On the performance of equiangular mascon solution in GRACE-like missions

Abbas Abedini,Wolfgang Keller,Ali Reza Amiri-Simkooei

doi:10.4401/ag-8621

Abbas Abedini, Wolfgang Keller + Show 1 more

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https://doi.org/10.4401/ag-8621

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Abstract

Mass concentration (mascon) solutions for GRACE (Gravity Recovery and Climate Experiment) data are widely used in various regional-to-global mass change studies. The current advances in the mascon solution have mainly concentrated on improving the spatial resolution of the solution, enhancing the applied least-squares regularization, and the characterization of the solution errors. Most of the mascon solutions are obtained on the equal-area grid, inducing complexities in creating the grid and its presentation. In this regard, estimation of the mascon solutions on equiangular grids can be appealing. Furthermore, in the equal-area methods, there is no global criterion to determine the size of the mascon areas. The mascon size is usually chosen in a subjective manner which hampers the objective application of different mascon solutions. In view of these challenges, two main questions are addressed in this study: i) what kind of modifications should be made in computation scheme of the mascon solution if equiangular grids are used to account for different areas of the grid patches, and ii) in case of non-equiangular solutions, how to define an objective criterion for the patch sizes based on the resolution of both the observation and the signal of interest. We investigate the performance of the high-resolution mascon-based approach, proposed by Abedini et al. [2021], which uses GRACE-like observations similar to level-1 data for a period of one month over the Greenland region. Two main practical issues are studied on the estimation of the surface density changes as follows. First, we show that for equiangular grids, the area of the patches should be accounted for in the regularization by introducing area-affected weights for the unknown parameters. We investigate the effect of three different area-affected weighting strategies on the derived solution. Secondly in order to obtain proper size for the patches, a novel approach is presented to investigate the performance of the mascon solution using the analysis of the resolution matrix entries. The proposed resolution analysis is used to obtain the optimal patch size for the discretization of the area of interest. Based on the results, it is demonstrated that the minimum legible patch size in the Greenland area for the current settings of the GRACE observations is 0.5 degree in the NS direction and a latitude-adaptive grid-size rather than equiangular grids at high latitude regions in the EW direction.

Highlights

The simulated data contains 342 arcs from Gravity Recovery and Climate Experiment (GRACE) satellites that cross over Greenland region during one-month
We addressed two practical issues regarding the GRACE-based mascon estimation using local basis functions
The proposed methodology is twofold. It helps to find out how regularization can bias the mascon solution using the singular value decomposition (SVD) decomposition of the resolution matrix, and second what would be the achievable resolution in the mascon solution over the Greenland region given the characteristics of GRACE mission

Summary

Introduction

Many studies have been performed in the hydrological applications using data extracted from satellite’s missions like Gravity Recovery and Climate Experiment (GRACE) [Awange et al, 2011; Bettadpur, 2007; Loomis et al, 2019; Luthcke et al, 2013; Sabaka et al, 2010; Save et al, 2012; Scanlon et al, 2016; Watkins et al, 2015; Wiese et al, 2016]. The main mission of the GRACE satellites was to monitor the time-variable gravity field, which indicates mass changes due to water movement in the Earth’s water cycle [Scanlon et al, 2016]. The Earth’s surface density can generally be estimated by analysis of GRACE data with two different methods. The first group uses spherical harmonics (SH) to present the mascon solutions [Bettadpur, 2007; Wahr et al, 1998], and the second group of methodologies uses the Stokes coefficients to estimate the mass concentration from the satellite-to-satellite-tracking (SST) data [Luthcke et al, 2013; Save et al, 2016; Watkins et al, 2015]. A comprehensive review of different methods and their pros and cons have been provided by Save et al [2016], Scanlon et al [2016], Jing et al [2019] and Abedini et al [2021]

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