Regional gravity recovery from GRACE using L-curve criterion and covariance functions

Abstract

The objective of this dissertation is to resolve the regional gravity field at best resolution using all available GRACE products. Because restrictions and limitations of contemporary global solutions, we present a method of estimating surface mass anomalies at regional scales directly using satellite-to-satellite K-band Ranging (KBR) data from the Gravity Recovery and Climate Experiment (GRACE) twin-satellite mission. Geopotential differences based primarily on KBR measurements are derived using a modified energy integral method with an extensive calibration for accelerometer measurements. Surface mass anomalies are computed based on a downward continuation method, and the best regularization parameter is estimated by the L-curve criterion method. We derive the covariance functions in both space- and space-time domains and use them as light constraints in the regional gravity estimation process. The space-time covariance function has a time-correlation distance of 1.2723 months, suggesting that GRACE observations between neighboring months are correlated. The bias in the regional gravity solution is mitigated by using the covariance functions. The averaged commission errors of the method itself are only 6.86% and 5.85% for the solutions based on the space-covariance function (SCF) and the space-time covariance function (STCF), respectively. Our regional gravity solution, which requires no further post-processing, shows enhanced regional gravity signatures, reduced edge effects and gravity artifacts, agrees with the NASA/GSFC’s GRACE MASCON solution to about 1 cm RMS in terms of water thickness change over the Amazon basin. The regional gravity solution also maintains the greatest signal energy while suppressing the short wavelength noises.

The objective of this dissertation is to resolve the regional gravity field at best resolution using all available GRACE products. Because restrictions and limitations of contemporary global solutions, we present a method of estimating surface mass anomalies at regional scales directly using satellite-to-satellite K-band Ranging (KBR) data from the Gravity Recovery and Climate Experiment (GRACE) twin-satellite mission. Geopotential differences based primarily on KBR measurements are derived using a modified energy integral method with an extensive calibration for accelerometer measurements. Surface mass anomalies are computed based on a downward continuation method, and the best regularization parameter is estimated by the L-curve criterion method. We derive the covariance functions in both space- and space-time domains and use them as light constraints in the regional gravity estimation process. The space-time covariance function has a time-correlation distance of 1.2723 months, suggesting that GRACE observations between neighboring months are correlated. The bias in the regional gravity solution is mitigated by using the covariance functions. The averaged commission errors of the method itself are only 6.86% and 5.85% for the solutions based on the space-covariance function (SCF) and the space-time covariance function (STCF), respectively. Our regional gravity solution, which requires no further post-processing, shows enhanced regional gravity signatures, reduced edge effects and gravity artifacts, agrees with the NASA/GSFC’s GRACE MASCON solution to about 1 cm RMS in terms of water thickness change over the Amazon basin. The regional gravity solution also maintains the greatest signal energy while suppressing the short wavelength noises.