Springer, Anne: A water storage reanalysis over the European continent: assimilation of GRACE data into a high-resolution hydrological model and validation. - Bonn, 2019. - Dissertation, Rheinische Friedrich-Wilhelms-Universität Bonn.
Online-Ausgabe in bonndoc: https://nbn-resolving.org/urn:nbn:de:hbz:5n-53930
urn: https://nbn-resolving.org/urn:nbn:de:hbz:5n-53930,
author = {{Anne Springer}},
title = {A water storage reanalysis over the European continent: assimilation of GRACE data into a high-resolution hydrological model and validation},
school = {Rheinische Friedrich-Wilhelms-Universität Bonn},
year = 2019,
month = apr,

note = {

Continental water storage and redistribution within the Earth’s system are key variables of the terrestrial water cycle. Changes in water storage and fluxes may affect resources for drinking water and irrigation, lead to drought or flood conditions, or cause severe changes of ecosystems e.g., through salinification. Hydrological models, which map water storages and fluxes, are being continuously improved and deepen our understanding of geophysical processes related to the water cycle. However, models are built on a simplified representation of reality, which leads to limited predicting skills of the simulation results. Assimilating remotely sensed total water storage variability from the Gravity Recovery and Climate Experiment (GRACE) mission has become a valuable tool for reducing uncertainties of hydrological model simulations. Simultaneously, coarse GRACE observations are disaggregated spatially and temporally through data assimilation.
In this thesis, GRACE data are assimilated into the Community Land Model version 3.5 (CLM3.5) yielding a unique daily 12.5 km reanalysis of total water storage evolution over Europe (2003 to 2010). Independent observations are evaluated to identify model deficits and to validate the performance of data assimilation. For the first time, the effect of data assimilation on modeled total water storage is also shown on the level of GRACE K-band observations. Optimal strategies for assimilating GRACE data into a high-resolution hydrological model are investigated through synthetic experiments. These experiments address the choice of the assimilation algorithm, localization, inflation of the ensemble of model states, ensemble size, error model of the observations, and spatial resolution of the observation grid. As the assimilation of GRACE data into CLM3.5 is realized within the Terrestrial Systems Modeling Platform (TerrSysMP), future assimilation experiments can be extended for the groundwater and atmosphere components included in TerrSysMP.


url = {https://hdl.handle.net/20.500.11811/7987}

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