From repeat‐pass interferometry, tropospheric signals often prevent the detection of ground deformation signals. In recent years, tropospheric corrections derived from global weather‐based models have been implemented in several InSAR processing chains. In this study, we evaluate the performance of two weather‐based models (ERA5 and GACOS) on two tropical volcanoes: Piton de la Fournaise and Merapi. For Piton de la Fournaise, the reduction of the tropospheric noise is efficient for 30% and 60% of the data sets for GACOS and ERA5, respectively. For Merapi, the performance reaches 40% for GACOS and 50% for ERA5. Although GNSS local stations provide real‐time information about tropospheric delays, their potential for improving InSAR corrections on active volcanoes is under‐exploited. Here, we produce local GNSS‐based tropospheric corrections and compare their performance to global weather‐based models. For Piton de la Fournaise, the gain of performance with 34 GNSS stations is about 25% compared to ERA5 models. GNSS‐based corrections increase the signal‐to‐noise ratio in InSAR time series allowing the detection of ground displacements between July and December 2021. For Merapi, GNSS‐based models with only 5 stations spatially distributed at different elevations are as efficient as ERA5 models. GNSS‐based corrections induce a decrease in the noise level from values 1–0.5 cm in a period of quiescence. Here, we show that GNSS‐based models are an efficient alternative to global weather‐based models for instrumented volcanoes. The proposed approach paves the way toward near real‐time InSAR monitoring of volcanic unrest and other processes (landslides, groundwater extraction).
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Albino et al. (2025) studied this question.
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