DEDUCING DYNAMIC PROPERTIES FROM SIMULATED HYDROGRAPHIC DATA .1. RESULTS FROM A NON-EDDY-RESOLVING MODEL

Authors
Citation
Hm. Zhang et Ng. Hogg, DEDUCING DYNAMIC PROPERTIES FROM SIMULATED HYDROGRAPHIC DATA .1. RESULTS FROM A NON-EDDY-RESOLVING MODEL, Journal of marine research, 54(4), 1996, pp. 679-703
Citations number
38
Categorie Soggetti
Oceanografhy
Journal title
ISSN journal
00222402
Volume
54
Issue
4
Year of publication
1996
Pages
679 - 703
Database
ISI
SICI code
0022-2402(1996)54:4<679:DDPFSH>2.0.ZU;2-Q
Abstract
Inverse models are widely used in oceanography. However, their reliabi lity remains an open question, as comparison of inverse model results with real values of ocean parameters is difficult due to insufficient knowledge of the latter. The feasibility of extracting the ocean gener al circulation, mixing rates, as well as air-sea heat and freshwater f luxes from hydrographic data is studied by applying an inverse model t o the CME (Community Modeling Effort) results where both the physics a nd parameter values are known. The inverse model assumes approximate t hermal wind balance and steady state conservation laws for mass, heat, and salt, assumptions satisfied by die GCM ocean although the residua ls in the tracer conservation equations are comparable to the diffusio n terms in the deep ocean. Effects of errors in these equations on inv erse model solutions for different variables are studied in detail. A surface layer model is designed to estimate the air-sea heat and fresh water fluxes and the results are compared to their ''true'' values. Ex periments on various parameterizations of different variables are carr ied out in the hope of getting some guidance in applying tile inverse model to the real ocean. The inverse model estimates for horizontal ci rculation are relatively robust-they are consistent with the GCM ocean circulations in most of the experiments, and effects of equation erro rs are more pronounced in the estimates for diffusivity and air-sea fl uxes, Residuals in the equations are noisy and resemble a random distr ibution. In such cases, the estimates for all the parameters are very close to their true values. The conclusions of this work are different from previous works, and the discrepancies are explained.