Climate change and extreme weather are a major threat to the sustainability of our society. Atmospheric water vapor, as an important greenhouse gas, plays a very important role in climate change research and weather forecasting, especially in extreme weather nowcasting. The presence of water vapor can lead to tens of meters range measurement error. Due to the rapid spatiotemporal variation characteristics of water vapor and the limited availability of robust water vapor acquisition techniques, it has been a great worldwide challenge to develop high-quality, high-resolution, multi-sensor based robust water vapor detection method and relevant theory and systematic research. This project will take advantage of the unprecedented development in the next generation GNSS, in particular the latest development and the forthcoming global full deployment of Chinese BeiDou system, as well as the new concept of GNSS+ (multi-sensor technologies) to comprehensively study new theory, new method and innovative applications related to data collection, data processing and big data analytics. Through high-precision detection, inversion and assimilation of the water vapor from different sources a four-dimensional advanced tomography technique will be investigated and a smart integration of ground-based, air and satellite-borne sensor system will be established. Coupled with other satellite remote sensing and meteorological measurements and models, we hope that the outcomes of this research will significantly improve the accuracy of weather forecasts especially the extreme weather events and now-casting capabilities, particularly in urban areas. A new research methodology based on BeiDou GNSS+ for multi-scale climate change analyses will be developed using big data analytics through mining the characteristics of long-term time series of atmospheric retrievals. .The inherent relationship between the mechanism of global and regional water vapor’s occurrence, evolution, precipitation, migration and transportation and climate change and global atmospheric circulation will be investigated by using ground-/air-/space-borne GNSS+ long-term historical measurements and synthetic system information. The project is expected to open new avenues of water vapor detection, measurement and innovative usages and signficiantly strengthen blue-skye research capability and reputation of China and lead the way of GNSS innovation in atmospheric sounding in the world. This research will help us to enhance our ability to respond to climate change and extreme weather events, further improve the navigation and positioning capability and capacity of BeiDou GNSS and promote other scientific innovation. Therefore, the proposed research is of great scientific significance and significant value in technology innovation.
气候变化和极端天气是人类社会可持续发展的重大威胁。作为重要的温室气体,大气水汽是预测全球气候变化、降雨和灾害性天气的重要信息源,也是北斗GNSS等对地观测系统的重要误差源。由于快速的时空变化和观测手段的局限,国际上还没有系统的、稳健的水汽时空分布探测方法和体系。本项目将综合运用新一代空间大地测量技术,研究GNSS+多源空间探测水汽的高精度数据处理理论与方法,构建融合地基、空基、星基、数值天气预报以及其它相关观测手段的综合体系,结合现代智能大数据挖掘与气象模式识别,实现短时极端天气智能预警;基于GNSS长时间历史观测,联合全球大气环流模型,挖掘水汽时间序列气候变化特征,揭示水汽变化与气候变化的联动机理,形成基于天-空-地水汽探测的多尺度气候变化研究新方法。引领该领域的国际前沿研究并提升我国实时水汽探测理论水平,增强应对气候变化和极端天气的能力,推动北斗创新应用,具有重要科学意义和应用价值。
在气候变化的大背景下,极端天气频发,严重威胁了人类社会的可持续发展。水汽作为重要的温室气体,在气候变化和极端天气生成过程中发挥了重要的作用,基于GNSS的大气探测技术具有高精度、高时空分辨率、全球覆盖等优势,为深入挖掘气候变化因子和极端天气短临预警提供了全新的技术手段。本项目综合运用“天-空-地”一体化大气监测手段,系统地研究了GNSS+多源探测水汽的高精度数据处理方法,完善了实时GNSS+水汽探测理论体系,搭建了实时数据处理平台,实现了高精度实时GNSS水汽反演;同时,基于增加多源数据、划分不规则格网等方法,改善了层析方程不适定性问题,提高了三维水汽获取精度,为研究大气水汽的三维运移规律提供了技术支撑。基于高精度的二维和三维水汽信息,揭示了大气水汽与极端天气的相互作用机理,挖掘了极端天气演变过程中大气水汽的响应规律,并且结合人工智能、气象模式识别等技术,构建了基于GNSS水汽数据的极端天气监测和短临预警模型,实现了极端天气短临预警服务。基于GNSS长期历史数据,提出了高精度的一致性检验和修复方法,构建了稳健的GNSS水汽时间序列,揭示了水汽与气候变化的联动机理。本项目的研究成果有力地推动了GNSS技术在气象领域的推广应用,对提升灾害预警能力具有重要科学意义和应用价值。
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数据更新时间:2023-05-31
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