Research And Implementation Of GPS Three-dimensional Water Vapor Tomography Algorithm

As a changeable composition in the atmosphere, water vapor plays a very important role in atmospheric energy transport and evolution of weather systems. Therefore, it is of great significance to study the spatial distribution of atmospheric water vapor and its changes over time when it comes to weather monitoring and water cycle research. The traditional measurements of atmospheric water vapor are limited to spatial and temporal resolution, which results lacking the description of the initial moisture field. Luckily, the three-dimensional water vapor chromatographic technique using GPS technology can quickly obtain a three-dimensional tomography vapor special distribution with high spatial and temporal resolution and contribute to the correction and improvement of the initial moisture field in the mode of mesoscale numerical weather prediction.Based on precise point positioning technology, this technique first adopts ground-based GPS water vapor sensing technology for inversion of GPS slant wet delay(SWD). Then, due to additional horizontal and vertical constraints, it establishes the joint observation equation and uses the least squares method and iterative algebraic reconstruction algorithm for water vapor chromatography solver and reconstruction of the three-dimensional water vapor distribution. This thesis is mainly based on the iterative algebraic reconstruction algorithm for the realization of three-dimensional water vapor tomography algorithm and the preparation of corresponding program modules. Next, according to test data, it compares and analyses different results from the algebraic reconstruction algorithm(ART) and the simultaneous algebraic reconstruction algorithm(SIRT), and mainly discusses the choice of initial iteration values and the selection of relaxation factors.Based on GPS three-dimensional water vapor chromatography preparation program, this thesis conducts a three-dimensional water vapor chromatographic test in Hong Kong and the Bohai seas, and obtains corresponding three-dimensional spatial distribution of water vapor. The test results demonstrate that:(1) In the GPS three-dimensional water vapor chromatography test in Hong Kong seas, the root-mean-square-deviations between chromatographic results based on ART and SIRT results and radiosonde data are less than 10mm/km, which means satisfactory results have been achieved. Compared with these two algorithms, they are both accurate, but SIRT algorithm is shorter in solving time. Therefore, in better solving the GPS three-dimensional water vapor tomography, the SIRT algorithm is superior to the ART algorithm.(2) When using the SIRT algorithm to conduct a three-dimensional GPS water vapor tomography experiment, the initial value of MM5 data and radiosonde data can guarantee higher accuracy of atmospheric wet refractive index. When corresponding data are lacking, using the model as the initial value can also guarantee good accuracy.(3) Adopting RMS error as the iterative quality standards to search for optimal relaxation factor in different times and regions, it turns out that the optimal relaxation factor is not fixed and further studies are needed to search for the optimal relaxation factor.