Toward Correcting InSAR Images for Tropospheric Delay A.W. Moore, S.L. Granger, S.E. Owen, F.H. Webb, E.J. Fetzer, E.J. Fielding, E.F. Fishbein Jet Propulsion.

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Presentation transcript:

Toward Correcting InSAR Images for Tropospheric Delay A.W. Moore, S.L. Granger, S.E. Owen, F.H. Webb, E.J. Fetzer, E.J. Fielding, E.F. Fishbein Jet Propulsion Laboratory, California Institute of Technology C.F. Bjorndahl, J. Lofgren Chalmers University of Technology 1.Motivation & Basic Info: InSAR, AIRS, GPS 2.Intercomparison of AIRS and GPS 3.Stretched Boundary Layer algorithm combining ECMWF and DEM 4.Selecting time periods conducive to tropospheric correction

InSAR: differencing two radar images to find the phase difference, and therefore ground displacement. Spatial density can reach 20m. But atmospheric differences between the two images can yield up to 20cm of differential tropospheric delay in the interferogram, obscuring the true signal. Idea: produce a tropo correction map to remove the atmospheric differences from the interferogram. Bock & Williams (1997) suggested use of GPS; limited coverage (few km+) has been a factor. Z. Li & colleagues more recently have investigated use of MERIS and MODIS data – 1kmX1km, but not at night and not in presence of clouds. Motivation: InSAR Basics

AIRS: Atmospheric Infrared Sounder High spectral resolution IR sounder with ~2400 channels. Atmospheric profiles at high vertical resolution. –2 km vertical resolution for water vapor. Nighttime retrievals, + in the presence of up to 70% cloud cover. Twice daily retrievals (ascending and descending nodes) 45km (horizontal) IWV product Highest-quality results not available in heavy rainfall

GPS tropo Temporally near-continuous (5min) Measures actual delay at L-band Spacing few km – 10s of km in S. Calif 32km 2km Zenith delay is formed from all rays passing through an inverted cone centered on the antenna. Most variability comes from the lowest 2km of atmosphere, which implies a cone of R=16km at its top for a cutoff angle of 7 degrees. Most authors treat the zenith delay as a point solution directly above the antenna.

AIRS/GPS intercomparison methodology GPS processed with GIPSY-OASIS II in PPP mode, using JPL’s Flinn final precise orbit. We used a 7 degree elevation cutoff and the GMF mapping function. Total tropospheric zenith delay and 2 gradients were estimated as stochastic parameters, updated at 5-minute intervals. GPS PWV calculated from total delay by method of Bevis, et.al. (1992) with surface pressure & temp from either NCEP(50km) or ECMWF (25km). AIRS products were generated at the Goddard DAAC using the v5.0 processing algorithm. Comparison points limited to measurements within 25km horizontally, 30m height, and 30minutes.

GPS, AIRS and ECMWF daily water vapor over Japan, January 2005 using ECMWF surface pressure to derive GPS PWV AIRS/GPS PWV Intercomparison (a) (a) GPS approximate ZWD estimated from GEONET GPS over Japan, January 3, 2005 (b) AIRS PWV over Japan on January (b) (a) Japan GEONET with NCEP: 0.75 correlation coefficient over Jan 05 Bias evident Consistent with previous study Fetzer 2006 May change with use of absolute antenna calibrations To be completed with data from all seasons, and other geographic areas.

ECMWF + DEM + GPS With Chalmers students J. Lofgren & F. Bjorndahl, JPL AIRS, GPS & InSAR investigators Modulates ECMWF (25kmx25km) weather data by 2 arcsecond (60m) USGS National Elevation Database (NED) topographic data in an interpolation algorithm to form 60m- resolution TWV maps, in the “stretched boundary layer approach” of E. Fishbein Will compare the interpolated ZWD with results from available Southern California GPS sites Will test a differential map as an InSAR correction product May use GPS data as a correction Los Angeles area interpolated total PWV map, :00 ECMWF el. over this “terrain” ECMWF Boundary layer stretched Boundary layer contracted

Quiet atmosphere predictor GPS trop+range differences overlaid on interferogram generally correllate but are too sparse to sample short-wavelength variations between satellite measurements Can we select days without high-frequency variations?

What is noisy atmosphere Short-spatial-wavelength activity is associated with a passing front, which moves through the area –Other causes include Winds Boundary layer convection Evaporation from local sources of water A front passing a single station will leave some signature in that station’s trop time series What can we look at in a single station’s time series that would indicate a passing front?

Quiet atmosphere predictor Range of ZWD over the day? Max abs(dZWD/dt) over the day? Std. Dev. of ZWD over the day? Correlated, and vary from day to day Look at “most different day” time series, 11 Jan 05

11 Jan 2005 Trop Behavior After 3.5 days of continuous rain, the weather cleared on Jan 11 Jan 10 was La Conchita landslide

Jan 19 – more favorable atmosphere Has potential to select days without quickly varying (temporally) and/or short-wavelength (spatially) atmosphere features, such that GPS can be used to run between satellite data collection more effectively Jan 11 Jan 19

Ahead/summary Complete GPS-AIRS comparisons using ECMWF pressure & temp data Evaluate effect of absolute antenna calibrations on GPS-AIRS bias Evaluate usage of gradients and/or slant delays in GPS GPS+MERIS+MODIS+AIRS+ECMWF+DEM =InSAR correction map???