Paper
17 December 1999 Comparison of different dynamical models to predict the upper ocean concentration of a photochemical tracer as a function of depth and time
A. J. Kettle, W. Martin, O. Zafiriou
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Abstract
Three different one dimensional upper ocean boundary dynamics models are used to predict the concentration of a short-lived natural photochemical tracer as a function of time and depth. The dynamics models are coupled with parameterizations of the production and destruction rates of the tracer using chemical rate constants from published experimental studies. The model predictions of the upper ocean concentration the tracer do not agree closely with the measured concentrations obtained during one expedition, probably mostly because of errors in the rate constants used in the chemical model (published values of the in situ rate constants show much variability). An optimization scheme is described to find the values of the production and destruction rate constants which minimize the difference between the modelled and measured upper ocean concentrations of the photochemical tracer and the uncertainty is assessed using a Monte Carlo simulation. Using the optimized estimates of the chemical production and destruction rate constants, the simulated upper ocean concentrations from the three dynamics models show close agreement with each other. However, it is still difficult to determine which of the models is the best description for actual observed tracer concentrations because of weaknesses in the existing in situ data sets and models.
© (1999) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
A. J. Kettle, W. Martin, and O. Zafiriou "Comparison of different dynamical models to predict the upper ocean concentration of a photochemical tracer as a function of depth and time", Proc. SPIE 3868, Remote Sensing for Earth Science, Ocean, and Sea Ice Applications, (17 December 1999); https://doi.org/10.1117/12.373144
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Cited by 8 scholarly publications.
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KEYWORDS
Data modeling

Quantum efficiency

Carbon monoxide

Monte Carlo methods

Solids

Absorption

Signal attenuation

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