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Poster communications

The influence of climate input uncertainties on the assimilation of GRACE data into the WaterGAP Global Hydrology Model

Abstract : Global hydrological models contribute to the understanding and quantification of the global water cycle. However, large uncertainties persist on the one hand due to the simplified representation of hydrological processes for a global scale analysis and, on the other hand due to input data uncertainties, e.g. climate forcing and data to the anthropogenic alteration of the water cycle. The time-variable solutions of the Gravity Recovery And Climate Experiment (GRACE) mission provide an independent observation of water storage change with global coverage, which can be used to improve global hydrological models. For this purpose, an ensemble Kalman filter approach is applied to assimilate GRACE total water storage (TWS) change grids into the WaterGAP Global Hydrology Model (WGHM). In contrast to existing studies, our approach involves the full error information of the GRACE solutions, i.e. spatial correlations, as well as the full spatial resolution of the data. To guarantee a realistic estimation of the uncertainties introduced by the climate forcing data, their covariance matrices are determined from an ensemble of forcing fields from different state-of-the-art climate inputs. Finally, the errors are propagated to the assimilated water storage outputs. Here, the results are presented with respect to the precipitation input.
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Poster communications
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https://hal-insu.archives-ouvertes.fr/insu-01119799
Contributor : Isabelle Dubigeon <>
Submitted on : Tuesday, February 24, 2015 - 9:55:59 AM
Last modification on : Friday, April 5, 2019 - 8:17:37 PM

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  • HAL Id : insu-01119799, version 1

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Citation

M. Schumacher, J. Kusche, Annette Eicker, Laurent Longuevergne, K. Franz, et al.. The influence of climate input uncertainties on the assimilation of GRACE data into the WaterGAP Global Hydrology Model. AGU Fall Meeting 2013, Dec 2013, San Francisco, United States. pp.G23A-0770, 2013. ⟨insu-01119799⟩

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