联合空基和地基BDS/GNSS观测反演大气水汽及其在暴雨监测中的应用

The frequent small-scale and short-lived severe weather events have seriously affected the safety of life and property as well as the development of social economy. As an important greenhouse gas, atmospheric water vapor is an important data source for monitoring and forecasting severe weather. This project aims to obtain atmospheric water vapor with high-precision as well as high-spatial and temporal resolution. We will develop the theory and method of combining space-based and ground-based BDS/GNSS to detect water vapor in near real time. The key points are as followings: 1) improving the inversion accuracy of space-based BDS/GNSS radio occultation in low troposphere; 2) the different spatial and temporal resolution of different types of observation in the combination; 3) deriving precise water vapor when the ground BDS/GNSS stations are not equipped with meteorological observations; 4) proposing a combined space-based and ground-based BDS/GNSS three-dimensional water vapor tomography model; 5) the water vapor products are uses to forecast the rainstorm and developing early warning system for severe events. The research results of this project have important scientific significance of application value for improving the theoretical level of detecting the water vapor in real-time, enhancing the ability to cope with extreme weather and promoting the innovative application of the BDS-3.

中小尺度范围、持续时间短的灾害性天气的频发严重影响了人类的生命财产安全和社会经济的发展。作为重要的温室气体，大气水汽是监测和预报灾害性天气的重要信息源。本项目以获得高精度、高时空分辨率大气水汽为主要研究目标，发展联合空基和地基BDS/GNSS近实时探测水汽的理论和方法。重点研究改善空基BDS/GNSS掩星在低对流层反演的精度、不同类观测数据时空分辨率的不一致性、地基BDS/GNSS未配备气象观测时高精度水汽反演、水汽层析模型中若干关键技术难题、建立联合空/地的层析模型和暴雨预警系统，服务于极端天气的监测和预报。本项目的研究成果对提升实时水汽探测理论水平，增强应对极端天气的能力及推动北斗三代导航系统的创新应用，具有重要科学意义和应用价值。

全球气候多变和极端天气事件的频发严重威胁了人类的生存和发展，而高精度、高时空分辨率的大气水汽是监测和预测全球气候变化和灾害性天气的重要信息源。本项目以改善GNSS实时探测水汽时空分布性能为主要研究目标，深入研究融合多源大气观测数据辅助地基GNSS层析探测的理论和方法。首先，改善GNSS无线掩星低对流层中大气产品的反演精度；然后，将无线掩星、探空气球和数值预报的历史资料作为背景场，建立区域性高精度、高动态的天顶对流层干延迟模型、天顶对流层湿延迟模型和大气加权平均温度模型，并准确地确定水汽层顶以及合理地划分层析网格等，力图提高水汽时空变化的探测精度；最后，根据获取的长序列水汽时空分布资料，探索水汽时间序列与降雨量及雾霾PM2.5之间的相关性。该研究成果可服务于空间大地测量学和大气科学等领域，对提高GNSS实时导航定位和增强应对极端天气的能力及推动北斗三代导航系统的创新应用，具有重要科学意义和应用价值。目前本项目已发表标注论文8篇（包括4篇SCI论文、4篇中文核心期刊论文），3项专利，较好地完成了各项拟定目标。