RIPPL, a Python-based InSAR stack and tropospheric delay software package

Interferometric Synthetic Aperture Radar (InSAR) has a wide range of applications, including the monitoring of solid-earth and cryospheric geophysical processes and the monitoring of the built environment. The use of InSAR for atmospheric applications is less thoroughly developed. To perform such analyses the atmospheric phase delay of the SAR signal between different overpasses is used, which needs to be disentangled from other phase constituents, such as displacements and topography, which requires stack processing of large data volumes. Typically, initial atmospheric delays are predicted using existing numerical weather prediction (NWP) models, but InSAR processing and NWP model delay estimation software are not well integrated. Here we present a pure Python-based software package that integrates the automatic downloading and processing of InSAR and NWP model data to create time-series of unwrapped InSAR interferograms and InSAR equivalent tropospheric delays from NWP models. By combining the geometry of the InSAR radar signals with different NWP model datasets the tropospheric delays can accurately be derived on a pixel by pixel basis. • Estimation of tropospheric slant delays from NWP models using scatterer heights and SAR imaging geometry. • Integration of InSAR processing and NWP model delay calculations in one software package. • Integration of download and processing of NWP model and InSAR time-series to create a user-friendly software package. • Provides ready-to-use datasets to evaluate water vapor fields from ERA5 and CERRA weather models using Sentinel-1 measurements.