Please use this identifier to cite or link to this item: http://dx.doi.org/10.18419/opus-3971
|Title:||Copula-based analysis of correlation structures in case of GRACE coefficients|
|Abstract:||Data from the Gravity Recovery and Climate Experiment (GRACE) has significantly improved our knowledge of the terrestrial water cycle. With the availability of GRACE data from 2002, we are now able to perform even climate change studies with respect to water storage variations. However, as GRACE is already after its expected lifetime, we have to find methods for filling the missing months in the past data and to possibly bridge the gap until GRACE Follow On. In this study, we, therefore, analyze the potential of Copula-based methods for simulating GRACE coefficients data from other hydrological data sources. The method exploits linear and non-linear relationships between two or more variables by fitting a theoretical Copula function into an empirical bivariate or multivariate distribution function. Finally, new data, which is then consistent with the previously derived dependence structure, can be simulated by evaluating the conditional distribution function given by the theoretical Copula. First, we want to analyze the applicability of the proposed method to spherical harmonic coefficients data from GRACE. As the approach involves several drawings of random data, we are interested if this random nature has any impact on the results. We therefore generate filtered out of unfiltered GRACE coefficients, based on the previously derived dependence structure. The comparison between the simulated and filtered data shows a very good agreement with negligible differences in both of the spatial and spectral domain. We also want to evaluate if Copula-based methods are able to estimate reliable water storage changes from the independent hydrological data. Therefore, we derive the dependence structure between filtered water storage changes from GRACE and global gridded precipitation data from the Global Precipitation Climatology Center GPCC. Based on the fitted theoretical Copula, we then simulate water storage changes from precipitation data. The Copula-based estimates are compared with filtered GRACE coefficients data in both of the spectral and spatial domain. We also perform a catchment-based analysis between area-aggregated time-series of simulated and GRACE-derived water storage change. The analysis shows that our estimates and the original filtered GRACE coefficients data are in very good agreement. Thus, we conclude that the proposed method is indeed able to fill the missing months in the GRACE-dataset and to extend even the time-series until the launch of GRACE Follow On.|
|Appears in Collections:||06 Fakultät Luft- und Raumfahrttechnik und Geodäsie|
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