Articles | Volume 21, issue 2
Research article
10 Feb 2017
Research article |  | 10 Feb 2017

Validation of terrestrial water storage variations as simulated by different global numerical models with GRACE satellite observations

Liangjing Zhang, Henryk Dobslaw, Tobias Stacke, Andreas Güntner, Robert Dill, and Maik Thomas

Abstract. Estimates of terrestrial water storage (TWS) variations from the Gravity Recovery and Climate Experiment (GRACE) satellite mission are used to assess the accuracy of four global numerical model realizations that simulate the continental branch of the global water cycle. Based on four different validation metrics, we demonstrate that for the 31 largest discharge basins worldwide all model runs agree with the observations to a very limited degree only, together with large spreads among the models themselves. Since we apply a common atmospheric forcing data set to all hydrological models considered, we conclude that those discrepancies are not entirely related to uncertainties in meteorologic input, but instead to the model structure and parametrization, and in particular to the representation of individual storage components with different spatial characteristics in each of the models. TWS as monitored by the GRACE mission is therefore a valuable validation data set for global numerical simulations of the terrestrial water storage since it is sensitive to very different model physics in individual basins, which offers helpful insight to modellers for the future improvement of large-scale numerical models of the global terrestrial water cycle.

Short summary
Global numerical models perform differently, as has been found in some model intercomparison studies, which mainly focused on components like evapotranspiration, soil moisture or runoff. We have applied terrestrial water storage that is estimated from a GRACE-based state-of-art post-processing method to validate four global numerical models and try to identify the advantages and deficiencies of a certain model. GRACE-based TWS demonstrates its additional benefits to improve the models in future.