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A Transfer Function Between Line‐of‐Sight Gravity Difference and GRACE Intersatellite Ranging Data and an Application to Hydrological Surface Mass Variation
Author(s) -
GhobadiFar Khosro,
Han ShinChan,
Weller Steven,
Loomis Bryant D.,
Luthcke Scott B.,
MayerGürr Torsten,
Behzadpour Saniya
Publication year - 2018
Publication title -
journal of geophysical research: solid earth
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.983
H-Index - 232
eISSN - 2169-9356
pISSN - 2169-9313
DOI - 10.1029/2018jb016088
Subject(s) - acceleration , gravitational field , transfer function , range (aeronautics) , geodesy , environmental science , physics , geology , materials science , engineering , composite material , electrical engineering , classical mechanics , astronomy
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/s 2 , whereas the actual GRACE data error is around 1.0 nm/s 2 . 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.