSMIC, Radiosonde,
GNSS.
1. Introduction
A network of about 1902 radiosonde weather observation
stations located globally is currently providing the
majority of atmospheric air information for global
weather forecasting and climatologic studies. Radiosonde
weather sensors attached to balloons measure
atmospheric properties (i.e., temperature, pressure and
relative humidity) from the Earth’s surface up to about 30
km altitude of atmosphere. One key problem of the
radiosonde observation network is its limited and
heterogeneous geographic distribution of stations due to,
for example, the difficulty to establish observation
stations over large ocean areas. Moreover, the high cost
of station operation and equipment of radiosonde
observation limits the coverage of the network and
observation frequency. In addition, the direct radiosonde
measurements have sensor-icing problem in the upper
atmosphere (over 10 km height) because of the very low
temperature (Wickert 2004). Therefore, the atmospheric
information currently derived by the radiosonde can not
adequately represent the complex dynamics (in both
space and time) of the Earth’s atmosphere.
GPS RO technique has demonstrated exciting potentials
for weather forecasting and climate studies since the first
LEO satellite equipped with a GPS receiver launched in
the early 1990s (Foelsche et al. 2003; Kirchengast 2002;
Kursinski et al. 1997; Steiner et al. 2001). This technique
has a number of advantages such as global coverage, high
vertical resolution, high accuracy, all weather capability
and calibration-free. Due to these unique advantages, it
has opened new opportunities for various meteorological
and climate related applications and for better
understanding of the Earth’s atmosphere. For example,
GNSS RO data can be used to (Anthes et al. 2000;
Kirchengast 1999; Zhang et al. 2007 (b)):
 Improve forecast accuracy of numerical weather
prediction and climate system studies;
 Provide accurate geopotential heights;
 Reveal the height and shape of the tropopause
on a global scale (an important goal in
atmospheric and climate research);

Fu et al.: An Evaluation of GNSS Radio Occultation Technology for Australian Meteorology 75
 Determine the global distribution of gravity
wave energy from the upper troposphere to
stratosphere;
 Investigate Ĕl Nino events;
 Investigate the global water vapor distribution
and map the atmospheric flow of water vapor;
 Improve the global surface pressure fields; and
 Study the electron density irregularities in the
ionosphere.
The joint effort of Stanford University and JPL in the
early 1960s pioneered the research of (planetary) RO
technique. Currently, more than a dozen of GPS receivers
are equipped onboard LEO satellites on Earth’s orbit (see
Fig. 1 for a historical overview) and they provide
thousands of GPS RO Earth’s atmospheric observations
every day. This new valuable data source can enhance
our knowledge of both Earth atmospheric structure and
processes (Pavelyev et al. 2002; Schmidt et al. 2004).
With the rapid development of the new GNSSs (e.g.,
European Galileo and Chinese Beidou systems) and the
increasing number of GNSS receivers onboard LEO
satellites available, the global coverage and temporal
resolution of such GNSS RO sounding observations will
be improved significantly (Schmidt et al. 2004).
Furthermore, continuing improvements in LEO satellite
orbits determination, space-borne GNSS receivers design,
GNSS signal processing algorithms, data retrieval and
data assimilation methods are boosting the reliability and
applicability of the GNSS RO meteorology technique. In
the near future, the GNSS-based remote observation
method can provide a robust alternative to monitor and
record in real time the Earth’s atmospheric dynamic
information with sufficient accuracy, resolution, and high
spatiotemporal coverage.
Fig. 1. Historical developments of the LEO satellite programs with GPS
receivers for GPS radio occultation meteorology research
Although the GNSS RO meteorology technique has many
advantages over the traditional radiosonde observation
technique, the characteristics of the GNSS RO retrievals
error have to be evaluated properly. Comprehensive
assessment of the GNSS RO retrievals will contribute to
better applications of the new technique and also provide
helpful information for the assimilation of the new data
sources into the current meteorological model systems. A
collaboration research team between Surveying,
Positioning and Navigation (SPAN) research group and
The Australian Bureau of Meteorology has been
investigating in the GNSS RO technique and its
applications in Australia since 2004. Early studies have
demonstrated good agreements of temperature and water
vapour between the CHAMP GPS RO retrievals and
radiosonde observations over four radiosonde weather
stations in Western Australia (Zhang et al. 2007 (a)).
