HyCOM

The Hybrid Coordinate Ocean Model (HyCOM) is an open-source ocean general circulation modeling system.^[1] HyCOM is a primitive equation type of ocean general circulation model. The vertical levels of this modeling system are slightly different than other models, because the vertical coordinates remain isopycnic in the open stratified ocean, smoothly transitioning to z-level coordinates in the weakly stratified upper-ocean mixed layer, to terrain-following sigma coordinates in shallow water regions, and back to z-level coordinates in very shallow water.^{[2] [3] [4]} Therefore, the setup is a “hybrid” between z-level and terrain-following vertical levels. HyCOM outputs are provided online for the global ocean at a spatial resolution of 0.08 degrees (approximately 9 km) from 2003 to present. HyCOM uses netCDF data format for model outputs.^[5]

Example of a gridded numerical modeling system. HyCOM uses mainly the ocean portion of what is shown in this example.

Applications

HyCOM model experiments are used to study the interactions between the ocean and atmosphere, including short-term and long-term processes. This modeling system has also been used to create forecasting tools. For example, HyCOM has been used to:

• Assimilate data and provide operational oceanographic forecasting for the United States Navy^[6]
• Determine the ideal way to parametrize how the sun heats the upper ocean (solar radiation and heat flux) in darker waters like the Black Sea^[7]
• Study mesoscale variability in sea surface height and temperature in the Gulf of Mexico^[8]
• Simulate drifting patterns of loggerhead sea turtles of the North American east coast^[9]
• Predict the extent of Arctic sea ice for naval operations^[10]

See also

• Climate model
• Computational geophysics
• General circulation model (GCM)
• Ocean general circulation model (OGCM)
• Oceanography
• List of ocean circulation models
• Physical oceanography
• ROMS
• Sigma coordinate system

References

1. "HYCOM Overview". HYbrid Coordinate Ocean Model (HYCOM) Center for Ocean-Atmospheric Prediction Studies (COAPS). Consortium for Data Assimilative Modeling.
2. Wallcroft, A.; Carroll, S. N.; Kelly, K. A.; Rushing, K. V. (2003). "Hybrid Coordinate Ocean Model (HYCOM) User's Guide" (PDF). Retrieved 15 September 2021.
3. Halliwell, G. R.; Bleck, R.; Chassignet, E. (1998). "Atlantic Ocean simulations performed using a new Hybrid Coordinate Ocean Model (HYCOM)". EOS, Fall AGU Meeting.
4. Chassignet, Eric P.; Smith, Linda T.; Halliwell, George R.; Bleck, Rainer (2003). "North Atlantic Simulations with the Hybrid Coordinate Ocean Model (HYCOM): Impact of the Vertical Coordinate Choice, Reference Pressure, and Thermobaricity". Journal of Physical Oceanography. 33 (12): 2504–2526. Bibcode:2003JPO....33.2504C. doi:10.1175/1520-0485(2003)033<2504:NASWTH>2.0.CO;2.
5. Fossette, Sabrina; et al. (2012). "A biologist's guide to assessing ocean currents: a review". Marine Ecology Progress Series. 457: 285–301. Bibcode:2012MEPS..457..285F. doi:10.3354/meps09581. hdl:10536/DRO/DU:30058348.
6. Chassignet, Eric P.; et al. (2007). "The HYCOM (HYbrid Coordinate Ocean Model) data assimilative system". Journal of Marine Systems. 65 (1–4): 60–83. Bibcode:2007JMS....65...60C. doi:10.1016/j.jmarsys.2005.09.016.
7. Birol Kara, A.; Wallcraft, Alan J.; Hurlburt, Harley E. (2005). "A New Solar Radiation Penetration Scheme for Use in Ocean Mixed Layer Studies: An Application to the Black Sea Using a Fine-Resolution Hybrid Coordinate Ocean Model (HYCOM)". Journal of Physical Oceanography. 35 (1): 13–32. Bibcode:2005JPO....35...13K. doi:10.1175/JPO2677.1.
8. Srinivasan, A.; et al. (2011). "A comparison of sequential assimilation schemes for ocean prediction with the HYbrid Coordinate Ocean Model (HYCOM): Twin experiments with static forecast error covariances". Ocean Modelling. 37 (3–4): 85–111. Bibcode:2011OcMod..37...85S. doi:10.1016/j.ocemod.2011.01.006.
9. Putman, Nathan F.; Scott, Rebecca; Verley, Philippe; Marsh, Robert; Hays, Graeme C. (2012). "Natal site and offshore swimming influence fitness and long-distance ocean transport in young sea turtles". Marine Biology. 159 (10): 2117–2126. Bibcode:2012MarBi.159.2117P. doi:10.1007/s00227-012-1995-5. S2CID 253745579.
10. Metsger, E. Joseph; et al. (2014). "US Navy Operational Global Ocean and Arctic Ice Prediction Systems". Oceanography. 27 (3): 32–43. doi:10.5670/oceanog.2014.66. JSTOR 24862187.

External links

https://www.hycom.org/