FN Archimer Export Format PT J TI Near‐Surface Oceanic Kinetic Energy Distributions From Drifter Observations and Numerical Models BT AF Arbic, Brian K. Elipot, Shane Brasch, Jonathan M. Menemenlis, Dimitris PONTE, Aurelien Shriver, Jay F. Yu, Xiaolong Zaron, Edward D. Alford, Matthew H. Buijsman, Maarten C. Abernathey, Ryan Garcia, Daniel Guan, Lingxiao Martin, Paige E. Nelson, Arin D. AS 1:1;2:2;3:3;4:4;5:5;6:6;7:5;8:7;9:8;10:9;11:10;12:3;13:3;14:10,11;15:1,12; FF 1:;2:;3:;4:;5:PDG-ODE-LOPS-OC;6:;7:PDG-ODE-LOPS-OH;8:;9:;10:;11:;12:;13:;14:;15:; C1 Department of Earth and Environmental Sciences University of Michigan Ann Arbor MI ,USA Rosenstiel School of Marine, Atmospheric, and Earth Science University of Miami Miami FL,USA Department of Electrical Engineering and Computer Science University of Michigan Ann Arbor MI ,USA Jet Propulsion Laboratory California Institute of Technology Pasadena CA ,USA Laboratoire d’Océanographie Physique et Spatiale IRD CNRS Ifremer Université de Brest IUEM Brest ,France Ocean Sciences Division, Naval Research Laboratory Stennis Space Center Hancock County MS, USA College of Earth, Ocean, and Atmospheric Sciences Oregon State University Corvallis OR, USA Scripps Institution of Oceanography University of California San Diego La Jolla CA ,USA Division of Marine Science University of Southern Mississippi Stennis Space Center, Hancock County MS ,USA Lamont‐Doherty Earth Observatory Columbia University New York City NY, USA Department of Physics University of Michigan Ann Arbor MI ,USA Graduate School of Oceanography University of Rhode Island Kingston RI ,USA C2 UNIV MICHIGAN, USA UNIV MIAMI, USA UNIV MICHIGAN, USA CALTECH, USA IFREMER, FRANCE NRL-SSC, USA UNIV OREGON STATE, USA UNIV CALIF SAN DIEGO, USA UNIV SOUTHERN MISSISSIPPI, USA UNIV NEW YORK, USA UNIV MICHIGAN, USA UNIV RHODE ISLAND, USA SI BREST SE PDG-ODE-LOPS-OC PDG-ODE-LOPS-OH UM LOPS IN WOS Ifremer UMR copubli-int-hors-europe IF 3.6 TC 11 UR https://archimer.ifremer.fr/doc/00797/90907/96574.pdf LA English DT Article DE ;drifters;numerical ocean models;tides;near-inertial motions;currents;eddies AB The geographical variability, frequency content, and vertical structure of near-surface oceanic kinetic energy (KE) are important for air-sea interaction, marine ecosystems, operational oceanography, pollutant tracking, and interpreting remotely sensed velocity measurements. Here, KE in high-resolution global simulations (HYbrid Coordinate Ocean Model; HYCOM, and Massachusetts Institute of Technology general circulation model; MITgcm), at the sea surface (0 m) and at 15 m, are compared with KE from undrogued and drogued surface drifters, respectively. Global maps and zonal averages are computed for low-frequency (<0.5 cpd), near-inertial, diurnal, and semidiurnal bands. Both models exhibit low-frequency equatorial KE that is low relative to drifter values. HYCOM near-inertial KE is higher than in MITgcm, and closer to drifter values, probably due to more frequently updated atmospheric forcing. HYCOM semidiurnal KE is lower than in MITgcm, and closer to drifter values, likely due to inclusion of a parameterized topographic internal wave drag. A concurrent tidal harmonic analysis in the diurnal band demonstrates that much of the diurnal flow is nontidal. We compute simple proxies of near-surface vertical structure—the ratio 0 m KE/(0 m KE + 15 m KE) in model outputs, and the ratio undrogued KE/(undrogued KE + drogued KE) in drifter observations. Over most latitudes and frequency bands, model ratios track the drifter ratios to within error bars. Values of this ratio demonstrate significant vertical structure in all frequency bands except the semidiurnal band. Latitudinal dependence in the ratio is greatest in diurnal and low-frequency bands. Key Points We examine frequency content of ocean kinetic energy (KE) at the sea surface (0 m) and 15 m depth with global drifter data and two models Near-surface near-inertial and tidal KE in numerical models are sensitive to atmospheric forcing frequency and damping The ratio 0 m KE/(0 m KE + 15 m KE) in models lies within error bars of the observational ratios over some latitudes and frequency bands Plain Language Summary It is important to map and understand ocean surface currents because they affect climate and marine ecosystems. Recent advances in global ocean models include the addition of astronomical tidal forcing alongside atmospheric forcing and the usage of more powerful computers that can resolve finer features. Here, we evaluate ocean surface currents in high-resolution simulations of two different ocean models through comparison with observations from surface drifting buoys. We examine near-inertial motions, forced by fast-changing winds; semidiurnal tides, forced by the astronomical tidal potential; diurnal motions, arising from tidal and other sources; and low-frequency currents and eddies, forced by atmospheric fields. Global patterns in the models and drifters are broadly consistent. The two models differ in their degree of proximity to drifter measurements in the near-inertial band, most likely due to different update intervals for atmospheric forcing and in the semidiurnal band, most likely due to different damping schemes. A simple proxy for vertical structure of the currents, measured by differences in drifter flows at the surface versus 15 m depth, is tracked reasonably well by the models. Discrepancies between models and observations motivate future improvements in the models. PY 2022 PD OCT SO Journal Of Geophysical Research-oceans SN 2169-9275 PU American Geophysical Union (AGU) VL 127 IS 10 UT 000866184800001 DI 10.1029/2022JC018551 ID 90907 ER EF