Abstract
The Gravity Recovery and Climate Experiment (GRACE) level-2 spherical harmonic (SH) solutions are noisy and thus require filtering. Filtering reduces noise but affects signal quality via signal leakage. Generally, a leakage correction is required for GRACE applications to remove leakage signal and recover the true signal. Forward modelling based on some a priori information is a widely used approach for leakage correction of GRACE data. The a priori information generally relies on global hydrological model simulations. There are many global hydrological models and therefore it is of interest to explore how different global hydrology model simulations influence leakage correction results. This study investigated the sensitivity of three leakage correction methods (additive method, scaling factor method and multiplicative method) to five global hydrology model simulations (four models from the Global Land Data Assimilation System (GLDAS) and the WaterGAP Global Hydrology Model (WGHM)). The sensitivity analysis was performed with observational data in Southwest China and one sub-region, Guangxi. Results show that although large differences were identified among the five global model simulations, the additive and scaling factor methods are less affected by the choice of a priori model in comparison to the multiplicative approach. For the additive and scaling factor methods, WGHM outperforms the other four GLDAS models in leakage correction of GRACE data. GRACE data corrected with the multiplicative method shows the highest amount of error, indicating this method is not applicable for leakage correction in the study area. This study also assessed the level-3 mascon (mass concentration) solutions of GRACE data. The mascon-based results are nearly as good as the leakage corrected results based on SH solutions.
Highlights
The Gravity Recovery and Climate Experiment (GRACE) twin-satellite mission was a unique remote sensing technique that could monitor land surface mass changes by sensing the time-variable gravity field
There may be large uncertainty in the global model simulations. This provides the opportunity for answering the scientific question: how is the sensitivity of leakage correction of GRACE data to various a priori model simulations? this study aims to explore whether the leakage-corrected terrestrial water storage anomaly (TWS) based on the level-2 spherical harmonic (SH) solution performs better than the level-3 mascon solution at the scale of SW China
A similar comparison can be found in Guangxi with r = 0.64, root mean square error (RMSE) = 18.5 mm for Community Land Model (CLM), and r = 0.61, RMSE = 19.4 mm for WGHM (Figure 2c and Table 1)
Summary
The Gravity Recovery and Climate Experiment (GRACE) twin-satellite mission was a unique remote sensing technique that could monitor land surface mass changes by sensing the time-variable gravity field. GRACE satellite data have been widely used for various hydrological applications, such as disaggregating of the groundwater storage component from total terrestrial water storage anomaly (TWS) [1,2,3], estimating glacier and ice mass changes [4,5], and deriving total drainable water storage at basin scales [6,7]. Substantial improvements (e.g., the update of background models) have been made on the GRACE data solutions [17], additional filtering is still necessary for removing the systematic stripes and high frequency random noises. The apparent mass changes at the grid scale (1◦ × 1◦ ) cannot represent the true signal. The signal at a grid is a mixture of true mass changes and leakage signals
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