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Toward the Generation of a Wind Geophysical Model Function for Spaceborne GNSS-R

AuthorsLin, Wenming ; Portabella, Marcos ; Foti, Giuseppe; Stoffelen, Ad; Gommenginger, Christine; He, Yijun
Issue DateFeb-2019
PublisherInstitute of Electrical and Electronics Engineers
CitationIEEE Transactions on Geoscience and Remote Sensing 57(2): 655-666 (2019)
AbstractThis paper presents a comprehensive procedure to improve the wind geophysical model function (GMF) for the Global Navigation Satellite System Reflectometry (GNSS-R) instrument onboard the TechDemoSat-1 satellite. The observable used to define the GMF is extracted from the measured delay-Doppler maps (DDMs) by correcting for the nongeophysical effects within the measurements. Besides the instrument and the geometric effects as provided in the bistatic radar equation, a calibration term that accounts for the uncalibrated receiver antenna gain and the unknown transmitter antenna gain is proposed to optimize the calculation of GNSS-R observables. Such calibration term is presented as a function of observing elevation and azimuth angles and is shown to remarkably reduce the measurement uncertainties. First, an empirical wind-only GMF is developed using the collocated Advanced Scatterometer (ASCAT) winds and European Centre for Medium-Range Weather Forecasts (ECMWF) model wind output. This empirical GMF agrees well with the model output. Then, the sensitivity of the observable to waves is analyzed using the collocated ECMWF wave parameters. The results show that it is difficult to include mean square slope (MSS) in the development of an empirical GMF, since the difference between ECMWF MSS and the MSS sensed by GNSS-R varies with incidence angle and wind speed. However, it is relevant to take significant wave height (Hs) in account, particularly for low wind conditions. Consequently, a wind/Hs approach is proposed for improved wind retrievals
Description12 pages, 12 figures, 1 table
Publisher version (URL)https://dx.doi.org/10.1109/TGRS.2018.2859191
Identifiersdoi: 10.1109/TGRS.2018.2859191
issn: 0196-2892
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