Expected performance of future MAGIC data-assimilated Terrestrial Water Storage (TWS) products

The planned MAGIC mission, a collaboration between ESA and NASA, is expected to deliver an extended record of the global mass transport time series with improved accuracy, temporal and spatial resolutions. ESA’s involvement in MAGIC is through its NextGeneration Gravity Mission (NGGM) and NASA contributes with its GRACE-C mission. One of the key deliverables is terrestrial water storage (TWS), which is vital for assessing changes in climate and managing water resources efficiently. As an essential climate variable, TWS plays an important role in providing information regarding extreme events. While the GRACE and its Follow-On mission distribute global TWS anomalies (TWSA), their coarse spatial resolution (around 150,000 km²) constrains detailed analysis of smaller basins. Given that freshwater is often sourced from localized aquifer systems, enhancing spatial resolution is necessary for effective local water management. Furthermore, improvements in spatio-temporal resolution would allow advances in early flood warning applications. To overcome these limitations, data assimilation (DA) techniques have been developed to combine GRACE observations with land surface models (LSMs), making it possible to downscale and disaggregate TWSA information into its individual components.This study evaluates the performance of data assimilation utilising GRACE-type and MAGIC error information within the LSMs NOAH-MP and CLSM, with a focus on two regions in South America and Europe. The model runs cover the period from January 2003 to December 2006, using data generated during the ESA Science Support study for MAGIC Phase A. The data is based on closed-loop simulations with a 30 day repeat orbit, containing the hydrology, ice and solid Earth (HIS) signal along with atmosphere-ocean errors, ocean tide errors and instrument noise. In total 12 years of monthly data were produced spanning from January 1995 to December 2006 with spherical harmonic coefficients up to degree and order 90. A reference HIS signal, acquired from the ESA ESM over the same period is used to compute retrieval errors. The results demonstrate that MAGIC data assimilation offers advantages across climatically different regions independent of LSMs chosen. Furthermore, this study indicates that unlike previous data assimilation studies, it will be possible to assimilate MAGIC into smaller basins sizes, seen by the relative improvements of MAGIC DA over GRACE-type DA. Lastly, it is shown that in case of MAGIC DA post-processing can be considerably reduced, such as removing the need of filtering up to degree and order 60. Thus, leakage quantification issues due to the applied filter would be alleviated achieving more straightforward uncertainty quantification.Overall, MAGIC data assimilation offers substantial improvements in TWS estimation and trend correction compared to GRACE-type data assimilation, demonstrating its potential for improving hydrological applications