HR: 1330h
AN: G23B-06    [Abstracts]
TI: Fuzzy Modeling of Continental Water Storage Changes Observed by GRACE
AU: * Akyilmaz, O
EM: akyilma2@itu.edu.tr
AF: Istanbul Technical University, Faculty of Civil Eng., Division of Geodesy, Ayazaga Campus, Istanbul, 34469 Turkey
AU: Han, S
EM: han.104@osu.edu
AF: Civil and Environmental Engineering and Geodetic Science, Laboratory for Space Geodesy and Remote Sensing, 470 Hitchcock Hall, 2070 Neil Avenue, Columbus, OH 43210 United States
AU: Shum, C
EM: ckshum@osu.edu
AF: Civil and Environmental Engineering and Geodetic Science, Laboratory for Space Geodesy and Remote Sensing, 470 Hitchcock Hall, 2070 Neil Avenue, Columbus, OH 43210 United States
AB: The low-low satellite-to-satellite (SST) tracking mission, Gravity Recovery and Climate Experiment (GRACE), provides scientists an efficient and cost-effective way to map the Earth's static and monthly temporal gravity fields with unprecedented accuracy and resolution. One of the major objectives of GRACE is to measure the climate-sensitive signals generated by mass redistributions on Earth at spatial scales greater than several hundred km and temporal scales longer than 30 days. Studies including non-isotropic filtering of GRACE signals and alternate processing of GRACE data have enabled enhancement of temporal and spatial resolutions. Fuzzy logic based methods have been widely used by various disciplines for improving model prediction, control, classification etc. Its ability of providing linguistic description of the relations between the model components has made it a valuable tool for potential model improvements. In this study, fuzzy inference systems whose parameters are optimized by mathematical optimization algorithms, have been used to recover monthly or sub-monthly mean water storage anomalies (MWSA) in South America from the gravity variations observed by GRACE. To this end, regularly gridded MWSA was computed by averaging daily water storage anomalies derived from NCEP (National Centers for Environmental Prediction) daily mean water storage (MWS) data. We tested the fuzzy logic algorithm on the GRACE Level 2 (L2) data products and the data products generated by processing Level 1B (L1B) data based on the energy conservation methods. Results from the obtained fuzzy model were tested with independent data that was not used for estimation of the model parameters. Performance of the resulting model was compared with those of other models previously used for detection of MWSA from GRACE observations.
DE: 1214 Geopotential theory and determination
DE: 1234 Regional and global gravity anomalies and Earth structure
SC: Geodesy [G]
MN: 2005 Joint Assembly