Good results have also been shown in another case study
that evaluates 10 CHAMP RO derived atmospheric
profiles over the whole Australian region using US
National Centres for Environmental Protection (NCEP)
numerical weather model (Fu et al. 2007). These studies
were conducted with few comparison pairs because of the
limited number of GNSS RO retrievals available from
one-satellite-constellation CHAMP, especially for
Australian regional studies.
Since the successful launch of the COSMIC mission with
a constellation of six LEO satellites in April 2006, about
2500 daily GPS RO events globally (see Fig. 2
(Occultation Locations for COSMIC, 2006)) and over
100 daily RO events in Australian region have been
obtained. Such a large number of retrievals bring
unprecedented opportunities for more detailed regional
evaluation studies of the GNSS RO retrievals. Therefore,
a further comparison research was conducted to evaluate
the COSMIC GPS RO retrieved atmospheric profiles
with radiosonde measurements for the whole Australian
area. A total number of 42 coincidences of COSMIC
derived atmospheric profiles and radiosonde observations
are identified using a radial buffer of 100 km and a
temporal buffer of 2-hour during a three-month period
(between January 01 and March 31, 2007). This paper
presents this evaluation study and its corresponding
results.
Fig. 2. A global distribution of typical daily GPS RO events (green dots)
observed by COSMIC, location of radiosonde in red
2. GPS radio occ ul t at ion techni q ue a nd COSMI C
GPS RO events happen when a GPS satellite sets or rises
behind the Earth’s atmospheric limb related to a LEO
satellite and the LEO onboard GPS receiver captures the
delayed signals that traverse the Earth’s atmospheric
limb. Fig. 3 illustrates the geometry of the RO event that

76 Journal of Global Positioning Systems
occurs between the LEO satellite and GPS satellite (2)
pair. The ray path and tangent point can be determined to
a high accuracy based on precise locations of both GPS
and LEO satellites. Tangent point radius ‘г’ and
asymptotic ray miss-distance ‘α’ can be obtained using
the knowledge of precise tangent point location, and the
bending angle ‘а’ can be then calculated.
A profile of bending angles can be processed to a
refractivity index profile by applying an Abel
transformation (Ware et al. 1996). The refractivity is a
function of the electron density in the ionosphere,
temperature, pressure and water vapour in the
atmosphere. Further processing of the refractivity index
provides valuable information on the profile of
temperature, water vapor and pressure in the neutral
atmosphere, and electron density in the ionosphere.
LEO
GPS (1)
GPS (2)
гα
α
а
Earth
Tangent Point
Fig. 3. A schematic demonstration of GPS radio occultation geometry
The COSMIC mission is designed for weather and space
weather forecast, climate monitoring, and atmospheric,
ionospheric and geodesy research by via a constellation
of six LEO satellites equipped with GPS receivers. Its
final orbits are between 750-800 km with an inclination
of 72˚ in 6 planes spaced 24˚ apart (Wu et al. 2005).
Three ground stations are established in Alaska, Sweden
and Taiwan and one multiple task station in Taiwan is for
communicating and controlling satellites.
Each COSMIC satellite is equipped with a GPS RO
payload for tracking GPS signals, a tiny ionospheric
photometer payload for measuring ionospheric total
electron content (TEC) from the satellite’s nadir
direction, and a tri-band beacon payload for generating
high resolution satellite to ground-station TEC (Rocken
et al. 2000). The COSMIC GPS receiver is generated
from NASA/JPL Black Jack space-borne GPS receiver
which was used by CHAMP programs. The integrated
GPS receiver system consists of five units, namely a
scientific grade GPS RO receiver, dual occultation
antennas, dual precision orbit determination antennas,
payload controller and solid state recorder. With the
robust space-borne GPS receiver system, the LEO
satellites’ precise orbit can be well determined and both
the rising and setting GPS RO events can be captured.
