The parameter optimization problem in oceanography is studied, in which an oceanic model with thermodynamics is used to determine the surface thermal forcing field by the adjoint technique. Two datasets are chosen, the climatological monthly-mean sea surface temperature (SST) and winds. The seasonal variability of the surface heat flux distribution over the tropical Pacific ocean is investigated. / The use of a priori information is investigated in the formulation of the cost function. Experimental evidence has verified that adding a priori information of the estimated parameters can increase the probability for the solution to be unique. The a priori information also plays the role of bogus data. It serves not only to increase the number of observations but to improve the conditioning of the Hessian. / The results are very promising. It has been possible, for the first time, to calculate the seasonal surface heat flux patterns which are consistent with both the ocean's physics and the observations. / Source: Dissertation Abstracts International, Volume: 53-11, Section: B, page: 5622. / Major Professor: James J. O'Brien. / Thesis (Ph.D.)--The Florida State University, 1992.
| Identifer | oai:union.ndltd.org:fsu.edu/oai:fsu.digital.flvc.org:fsu_76824 |
| Contributors | Yu, Lisan., Florida State University |
| Source Sets | Florida State University |
| Language | English |
| Detected Language | English |
| Type | Text |
| Format | 178 p. |
| Rights | On campus use only. |
| Relation | Dissertation Abstracts International |
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