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 deliveran extended record of the global mass transport time series with improved accuracy,temporal and spatial resolutions. ESAs involvement in MAGIC is through its NextGeneration Gravity Mission (NGGM) and NASA contributes with its GRACE-C mission. Oneof the key deliverables is terrestrial water storage (TWS), which is vital for assessingchanges in climate and managing water resources efficiently. As an essential climatevariable, TWS plays an important role in providing information regarding extreme events.While the GRACE and its Follow-On mission distribute global TWS anomalies (TWSA), theircoarse spatial resolution (around 150,000 km) constrains detailed analysis of smallerbasins. Given that freshwater is often sourced from localized aquifer systems, enhancingspatial resolution is necessary for effective local water management. Furthermore,improvements in spatio-temporal resolution would allow advances in early flood warningapplications. To overcome these limitations, data assimilation (DA) techniques have beendeveloped to combine GRACE observations with land surface models (LSMs), making itpossible to downscale and disaggregate TWSA information into its individual components.This study evaluates the performance of data assimilation utilising GRACE-type and MAGICerror information within the LSMs NOAH-MP and CLSM, with a focus on two regions inSouth America and Europe. The model runs cover the period from January 2003 toDecember 2006, using data generated during the ESA Science Support study for MAGICPhase A. The data is based on closed-loop simulations with a 30 day repeat orbit, containingthe hydrology, ice and solid Earth (HIS) signal along with atmosphere-ocean errors, oceantide errors and instrument noise. In total 12 years of monthly data were produced spanningfrom January 1995 to December 2006 with spherical harmonic coefficients up to degree andorder 90. A reference HIS signal, acquired from the ESA ESM over the same period is usedto compute retrieval errors.The results demonstrate that MAGIC data assimilation offers advantages across climaticallydifferent regions independent of LSMs chosen. Furthermore, this study indicates that unlikeprevious data assimilation studies, it will be possible to assimilate MAGIC into smaller basinssizes, seen by the relative improvements of MAGIC DA over GRACE-type DA. Lastly, it isshown that in case of MAGIC DA post-processing can be considerably reduced, such asremoving the need of filtering up to degree and order 60. Thus, leakage quantification issuesdue to the applied filter would be alleviated achieving more straightforward uncertaintyquantification.Overall, MAGIC data assimilation offers substantial improvements in TWS estimation andtrend correction compared to GRACE-type data assimilation, demonstrating its potential forimproving hydrological applications