基于三维射线追踪算法和多源数据的GNSS水汽层析技术研究

Water vapor is crucial in weather processes such as clouds and precipitation. The real-time three-dimensional water vapor distribution with high space-time resolution plays an important role for the weather forecast and severe weather monitoring. As a powerful complement to traditional water vapor detection, GNSS three-dimensional water vapor tomography has received extensive attention all over the world. However, GNSS water vapor tomography has ill-posed and ill-conditioned problem due to the scarcity and unevenly distributed observation conditions. This project is based on multi-source observations (e.g. multi-GNSS, radiosonde, meteorological data) and the latest ERA5 reanalysis data is used as the background value。 A water vapor tomography model with high accuracy and high resolution is developed based on 3D ray-tracing and algebraic reconstruction technique for Jiangsu province. The optimal weights for multi-source data are selected by considering the data features and humidity density factor. ERA5 and 3D ray-tracing are used to get high accurate slant delays and the GNSS signals pass the sides and with the low elevation angle are also utilized for the water vapor tomography. The algorithm is improved, the optimal voxel distribution is studied and hope to establish a high-temporal resolution water vapor tomography model. This project is useful for the development of GNSS water vapor tomography technology and its application in severe weather such as rainstorm, typhoon etc. monitoring and forecasting in Jiangsu province.

水汽在云、降水等天气过程中起到至关重要的作用，高精度、高时空分辨率的三维水汽数据对于天气预报、灾害天气预警具有重要意义。GNSS三维水汽层析作为传统水汽探测的有力补充，受到国内外广泛关注。由于GNSS观测数据的不足以及CORS站点稀少且分布不均，三维水汽层析存在求解不适定和病态问题。本项目拟基于多源观测数据，包括多模GNSS、无线电探空、气象数据等，以最新的ERA5再分析资料作为背景值，同时使用三维射线追踪、代数重构技术建立适用于江苏省的高精度、高时空分辨率水汽层析模型。项目通过综合考虑数据特征以及水汽密度因子选取最优权重进行多源数据融合，运用ERA5和三维射线追踪技术得到高精度的GNSS斜延迟观测数据，并充分利用反演区域内的GNSS射线包括通过侧面的以及低高度角的射线来改善层析结果，以期获得满足气象需求的高精度高时空分辨率的三维水汽模型，为江苏省暴雨、台风等灾害性天气监测和预报提供保障。

近年来全球气候变化为研究热点，与气象相关的自然灾害频发，造成了大量人员伤亡和经济损失，是人类社会可持续发展的重要威胁。利用GNSS大气探测技术可反演高精度高时空分辨率的水汽三维分布，为气候研究、灾害天气监测等提供重要的数据源。本项目基于多源数据和射线追踪技术，围绕对流层延迟建模和大气水汽精确反演及应用展开了系统性的研究，取得的主要研究成果如下：（1）定量评估了不同再分析产品对流层延迟产品的精度，分析其时空特性。对区域加权平均温度模型进行了精化，提高了大气水汽的反演精度。（2）基于深度学习建立了高精度GNSS水汽预测模型，该模型可准确预测6小时内的水汽数据。基于GNSS数据建立了具有自适应能力的水汽融合模型，并在中国区域的适用性和精度进行了验证。（3）系统研究了射线追踪算法，开发了射线追踪软件，能基于再分析资料和数值天气模式计算对流层延迟，提出了一种利用ERA5和射线追踪算法得到的对流层斜延迟对层析观测增加密度的方法，提高水汽层析结果的稳定性和精度。并进一步评估了利用射线追踪算法进行InSAR大气改正的效果。（4）深入分析了上对流层下对流层水汽对该区域半年周期振荡的贡献，有助于推动水汽数据在气候变化和大气模式中的应用。并联合GNSS水汽、地壳形变数据及GRACE陆地水储量变化，选取洪涝事件进行了相关分析，证明了联合GNSS和GRACE预测洪水的可行性，拓展了GNSS水汽的应用。