基于观测约束的地基GPS三维水汽层析技术研究

A study of the ground-based GPS 3D water vapor tomography with radiosonde vertical constraining

全球定位系统(GPS)卫星信号穿过大气层时发生的偏折和延迟,可以用来反演信号传播路径上的大气水汽总量。为获取区域高精度的大气水汽三维分布,借助分布密集的地基GPS观测网及其斜路径水汽观测,建立新的观测约束层析模型,提出以高斯函数为水平约束,区域逐月多年探空观测为垂直约束,即以平均量为先验值,以标准偏差为权重矩阵的新方法;并在层析算法中引入地面观测,以提高整体尤其是低层反演精度。三维水汽层析网格模型基于长江中游鄂东区域的22站地基GPS加密网搭建,实时解算系统可逐时输出三维水汽产品。三维湿折射度和水汽密度可以分别由斜路径的湿延迟总量和水汽总量观测反演获得。以2010年开展的汛期联合加密探空观测为参照,对三维层析的总体反演精度、低层反演精度、层析区域中心与边缘反演精度进行了对比和分析。结果显示:整体样本检验三维水汽密度平均偏差为-0.63 g/m^3,标准偏差为1.22 g/m^3,与探空相关系数为0.98;水汽密度与探空资料的相关比湿折射度与探空资料的相关好;对于不同层析区域,中心区域观测元数量较为丰富,使得位于中心的层析精度好于整体和边缘;加入低层观测的层析结果与探空的相关比未加低层观测时的好,低层观测的加入提高了层析与探空的相关,减小了低层层析标准差、区域中心和2 km以上层析的均差,有效提高了反演精度;低层观测的加入对整体标准差的影响,可能与加剧观测方程中长度矩阵元素间的量级差异有关。

The atmospheric water vapor can be retrieved exactly on certain scales by the deflection and delay of the Navigation Satcllite Timing And Ranging Global Position System（GPS） satellite signal along signal path. Based on the water vapor obscr-vations along the signal paths over the density ground-based GPS network,a new GPS tomography model has been established by using a Gauss function as horizontal constraint and the radiosondc（RS） observation vertical constraint, which includes RS mean values of 4 years as priori information and RS standard deviation as the weight matrix to get the regional high-accuracy three-dimensional （3D） distribution of the atmospheric water vapor. The observations on the ground surface have been used in the tomography formulation to improve the tomographic result accuracy in the overall region, especially the low-level. A 3D water vapor tomographic grid has been designed based on the GPS observation network with 22 GPS sites in the eastern part of Hubei Province in the middle reaches of the Yangtze River. The quasi-real-time retrieval system can provide the hourly output of 3D water vapor density. The 3D wet refraction and water vapor density can be retrieved from the observations of Slant Wet Delay（SWD） and Slant Water Vapor（SWV）, respectively. The accuracy of the retrieval results in the 3D tomography domain of the overall, the low-level, the center and the edge has been analyzed by comparing to the RS observations during the flood season of 2010. The results show that for overall sample tests the 3D water vapor density average deviation is -0.63 g/m3, the standard deviation is 1.22 g/m3, and the correlation coefficient with RS is 0.98. The correlation between the retrieval results for water vapor density and soundings is better than that between those for the wet refraction and RS ohservations, and the correlation hctween RS ohscrvations and the results of water vapor density after joining the ground surface observations is better than those without joining the ground surface observations in the tomography. For the rich observations path of GPS, the accuracy at the center of the tomography domain is better than that in the overall and at the marginal domain. Combined with the ground surface observations, the 3D water vapor retrieval accuracy is improved with enhancing the correlation between tomographic results and RS observations, reducing the standards deviation of tomographic results in low-level of the region, and the average deviation of tomographic results in the center and the layer above 2 km of the region. The magnitude order difference between the elements in the signal length matrix due to the ground surface observation being used in tomography could disturb the stability of the observation equations and thus increase the overall standard deviation.