Two-dimensional Numerical Simulations of Mixing under Ice Keels Data ...
This deposition contains time series of relevant outputs from the ice keel simulations. These include: The buoyancy frequency squared (Nstar_sq) The spatially-average irreversible mixing rate (phi_d) The spatially-averaged dimensionless diapycnal diffusivity (K) The mixing depth (95% of mixing occur...
Main Authors: | , , , , , |
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Format: | Dataset |
Language: | English |
Published: |
Zenodo
2024
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Subjects: | |
Online Access: | https://dx.doi.org/10.5281/zenodo.12627826 https://zenodo.org/doi/10.5281/zenodo.12627826 |
Summary: | This deposition contains time series of relevant outputs from the ice keel simulations. These include: The buoyancy frequency squared (Nstar_sq) The spatially-average irreversible mixing rate (phi_d) The spatially-averaged dimensionless diapycnal diffusivity (K) The mixing depth (95% of mixing occurs above this depth) in meters (z_mix) The relative mixing depth (z_mix_rel). This differs from the previous quantity as it is relative to the keel depth. That is, if the mixing depth was the keel height then the relative mixing depth would be 0. The files are formatted to be imported as a dictionary into a Python file via the Json package. The keys are the simulation names. The key values are a tuple with the first value being the time series and the second being an array of times at which the respective values were recorded. All values are separated into upstream and downstream files. ... |
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