COSMIC data products are classified into four classes
(Levels 0, 1A, 1B and 2). Level 0 is raw GPS
measurement data while Level 2 is the final products
including atmospheric refractivity, temperature, pressure
and water vapour pressure profiles. Intermediate products
(Levels 1A and 1B) consist of atmospheric phase delay,
signal amplitude and atmospheric Doppler shifts and
bending angles respectively. In this study, 42
coincidences of the radiosonde atmospheric records and
the COSMIC derived atmospheric profiles (Level 2 data)
are identified using 100 km radial distance buffer and 2
hours temporal buffer based on the radiosonde station
locations and records.
3. Numerical analysis an d discussion
Fig. 4. Distributions of the radiosonde stations (big dots) and COSMIC
RO events (small dots)
The Australian regional atmospheric information is
primarily obtained from 38 radiosonde weather stations
(big dots in Fig. 4). On the other hand, with a window of
latitude [-10˚,-70˚] and longitude [75˚, 170˚] (covers all
the 38 stations), 14,638 COSMIC RO events (small dots
in Fig. 4) were recorded during a 3-month period (from
January 1 to March 31 2007). In order to determine the
comparable pairs, 100 km radial distance buffer and 2
hours temporal buffer based on the radiosonde records
are employed and 42 coincidences are identified.
3.1 Data pre -processing an d overview resu lt
Data pre-processing is a necessary step for data analysis.
Meteorological information, especially for the upper-air
profiles, is extremely dynamic in both space and time.
Consequently, its database is extremely large and
complicated. The three-month COSMIC data sets include
millions of measurements. For an effective management
and analysis of information in such a large database, all
the textfile-based data (i.e., each atmospheric profile is
stored in one TEXT file) is transferred into Oracle
database management system and organized using logical
tables and views. SQL (Structured Query Language)
database functions are designed for automatically data
processing, such as data input and unit conversion.

Fu et al.: An Evaluation of GNSS Radio Occultation Technology for Australian Meteorology 77
Interpolation of the atmospheric profiles is necessary
since the profiles measured by radiosonde and COSMIC
are different in heights. COSMIC has a much better
vertical resolution (about 100 meters) than CHAMP
(about 300 meters) due to the improvements of the
onboard GPS receivers. The radiosonde data acquired
from The Australian Bureau of Meteorology has a
vertical resolution of about 200-meter. Hence, COSMIC
data is interpolated to match with radiosonde data set.
‐2
‐1
0
1
2
3
‐70 ‐60 ‐50 ‐40 ‐30 ‐20 ‐10
Latitude
Temperature(C)
Tempe r at ur e
‐4
‐3
‐2
‐1
0
1
‐70 ‐60 ‐50 ‐40 ‐30 ‐20 ‐10
Latitude
Pr essu r e (mbar)
Pressure
Fig. 5. Temperature (upper plot) and pressure (lower plot) mean
differences of the 42 coincidences against different latitudes
Temperature and dry pressure derived from both
radiosonde and COSMIC are compared at the 42 selected
coincidence samples in the altitude range 0~30km. A
good agreement between the two data sources has been
found. There are 88% matches that have less than 1˚C
mean differences in temperature. The difference in mean
average temperature is about 0.05˚C with a standard
deviation of 1.52˚C. For pressure, 90% samples have less
than 2 hPa mean differences and the average of mean
differences is -1.06 hPa with a standard deviation of 0.91
hPa. Fig. 5 shows the temperature (upper plot) and
pressure (lower plot) mean differences of the 42 pairs
against with their latitudes. Most samples have negative
pressure mean differences which suggest that COSMIC
results have general larger values than radiosonde. It also
can be seen that some larger errors appear in the middle
latitudes. However, this is not conclusive since the
limited numbers of samples are in the lower and higher
altitude regions.
3.2 Homoscedasticity method
Fig. 6 shows the differences of both temperature (upper
plot) and pressure (lower plot) against the heights with a
95% statistical confidence level. These estimates were
obtained by transforming the response variable in each
case so that the assumptions required by the ordinary
least squares estimation procedure for regression models
(in particular the requirement of homoscedasticity for the
residuals of the model) were satisfied. Polynomials of
sufficiently high degree were fitted, the prediction
intervals calculated (that is, the confidence intervals for
the individual response) and the inverse transformation
applied to the fitted curve and the associated prediction
intervals. These graphs present errors’ characteristics and
patterns along their heights. The random errors of the
COSMIC GPS RO temperature retrievals along altitude
are apparent since the mean difference line is close to
zero and nearly parallel to the 95% confidence interval
lines. For pressure, the errors in lower heights are much
greater than those in upper heights and the mean
difference line is always under the zero standard line
which again indicates the smaller COSMIC pressure
retrievals comparing with radiosonde measurements.
