Remote Sensing of Water Vapor using GPS Data in the Hong Kong Region

This paper focuses on the methodology for accurately remote sensing of the Precipitable Water Vapor using Hong Kong GPS data. The precipitable water vapor is converted from the wet zenith delay in GPS signals. The azimuthal asymmetry of water vapor distribution is modeled by a horizontal gradient. This model has proven to be beneficial to GPS height determination and estimation of wet zenith delay.

Three common zenith hydrostatic delay models, namely Saastamoinen, Hopfield and Black, are calibrated for the accurate determination of dry zenith delay using Hong Kong radiosonde data. The test results indicated that the revised models can remove a 15 millimeter systematic error in local conditions.

The mapping scale factor varies with season and geography, and is dominated by the weighted mean tropospheric temperature. A real-time method for the calculation of the weighted mean tropospheric temperature which is suitable for the Hong Kong region, is developed by using the Sequential Regression Analysis method.

Radiosonde data are treated as a standard to calculate the precipitable water vapor, dry zenith delay and weighted mean tropospheric temperature. The accuracy caused by observed errors is analyzed. The results show that the observed errors cause 1.2 millimeter uncertainty for precipitable water vapor, 2 millimeter dry zenith delay error and 1 K uncertainty for the weighted mean tropospheric temperature.

One-month GPS data have been used to derive the precipitable water vapor in Hong Kong. The GPS-derived result is in good agreement with that from radiosonde data. The actual difference of the precipitable water vapor is less than 2 millimeter for the two techniques. This result also indicates that the ground-based GPS remote sensing technique used in this research is applicable to GPS Meteorology in Hong Kong. Based on these investigations steps for additional research and development will be outlined.