We examined the first‐ever laser ranging interferometer (LRI) measurements of inter‐satellite tracking acquired by Gravity Recovery and Climate Experiment (GRACE) Follow‐On satellites. Through direct along‐orbit analysis of instantaneous inter‐satellite measurements, we demonstrate the higher sensitivity of LRI (than K‐band microwave ranging [KBR]) to anomalies associated with the Earth static gravity field at high spatial resolutions of 100–200 km. We found that LRI captures gravitational signals as small as 0.1 nm/s2 at 490 km altitude, improved by 1 order of magnitude from KBR. This allows LRI to uniquely detect un‐/mis‐modeled short‐wavelength gravitational perturbations. We employed all LRI data in 2019 to validate various state‐of‐the‐art global static gravity field models and show that LRI measurements, even over 1 month, can distinguish subtle differences among the models computed from ~15 years of GRACE KBR and ~4 years of Gravity Field and Steady‐State Ocean Circulation Explorer (GOCE) gradiometry data. Ultra‐precise LRI measurements will be yet another critical data set for future gravity field model development.

We develop a transfer function to determine in situ line‐of‐sight gravity difference (LGD) directly from Gravity Recovery and Climate Experiment (GRACE) range‐acceleration measurements. We first reduce GRACE data to form residual range‐acceleration referenced to dynamic orbit computed with a reference gravity field and nonconservative force data. Thus, the residuals and the corresponding LGD data reflect time‐variable gravity signals. A transfer function is designed based on correlation‐admittance spectral analysis. The correlation spectrum shows that residual range‐acceleration and LGD are near‐perfectly correlated for frequencies >5 cycles‐per‐revolution. The admittance spectrum quantifies that the LGD response to range‐acceleration is systematically larger at lower frequencies, due to the increased contribution of centrifugal acceleration. We find that the correlation and admittance spectra are stationary (i.e., are independent of time, satellite altitude, and gravity strength) and, therefore, can be determined a priori with high fidelity. We determine the spectral transfer function and the equivalent time domain filter. Using both synthetic and actual GRACE data, we demonstrate that in situ LGD can be estimated via the transfer function with an estimation error of 0.15 nm/s2, whereas the actual GRACE data error is around 1.0 nm/s2. We present an application of LGD data to surface water storage changes in large basins such as Amazon, Congo, Parana, and Mississippi by processing 11 years of GRACE data. Runoff routing models are calibrated directly using LGD data. Our technique demonstrates a new way of using GRACE data by forward modeling of various geophysical models and in‐orbit comparison with such GRACE in situ data.

No abstract

We examined the sensitivity of GRACE Follow‐On (GRACE‐FO) laser ranging interferometer (LRI) measurements to sub‐monthly time‐variable gravity (TVG) signals caused by transient, high‐frequency mass changes in the Earth system. GRACE‐FO LRI provides complementary inter‐satellite ranging measurements with higher precision over a wider range of frequencies than the baseline K‐band microwave ranging system. The common approach for studying mass variation relies on the inverted TVG or mascon solutions over a period of, for example, one month or 10 days which are adversely affected by temporal aliasing and/or smoothing. In this article, we present the alternative along‐orbit analysis methodology in terms of line‐of‐sight gravity difference (LGD) to fully exploit the higher precision LRI measurements for examination of sub‐monthly mass changes. The discrepancy between “instantaneous” LGD LRI observations and monthly‐mean LGD (from Level‐2 data) at satellite altitude indicates the sub‐monthly gravitational variability not captured by monthly‐mean solutions. In conjunction with the satellite ocean altimetry observations, high‐frequency non‐tidal atmosphere and ocean models, and hydrology models, we show that the LGD LRI observations detect the high‐frequency oceanic mass variability in the Argentine Basin and the Gulf of Carpentaria, and sub‐monthly variations in surface (river) water in the Amazon Basin. We demonstrate the benefits gained from repeat ground track analysis of GRACE‐FO LRI data in the case of the Amazon surface water flow. The along‐orbit analysis methodology based on LGD LRI time series presented here is especially suitable for quantifying temporal and spatial evolution of extreme, rapidly changing mass variations.