Far-Field Ocean Conditions and Concentrate Discharges Modeling Along the Saudi Coast of the Red Sea
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An integrated modeling system is developed to simulate the far-field dispersions of concentrate discharges along the Saudi coast of the Red Sea. It comprises the Weather Research and Forecast (WRF) model for simulating the atmospheric circulations, the MIT general circulation model (MITgcm) for simulating the large-scale ocean conditions, and the Connectivity Modeling System (CMS) for tracking particle pathways. We use the system outputs and remote sensing altimetry data to study and analyze the atmospheric and oceanic conditions along the Saudi coast of the Red Sea and to conduct particle tracking experiments. The model simulations show distinctive patterns of seasonal variations in both the atmospheric conditions and the large-scale ocean circulation in the Red Sea, which are also reflected in the salinity and temperature distributions along the Saudi coast. The impact of this seasonality on the far-field dispersion of concentrate discharges are illustrated in seasonal dispersion scenarios with discharging outfalls located at the northern, central and southern Saudi coasts of the Red Sea.
KeywordsEmpirical Orthogonal Function Mean Dynamic Topography Concentrate Discharge Integrate Modeling System Absolute Dynamic Topography
The research reported in this publication was supported by the King Abdullah University of Science and Technology (KAUST).
- Dibarboure, G., Lauret, O., Mertz, F., Rosmorduc, V., & Maheu, C. (2008). SSALTO/DUACS user handbook:(M) SLA and (M) ADT near-real time and delayed time products. Rep. CLS-DOS-NT, 6, 39.Google Scholar
- Emery, W. J., & Thomson, R. E. (2001). Data analysis methods in physical oceanography (2nd ed.). Amsterdam: Elsevier.Google Scholar
- Haza, A. C., Piterbarg, L. I., Martin, P., Ozgokmen, T. M., & Griffa, A. (2007). A Lagrangian subgridscale model for particle transport improvement and application in the Adriatic Sea using the Navy Coastal Ocean Model. Ocean Modelling, 17(1), 68–91. doi: 10.1016/J.Ocemod.2006.10.004.CrossRefGoogle Scholar
- Hegarty, J., Draxler, R. R., Stein, A. F., Brioude, J., Mountain, M., Eluszkiewicz, J., et al. (2013). Evaluation of Lagrangian particle dispersion models with measurements from controlled tracer releases. Journal of Applied Meteorology and Climatology, 52(12), 2623–2637. doi: 10.1175/Jamc-D-13-0125.1.CrossRefGoogle Scholar
- Ioc, I. (2003). BODC, 2003. Centenary edition of the GEBCO Digital Atlas, published on CD-ROM on behalf of the Intergovernmental Oceanographic Commission and the International Hydrographic Organization as part of the general bathymetric chart of the oceans. Liverpool, United Kingdom: British Oceanographic Data Centre.Google Scholar
- Langodan, S., Cavaleri, L., Viswanadhapalli, Y., & Hoteit, I. (2014). The Red Sea: A natural laboratory for wind and wave modeling. Journal of Physical Oceanography. Accepted with ref no: JPO-D-13-0242.Google Scholar
- Lo, J. C. F., Yang, Z. L., & Pielke, R. A. (2008). Assessment of three dynamical climate downscaling methods using the weather research and forecasting (WRF) model. Journal of Geophysical Research: Atmospheres, 113(D9).Google Scholar
- Michalakes, J., Dudhia, J., Gill, D., Henderson, T., Klemp, J., Skamarock, W., et al. (2005). The weather research and forecast model: Software architecture and performance. Use of High Performance Computing in Meteorology. 156–168, doi: 10.1142/9789812701831_0012.
- Skamarock, W., Klemp, J., Dudhia, J., Gill, D., Barker, D., Dudha, M., et al. (2008). A description of the advanced research WRF ver 30. Technical Note. NCAR/TN-475+STR. 113.Google Scholar
- Sofianos, S. S., & Johns, W. E. (2002). An oceanic general circulation model (OGCM) investigation of the Red Sea circulation, 1. Exchange between the Red Sea and the Indian Ocean. Journal of Geophysical Research: Oceans, 107(C11), doi:Artn 3196, doi: 10.1029/2001jc001184.
- Veneziani, M., Griffa, A., Reynolds, A. M., & Mariano, A. J. (2004). Oceanic turbulence and stochastic models from subsurface Lagrangian data for the northwest Atlantic Ocean. Journal of Physical Oceanography, 34(8), 1884–1906. doi: 10.1175/1520-0485(2004)034<1884:Otasmf>2.0.Co;2.CrossRefGoogle Scholar
- Zhan, P., Subramanian, A. C., Yao, F., & Hoteit, I. (2014). Eddies in the Red Sea: A statistical and dynamical study. Journal of Geophysical Research: Oceans, 119(6), 3909–3925, doi: 10.1002/2013JC009563.