Comparison of Daily GRACE Gravity Field and Numerical Water Storage Models for De-aliasing of Satellite Gravimetry Observations
Autor: | I. Bergmann-Wolf, Henryk Dobslaw, Andreas Güntner, Robert Dill, Saskia Esselborn, Th. Gruber, L. Zenner, Martin Wattenbach |
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Rok vydání: | 2014 |
Předmět: | |
Zdroj: | Surveys in Geophysics |
ISSN: | 1573-0956 0169-3298 |
Popis: | Reducing aliasing effects of insufficiently modelled high-frequent, non-tidal mass variations of the atmosphere, the oceans and the hydrosphere in gravity field models derived from the Gravity Recovery and Climate Experiment (GRACE) satellite mission is the topic of this study. The signal content of the daily GRACE gravity field model series (ITG-Kalman) is compared to high-frequency bottom pressure variability and terrestrially stored water variations obtained from recent numerical simulations from an ocean circulation model (OMCT) and two hydrological models (WaterGAP Global Hydrology Model, Land Surface Discharge Model). Our results show that daily estimates of ocean bottom pressure from the most recent OMCT simulations and the daily ITG-Kalman solutions are able to explain up to 40 % of extra-tropical sea-level variability in the Southern Ocean. In contrast to this, the daily ITG-Kalman series and simulated continental total water storage variability largely disagree at periods below 30 days. Therefore, as long as no adequate hydrological model will become available, the daily ITG-Kalman series can be regarded as a good initial proxy for high-frequency mass variations at a global scale. As a second result of this study, based on monthly solutions as well as daily observation residuals, it is shown that applying this GRACE-derived de-aliasing model supports the determination of the time-variable gravity field from GRACE data and the subsequent geophysical interpretation. This leads us to the recommendation that future satellite concepts for determining mass variations in the Earth system should be capable of observing higher frequeny signals with sufficient spatial resolution. |
Databáze: | OpenAIRE |
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