Data Repository for Breaking Internal Waves and Ocean Diapycnal Diffusivity in a High-Resolution Regional Ocean Model: Evidence of a Wave-turbulence Cascade (doi:10.7910/DVN/RZUCLE)

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Data Repository for Breaking Internal Waves and Ocean Diapycnal Diffusivity in a High-Resolution Regional Ocean Model: Evidence of a Wave-turbulence Cascade

doi:10.7910/DVN/RZUCLE

Harvard Dataverse

2024-03-13

3

Momeni, Kayhan; Ma, Yuchen; Peltier, WR; Menemenlis, Dimitris; Thakur, Ritabrata; Pan, Yulin; Arbic, Brian K; Skitka, Joseph; Alford, Matthew H, 2024, "Data Repository for Breaking Internal Waves and Ocean Diapycnal Diffusivity in a High-Resolution Regional Ocean Model: Evidence of a Wave-turbulence Cascade", https://doi.org/10.7910/DVN/RZUCLE, Harvard Dataverse, V3

Data Repository for Breaking Internal Waves and Ocean Diapycnal Diffusivity in a High-Resolution Regional Ocean Model: Evidence of a Wave-turbulence Cascade

doi:10.7910/DVN/RZUCLE

Momeni, Kayhan (Department of Physics, University of Toronto, Toronto, Ontario, Canada)

Ma, Yuchen (Department of Physics, University of Toronto, Toronto, Ontario, Canada)

Peltier, WR (Department of Physics, University of Toronto, Toronto, Ontario, Canada)

Menemenlis, Dimitris (Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA)

Thakur, Ritabrata (Department of Earth and Environmental Sciences, University of Michigan, Ann Arbor, MI, USA)

Pan, Yulin (Department of Naval Architecture and Marine Engineering, University of Michigan, Ann Arbor, MI, USA)

Arbic, Brian K (Department of Earth and Environmental Sciences, University of Michigan, Ann Arbor, MI, USA)

Skitka, Joseph (Department of Earth and Environmental Sciences, University of Michigan, Ann Arbor, MI, USA)

Alford, Matthew H (Scripps Institution of Oceanography, University of California San Diego, La Jolla, CA, USA)

Harvard Dataverse

Momeni, Kayhan

Momeni, Kayhan

2024-03-13

https://doi.org/10.7910/DVN/RZUCLE

Earth and Environmental Sciences, Physics

Data for Momeni et al. JGR:Oceans 2024

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KPPdiffT_avg_0.7.nc

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Dimension: [nz=88 vertical levels, nt=60 time steps]

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KPPdiffT_avg_0.8.nc

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KPPdiffT_avg_0.9.nc

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KPPdiffT_avg_1.0.nc

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KPPdiffT_avg_1.1.nc

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KPPdiffT_avg_1.2.nc

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KPPdiffT_avg_1.3.nc

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KPPdiffT_avg_1.4.nc

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KPPdiffT_avg_1.6.nc

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KPPdiffT_avg_1.8.nc

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KPPdiffT_avg_10.0.nc

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KPPdiffT_avg_11.0.nc

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KPPdiffT_avg_12.0.nc

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KPPdiffT_avg_13.0.nc

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KPPdiffT_avg_14.0.nc

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KPPdiffT_avg_2.0.nc

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KPPdiffT_avg_2.2.nc

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KPPdiffT_avg_2.4.nc

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KPPdiffT_avg_2.6.nc

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KPPdiffT_avg_2.8.nc

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KPPdiffT_avg_3.0.nc

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KPPdiffT_avg_3.2.nc

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KPPdiffT_avg_3.4.nc

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KPPdiffT_avg_3.5.nc

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KPPdiffT_avg_3.6.nc

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KPPdiffT_avg_4.0.nc

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KPPdiffT_avg_4.5.nc

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KPPdiffT_avg_5.0.nc

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KPPdiffT_avg_5.5.nc

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KPPdiffT_avg_6.0.nc

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KPPdiffT_avg_6.5.nc

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KPPdiffT_avg_7.0.nc

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KPPdiffT_avg_7.5.nc

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KPPdiffT_avg_8.0.nc

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KPPdiffT_avg_8.5.nc

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KPPdiffT_avg_9.0.nc

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KPPdiffT_avg_9.5.nc

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Ricr0.25_KPPdiffT_avg.nc

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Ricr0.2_KPPdiffT_avg.nc

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Ricr0.3_KPPdiffT_avg.nc

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Ricr0.4_KPPdiffT_avg.nc

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Ricr0.5_KPPdiffT_avg.nc

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Ricr0.6_KPPdiffT_avg.nc

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Ricr0.7_KPPdiffT_avg.nc

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Dimension: [nz=264 vertical levels, nt=20 timestep]

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Ricr0.8_KPPdiffT_avg.nc

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Ricr0.9_KPPdiffT_avg.nc

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Ricr1.0_KPPdiffT_avg.nc

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Ricr1.1_KPPdiffT_avg.nc

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Ricr1.2_KPPdiffT_avg.nc

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Ricr1.3_KPPdiffT_avg.nc

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Ricr1.4_KPPdiffT_avg.nc

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Ricr1.5_KPPdiffT_avg.nc

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Ricr3.5_KPPdiffT_avg.nc

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Dimension: [nz=264 vertical levels, nt=20 timestep]

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