Benchmarking Gap-Filling Techniques in Satellite Altimetry-Based Lake Water-Level Time Series

An improved method is used to integrate satellite-derived terrestrial water storage and surface soil moisture observations into a hydrological model within the Brahmaputra River basin (South Asia). This integration leads to a more realistic representation of the water stored in the land, allowing us to better understand its changes in space and time, which is crucial in this basin due to its increasing water demand and vulnerability to extreme events due to climate change.

Satellite gravimetry enables direct measurement of total water storage (TWS), a capability that was previously unattainable. In this study, we present an open-source land data assimilation system with global hydrological model, which temporally, vertically, and laterally dis-aggregates satellite-based TWS. This study provides a practical framework establishing operational water management with current and future satellite gravity missions.

We introduce China's first de-aliasing computation platform, incorporating China's Atmospheric Reanalysis and an in-house ocean circulation model. This platform produces CRA-LICOM, a high-frequency atmospheric and oceanic gravity de-aliasing product with a 6-hourly, 50 km resolution covering 2002–2024 globally. This product is reliable for de-aliasing, signal separation in satellite gravity missions, and climate change studies.