Fig. 6. A graph shows 95% confidence interval of the temperature differences (upper plot) and pressure differences (lower plot): The differences (dark
dots), the means (middle line) and the 95% confidence intervals (between upper and lower lines).

78 Journal of Global Positioning Systems
3.3 Spatial and temporal characteristics
Spatial and temporal characteristics of the new data
sources are vital for meteorological research and practical
applications. Spatial representation is an effective way to
illustrate spatial patterns to understand the errors’ spatial
characteristics of the COSMIC GPS RO technique. In
Fig. 7, the temperature error range is between -0.91˚C
and 1.98˚C. Many sites (red dots) have small error, which
is less than 0.5 ˚C; a few have negative and less than -0.5
˚C (green dots), and only a couple of sites have greater
than 1˚C (darker blue dots). From this graph, no spatial
pattern can be identified.
Fig. 7. Temperature differences between radiosonde measurements and
COSMIC derived values
Similarly, Fig. 8 is a map of pressure differences between
radiosonde and COSMIC. Those sites in red dots have
less than 0.5˚C differences. Pink dots in the map
represent those values between – 1˚C and -0.5˚C and
green dots are those from -1˚C up to -1.94 ˚C. From this
figure, it can be seen that the differences between the
COSMIC and radiosonde data are smaller in the higher
latitude regions. However, the conclusion cannot be
justified based on the limited data. Further research
applying more data will be conducted.
Fig. 8. Pressure differences between radiosonde measurements and
COSMIC derived values
4. Conclusions
Continuous and accurate measurements of atmospheric
profiles with good spatial and temporal resolution are
important for numerical weather prediction analysis and
climate related studies. GNSS RO derived atmospheric
profiles have been considered as good data sources for
atmospheric related research. In this study, the quality of
the COSMIC data is assessed with detailed statistical
methods and the outcome of this study shows a very good
agreement with the Australian regional radiosonde data.
Such a large volume of stream-in high resolution
atmospheric profiles will have a tremendous impact on
meteorological studies and applications. Most
importantly, the GNSS RO derived atmospheric profiles
are not restricted by the geographic locations unlike the
radiosonde technique (only 38 stations in Australia).
Therefore, the new data sources derived from the GNSS
RO technique has a great potential to fill up the gaps in
current ground-based weather station networks.
Many countries, such as U.S., German, Austria, Russia,
Finland, Italy, Denmark, Argentina, Brazil and South
Africa, are investigating GNSS RO technique for
meteorological purposes. The importance of applying the
GNSS RO meteorological technique in Australia is clear
since Australia has large but unpopulated areas (limited
weather observation stations), dry continent (better
retrieval results in troposphere) and large areas
surrounded by oceans. SPAN group at RMIT is currently
collaborating with scientists from The Australian Bureau
of Meteorology, UNSW, Wuhan University, Canada and
Taiwan to identify key issues for a long-term research
effort in order to exploit the potential and full benefits of
this emerging and enabling technology for the Australian
community. Further research with newly released
COSMIC data will be employed for long-term and more
detailed evaluation studies. Research on the core data
retrieval techniques that transfer GPS measurements to
atmospheric profiles are being implemented now.
Acknowledgements
The Australian Bureau of Meteorology partially funded
this research and provided radiosonde data. The COSMIC
radio occultation data are collected from NASA. The
early version of this paper was submitted to ION
conference.
References
Anthes, RA, Rocken, C & Kuo, YH (2000) Applications of
COSMIC to meteorology and climate, Terrestrial,
Atmospheric and Oceanic Sciences, vol. 11, no. 1, pp. 115-
56.

