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• GPS TRACKS IN ARC COLKECTOR FULL

Wind speed, direction, MSL and SST are from the European Centre for Medium-Range Weather Forecasts (ECMWF). Therefore, this paper expands more characteristic parameters, including L1 parameters and geophysical parameters such as wind speed, mean sea surface pressure (MSL), sea surface temperature (SST).

GPS TRACKS IN ARC COLKECTOR FULL

Compared with CYGNSS full DDM, L1 compact DDM has a reduced dimension. Based on this, this paper extracts two angle characteristic parameters from DDM. Wind direction will cause the asymmetry of Delay Doppler Map (DDM). Using Cyclone Global Navigation Satellite System (CYGNSS) L1 data with large amount and wide coverage, this paper establishes a sea surface wind direction retrieval model based on three machine learning algorithms. This study proves the potential of GNSS-IR, used as a new operational tool in the automatic meteorological system, to monitor snow disasters over southern China, particularly as an efficient and cost-effective framework for real-time and accurate monitoring.

The 6 h snow depth results also showed a swift and significant response to the snowfall event.

The percentage MAE when snow depths > 5 cm for the three ground surface substances was 26.8%, 53.7%, and 35.0%, respectively. The daily snow depths retrieved from different ground surfaces, i.e., dry grass, wet grass, and concrete, agreed well with the measured snow depth, with Mean Absolute Error (MAE) of 2.79 cm, 3.36 cm, and 2.53 cm, respectively. A snow depth retrieval framework considering data quality control and specific ground surface substances was developed using 8-day data from 13 operational GNSS/Meteorology stations. This study presents a case study to explore utilizing the GNSS-IR-derived snow depth to monitor the 2022 early February snowstorm over southern China. The Global Navigation Satellite System Interferometric Reflectometry (GNSS-IR) technique has been proven to be a practical approach to retrieving snow depth. Snow depth is an essential meteorological indicator for monitoring snow disasters.