Abstract
Spaceborne Global Navigation Satellite Systems-Reflectometry (GNSS-R) can estimate the geophysical parameters by receiving Earth’s surface reflected signals. The CYclone Global Navigation Satellite System (CYGNSS) mission with eight microsatellites launched by NASA in December 2016, which provides an unprecedented opportunity to rapidly acquire ocean surface wind speed globally. In this paper, a refined spaceborne GNSS-R sea surface wind speed retrieval algorithm is presented and validated with the ground surface reference wind speed from numerical weather prediction (NWP) and cross-calibrated multi-platform ocean surface wind vector analysis product (CCMP), respectively. The results show that when the wind speed was less than 20 m/s, the RMS of the GNSS-R retrieved wind could achieve 1.84 m/s in the case where the NWP winds were used as the ground truth winds, while the result was better than the NWP-based retrieved wind speed with an RMS of 1.68 m/s when the CCMP winds were used. The two sets of inversion results were further evaluated by the buoy winds, and the uncertainties from the NWP-derived and CCMP-derived model prediction wind speed were 1.91 m/s and 1.87 m/s, respectively. The accuracy of inversed wind speeds for different GNSS pseudo-random noise (PRN) satellites and types was also analyzed and presented, which showed similar for different PRN satellites and different types of satellites.
Highlights
Acquiring global high temporal and spatial resolution ocean surface wind field has extremely significant in many fields
The CYclone Global Navigation Satellite System (CYGNSS) dataset became available in March 2017, and the experiments in this work used the V2.1 version of CYGNSS level 1 data downloaded from the Physical Oceanography Distributed Active Archive Center (PO.DAAC)
It can be seen that the accuracy of the inversed wind speed with different pseudo-random noise (PRN) satellites is approximately similar to the two different surface reference wind speed sources and there are no significant differences between the different types of satellites
Summary
Acquiring global high temporal and spatial resolution ocean surface wind field has extremely significant in many fields. Spaceborne GNSS-R is a relatively new remote sensing technique with promising prospects, which receives reflected GNSS signals from the Earth’s surface. With the GNSS-R receiver mounted on a low Earth orbit (LEO) microsatellite, it can form a spaceborne bistatic radar scatterometer to sense wind speed near the sea surface. Through reasonable satellite constellation designing, continuous and rapid measurement of the global sea surface wind speed can be reached, which will effectively compensate for the shortcomings of the traditional monostatic scatterometer and radiometer. In 1996, Katzberg conceived of receiving GNSS signals from ocean surface reflection using receivers mounted on LEO satellites to remotely sense ocean states and ocean surface physical parameters [2]
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