| This research develops techniques for reducing error in estimates of surface-mass variability made from time-variable gravity measurements from the GRACE satellite mission. When inferring water storage anomalies from GRACE, the atmospheric gravity signal may be considered a source of noise. Models were developed to approximate the atmosphere's three-dimensional density structure from surface values of temperature and pressure. Comparisons of the atmospheric gravity signals from these models to that derived from realistic density fields computed by a global climate model show that using models based solely on surface data can introduce errors in the time variable surface mass signal inferred from GRACE as large as a few millimeters equivalent water thickness, with a global rms of about 1 mm.; In addition to errors resulting from the imperfect removal of the atmospheric gravity signal, GRACE data contains instrument measurement errors. To mitigate the effects of these errors, techniques for smoothing spatial averaging kernels of arbitrary regions were created. These techniques attempt to isolate the gravity signal in a region while simultaneously minimizing the effects of GRACE observational errors and contamination from surrounding glacial, hydrological, and oceanic gravity signals. Total errors in water storage estimates recovered from synthetic GRACE data with these methods may be reduced by as much as an order of magnitude from the values obtained via the exact averaging kernels. Simulations show that GRACE will be capable of estimating monthly changes in water storage to accuracies of better than 1 cm of water thickness, for regions having areas of 4.0 · 105 km2 or larger. |
