Multidecadal Reconstruction Of Terrestrial Water Storage Changes By Combining Pre-GRACE Satellite Observations And Climate Data
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https://doi.org/10.5194/essd-18-1747-2026 <-- shared paper
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https://doi.org/10.5281/zenodo.15827789 <-- reconstructed fields and corresponding uncertainty datasets
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https://doi.org/10.5281/zenodo.16643628 <-- corresponding time series datasets
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“The Gravity Recovery And Climate Experiment (GRACE) and its follow-on mission, GRACE-FO, have observed global mass changes and transports, expressed as terrestrial water storage anomalies (TWSA), for over two decades. However, for climate model evaluation, climate change attribution and other applications, multi-decadal TWSA time series are required. This need has triggered several studies on reconstructing TWSA via regression approaches or machine learning techniques, with the help of predictor variables such as rainfall, land or sea surface temperature. Here, [they] combine[d] such an approach, for the first time, with large-scale time-variable gravity information from geodetic satellite laser ranging (SLR) and Doppler Orbitography by Radiopositioning Integrated on Satellite (DORIS) tracking. The new reconstruction TWSTORE (Terrestrial Water STOrage REconstruction) is formulated in a GRACE-derived empirical orthogonal functions (EOFs) basis and complemented with the Löcher et al. (2025) approach, in which global gravity fields are solved from SLR ranges and DORIS observations in EOF space for the pre-GRACE time frame. Our approach is highly modular, allowing [them] to use different data sets at several steps in the workflow.
[They] reconstruct[ed] GRACE-like TWSA for the global land, excluding Greenland and Antarctica, from 1984 onward. [They found] that the new combined reconstruction inherits information from the geodetic method, mainly at longer timescales. In contrast, at the seasonal scale, the climate-driven reconstruction and the geodetic product are already surprisingly consistent. In comparison to other reconstructions, [they found this] major differences mainly at the multi-decadal timescale. All in all, [their] study confirms the presence of significant changes in storage trends, showing that GRACE-derived results should NOT be extrapolated to the past…”
#GIS #spatial #mapping #remotesensing #earthobservation #GRACE #GRACEFO #water #hydrology #hydrography #waterresources #waterstorage #planning #monitoring #spatialanalysis #spatiotemporal #climatemodel #climatechange #extremeweather #regression #AI #machinelearning #rainfall #precipitation #remperatures #parameters #gravity #geodetic #satellite #orbitography #geomorphometry #DORIS #global #reconstruction #limitations #usecase