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|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.|
|Laurencin, C. N., & Misra, V. (2017). Characterizing the Variations of the motion of the North Atlantic tropical cyclones. Meteorology and Atmospheric Physics, .|
|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.
Keywords: eddy available potential energy; mesoscale eddies; mixing; model‐ data comparison; ocean energy reservoirs; Argo
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|Maddison, J. R., & Hiester, H. R. (2017). Optimal Constrained Interpolation in Mesh-Adaptive Finite Element Modeling. SIAM J. Sci. Comput., 39(5), A2257–A2286.|
|Maksimova, E. V. (2017). On the observed synoptic signal in the Mississippi-Alabama slope flow. J. Geophys. Res. Oceans, 122(1), 185–192.|
|Misra, V., Bhardwaj, A., & Noska, R. (2017). Understanding the Variations of the Length and the Seasonal Rainfall Anomalies of the Indian Summer Monsoon. J. Climate, 30(5), 1753–1763.|
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