Surface Kinetic Energy Distributions in the Global Oceans From a High‐Resolution Numerical Model and Surface Drifter Observations
|Author(s)||Yu Xiaolong1, Ponte Aurelien1, Elipot Shane2, Menemenlis Dimitris3, Zaron Edward D.4, Abernathey Ryan5|
|Affiliation(s)||1 : Ifremer, Université de Brest, CNRS, IRD, Laboratoire d'Océanographie Physique et Spatiale, IUEM Brest ,France
2 : Rosenstiel School of Marine and Atmospheric SciencesUniversity of Miami Miami FL ,USA
3 : Jet Propulsion LaboratoryCalifornia Institute of Technology Pasadena CA ,USA
4 : Department of Civil and Environmental Engineering Portland State University Portland OR ,USA
5 : Department of Earth and Environmental SciencesColumbia University New York NY, USA
|Source||Geophysical Research Letters (0094-8276) (American Geophysical Union (AGU)), 2019-08 , Vol. 46 , N. 16 , P. 9757-9766|
|WOS© Times Cited||27|
|Keyword(s)||LLC4320, surface drifter, rotary spectrum, SWOT|
The surface kinetic energy of a 1/48° global ocean simulation and its distribution as a function of frequency and location are compared with the one estimated from 15,329 globally distributed surface drifter observations at hourly resolution. These distributions follow similar patterns with a dominant low‐frequency component and well‐defined tidal and near‐inertial peaks globally. Quantitative differences are identified with deficits of low‐frequency energy near the equator (factor 2) and at near‐inertial frequencies (factor 3) and an excess of energy at semidiurnal frequencies (factor 4) for the model. Owing to its hourly resolution and its near‐global spatial coverage, the array of surface drifters is an invaluable tool to evaluate the realism of tide‐resolving high‐resolution ocean simulations used in observing system simulation experiments. Sources of bias between model and drifter data are discussed, and associated leads for future work highlighted.
Plain Language Summary
Ocean currents predominately control the transport and distribution of physical properties (such as heat and momentum) and biochemical tracers (such as carbon, oxygen, and nutrients) in the global oceans. These currents are generally most energetic at the ocean surface and distributed across a broad range of temporal and spatial scales. Global ocean models simulate ocean variability from large‐scale circulations to tidal motions and are used to provide guidance for new global oceanographic observations, especially for future high‐resolution satellite missions. Therefore, it is crucial to assess the realism of global ocean models. In this study, we use drifter observations of global surface currents to compare with the output from a 1/48° global ocean simulation. Our results show that the model exhibits a broad qualitative consistency with the surface drifter data but also displays some key differences at high‐frequency dynamics. The model shows a 3 times deficit of near‐inertial variance and a 4 times excess of semidiurnal variance when compared with surface drifter data. Our findings demonstrate that the global drifter data set with hourly temporal resolution provides a resource for assessment of the surface circulation predicted by state‐of‐the‐art global ocean models.