HR: 0800h
AN: G51C-0857    [Abstracts]
TI: Using spatially-variable wind fields derived from GPS zenith wet delay timeseries to compensate atmospheric phase signatures in SAR interferograms
AU: * Onn, F
EM: phae@stanford.edu
AF: Electrical Engineering Department, Stanford University, U.S.A, 322 Packard Building 350 Serra Mall, Stanford, CA 94305 United States
AU: Zebker, H A
EM: zebker@stanford.edu
AF: Electrical Engineering Department, Stanford University, U.S.A, 322 Packard Building 350 Serra Mall, Stanford, CA 94305 United States
AB: Fluctuations in the distribution of water vapor near the surface of the earth causes variations in neutral atmospheric refractive index. These fluctuations appear as excess delays in Global Positioning System (GPS) signals and as phase shifts in Interferometric Synthetic Aperture Radar (InSAR) images. Because the neutral atmospheric medium affects the propagation of GPS and SAR signals in comparable ways, we use timeseries of observations of zenith wet delay (ZWD) from a network of continuous GPS stations operating in the area imaged by a spaceborne SAR to correct atmospheric phase signatures observed in a radar interferogram of the study area. We interpolate spatial samples of GPS ZWD to derive maps of atmospheric delay which we subtract from the observed atmospheric phase in the SAR interferogram. We interpolate ZWD samples recorded in a virtual network of GPS data generated by applying Taylor's ``frozen-flow'' hypothesis to ZWD measurements recorded before and after the SAR acquisition instances. The ``frozen-flow'' hypothesis is used in a stochastic transport model for integrated refractivity fields, which assumes that the observed timeseries of ZWD at a fixed GPS site consists of a superposition of ``frozen-in'' refractivity fields moving across the study area under the action of a slowly-varying mean wind field. The measured relative time delays between pairs of ZWD timeseries permit calculation of the wind field as a function of time. These spatially-variable wind field estimates are then used to translate GPS ZWD measurements observed before and after the radar acquisition times to equivalent spatial samples on the grid of the radar interferogram. Thus, we infer a denser distribution of ZWD samples from GPS than is possible by considering GPS delay measurements acquired only at the SAR observation times. We find that the atmospheric delay map generated by interpolation of the virtual network of GPS ZWD observations results in lower rms error than the corresponding map generated from GPS data recorded only at the satellite SAR times. We compare the resulting spatial disribution of GPS ZWD samples with colocated observations InSAR differential to verify our estimates of wind fields. We also compare our estimates of wind with in situ measurements of surface layer wind obtained from National Weather Service (NWS) meteorological stations operating in the study area.
DE: 0689 Wave propagation (2487, 3285, 4275, 4455, 6934)
DE: 1220 Atmosphere monitoring with geodetic techniques (6952)
DE: 1240 Satellite geodesy: results (6929, 7215, 7230, 7240)
DE: 1295 Integrations of techniques
DE: 3270 Time series analysis (1872, 4277, 4475)
SC: Geodesy [G]
MN: Fall Meeting 2005