| 16 Mar 2026
SYSU TWSA v1.0: Global High-Resolution Terrestrial Water Storage Anomalies via Satellite Gravimetry
Abstract. Publicly available global high-resolution terrestrial water storage anomaly (TWSA) datasets derived from satellite gravimetry remain scarce. Many existing global downscaling products rely heavily on hydrological models. Consequently, their performance can degrade in regions where key mass variations observed by the Gravity Recovery and Climate Experiment (GRACE) and its successor mission GRACE Follow-On (GFO) are poorly represented in the models, notably those associated with mountain glaciers and large lakes. Here we provide SYSU TWSA, a global monthly 0.5° TWSA dataset spanning April 2002 to December 2022, generated using a joint-inversion spatial downscaling framework that integrates large-scale constraints from GRACE/GFO, high-resolution spatial patterns from the WaterGAP Global Hydrological Model (WGHM), and additional mascon groups that explicitly represent mountain glaciers and selected large or rapidly changing lakes. The dataset helps alleviate the current shortage of global high-resolution products and explicitly strengthens the representation of glacier- and lake-related signals. We assess SYSU TWSA through four complementary evaluations: (1) basin-wise consistency with raw GRACE/GFO estimates, (2) a basin water-balance consistency check, (3) independent evaluation against in situ groundwater well observations, and (4) comparisons with representative downscaled products in both the spectral and spatial domains. SYSU TWSA shows strong agreement with GRACE/GFO at the basin scale, with coefficients of determination (R2) exceeding 0.85 across basin-size classes. In small basins, consistency with terrestrial water fluxes derived from the basin water-balance equation improves substantially, with NSE increasing by 17.1 % relative to raw GRACE/GFO across 1,200 basins. Agreement with groundwater wells also improves, with correlations increasing at 67.7 % of 28,248 wells. Comparisons with representative assimilation-based and deep-learning downscaled products further indicate that SYSU TWSA achieves competitive overall accuracy while strengthening the representation of glacier- and lake-related signals.
In this study, Xiong et al. applied a joint inversion downscaling method to downscale GRACE/GFO products to 0.5 degrees. The method extracts spatial information from hydrological simulations (WGHM) and applies spatial corrections to glaciers and lakes to account for components that WGHM insufficiently models. Then, the temporal consistency with GRACE/GFO is ensured to keep the mass conservation. The authors provide comprehensive evaluations in different aspects and compare them with some other downscaled/data assimilation products, and demonstrate the quality of SYSU TWSAv1.0.
This paper is generally well written and provides valuable contributions to the community. The special care of inland glaciers and large lakes is especially appreciated. In the end, it shows remarkable improvements in the glaciated regions compared to Gou and Soja (2024), who clearly stated that such regions are their product's main limitation. No major issues exist for this approach and dataset, but some descriptions are a bit too brief and need to be elaborated more for the audience to understand the product/approach better. Therefore, I would recommend publication of this paper after some rather minor revisions. The specific comments are as follows:
About Section 2 Data:
About Section 3 Joint Inversion Downscaling Framework
This section is important for the audience to understand the whole approach. Although I understand the method is based on their earlier publication (Xiong et al. 2025), I highly recommend that the authors expand this section to describe the methods in more detail. For example:
About Section 4 Results
General comments: Some of the figures have relatively low resolution. Please provide high-resolution figures and ideally vector figures for the final publication.
References
Müller Schmied et al. (2024). The global water resources and use model WaterGAP v2.2e: description and evaluation of modifications and new features. https://doi.org/10.5194/gmd-17-8817-2024
Xiong et al. (2025). High-Resolution Terrestrial Water Storage Anomalies and Components in China From GRACE/GFO via Joint Inversion Downscaling. https://doi.org/10.1029/2024WR038996