Tropospheric phase delay in interferometric synthetic aperture radar estimated from meteorological model and multispectral imagery

Details Tropospheric phase delay in interferometric synthetic aperture radar estimated from meteorological model and multispectral imagery Tropospheric phase delay in interferometric synthetic aperture radar estimated from meteorological model and multispectral imagery

May 2007

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2007jgrb..11205419p&link_type=abstract

Journal of Geophysical Research, Volume 112, Issue B5, CiteID B05419

Physics

12

Radio Science: Interferometry (1207, 1209, 1242), Geodesy And Gravity: Satellite Geodesy: Technical Issues (6994, 7969), Radio Science: Radar Atmospheric Physics (1220), Radio Science: Remote Sensing

Scientific paper

ENVISAT Medium Resolution Imaging Spectrometer Instrument (MERIS) multispectral data and the mesoscale meteorological model MM5 are used to estimate the tropospheric phase delay in synthetic aperture radar (SAR) interferograms. MERIS images acquired simultaneously with ENVISAT Advanced Synthetic Aperture Radar data provide an estimate of the total water vapor content W limited to cloud-free areas based on spectral bands ratio (accuracy 0.17 g cm-2 and ground resolution 300 m). Maps of atmospheric delay, 2 km in ground resolution, are simulated from MM5. A priori pertinent cumulus parameterization and planetary boundary layer options of MM5 yield near-equal phase correction efficiency. Atmospheric delay derived from MM5 is merged with available MERIS W product. Estimates of W measured from MERIS and modeled from MM5 are shown to be consistent and unbiased and differ by ~0.2 g cm-2 (RMS). We test the approach on data over the Lebanese ranges where active tectonics might contribute to a measurable SAR signal that is obscured by atmospheric effects. Local low-amplitude (1 rad) atmospheric oscillations with a 2.25 km wavelength on the interferograms are recovered from MERIS with an accuracy of 0.44 rad or 0.03 g cm-2. MERIS water product overestimates W in the clouds shadow due to mismodeling of multiple scattering and underestimates W on pixels with undetected semitransparent clouds. The proposed atmospheric filter models dynamic atmospheric signal which cannot be recovered by previous filtering techniques which are based on a static atmospheric correction. Analysis of filter efficiency with spatial wavelength shows that ~43% of the atmospheric signal is removed at all wavelengths.

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