基于GNSS-R技术的北极黄河站雪深反演研究

Research on Snow Depth Inversion at Arctic Yellow River Station Based on GNSS-R Technique

雪深探测在两极地区的气候和环境变化研究中有重要作用,但现有的观测手段在获取高时空分辨率的雪深资料上有较多的局限性。近年来,利用GNSS多路径信号反演陆地、海洋等表面信息的GNSS-R技术得到广泛重视。在系统分析GNSS-R雪深反演原理的基础上,在中国北极黄河站设计了GNSS-R雪深反演实验,并利用信噪比资料提取了2015年上半年的黄河站雪深变化情况,实验结果表明,GNSS-R雪深反演结果与实测结果吻合很好,这表明GNSS-R技术可以用于极区的雪深探测。

Snow depth detection plays an important role in the research of climate and environment for the polar regions. However, the existing observational approaches have many limitations in snow depth detection. In recent years, GNSS-R technology, which utilizes GNSS multipath signal to retrieve surface information on land and o- cean, has attracted wide attention. In this paper, the snow depth inversion principle of GNSS-R technology is firstly analyzed. A self-designed GNSS-R snow depth Yellow River Station. Finally, the snow depth changes inversion experiment is then carried out at Chinese Arctic in the first half of 2015 are extracted by SNR data. This experimental results show that snow depth derived from GNSS-R is in good agreement with field measurements, which means GNSS-R technology can be used to obtain snow depth in polar regions.