【摘要】 GNSS水汽层析技术凭借其高精度、全天候的探测优势，成为反演高时空大气水汽分布的重要手段。现有GNSS水汽层析模型通常采用均匀离散化方式对三维层析区域进行划分，但由于大气水汽的空间异质性，均匀离散化方法并不符合大气水汽在垂直方向的真实分布特点。本文充分考虑大气水汽的垂直变化规律，提出了一种顾及水汽分布的非均匀离散化GNSS水汽层析精化方法。该方法根据水汽含量的垂直递减特征，构造了基于可降水量变化率的垂直非均匀分层方法，并在不同高度层设置了水平非均匀离散化方案，形成了从地表到对流层顶体素分辨率逐渐减小的非均匀离散化水汽层析模型框架。基于2017年7月香港地区的GNSS实测数据、探空数据和ERA5再分析资料开展了水汽层析试验，结果表明：以探空水汽廓线为参考值，非均匀离散化方法的均方根误差相较于传统方法的3种方案分别降低了21.8%、20.9%、20.5%;以ERA5三维水汽数据为参考值，本文方法对应的整个区域层析结果的RMSE值分别降低了15.4%、11.4%、12.6%。此外，在2 km以下的近地区域，本文方法的层析结果精度也要明显优于传统方法，有望为降雨预报提供更高精度和更高分辨率的近地表三维大气水汽产品。更多还原

【Abstract】 GNSS water vapor tomography technique has become a crucial tool for retrieving atmospheric water vapor distributions with high spatiotemporal resolution, owing to its high precision and all-weather availability. The existing GNSS water vapor tomography method divides the three-dimensional(3D) tomography area with a uniform discretization scheme. However, due to the spatial heterogeneity of atmospheric water vapor, this method does not follow the actual distribution of atmospheric water vapor in the vertical direction. Based on the vertical decreasing tendency of atmospheric water vapor, an improved non-uniform discretized GNSS water vapor tomography method that considers water vapor distributions is proposed. The method analyzes the vertical decreasing characteristics of water vapor content and constructs a vertically non-uniform stratification scheme based on the change rate of precipitable water vapor. Furthermore, a horizontal non-uniform discretization scheme at different altitude layers is set up, forming an uneven discretization tomography framework with the decreasing resolution voxels from the surface to the top of the tomography area. Experiments are conducted using actual GNSS measurements, radiosonde data and ERA5 reanalysis in the Hong Kong region in July 2017. Taking radiosonde water vapor profiles as reference, the root mean square errors(RMSE) of the tomography results obtained from the non-uniform discretization approach are reduced by 21.8%, 20.9%, and 20.5% against three traditional schemes, respectively. Compared with ERA5 data, the RMSE values of the proposed method’s tomography results are reduced by 15.4%, 11.4%, and 12.6%, respectively. Additionally, in the near-surface tomographic region below 2 km, the accuracy of the tomographic results obtained by the proposed method is significantly superior to that of the traditional method, which highlights that the proposed method is expected to provide higher accuracy and higher resolution near-surface 3D atmospheric water vapor products for rainfall forecasting.更多还原