Fu et al.: An Evaluation of GNSS Radio Occultation Technology for Australian Meteorology 79
Foelsche, U, Kirchengast, G & Steiner, A (2003) Global
climate monitoring based on CHAMP/GPS radio
occultation data, paper presented to the conference of the
First CHAMP Mission Results for Gravity, Magnetic and
Atmospheric Studies.
Fu, E, Wu, F, Zhang, K, Xu, X, Rea, A, Kuleshov, Y &
Biadeglgne, B (2007) Validation of GNSS Radio
Occultations' Performance Using NCEP Data in
Australia, paper presented to International Global
Navigation Satellite Systems, Sydney, Australia,
December 4-6, 2007.
Kirchengast, G (1999) A simple analytical atmospheric model
for radio Occultation applications, Inst. Meteorol.
Geophys., Univ. of Graz, Austria.
Kirchengast, G (2002) Climate change monitoring by radio
occultation: From simulation studies via CHAMP to
COSMIC and ACE+ constellations, Preprint COSMIC
Radio Occ. Science Workshop, pp. 6.2-1.
Kursinski, ER, Hajj, G, Schofield, JT, Linfield, RP & Hardy, K
(1997) Observing Earth's atmosphere with radio
occultation measurements using the Global Positioning
System, Journal of Geophysical Research, vol. 102, no.
D19, pp. 23429-65.
Occultation Locations for COSMIC (2006), retrieved March 20,
2008 from
http://www.ucar.edu/news/releases/2006/cosmicvisuals.sht
ml
Pavelyev, AA, Liou, YA, Reigber, C, Wickert, J, Igarashi, K,
Hocke, K & Huang, CY (2002) GPS radio holography as
a tool for remote sensing of the atmosphere, mesosphere,
and terrestrial surface from space, GPS Solutions, vol. 6,
no. 1-2, pp. 100-8.
Rocken, C, Kuo, YH, Schreiner, W, Hunt, D, Sokolovskiy, S &
McCormick, C (2000) COSMIC system description,
Terrestrial, Atmospheric and Oceanic Sciences, vol. 11, no.
1, pp. 21-52.
Schmidt, T, Heise, S, Wickert, J, Beyerle, G & Reigber, C
(2004) GPS radio occultation with champ: monitoring of
climate change parameters, Atmospheric Chemisty and
Physics, vol. 4, pp. 7837-57.
Steiner, AK, Kirchengast, G, Foelsche, U, Kornblueh, L,
Manzini, E & Bengtsson, L (2001) GNSS Occultation
Sounding for Climate Monitoring, Physics and Chemistry
of the Earth, Part A: Solid Earth and Geodesy, vol. 26, no.
3, pp. 113-24.
Ware, R, Exner, M, Feng, D, Gorbunov, M, Hardy, K, Herman,
B, Kuo, YH, Meehan, TK, Melbourne, W, Rocken, C,
Schreiner, W, Sokolovskiy, S, Solheim, F, Zou, X, Anthes,
RA, Businger, S & Trenberth, K (1996) GPS sounding of
the atmosphere from low Earth orbit: Preliminary results,
Bulletin of the American Meteorological Society, vol. 77,
no. 1, p. 19
Wickert, J (2004) Comparison of Vertical Refractivity and
Temperature Profiles From CHAMP With Radiosonde
Measurements DMI, Copenhagen.
Wu, BH, Chu, V, Chen, P & Ting, T (2005) FORMOSAT-
3/COSMIC Science Mission Update, GPS Solutions, vol.
9, no. 2, pp. 111-21.
Zhang, K, Biadeglgne, B, Wu, F, Kuleshov, Y, Rea, A, Hodet,
Gd & Fu, E (2007a) A Comparison of Atmospheric
Temperature and Moisture Profiles Derived from GPS
Radio Occultation and Radiosone in Australia, paper
presented to Workshop for Space, Aeronautical and
Navigational Electronics, Perth, Australia, April 12.
Zhang K, Fu, E, Wu, F, Xu, X, Rea, A, Kuleshov, Y &
Biadeglgne, B (2007b) GNSS Radio Occultation for
Weather and Climate Research - A Case Study in
Australia, paper presented to International Global
Navigation Satellite Systems 2007, Sydney, Australia,
December 4-6, 2007.