High-Resolution PyGLDA-based Hydrological Data Assimilation to Reveal Added Values of Future NGGM and MAGIC Satellite Gravity Products

The future gravity missions, i.e., ESA’s NGGM (a single low-low satellite-to-satellite, ll-sst, gravity mission on an inclined orbit) and MAGIC (a double ll-sst gravity mission including NASA/DLR’s GRACE-C and ESA’s NGGM), are designed to provide gravity solutions with 5-day and monthly temporal resolutions with short latency. Their spatial resolution is expected to be better and their uncertainty smaller than the GRACE-type gravity missions. Therefore, in this study, we evaluate the added value of the NGGM and MAGIC missions in hydrological DA applications, especially for simulating sub-weekly to multi-year water storage variations. This assessment is important to understand the role of the NGGM and MAGIC products in future hydrological applications. Our experiments are performed using the daily 0.1° resolution W3RA water balance model, forced by the ERA5 climate inputs, during floods in the Brahmaputra and Danube River Basins. As observations, 5-day and monthly GRACE-C-like, NGGM-like, and MAGIC-like TWS estimates will be used. The full error covariance matrix information of the observed TWS will be considered during the DA experiments, which are the outputs of closed-loop simulations of the ESA SING project, considering both instrumental and dealiasing errors.