InSAR bias and uncertainty due to the systematic and stochastic tropospheric delay. Issue 12 (28th December 2015) - Fattahi, Heresh; Amelung, Falk
Abstract: We quantify the bias and uncertainty of interferometric synthetic aperture radar (InSAR) displacement time series and their derivatives, the displacement velocities, by analyzing the systematic and stochastic components of the temporal variation of the tropospheric delay. The biases due to the systematic seasonal delay depend on the SAR acquisition times, whereas the uncertainties depend on the standard deviation of the random delay, the number of acquisitions, the total time span covered, and the covariance of the time series of the stochastic delay between a pixel and the reference. We study the contribution of the wet delay to the InSAR observations along the western India plate boundary using (i) Moderate Resolution Imaging Spectroradiometer precipitable water vapor, (ii) stratified tropospheric delay estimated from the ERA‐I global atmospheric model, and (iii) seven Envisat InSAR swaths. Our analysis indicates that the amplitudes of the annual delay vary by up to 10 cm in this region equivalent to a maximum displacement bias of 24 cm in InSAR line of sight direction between two epochs (assuming Envisat IS6 beam mode). The stratified tropospheric delay correction mitigates this bias and reduces the scatter due to the stochastic delay. For 7 years of Envisat acquisitions along the western India plate boundary, the uncertainty of the InSAR velocity field due to the residual stochastic wet delay after stratified tropospheric delay correction using the ERA‐I model is in the order of 2 mm/yr over 100 km and 4 mm/yr over 400 km. We discuss the implication of the derived uncertainties on the full variance‐covariance matrix of the InSAR data. Key Points: Temporal variation of tropospheric delay includes systematic and stochastic components Time series of wet delay from satellite spectrometers can quantify the InSAR uncertainty The uncertainty of the InSAR displacement and velocity is dominated by the stochastic delay