Error Assessment of GRACE and GRACE Follow‐On Mass Change. Issue 9 (2nd September 2021)

• Record Type: Journal Article
• Authors: Chen, Jianli; Tapley, Byron; Tamisiea, Mark E.; Save, Himanshu; Wilson, Clark; Bettadpur, Srinivas; Seo, Ki‐Weon
• Is Part Of: Journal of geophysical research. Volume 126:Issue 9(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-09-02
• Subjects: GRACE -- GRACE‐FO -- GFO -- uncertainty -- gravity -- mass change -- Three‐Cornered Hat -- open ocean residual; Geomagnetism -- Periodicals; Geochemistry -- Periodicals; Geophysics -- Periodicals; Earth sciences -- Periodicals; 551.1
• DOI: 10.1029/2021JB022124
• Languages: English
• ISSNs: 2169-9313

Abstract

Abstract: We carry out a comprehensive error assessment of Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow‐On (GFO) Release‐6 (RL06) solutions from the Center for Space Research (CSR) at the University of Texas at Austin, NASA Jet Propulsion Laboratory (JPL), and Geoforschungszentrum (GFZ). The study covers the period April 2002 to August 2020 and uses two different methods, one based upon open ocean residuals (OOR) and the other a Three‐Cornered Hat (TCH) calculation. General results from the two methods are similar. With 300 km Gaussian smoothing OOR RMS errors for CSR, JPL, and GFZ solutions are ∼2.01, 3.19, and 3.67 cm, respectively. With additional decorrelation filtering OOR RMS values are reduced to ∼1.24, 1.53, and 1.69 cm, respectively. TCH analysis also shows that CSR has the lowest noise levels with similar RMS values, and additional decorrelation filtering reduces error levels. TCH may underestimate errors if there are common errors among geophysical background models. Errors in GFO's first two years (25 solutions for 2018.06 to 2020.08) are comparable to those of GRACE when zonal degree 2 and 3 coefficients are replaced by Satellite Laser Ranging estimates. The OOR method reveals mismodeled intra‐seasonal dynamic ocean signals associated with the Argentine Gyre during de‐aliasing, while the TCH method shows differences between ocean tide models near Australia and Antarctica. Both OOR and TCH RMS analysis offer a means to assess the noise level of GRACE/GFO estimated mass change. The actual uncertainty of GRACE/GFO estimate averaged (or totaled) over a given region is also affected by other error sources. Plain Language Summary: The Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow‐On (GFO) satellite gravity missions provide global measurements of the Earth gravity change, which can be used to study mass redistribution in the Earth system, such as sea level rise, glacial melting, and land water storage change. However, it is difficult to determine the noise level of GRACE/GFO observations. In this study, we estimate GRACE/GFO noise level using two methods. One is based on GRACE/GFO residuals over the ocean, as the true ocean signals can be predicted. The other method is based on the so‐called Three‐Cornered Hat (TCH) calculation. The OOR estimates show that the noise level of three commonly used GRACE/GFO Release‐6 (RL06) gravity solutions, provided by the Center for Space Research (CSR) at the University of Texas at Austin, US NASA Jet Propulsion Laboratory (JPL), and German Research Centre for Geosciences (GFZ), are about 2.01, 3.19, and 3.67 cm, respectively, when 300 km Gaussian smoothing is applied. The TCH calculation shows similar results. Both OOR and TCH estimates suggests that the CSR solutions shown the lowest noise level. The OOR and TCH calculations also capture some geophysical signals that are related errors in background geophysical models used in GRACE/GFO data processing. Key Points: We provide an error assessment of Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow‐On (GFO) measurements using the open ocean residual (OOR) and Three‐Cornered Hat (TCH) methods With 300 km Gaussian smoothing, OOR RMS errors for Center for Space Research (CSR), Jet Propulsion Laboratory (JPL), and Geoforschungszentrum Release‐6 (RL06) are estimated to be ∼2.01, 3.19, and 3.67 cm, respectively TCH shows similar results, confirming CSR RL06 has lowest noise level, and both methods capture issues with background geophysical models