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Acadlore takes over the publication of IJCMEM from 2025 Vol. 13, No. 3. The preceding volumes were published under a CC BY 4.0 license by the previous owner, and displayed here as agreed between Acadlore and the previous owner. ✯ : This issue/volume is not published by Acadlore.

Open Access
Research article

The Effect of Numerical Parameters on Eddies in Oceanic Overflows: A Laboratory and Numerical Study

Shanon M. Reckinger,
Thomas H. Gibson,
Fred M. Hohman,
Theresa J. Morrison,
Scott J. Reckinger,
Mateus Carvalho
Fairfield University, United States of America
International Journal of Computational Methods and Experimental Measurements
|
Volume 7, Issue 2, 2019
|
Pages 142-153
Received: N/A,
Revised: N/A,
Accepted: N/A,
Available online: N/A
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Abstract:

Overflows in the ocean occur when dense water flows down a continental slope into less dense ambient water. It is important to study idealized and small-scale models, which allow for confidence and control of parameters. The work presented here is a direct qualitative and quantitative comparison between physical laboratory experiments and lab-scale numerical simulations. Physical parameters are varied, including the Coriolis parameter, the inflow density, and the inflow volumetric flow rate. Laboratory experiments are conducted using a rotating square tank and high-resolution camera mounted on the table in the rotating reference frame. Video results are digitized in order to compare directly to numeri- cal simulations. The MIT General Circulation Model (MITgcm), a three-dimensional ocean model, is used for the direct numerical simulations corresponding to the specific laboratory experiments. It was found that the MITgcm was not a good match to laboratory experiments when physical parameters fell within the high eddy activity regime. However, a more extensive resolution study is needed to understand this fully. The MITgcm simulations did provide a good qualitative and quantitative match to laboratory experiments run in a low eddy activity regime. In all cases, the MITgcm simulations had more eddy activity than the laboratory experiments.

Keywords: density-driven currents, lab-scale, numerical parameters, ocean modelling, overflows.


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Reckinger, S. M., Gibson, T. H., Hohman, F. M., Morrison, T. J., Reckinger, S. J., & Carvalho, M. (2019). The Effect of Numerical Parameters on Eddies in Oceanic Overflows: A Laboratory and Numerical Study. Int. J. Comput. Methods Exp. Meas., 7(2), 142-153. https://doi.org/10.2495/CMEM-V7-N2-142-153
S. M. Reckinger, T. H. Gibson, F. M. Hohman, T. J. Morrison, S. J. Reckinger, and M. Carvalho, "The Effect of Numerical Parameters on Eddies in Oceanic Overflows: A Laboratory and Numerical Study," Int. J. Comput. Methods Exp. Meas., vol. 7, no. 2, pp. 142-153, 2019. https://doi.org/10.2495/CMEM-V7-N2-142-153
@research-article{Reckinger2019TheEO,
title={The Effect of Numerical Parameters on Eddies in Oceanic Overflows: A Laboratory and Numerical Study},
author={Shanon M. Reckinger and Thomas H. Gibson and Fred M. Hohman and Theresa J. Morrison and Scott J. Reckinger and Mateus Carvalho},
journal={International Journal of Computational Methods and Experimental Measurements},
year={2019},
page={142-153},
doi={https://doi.org/10.2495/CMEM-V7-N2-142-153}
}
Shanon M. Reckinger, et al. "The Effect of Numerical Parameters on Eddies in Oceanic Overflows: A Laboratory and Numerical Study." International Journal of Computational Methods and Experimental Measurements, v 7, pp 142-153. doi: https://doi.org/10.2495/CMEM-V7-N2-142-153
Shanon M. Reckinger, Thomas H. Gibson, Fred M. Hohman, Theresa J. Morrison, Scott J. Reckinger and Mateus Carvalho. "The Effect of Numerical Parameters on Eddies in Oceanic Overflows: A Laboratory and Numerical Study." International Journal of Computational Methods and Experimental Measurements, 7, (2019): 142-153. doi: https://doi.org/10.2495/CMEM-V7-N2-142-153
RECKINGER S M, GIBSON T H, HOHMAN F M, et al. The Effect of Numerical Parameters on Eddies in Oceanic Overflows: A Laboratory and Numerical Study[J]. International Journal of Computational Methods and Experimental Measurements, 2019, 7(2): 142-153. https://doi.org/10.2495/CMEM-V7-N2-142-153