Impact of rain, swell, and surface currents on the electromagnetic bias in GNSS-Reflectometry

The assessment of the electromagnetic (EM) bias is required to predict the performance of upcoming global navigation satellite systems-reflectometry (GNSS-R) altimetry systems, and its impact in data assimilation climate studies. In previous studies, the EM bias in bistatic GNSS-R altimetry (L-band) was numerically estimated for a wind-driven sea surface height spectrum, including the time-domain variability. In the present study, spectral models for the rain, swell, and surface currents are used to compute a perturbed wind-driven sea surface height spectrum, from which a perturbed three-dimensional (3-D) time-evolving wind-driven sea surface height is computed. The generated sea surface is then illuminated by a right hand circular polarization (RHCP) L-band EM wave, and the wave scattered from each facet is computed from each facet using the physical optics (PO) method under the Kirchhoff approximation (KA). Finally, the EM bias is computed numerically as the height of each patch times the forward-scattering coefficient, divided by the average of the forward-scattering coefficient. The impact of rain on the EM bias is a moderate decrease (in magnitude) due to the damping of the large gravity waves, which is more significant as the wind speed increases. The impact of swell is a small increase (in magnitude) mostly due to the change of the local incidence angles. The impact of currents can be either a moderate increase or decrease (in magnitude), depending on the sense of the current with respect to the wind, due to a change in the surface roughness.Peer ReviewedPostprint (author's final draft

Impact of rain, swell, and surface currents on the electromagnetic bias in GNSS-Reflectometry

The assessment of the electromagnetic (EM) bias is required to predict the performance of upcoming global navigation satellite systems-reflectometry (GNSS-R) altimetry systems, and its impact in data assimilation climate studies. In previous studies, the EM bias in bistatic GNSS-R altimetry (L-band) was numerically estimated for a wind-driven sea surface height spectrum, including the time-domain variability. In the present study, spectral models for the rain, swell, and surface currents are used to compute a perturbed wind-driven sea surface height spectrum, from which a perturbed three-dimensional (3-D) time-evolving wind-driven sea surface height is computed. The generated sea surface is then illuminated by a right hand circular polarization (RHCP) L-band EM wave, and the wave scattered from each facet is computed from each facet using the physical optics (PO) method under the Kirchhoff approximation (KA). Finally, the EM bias is computed numerically as the height of each patch times the forward-scattering coefficient, divided by the average of the forward-scattering coefficient. The impact of rain on the EM bias is a moderate decrease (in magnitude) due to the damping of the large gravity waves, which is more significant as the wind speed increases. The impact of swell is a small increase (in magnitude) mostly due to the change of the local incidence angles. The impact of currents can be either a moderate increase or decrease (in magnitude), depending on the sense of the current with respect to the wind, due to a change in the surface roughness.Peer Reviewe

Engineering Calibration and Physical Principles of GNSS-Reflectometry for Earth Remote Sensing

The Cyclone Global Navigation Satellite System (CYGNSS) is a NASA mission that uses 32 Global Positioning System (GPS) satellites as active sources and 8 CYGNSS satellites as passive receivers to measure ocean surface roughness and wind speed, as well as soil moisture and flood inundation over land. This dissertation addresses two major aspects of engineering calibration: (1) characterization of the GPS effective isotropic radiated power (EIRP) for calibration of normalized bistatic radar cross section (NBRCS) observables; and (2) development of an end-to-end calibration approach using modeling and measurements of ocean surface mean square slope (MSS). To estimate the GPS transmit power, a ground-based GPS constellation power monitor (GCPM) system has been built to accurately and precisely measure the direct GPS signals. The transmit power of the L1 coarse/acquisition (C/A) code of the full GPS constellation is estimated using an optimal search algorithm. Updated values for transmit power have been successfully applied to CYGNSS L1B calibration and found to significantly reduce the PRN dependence of CYGNSS L1 and L2 data products. The gain pattern of each GPS satellite’s transmit antenna for the L1 C/A signal is determined from measurements of signal strength received by the 8-satellite CYGNSS constellation. Determination of GPS patterns requires knowledge of CYGNSS patterns and vice versa, so a procedure is developed to solve for both of them iteratively. The new GPS and CYGNSS patterns have been incorporated into the science data processing algorithm used by the CYGNSS mission and result in improved calibration performance. Variable transmit power by numerous Block IIF and IIR-M GPS space vehicles has been observed due to their flex power mode. Non-uniformity in the GPS antenna gain patterns further complicates EIRP estimation. A dynamic calibration approach is developed to further address GPS EIRP variability. It uses measurements by the direct received GPS signal to estimate GPS EIRP in the specular reflected direction and then incorporates them into the calibration of NBRCS. Dynamic EIRP calibration instantaneously detects and corrects for power fluctuations in the GPS transmitters and significantly reduces errors due to GPS antenna gain azimuthal asymmetry. It allows observations with the most variable Block IIF transmitters (approximately 37% of the GPS constellation) to be included in the standard data products and further improves the calibration quality of the NBRCS. A physics-based approach is then proposed to examine potential calibration errors and to further improve the Level 1 calibration. The mean square slope (mss) is a key physical parameter that relates the ocean surface properties (wave spectra) to the CYGNSS measurement of NBRCS. An approach to model the mss for validation with CYGNSS mss data is developed by adding the contribution of a high frequency tail to the WAVEWATCH III (WW3) mss. It is demonstrated that the ratio of CYGNSS mss to modified WW3 mss can be used to diagnose potential calibration errors that exist in the Level 1 calibration algorithm. This approach can help to improve CYGNSS data quality, including the Level 1 NBRCS and Level 2 ocean surface wind speed and roughness. The engineering calibration methods presented in this dissertation make significant contributions to the spatial coverage, calibration quality of the measured NBRCS and the geophysical data products produced by the NASA CYGNSS mission. The research is also useful to the system design, science investigation and engineering calibration of future GNSS-reflectometry missions.PHDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/168052/1/wangtl_1.pd