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A new assessment of temporal correlations in GRACE TWS time series

Authors

Gunes,  Ozge
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Klos,  Anna
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Lenczuk,  Artur
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Aydin,  Cuneyt
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Bogusz,  Janusz
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

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Citation

Gunes, O., Klos, A., Lenczuk, A., Aydin, C., Bogusz, J. (2023): A new assessment of temporal correlations in GRACE TWS time series, XXVIII General Assembly of the International Union of Geodesy and Geophysics (IUGG) (Berlin 2023).
https://doi.org/10.57757/IUGG23-0424


Cite as: https://gfzpublic.gfz.de/pubman/item/item_5016027
Abstract
We focus on evaluating the time correlations present in the Total Water Storage (TWS) time series observed by the GRACE missions over the period 2002-2022. We subject the original TWS time series provided in the form of a mascon solution by the NASA, GSFC to analysis of temporal correlations using the maximum likelihood estimation. We assume a conventional deterministic model of trend plus annual and semi-annual periodicities. We find that in many areas around the world colored noise similar to random-walk noise dominates, the spatial pattern of which is inconsistent. In the next step, we change the conventional model to a new redefined deterministic model that, in addition to seasonal components, includes third-, fourth- or fifth-degree polynomials, depending on the location of the mascon to parameterize the nonlinearity of long-term changes. Once the definition of the deterministic model has been changed, we re-run the analysis. We show that the spatial pattern of temporal dependencies is much more consistent than with the conventional model. Many regions are characterized by a change in stochastic character from random-walk noise to one closer to white noise. The TWS time series for these regions is characterized by white noise, meaning that there are no short-period signals associated with the hydrosphere, and the previously observed random-walk noise was only associated with long-term changes that carried over into the stochastic part. The random-walk noise observed for TWS time series after redefining the deterministic model has a high correlation with the occurrence of short-term events such as droughts and floods.