A new approach for the determination of the drag coefficient from the upper ocean response to a tropical cyclone: A feasibility study
KAUST DepartmentEarth Fluid Modeling and Prediction Group
Earth Science and Engineering Program
Environmental Science and Engineering Program
Physical Sciences and Engineering (PSE) Division
KAUST Grant NumberKUS-C1-016-04
Permanent link to this recordhttp://hdl.handle.net/10754/561967
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AbstractWe seek to determine if a small number of measurements of upper ocean temperature and currents can be used to make estimates of the drag coefficient that have a smaller range of uncertainty than previously found. We adopt a numerical approach using forward models of the ocean's response to a tropical cyclone, whereby the probability density function of drag coefficient values as a function of wind speed that results from adding realistic levels of noise to the simulated ocean response variables is sought. Allowing the drag coefficient two parameters of freedom, namely the values at 35 and at 45 m/s, we found that the uncertainty in the optimal value is about 20% for levels of instrument noise up to 1 K for a misfit function based on temperature, or 1.0 m/s for a misfit function based on 15 m velocity components. This is within tolerable limits considering the spread of measurement-based drag coefficient estimates. The results are robust for several different instrument arrays; the noise levels do not decrease by much for arrays with more than 40 sensors when the sensor positions are random. Our results suggest that for an ideal case, having a small number of sensors (20-40) in a data assimilation problem would provide sufficient accuracy in the estimated drag coefficient. © 2011 The Oceanographic Society of Japan and Springer.
SponsorsThis publication was based on work supported by award no. KUS-C1-016-04, made by King Abdullah University of Science and Technology (KAUST). I would like to thank Peter Niiler and the other PIs on the Coupled Boundary Layer Air-Sea Transfer Experiment for designing the field experiment that motivated this study. Thanks to Gerry Creager and Guy Almes for providing computer support. We would like to acknowledge three anonymous reviewers for very helpful comments on an earlier draft of this paper. Additionally, we thank statisticians Cornelis Potgieter and Avishek Charkraborty (who specializes in Bayesian techniques) for reviewing our methodology and providing helpful commentary.
JournalJournal of Oceanography