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

Journal Article (2026)
Author(s)

G. Mulder (TU Delft - Mathematical Geodesy and Positioning)

F. J. van Leijen (TU Delft - Mathematical Geodesy and Positioning)

P. Lopez-Dekker (TU Delft - Mathematical Geodesy and Positioning)

R. F. Hanssen (TU Delft - Mathematical Geodesy and Positioning)

Research Group
Mathematical Geodesy and Positioning
DOI related publication
https://doi.org/10.1016/j.cageo.2025.106069
More Info
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Publication Year
2026
Language
English
Research Group
Mathematical Geodesy and Positioning
Volume number
207
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Abstract

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.