Comparison of Criteria for the Identification of Correlated Orders in GRACE Spherical Harmonic Coefficients
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-wi
- PDF / 707,293 Bytes
- 8 Pages / 595.516 x 790.987 pts Page_size
- 36 Downloads / 197 Views
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. Keywords
Empirical decorrelation Filtering GRACE Spherical harmonic coefficients
1
Introduction
Monthly gravity field solutions in the form of spherical harmonic coefficients derived from data of the Gravity Recovery and Climate Experiment (GRACE; Tapley et al. 2004) satellite mission are routinely used for monitoring mass variations in the Earth system. These solutions contain correlated
Electronic Supplementary Material The online version of this chapter (https://doi.org/10.1007/1345_2019_83) contains supplementary material, which is available to authorized users. D. Piretzidis () · M. G. Sideris Department of Geomatics Engineering, University of Calgary, Calgary, AB, Canada e-mail: [email protected]; [email protected] D. Tsoulis Department of Geodesy and Surveying, Aristotle University of Thessaloniki, Thessaloniki, Greece e-mail: [email protected]
errors, which manifest when month-to-month differences or monthly differences from a static gravity field solution are calculated. In the spatial domain, these errors produce longitudinal artifacts, commonly referred to as “stripes”. The removal of correlated errors from GRACE coefficient changes is usually performed using an empirical decorrelation filter (EDF), also known as destriping filter. This type of filter removes the contribution of a smoothing polynomial from the even- and odd-degree coefficient series of a specific order (Swenson and Wahr 2006). The EDF is usually implemented from an order mmin , where the correlated errors approximately start to appear, up to the maximum order of each monthly set of coefficient changes. A different and not so commonly used approach is the selective implementation of the EDF to the coefficient series that appear to be heavily influenced by correlated errors. This idea originates from Huang et al. (2012), who used a selective EDF scheme to study the groundwater storage variability in the Great Lakes and in Alberta, Canada. More recently, Piretzidis et al. (2018) a
Data Loading...
