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Comparison of Criteria for the Identification of Correlated Orders in GRACE Spherical Harmonic Coefficients

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IX Hotine-Marussi Symposium on Mathematical Geodesy

Part of the book series: International Association of Geodesy Symposia ((IAG SYMPOSIA,volume 151))

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Abstract

The study of the Earth’s time-varying gravity field using GRACE data requires the removal of correlated errors using filtering techniques in the spherical harmonic domain. The empirical decorrelation filter is an effective method of decorrelating order-wise series of spherical harmonic coefficients, although its improper implementation can lead to signal attenuation. To reduce geophysical signal over-filtering, decorrelation should be performed only for orders that show evidence of high correlation. In this paper we investigate and compare the behavior of three criteria, i.e., the root mean square ratio, the angle distribution of phase spectrum and the geometric properties of order-wise coefficient series, that can be used for the identification of correlated orders in GRACE data. Our analysis indicates that the root mean square ratio is the most reliable criterion, due to its simple implementation and for providing averaged time series of equivalent water height with smaller root mean square error, based on a simulation.

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Acknowledgements

The two anonymous reviewers are thanked for their valuable comments and suggestions. NASA’s PODAAC and GES DISC services are thanked for making freely available the GRACE Level 2 data and the GLDAS-1 Noah models. This work is financially aided by a grant from Canada’s Natural Sciences and Engineering Research Council (NSERC) to the second author.

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Correspondence to Dimitrios Piretzidis .

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Piretzidis, D., Sideris, M.G., Tsoulis, D. (2019). Comparison of Criteria for the Identification of Correlated Orders in GRACE Spherical Harmonic Coefficients. In: NovĂ¡k, P., Crespi, M., Sneeuw, N., SansĂ², F. (eds) IX Hotine-Marussi Symposium on Mathematical Geodesy. International Association of Geodesy Symposia, vol 151. Springer, Cham. https://doi.org/10.1007/1345_2019_83

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