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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 total water storage anomalies (TWSA), for over two decades. However, for 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 or sea surface temperature. Here, we combine such an approach, for the first time, with low-resolution information from geodetic satellite laser ranging (SLR). The reconstruction is formulated on a GRACE-derived empirical orthogonal functions (EOFs) basis and complemented with the Lcher and Kusche (2021) approach, in which global gravity fields are solved from SLR ranges in a GRACE EOF basis for the pre-GRACE time frame. Although our technique works globally, we focus mainly on European basins and reconstruct water storage anomalies from 1992 onward.
Hacker et al. (Fri,) studied this question.
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