Recovery of Terrestrial Water Storage Change from Low-Low Satellite-to-Satellite Tracking
Loading...
Date
2007-12
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Ohio State University. Division of Geodetic Science
Abstract
Gravity Recovery and Climate Experiment (GRACE) spaceborne gravimetry provides a
unique opportunity for quantifying geophysical signals including terrestrial water storage
change for a wide variety of climate change and geophysical studies. The contemporary
methodology to process GRACE data for temporal gravity field solutions is based on
monthly estimates of the mean geopotential field with a spatial resolution longer than 600
km (the Level-2 or L2 data products), after appropriate Gaussian smoothing to remove
high-frequency and geographically-correlated errors. Alternative methods include the
direct processing of the GRACE low-low satellite-to-satellite tracking data over a region
of interest, leading to improved or finer spatial and temporal resolutions of the resulting
local gravity signals. The GRACE Level 1B data have been analyzed and processed to
recover continental water storage in a regional solution, by first estimating in situ Line-
Of-Sight (LOS) gravity differences simultaneously with the relative position and velocity
vectors of the twin GRACE satellites. This new approach has been validated using a
simulation study over the Amazon basin (with three different regularization methods to
stabilize the downward continuation solutions), and it is demonstrated that the method
achieves an improved spatial resolution as compared to some of the other GRACE
processing techniques, including global spherical harmonic solutions, and regional
solutions using in situ geopotential differences.
Description
This report was prepared for and submitted to the Graduate School of the Ohio State University as a dissertation in partial fulfillment of the requirements of the Ph.D. degree.
The research is supported by grants from NSF's Collaboration in Mathematical Geociences Program (EAR0327633), NASA Earth Science programs (NNG04GN19G, NNG05GL26G, JPL 1265252), and a Shell Fellowship (July-Sept., 2007), School of Earth Sciences, The Ohio State University. Additional computing resources are provided by the Ohio Supercomputer Center.
The research is supported by grants from NSF's Collaboration in Mathematical Geociences Program (EAR0327633), NASA Earth Science programs (NNG04GN19G, NNG05GL26G, JPL 1265252), and a Shell Fellowship (July-Sept., 2007), School of Earth Sciences, The Ohio State University. Additional computing resources are provided by the Ohio Supercomputer Center.