A new snow depth data set over northern China derived using GNSS interferometric reflectometry from a continuously operating network (GSnow-CHINA v1.0, 2013–2022)

[摘要] The currently available long-term snow depth data sets are eitherfrom point-scale ground measurements or from griddedsatellite/modeled/reanalysis data with coarse spatial resolution, whichlimits the applications in climate models, hydrological models, and regionalsnow disaster monitoring. Benefitting from its unique advantages ofcost-effective and high spatiotemporal resolution ( ∼  1000 m 2 , hourly in theory), snow depth retrieval using the Global Navigation Satellite System Interferometric Reflectometry (GNSS-IR) technique hasbecome a popular topic in recent years. However, due to complexenvironmental and observation conditions, developing robust and operationaltechnology to produce long-term snow depth data sets using observations fromvarious GNSS station networks is still challenging. The two objectives ofthis study are (1) to propose a comprehensive framework using raw data of thecomplex GNSS station networks to retrieve snow depth and control itsquality automatically; and (2) to produce a long-term snow depth data setover northern China (i.e., GSnow-CHINA v1.0, 12 h or 24 h, 2013–2022) using theproposed framework and historical data from 80 stations. The data set hashigh internal consistency with regards to different GNSS constellations(mean r =0 .98, RMSD  =  0.99 cm, and nRMSD (snow depth >  5 cm) =  0.11), different frequency bands (mean r   =  0.97, RMSD  =  1.46 cm, andnRMSD (snow depth >  5 cm) =  0.16), and different GNSS receivers(mean r   =  0.62). The data set also has high external consistency with thein situ measurements and the passive microwave (PMW) product, with aconsistent illustration of the interannual snow depth variability. Additionally, theresult show the potential of GNSS to derive hourly snow depthobservations for better monitoring of snow disasters. The proposed framework todevelop the data set provides comprehensive and supportive information forusers to process raw data of ground GNSS stations with complex environmentalconditions and various observation conditions. The resulting GSnow-CHINAv1.0 data set is distinguished from the current point-scale in situ data orcoarse-gridded data, which can be used as an independent data source forvalidation purposes. The data set is also useful for regional climateresearch and other meteorological and hydrological applications. Thealgorithm and data files will be maintained and updated as more databecome available in the future. The GSnow-CHINA v1.0 data set is availableat the National Tibetan Plateau/Third Pole Environment Data Center via https://doi.org/10.11888/Cryos.tpdc.271839 (Wan et al., 2021).

[学科分类] 眼科学