GPS radio occultation and the role of atmospheric pressure on spaceborne gravity estimation over Antarctica
To recover temporal variable gravity signals from space, the gravity measurements from the Gravity Recovery and Climate Experiment (GRACE) require the atmospheric pressure loading to be accurately modeled and removed. The pressure fields from Numerical Weather Prediction (NWP) models are less accurate over the Southern Ocean and Antarctica. GPS radio occultation observations could achieve dense spatial coverage in remote regions. In this research, GPS occultation pressure profiles are accurately retrieved and validated. The special physical properties of occultation over Antarctica are investigated. Using a 1-D variational approach, we show that GPS occultation can improve pressure modeling for data-sparse regions, such as Antarctica. The global NWP models show large uncertainties in the Antarctic region. We study the atmospheric effects on gravity solutions, including topography, atmospheric tides, degree 0 and 1 terms, inverted barometer (IB) assumptions, and the use of different NWP models. The atmospheric aliasing error primarily caused by GRACE orbital sampling and its correlation with the atmospheric variability are also investigated. Our study shows that the model correlation and IB assumption underestimate the true aliasing error. The analysis models are assessed using Automatic Weather Station (AWS) observations on the Antarctic continent. ECMWF operational data show a much better agreement with AWS than NCEP reanalysis does. The result shows strong correlation with the topography with lower standard deviation values in the interior and higher standard deviation values around the coastal area, while the difference between analysis models exhibits large difference in the interior of Antarctica. We also investigate the influences of different algorithms and assumptions of 2-D or 3-D atmospheric structures on the atmospheric de-aliasing product. Air densities derived from the hydrostatic equation and the equation of state show non-negligible difference. The difference between our improved algorithm and the GRACE de-aliasing product, as well as the difference between 3-D hydrostatic formulation and 2-D algorithm, are found to be almost below the GRACE sensitivity. We discover that the atmospheric structure and latitudinal variations of gravity are largely compensated by removing their respective long-term means. Removing mean field does not help to reduce the discrepancies between ECMWF and NCEP.
School:The Ohio State University
School Location:USA - Ohio
Source Type:Master's Thesis
Keywords:gps occultation pressure time variable gravity grace de aliasing
Date of Publication:01/01/2006