Articles | Volume 30, issue 4
https://doi.org/10.5194/hess-30-1097-2026
https://doi.org/10.5194/hess-30-1097-2026
Research article
 | 
24 Feb 2026
Research article |  | 24 Feb 2026

Skills in sub-seasonal to seasonal terrestrial water storage forecasting: insights from the FEWS NET land data assimilation system

Bailing Li, Abheera Hazra, Amy McNally, Kimberly Slinski, Shraddhanand Shukla, and Weston Anderson

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Short summary
Accurate prediction of terrestrial water storage (TWS) changes is essential for disaster response. This study evaluates TWS forecast skill over Africa using observations from the Gravity Recovery and Climate Experiment (GRACE). Results show that the NASA Catchment Land Surface Model (CLSM) outperforms Noah with Multi-Parameterization (Noah-MP) across 1-6 months lead times, owing to more accurate reanalysis-based initial conditions and stronger representation of TWS interannual variability.
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