On the joint estimation of model and satellite sea surface height anomaly errors |
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| Institution: | 1. Department of Oceanography, Naval Postgraduate School, Monterey, CA 93943-5122, USA;2. James Rennell Division for Ocean Circulation and Climate, Southampton Oceanography Centre, Southampton, UK;1. Federal University of São Carlos, Cardiovascular Physical Therapy Laboratory, Department of Physiotherapy, Rod. Washington Luís, km 235, São Carlos, 13.565-905, Brazil;2. University of Waterloo, Faculty of Applied Health Sciences, 200 University Ave W, Waterloo, N2L 3G1, Canada;3. Schlegel-University of Waterloo Research Institute for Aging, 250 Laurelwood Drive, Waterloo, N2J 0E2, Canada;4. Federal University of São Carlos, Department of Statistics, Rod. Washington Luís, km 235, São Carlos, 13.565-905, Brazil;5. Wellman Center for Photomedicine, Massachusetts General, Hospital - Harvard Medical School, 40 Blossom Street, Massachusetts, MA 02114, USA;6. São Paulo University, Departament of Physics, Av. Trabalhador São-carlense, 400, São Carlos, 13566-590, Brazil;7. University of Milan, Department of Biomedical Sciences for Health, Via C. Pascal 36, Milan, 20133, Italy;8. IRCCS Policlinico San Donato, Department of Cardiothoracic, Vascular Anesthesia and Intensive Care, Via F. Fellini 4, Milan, 20097, Italy |
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| Abstract: | We describe a technique to estimate the error field in the sea surface height (SSH) anomaly field of an ocean model through the joint use of SSH anomaly fields measured from two satellites, Topex/Poseidon (T/P) and ERS-2. The joint error maps for the model, T/P and ERS-2 show distributions distinctly different from one another and globally inhomogeneous. Both sampling errors and instrument errors are represented in the mapped fields. Additionally, we compare the joint error estimation method to a technique using the model and only one satellite, and show the importance of the cross covariance between the measured SSH and the true SSH field in the estimation of the error field. Finally, we look at the distribution of the error versus the variance of the SSH at a location. This logged distribution suggests that the model errors are generally proportional to the model's variance (regression coefficient of 0.99, globally) while the satellites' errors do not exhibit this linear relationship (regression coefficients on the average of 0.60). The comparison of the two satellite distributions implies that ERS-2 has a lower sampling error than the T/P instrument except in the tropical region. |
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