Snow Water Equivalent retrieval and InSAR Coherence modeling using L-band Lutan-1 data

Snow Water Equivalent (SWE) is a critical parameter in the global and regional water cycle and climate system. However, accurately measuring SWE change using satellite remote sensing remains a challenge. While the Interferometric Synthetic Aperture Radar (InSAR) is a promising technique to retrieve SWE from space, its application has been constrained until recently by the lack of spaceborne observations combining optimal low-frequency (e.g., L-band) radar frequencies with short temporal baselines. Furthermore, interferometric coherence is a key factor that affects the accuracy of the unwrapped phase and the subsequent SWE retrieval. However, the repeat-pass InSAR coherence modelling over snow has not been sufficiently investigated.

Our study presents the first demonstration of SWE change retrieval using spaceborne repeat-pass L-band InSAR observations from the Chinese Lutan-1 mission. The study area focused on the Altay region in Xinjiang, China, during the winter of 2023–2024. Continuous interferometric pairs with 4/8-day temporal baselines are processed for phase changes and then estimate SWE variations. The retrieved SWE change shows a good agreement with in-situ SWE observations during the dry snow period (January 12 to February 9, 2024), with a Root Mean Square Error (RMSE) of 9 mm and a correlation coefficient (R) of 0.48 for the 4-day temporal baselines. However, a heavy snowfall event observed from February 9 to 17, 2024, induced severe decorrelation, leading to phase unwrapping errors that pose a challenge to SWE retrieval. To address the decorrelation mechanism of snow, the InSAR coherence model for snow is established based on the assumption of a bivariate Gaussian distribution for the ground and snow surface. The time-series modeled coherence shows a consistent trend with the observed Lutan-1 coherence, capturing effectively the decorrelation process caused by snowfall events and snow compaction processes. Furthermore, validation of the modeled coherence against Lutan-1 observations shows a strong agreement (R=0.87) over the entire study period from January 12 to March 28, 2024.

Overall, this study demonstrates the capability of spaceborne L-band InSAR with short revisit intervals to effectively retrieve SWE change under appropriate snow conditions. However, the retrieval accuracy is significantly constrained by severe decorrelation during heavy snowfall events. These results highlight both the potential and challenges of operational SWE monitoring from existing and upcoming L-band SAR missions such as Chinese Lutan-1, NASA’s NISAR, JAXA’s ALOS-4, and ESA’s ROSE-L, which are characterized by short repeat cycles, wide swath coverage, and high spatial resolution.