Scientific Applications of GPS in Taiwan

by
Y.A. Liou

The Global Positioning System (GPS) has been applied in a wide range of applications in Taiwan, which may be divided into two major categories based on the platform of the receivers, namely ground-based and space-borne approaches.

For the ground-based approach, the island-wide GPS network of 16 receivers was established in 1989 as shown in Figure 1, and has been continuously providing measurements since 1990. After the destructive 1999 Chi-Chi earthquake (Mw 7.5), the number of GPS permanent network stations has been constantly and rapidly increasing at a rate of roughly 30 GPS receivers per year. At the time of the publication of this report, there are about 120 permanent station receivers around the island, while the number is expected to reach 200 in 2005. The network will become the densest (roughly one station per 180 km²) in the world after its setup is completed. Since most of the GPS network stations are equipped with surface meteorological measurement systems co-located with the weather station sites, its data can be used to extract atmospheric water vapor in addition to its tectonic applications. For the space-borne approach, Taiwan and USA space agencies will launch the ROCSAT3/COSMIC (ROC Satellite No. 3/Constellation Observing System for Meteorology, Ionosphere, and Climate) constellation in 2005. The ROCSAT3/COSMIC will consist of six low earth orbit (LEO) satellites that collect the GPS emitted signals occulted by the Earth’s atmosphere.

The Center for Space and Remote Sensing Research (CSRSR) at National Central University is leading in the research of GPS Meteorology on Taiwan. The Center maintains two permanent GPS sites, which, together with the Central Weather Bureau’s GPS stations provide the observation data essential for the investigation in the GPS Meteorology. Figure 2 shows the (a) Trimble 4700 GPS receiver and (b) Paroscientific Met3A Meteorological Measurement System installed by the research center. The Met3A system measures surface temperature, relative humidity, and pressure at high precision accuracy. Currently, the research topics that are covered by the Center include five major fields.

Radio signals emitted by the GPS satellites are delayed by the atmosphere before they are received on the ground. The delay due to the wet component of the troposphere provides the opportunity for sensing water vapor with ground-based GPS. The data are processed using the GPS data processing software developed by the University of Berne to solve the carrier phase observables for excess optical path length (Beutler et al. 1996). Zenith wet delay was subsequently derived by subtracting zenith hydrostatic delay from the excess OPL, and mapped onto PW by a linear conversion scheme proposed by Bevis et al. (1994) where MET3A measurements are needed to derive the wet delay and perform the conversion. The magnitude of the conversion factor ranges from 0.160 in winter to 0.167 in summer based on calculations from 10-year (1988-1997) radiosonde measurements (Liou et al. 2000).

Later, we examined three factors that would influence the accuracy of the sensing of precipitable water (PW) using the Global Positioning System (GPS) in the near tropics. The three factors are the baseline between any two GPS sites, the cutoff angle, and the total water vapor with a vertical column of the atmosphere (Liou et al. 2001). It was concluded that the rms difference between GPS and water vapor radiometer (WVR) observed PW scales with the variability of the total water vapor burden (PW); and accurate absolute PW estimates from the GPS data may be obtained for baseline lengths between 1,500 and 3,000 km at a cutoff angle near 12 degrees.

GPS water vapor sensing is used to monitor the dynamics of the water vapor during severe weather systems (Liou and Huang. 2000). Typhoon Zeb, which caused serious damage in the Philippines, Taiwan, and Japan in mid-October 1998, is used as an example. It took 39 lives, destroyed 30 buildings, and caused agricultural loss of US$170 million in Taiwan. GPS data are analyzed from the Central Weather Bureau’s (CWB’s) three weather stations in Taiwan, and from a site in Tsukuba, Japan. Figure 3 shows the GPS-observed PW time series (Liou and Huang 2000, Liou et al. 2000b). The trend of the GPS-observed PW matches well with those from MM5 simulations and radiosonde observations. The figure demonstrates that PW is, in general, high before and during the occurrence of the typhoon, and low after the typhoon. PW increased from about 5 cm on DoY 285 (October 13) to near 8 cm or so on DoY 288 (October 16) when the typhoon was striking Taiwan, and, then, decreased to 2-3 cm after passage of the typhoon. In addition, GPS-observed PW depletion from 8 cm on DoY 288 to about 3 cm on DoY 290 is found to be consistent with radiosonde observations acquired at the Taipei weather station.

Figure 3. GPS-observed PW time series (Liou and Huang 2000, Liou et al. 2000b)

The accuracy of vertical component in the position determination through the GPS surveying approach is relatively poor due to the highly spatial and temporal variability and inhomogeneity of the water vapor. One way to reduce the impact of this limitation is to take into account and correct the effect of the water vapor in the process of position determination. On the other hand, a detailed water vapor structure is needed to characterize the intensive convective activity of the atmosphere. Apparently, reconstruction of the atmospheric water vapor or refractivity by a tomographic model is required to improve the weather forecasting through assimilating the GPS measured atmospheric wet refractivity into numerical weather prediction models. We developed a tomographic method to reconstruct the 3D wet refractivity structures of the lower troposphere using ground-based GPS measured slant delay based on an observing system simulation experiment (OSSE)-type approach (Liou et al. 2003). The slant delay is derived from reference atmospheric temperature, pressure, and water vapor profiles (or “ground truth”) measured by a multi-channel microwave radiometer, which subsequently serves as reference for comparison with the reconstructed 3D wet delay distribution. A uniformly distributed 5 km by 5 km GPS receivers network is simulated. The distance between two consecutive GPS receivers is 4 km.

Figure 4. The reference profiles of the atmospheric wet refractivity and the root mean square errors (RMSEs) between the reconstructed profiles and the reference for the six hours of concern with given known surface meteorological conditions and null atmospheric wet refractivity conditions at 10 km height

The atmosphere is divided into 11 layers whose thickness is one km, and, hence, consists of 160 cubes (5 by 5 by 11 unknown points). Figure 4 compares the reference profiles of the atmospheric wet refractivity and the root mean square errors (RMSEs) between the reconstructed profiles and the reference for the six hours of concern with given known surface meteorological conditions and null atmospheric wet refractivity conditions at 10 km height. The relative errors of the reconstructed wet refractivity can be as low as 5 to 10% below 3-5 km altitude compared with the ground truth. They can be further decreased when surface meteorological measurements and an assumption of null refractivity at a reasonable height are applied as constraints.

Liou, Y.-A., and C.-Y. Huang, 2000: GPS observation of PW during the passage of a typhoon. Earth, Planets, and Space, 52(10), 709-712.

Liou, Y.-A., C.-Y. Huang, and Y.-T. Teng, 2000: Precipitable water observed by ground-based GPS receivers and microwave radiometry. Earth, Planets, and Space, 52(6), 445-450.

Liou, Y.-A., Cheng-Yung Huang, and Chun-Chieh Wu, “GPS observations of precipitable water dynamics associated with Typhoon Zeb (1998)”, IGARSS2000, Hawaii, U.S.A., July 24-28, 2000b.

Liou, Y.-A., Y.-T. Teng, T. Van Hove, and J. Liljegren, 2001b: Comparison of precipitable water observations in the near tropics by GPS, microwave radiometer, and radiosondes. J. Appl. Meteor, 40(1), 5-15.
 

Author: This article is submitted by Y.A. Liou
Center for Space and Remote Sensing Research, National Central University, Taiwan