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The rapid expansion of SAR data availability and advancements in InSAR processing methods has enabled the formation of ground displacement time series for many parts of the world where such research was previously hindered by decorrelation due to sparse temporal sampling and SAR operating frequency. In particular, free and open data access from the European Sentinel-1 constellation and the future NASA-ISRO SAR (NISAR) mission is encouraging the global community to move towards automated, cloud-based processing that can accommodate these rapidly growing data volumes and facilitate the use of a suite of corrections to the data. A key challenge is related to path delays introduced when the radar signal propagates through the troposphere. Tropospheric corrections estimated from empirical, phase-based methods and those using independent data from weather models, GPS, and radiometers …