| Summary: | 博士 === 國立中央大學 === 電機工程學系 === 101 === Radio occultation (RO) technique, which has been used in planetary science, is a method to obtain the parameter profiles of the atmosphere. With the advent of Global Positioning System (GPS), to observe the global atmosphere and ionosphere of the Earth becomes possible by using low Earth orbit (LEO) satellites to receive the signal of GPS. In 2006, Taiwan launched six LEO satellites as a RO constellation mission, known as Constellation Observing System for Meteorology, Ionosphere and Climate (FORMOSAT-3/COSMIC, or F-3) and the data of F-3 is used in this thesis. The motivation of this thesis is bring up the methods to understand the influence of atmospheric anomaly, which occurs on the signal trajectory, on the observational and retrieval results in order to increase the retrieval accuracy in the future. In order to reach the motivation, three steps are contained in this thesis: (1) A retrieval algorithm is developed to understand the process of the RO data retrieval; (2) A ray tracing model for GPS signal is proposed to understand the signal propagating process in the atmosphere; (3) The ionospheric sporadic-E (Es) layer is used to be an example of atmospheric anomaly to simulate its influence on the amplitude profile by using ray tracing model and compare with the observational data.
In order to know the influence of atmospheric anomaly on the observational and retrieval results, a retrieval algorithm should be developed first. A retrieval algorithm, NCURO (National Central University Radio Occultation), is developed in this thesis to obtain the information of atmospheric parameter profiles. The focus of the algorithm development is on the correction of the excess phase of the signal received with open loop (OL) technique, and the criteria for assessment of the data quality. When the OL is activated, the excess phase of the GPS signal is modulated with navigation messages of satellites. In our algorithms, two methods are incorporated to recover the excess phase. Moreover, as the altitude of the received signal decreases, the quality of the GPS signal generally deteriorates, and eventually the signal is too noisy to be processed. In order to assess the quality of the signal, instead of the signal-to-noise ratio (SNR), the degree of unclearness is defined and used in the algorithm. In this thesis, the algorithm including the phase correction methods and the criteria for the quality assessment will be described. The data retrieval using the algorithm will be compared with those obtained from CDAAC at UCAR and Pingtung radiosonde measurement. Some intermediate results of the NCURO algorithm will also be demonstrated.
Except considering the atmospheric anomaly influenced on the observational and retrieval results, the influence of atmospheric anomaly on the signal propagation should be known. A three-dimensional ray tracing model for GPS signal is proposed to make simulation conform to the realistic RO signal propagation. In the model, two aiming algorithms are developed to ensure the initial and end points of the ray trajectory located in the prescribed region. In past studies, the ray tracing algorithms are often used to support the retrieval algorithms and assess the impact of data assimilation. The ray tracing techniques applied to the RO signal simulation usually assumed a spherically symmetric atmosphere for simplicity. Also, the exact locations of of GPS and LEO satellites are not considered in the simulation. These two assumptions make the simulation unrealistic for the GPS signal propagation in RO technique. In the proposed model, the shape of the Earth is assumed as an ellipse. The information from European Centre for Medium-Range Weather Forecasts (ECMWF) analysis is used to setup the atmosphere in the simulation. Two aiming algorithms are developed to determine the initial propagating direction of GPS signal. The aiming algorithms will also make the simulated signal start from the prescribed GPS satellite position and end in the close vicinity of the LEO satellite position. The proposed model is examined and demonstrated in the designed simulation using three atmospheric structures: the ideal structure of spherical symmetry, the ECMWF analysis with the consideration of the Earth’s flattening, and the artificial perturbation added in ECMWF analysis which allows consideration of gravity waves and the tropopause. For the ideal atmospheric structure, the fractional difference between real and simulated refractivity results is less than 0.6%. For the ECMWF analysis and the consideration of the Earth’s flattening, all the simulated end points are located in the prescribed region. And for the artificial perturbation added in ECMWF, the simulated results show the corresponding characteristics of the artificial perturbation.
The signal propagating through the ionospheric Es layer, which is an example of atmospheric anomaly, is simulated by using the ray tracing model. The relation between the amplitude of RO signals and the electron density profiles of the ionosphere is simulated and compare with the observational data. Furthermore, the RO data recorded in the time period from mid-2008 to mid-2011 are used for the analysis. Based on the simulation results, the multiple-layer-type (MLT) and the single-layer-type (SLT) Es layers which are defined by the shape of SNR, are used to analyze the global distribution of Es layer. The seasonal MLT Es layer is compared with the seasonal wind shear, which is obtained from the Horizontal Wind Model (HWM07). Furthermore, the seasonal MLT Es layer is compared with the SLT Es layer, and the global altitude distributions of MLT and SLT Es layers are similar while the magnitude distributions are different. Unlike the MLT Es layer, the global distribution of the SLT Es layer is similar to the distribution of E region peak electron density (NmE), which is related to the solar zenith angle.
In this thesis, the ionospheric Es layer is an example to show the influence of atmospheric anomaly on RO data by using ray tracing model. And the influence of the atmospheric anomaly on retrieval results also can be anticipated by using the retrieval algorithm. With the information of the influence caused by atmospheric anomaly, the retrieval algorithm can be corrected and developed to retrieve atmospheric parameter profiles with more accuracy in the future.
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