GLWS 2.0: A global product that provides total water storage anomalies, groundwater, soil moisture and surface water with a spatial resolution of 0.5° from 2003 to 2019

The global land water storage (GLWS) data set is produced by assimilating (Eicker at al., 2014) gridded GRACE and GRACE-FO-derived total water storage anomalies (TWSA) into the WaterGAP global hydrological model using the Parallel Data Assimilation Framework (PDAF, Nerger and Hiller, 2013). The resulting data set represents thus an optimal synthesis of GRACE data and all data sets that went into the hydrological model. This synthesis seeks to fit GRACE (-FO) TWSA grids within error bars, and at the same time it solves the horizontal and vertical water balances as represented in the hydrological model, again within error bars. To this end, the uncertainty of the hydrological model simulation is represented via an n-member ensemble, where we take into account the uncertainty of forcing (precipitation and radiation) data as well as the uncertainty of some model calibration parameters. As a result, when no GRACE (-FO) data is available, the GLWS data set represents the mean – or the median additionally provided - of an ensemble where each member is dynamically consistent with the model. It is important to understand that this mean/median depends on the ensemble creation and thus will differ from published WaterGAP standard runs, even if there is no GRACE data within a particular month. It is also important to understand the assimilation-derived GLWS data set does not represent a simple downscaling of the GRACE data, i.e. spatial smoothing of GLWS does not necessarily correspond to GRACE (-FO) TWSA. The monthly level 3 GLWS data represent the total water storage anomaly (TWSA) on 0.5° grids and level 2 GLWS data represent groundwater, soil moisture and surface water. They are provided now for 01/2003 to 12/2019. Additionally, the standard deviation is provided (computed from the ensemble). As default, GLWS is derived from the ensemble mean, here, we additionally provide the ensemble median. The main updates with respect to the release 001 were the use of an updated version of WaterGAP as well as minor bug fixes in the assimilation.

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Cite this as

Gerdener, Helena, Schulze, Kerstin, Kusche, Jürgen (2023). Dataset: GLWS 2.0: A global product that provides total water storage anomalies, groundwater, soil moisture and surface water with a spatial resolution of 0.5° from 2003 to 2019. https://doi.org/10.1594/PANGAEA.954742

DOI retrieved: 2023

Additional Info

Field Value
Imported on November 29, 2024
Last update November 30, 2024
License CC-BY-4.0
Source https://doi.org/10.1594/PANGAEA.954742
Author Gerdener, Helena
Given Name Helena
Family Name Gerdener
More Authors
Schulze, Kerstin
Kusche, Jürgen
Source Creation 2023
Publication Year 2023
Resource Type text/tab-separated-values - filename: GLWS2
Subject Areas
Name: Geophysics

Name: LandSurface

Related Identifiers
Title: The global land water storage data set release 2 (GLWS2.0) derived via assimilating GRACE and GRACE-FO data into a global hydrological model
Identifier: https://doi.org/10.1007/s00190-023-01763-9
Type: DOI
Relation: References
Year: 2023
Source: Journal of Geodesy
Authors: Gerdener Helena , Kusche Jürgen , Schulze Kerstin , Döll Petra , Klos Anna , Eicker Annette , Schumacher Maike , Kusche Jürgen , Döll Petra , Müller Schmied Hannes .

Title: Calibration/Data Assimilation Approach for Integrating GRACE Data into the WaterGAP Global Hydrology Model (WGHM) Using an Ensemble Kalman Filter: First Results
Identifier: https://doi.org/10.1007/s10712-014-9309-8
Type: DOI
Relation: References
Year: 2014
Source: Surveys in Geophysics
Authors: Gerdener Helena , Kusche Jürgen , Schulze Kerstin , Döll Petra , Klos Anna , Eicker Annette , Schumacher Maike , Kusche Jürgen , Döll Petra , Müller Schmied Hannes .

Title: GLWS 2.0 - processing details
Type: DOI
Relation: References
Authors: Gerdener Helena , Kusche Jürgen , Schulze Kerstin , Döll Petra , Klos Anna , Eicker Annette , Schumacher Maike , Kusche Jürgen , Döll Petra , Müller Schmied Hannes .