Chassignet, E. P., & Xu, X. (2017). Impact of Horizontal Resolution (1/12° to 1/50°) on Gulf Stream Separation, Penetration, and Variability.
J. Phys. Oceanogr., 47(8), 1999–2021.
Dukhovskoy, D. S., Leben, R. R., Chassignet, E. P., Hall, C. A., Morey, S. L., & Nedbor-Gross, R. (2015). Characterization of the uncertainty of loop current metrics using a multidecadal numerical simulation and altimeter observations.
Deep Sea Research Part I: Oceanographic Research Papers, 100, 140–158.
Fox-Kemper, B., Adcroft, A., Böning, C. W., Chassignet, E. P., Curchitser, E., Danabasoglu, G., et al. (2019). Challenges and Prospects in Ocean Circulation Models.
Front. Mar. Sci., 6.
Abstract: We revisit the challenges and prospects for ocean circulation models following Griffies et al. (2010). Over the past decade, ocean circulation models evolved through improved understanding, numerics, spatial discretization, grid configurations, parameterizations, data assimilation, environmental monitoring, and process-level observations and modeling. Important large scale applications over the last decade are simulations of the Southern Ocean, the Meridional Overturning Circulation and its variability, and regional sea level change. Submesoscale variability is now routinely resolved in process models and permitted in a few global models, and submesoscale effects are parameterized in most global models. The scales where nonhydrostatic effects become important are beginning to be resolved in regional and process models. Coupling to sea ice, ice shelves, and high-resolution atmospheric models has stimulated new ideas and driven improvements in numerics. Observations have provided insight into turbulence and mixing around the globe and its consequences are assessed through perturbed physics models. Relatedly, parameterizations of the mixing and overturning processes in boundary layers and the ocean interior have improved. New diagnostics being used for evaluating models alongside present and novel observations are briefly referenced. The overall goal is summarizing new developments in ocean modeling, including how new and existing observations can be used, what modeling challenges remain, and how simulations can be used to support observations.
Krishnamurti, T. N., Kumar, V., Simon, A., Thomas, A., Bhardwaj, A., Das, S., et al. (2017). March of buoyancy elements during extreme rainfall over India.
Clim Dyn, 48(5-6), 1931–1951.
Luecke, C. A., Arbic, B. K., Bassette, S. L., Richman, J. G., Shriver, J. F., Alford, M. H., et al. (2017). The Global Mesoscale Eddy Available Potential Energy Field in Models and Observations.
J. Geophys. Res. Oceans, 122(11), 9126–9143.
Luecke, C. A., Arbic, B. K., Bassette, S. L., Richman, J. G., Shriver, J. F., Alford, M. H., et al. (2017). The Global Mesoscale Eddy Available Potential Energy Field in Models and Observations: GLOBAL LOW-FREQUENCY EDDY APE.
J. Geophys. Res. Oceans, 122(11), 9126–9143.
Abstract: Global maps of the mesoscale eddy available potential energy (EAPE) field at a depth of 500 m are created using potential density anomalies in a high‐resolution 1/12.5° global ocean model. Maps made from both a free‐running simulation and a data‐assimilative reanalysis of the HYbrid Coordinate Ocean Model (HYCOM) are compared with maps made by other researchers from density anomalies in Argo profiles. The HYCOM and Argo maps display similar features, especially in the dominance of western boundary currents. The reanalysis maps match the Argo maps more closely, demonstrating the added value of data assimilation. Global averages of the simulation, reanalysis, and Argo EAPE all agree to within about 10%. The model and Argo EAPE fields are compared to EAPE computed from temperature anomalies in a data set of “moored historical observations” (MHO) in conjunction with buoyancy frequencies computed from a global climatology. The MHO data set allows for an estimate of the EAPE in high‐frequency motions that is aliased into the Argo EAPE values. At MHO locations, 15–32% of the EAPE in the Argo estimates is due to aliased motions having periods of 10 days or less. Spatial averages of EAPE in HYCOM, Argo, and MHO data agree to within 50% at MHO locations, with both model estimates lying within error bars observations. Analysis of the EAPE field in an idealized model, in conjunction with published theory, suggests that much of the scatter seen in comparisons of different EAPE estimates is to be expected given the chaotic, unpredictable nature of mesoscale eddies.
Nguyen, T. T. (2014).
Variability of Cross-Slope Flow in the Desoto Canyon Region. Master's thesis, Florida State University, Tallahassee, FL.
Robinson, W., Speich, S., & Chassignet, E. (2018). Exploring the Interplay Between Ocean Eddies and the Atmosphere.
Abstract: Climate models, for the first time, have sufficient resolution to capture mesoscale ocean eddies and their interactions with the atmosphere.New model results suggest that the atmosphere, at weather scales or larger, responds to cumulative effects of the much smaller ocean eddies. Intriguing new model results presented at the workshop suggested that the atmosphere, at weather scales or larger.
Smedstad, O. M., Hurlburt, H. E., Metzger, E. J., Rhodes, R. C., Shriver, J. F., Wallcraft, A. J., et al. (2003). An operational Eddy resolving 1/16° global ocean nowcast/forecast system.
Journal of Marine Systems, 40-41, 341–361.
Yu, L., & Jin, X. (2014). Insights on the OAFlux ocean surface vector wind analysis merged from scatterometers and passive microwave radiometers (1987 onward).
J. Geophys. Res. Oceans, 119(8), 5244–5269.