Advanced InSAR Tropospheric Corrections From Global Atmospheric Models that Incorporate Spatial Stochastic Properties of the Troposphere

Cao, Yunmeng; Jonsson, Sigurjon; Li, Zhi Wei

Advanced InSAR Tropospheric Corrections From Global Atmospheric Models that Incorporate Spatial Stochastic Properties of the Troposphere

Files

Preprint_ICAMS_JGR_revision.pdf (2.01 MB)

Type

Article

Authors

Cao, Yunmeng

Jonsson, Sigurjon

Li, Zhi Wei

KAUST Department

Crustal Deformation and InSAR Group
Earth Science and Engineering Program
Physical Science and Engineering (PSE) Division

KAUST Grant Number

BAS/1/1353-01-01

Online Publication Date

2021-05-24

Print Publication Date

2021-05

Date

2021-05-24

Submitted Date

2020-09-11

Abstract

Tropospheric delays are still the main error source of satellite-based Interferometric Synthetic Aperture Radar (InSAR) mapping of Earth’s surface movements. Recent studies have demonstrated the potential of global atmospheric models (GAMs) in reducing InSAR tropospheric delays. However, the importance of appropriate interpolation and weighting strategies in GAM corrections has largely been overlooked. Here we present a new GAM-based tropospheric correction method that incorporates spatial stochastic models of the troposphere into the weighting strategy of the correction. The method determines the correlation between a pixel of interest and neighboring GAM grid locations (3D) according to the spatial variability of the tropospheric random field, instead of subjectively using an inverse distance method, a local spline function, or other standard interpolation scheme. Also, our new method considers horizontal heterogeneities of the tropospheric field by estimating the integral of the tropospheric delays along the satellite line-of-sight (LOS) direction, instead of calculating projected zenith-delays. The method can be used with any GAM, but we here implement it with the latest ECMWF (European Center for Medium-Range Weather Forecasts) ERA5 reanalysis products. We validate the new method with hundreds of Sentinel-1 images from 2015 to 2020 over the island of Hawaii, a location with variable topography, surface conditions, local climate, and deformation, and explore the tropospheric corrections for both interferograms and time-series analysis products (deformation velocities and time-series solutions). Compared with other GAM corrections (PyAPS, d-LOS, and GACOS), our new method yields a larger reduction of the average standard deviation of the corrected interferograms, i.e., from 2.55 to 1.91 cm, instead of 2.47 cm (PyAPS), 2.44 cm (d-LOS), and 2.10 cm (GACOS). Also, a larger fraction of 87% of the interferograms (243 out of 280) is improved, compared with 52%, 53%, and 66% for the other GAM corrections, respectively. These results demonstrate the importance of considering (1) tropospheric stochastic models in GAM corrections, (2) horizontal heterogeneities when estimating the LOS delays, and (3) tropospheric delays when mapping long-wavelength or small-magnitude deformations using InSAR.

Citation

Cao, Y., Jónsson, S., & Li, Z. (2021). Advanced InSAR Tropospheric Corrections From Global Atmospheric Models that Incorporate Spatial Stochastic Properties of the Troposphere. Journal of Geophysical Research: Solid Earth, 126(5). doi:10.1029/2020jb020952

Acknowledgements

This research was supported by King Abdullah University of Science and Technology (KAUST), under award number BAS/1/1353-01-01, and the National Science Fund for Distinguished Young Scholars (Grant 41925016).