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On the Value of LES Models for Evaluating Spatio-Temporal Tropospheric Variability in Multitemporal SAR Interferograms

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Atmospheric delay has a profound impact on synthetic aperture radar (SAR) interferometry, inducing a spatial signal that significantly devaluates interferometric products. While the wide-scale variability of the atmosphere can be… Click to show full abstract

Atmospheric delay has a profound impact on synthetic aperture radar (SAR) interferometry, inducing a spatial signal that significantly devaluates interferometric products. While the wide-scale variability of the atmosphere can be adequately modeled with global or regional weather models, it is especially the turbulent and convective part of the atmosphere at smaller spatial and temporal scales that is typically poorly captured. Due to the high resolution and precision of InSAR, there is a need for a realistic modeling of the 3-D distribution of turbulent refractivity in the boundary layer. This would enable assessment of the impact of a temporal or spatial model misalignment on the interferometric products, and contribute to studying the impact for future SAR missions. Here we test the feasibility of an advanced large Eddy simulation (LES) model to simulate a time-series refractivity distribution with a high spatio-temporal resolution to show the spatio-temporal variability of the troposphere on short time scales. We found for a fair-weather situation that the LES model produces realistic atmospheric simulations that match stochastically with results found in interferometric studies and that tropospheric delay variation leads to significant phase gradients within several minutes. This implies that even when using an (unrealistic) perfect weather model with resolutions similar to the SAR image, realizations that are several minutes apart from the time of the SAR acquisition will lead to significant phase errors. We propose the use of LES models as a realistic instrument to perform InSAR quality-assessments and for the development and simulation for future missions.

Keywords: models evaluating; les models; variability; value les; spatio temporal; sar

Journal Title: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Year Published: 2022

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