Geodetic analysis of postseismic responses to major earthquakes offers insight into potential subsequent seismic activities and aseismic strain release. Interferometric Synthetic Aperture Radar (InSAR) provides a particularly high-resolution imaging capability for such transient events, particularly in regions without dense Global Navigation Satellite Systems (GNSS) networks. However, InSAR suffers from decorrelation errors and atmospheric noise, which can distort the interpretation of deformation patterns. To take a step towards addressing these challenges, this study introduces an advanced InSAR processing workflow and applies it to Sentinel-1 observations of postseismic deformation following the 2021 Haiti earthquake. We address decorrelation errors by employing phase linking through the Fine Resolution InSAR with Generalized Eigenvectors (FRInGE) method. We compare three methods for mitigating atmospheric effects, including a grouped Independent Component Analysis (ICA) method, and find that ICA performs best in removing atmosphere. Without applying these methods most of the signal is lost or hidden in the noise; after processing transient postseismic deformation, likely related to shallow fault creep, can be observed over ~3 months following the earthquake on the eastern EPGFZ. We compare the estimated cumulative slip to that obtained from ALOS-2 observations and find a good match, with ~3 cm of differential displacement on either side of the EPGFZ east of the rupture area. Our workflow provides a method for more precise characterization of localized transient deformation signals using C-band InSAR.

The Global Navigation Satellite System (GNSS) airborne radio occultation (ARO) technique is used to retrieve profiles of the atmosphere during reconnaissance missions for atmospheric rivers (ARs) on the west coast of the United States. The measurements are a horizontal integral of refractive index over long ray-paths extending between a spaceborne transmitter and a receiver onboard an aircraft. A specialized forward operator is required to allow assimilation of ARO observations into numerical weather prediction models to support forecasting of ARs. A two-dimensional (2D) bending angle operator is proposed to enable capturing key atmospheric features associated with strong ARs. Comparison to a one-dimensional (1D) forward model supports the evidence of large bending angle departures within 3-7 km impact heights for observations collected in a region characterized by the integrated water vapor transport (IVT) magnitude above 500 kg m-1 s-1. The assessment of the 2D forward model for ARO retrievals is based on a sequence of six flights leading up to a significant AR precipitation event in January 2021. Since the observations often sampled regions outside the AR where moisture is low, the significance of horizontal variations is obscured in the average statistics. However, examples from an individual flight preferentially sampling the cross-section of an AR further support the need for the 2D forward model for targeted ARO observations. Additional simulation experiments are performed to quantify forward modeling errors due to tangent point drift and horizontal gradients suggesting contributions on the order of 5 % and 20 %, respectively.