Abstract
Abstract. Traditionally, balloon-based radiosonde soundings are used to study the spatial distribution of atmospheric water vapour. However, this approach cannot be frequently employed due to its high cost. In contrast, GPS tomography technique can obtain water vapour in a high temporal resolution. In the tomography technique, an iterative or non-iterative reconstruction algorithm is usually utilised to overcome rank deficiency of observation equations for water vapour inversion. However, the single iterative or non-iterative reconstruction algorithm has their limitations. For instance, the iterative reconstruction algorithm requires accurate initial values of water vapour while the non-iterative reconstruction algorithm needs proper constraint conditions. To overcome these drawbacks, we present a combined iterative and non-iterative reconstruction approach for the three-dimensional (3-D) water vapour inversion using GPS observations and COSMIC profiles. In this approach, the non-iterative reconstruction algorithm is first used to estimate water vapour density based on a priori water vapour information derived from COSMIC radio occultation data. The estimates are then employed as initial values in the iterative reconstruction algorithm. The largest advantage of this approach is that precise initial values of water vapour density that are essential in the iterative reconstruction algorithm can be obtained. This combined reconstruction algorithm (CRA) is evaluated using 10-day GPS observations in Hong Kong and COSMIC profiles. The test results indicate that the water vapor accuracy from CRA is 16 and 14% higher than that of iterative and non-iterative reconstruction approaches, respectively. In addition, the tomography results obtained from the CRA are further validated using radiosonde data. Results indicate that water vapour densities derived from the CRA agree with radiosonde results very well at altitudes above 2.5 km. The average RMS value of their differences above 2.5 km is 0.44 g m−3.
Highlights
When GPS signals propagate through the troposphere, they experience a distance delay, which is usually called tropospheric delay
The non-iterative reconstruction technique (NIRT) is applied to derive the water vapour densities at all the voxels using slant water vapour (SWV) values obtained from GPS data, pseudo-observations derived from the COSMIC profiles and horizontal constraints
The computed values are employed as initial values for the IRT to improve the tomography accuracy
Summary
When GPS signals propagate through the troposphere, they experience a distance delay, which is usually called tropospheric delay. The zenith troposphere delay (ZTD) is one of the most important error sources in the GPS signal propagation (Kouba and Héroux, 2001) It contains two parts, namely zenith hydrostatic delay (ZHD) and zenith wet delay (ZWD) (Davis et al, 1985). GPS water vapour tomography has attracted increasing interest in applications such as climate simulation and natural disaster (Jacob et al, 2007; Falconer et al, 2009). The accuracy of IRT solutions is largely dependent on the initial values In view of these disadvantages, Notarpietro et al (2011) jointly used the SIRT-based iterative reconstruction algorithm and the non-iterative reconstruction algorithm with regularisation constraint conditions and non-negative boundary conditions for 3-D troposphere tomography.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
