Abstract

During its science phase from 2002–2017, the low-low satellite-to-satellite tracking mission Gravity Field Recovery And Climate Experiment (GRACE) provided an insight into Earth’s time-variable gravity (TVG). The unprecedented quality of gravity field solutions from GRACE sensor data improved the understanding of mass changes in Earth’s system considerably. Monthly gravity field solutions as the main products of the GRACE mission, published by several analysis centers (ACs) from Europe, USA and China, became indispensable products for quantifying terrestrial water storage, ice sheet mass balance and sea level change. The successor mission GRACE Follow-On (GRACE-FO) was launched in May 2018 and proceeds observing Earth’s TVG. The Institute of Geodesy (IfE) at Leibniz University Hannover (LUH) is one of the most recent ACs. The purpose of this article is to give a detailed insight into the gravity field recovery processing strategy applied at LUH; to compare the obtained gravity field results to the gravity field solutions of other established ACs; and to compare the GRACE-FO performance to that of the preceding GRACE mission in terms of post-fit residuals. We use the in-house-developed MATLAB-based GRACE-SIGMA software to compute unconstrained solutions based on the generalized orbit determination of 3 h arcs. K-band range-rates (KBRR) and kinematic orbits are used as (pseudo)-observations. A comparison of the obtained solutions to the results of the GRACE-FO Science Data System (SDS) and Combination Service for Time-variable Gravity Fields (COST-G) ACs, reveals a competitive quality of our solutions. While the spectral and spatial noise levels slightly differ, the signal content of the solutions is similar among all ACs. The carried out comparison of GRACE and GRACE-FO KBRR post-fit residuals highlights an improvement of the GRACE-FO K-band ranging system performance. The overall amplitude of GRACE-FO post-fit residuals is about three times smaller, compared to GRACE. GRACE-FO post-fit residuals show less systematics, compared to GRACE. Nevertheless, the power spectral density of GRACE-FO and GRACE post-fit residuals is dominated by similar spikes located at multiples of the orbital and daily frequencies. To our knowledge, the detailed origin of these spikes and their influence on the gravity field recovery quality were not addressed in any study so far and therefore deserve further attention in the future. Presented results are based on 29 monthly gravity field solutions from June 2018 until December 2020. The regularly updated LUH-GRACE-FO-2020 time series of monthly gravity field solutions can be found on the website of the International Centre for Global Earth Models (ICGEM) and in LUH’s research data repository. These operationally published products complement the time series of the already established ACs and allow for a continuous and independent assessment of mass changes in Earth’s system.

Highlights

  • The carried out comparison of Gravity Recovery and Climate Experiment (GRACE) and GRACE-FO K-band range-rates (KBRR) post-fit residuals highlights an improvement of the GRACE-FO K-band ranging system performance

  • To evaluate the quality of the computed monthly gravity field solutions, the LUHGRACE-FO-2020 time series is compared to solutions of the Science Data System (SDS) and Combination Service for Time-variable Gravity Fields (COST-G) analysis centers (ACs)

  • The solutions are computed with the MATLABbased GRACE-SIGMA software package recently developed at Leibniz University Hannover

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Summary

Introduction

The relative position change of the two satellites in terms of the inter-satellite range was measured by a microwave K/Ka-band ranging (KBR) system with a micron level precision. This principal measuring technique—the low-low satellite-to-satellite tracking—was established for the first time on a geodetic satellite mission, and in combination with additional scientific payload [2,3], revolutionized the monitoring of Earth’s gravity variations from space. The gravity field solutions help to quantify terrestrial water storage changes, e.g., [26,27,28,29,30,31], monitor ice sheet and glacier mass balance, e.g., [32,33,34,35,36], and the mass contribution to sea level change, e.g., [36,37,38,39]

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