https://doi.org/10.5281/zenodo.6700539: Python code to solve for a linear lee wave field with a given topography and background flow profile. Accompanies 'Surface reflection of bottom generated oceanic lee waves', Baker & Mashayek (2021), Journal of Fluid Mechanics, https://doi.org/10.1017/jfm.2021.627

https://doi.org/10.5281/zenodo.6659507: Software and data associated with the preprint 'The impact of realistic topographic representation on the parameterisation of oceanic lee wave energy flux', Baker & Mashayek (2022), https://www.essoar.org/doi/abs/10.1002/essoar.10511680.1

https://zenodo.org/record/4672142#.YwYB_uzMJVA: Matlab code to fit a log-skew-normal distribution to microstructure-based epsilon (rate of dissipation of turbulent kinetic energy) data. Accompanies `Log-Skew-Normality of Ocean Turbulence’, Cael & Mashayek (2021), https://doi.org/10.1103/PhysRevLett.126.224502

https://zenodo.org/record/6857164#.YwYD0-zMJVA: Jupyter-notebook and python scripts for Machine-Learning-based prediction of vertical turbulent diffusivity and dissipation rate from hydrographic information. Acompanies `Deep Ocean Learning of Small Scale Turbulence’, Mashayek et al. (2022), https://doi.org/10.1029/2022GL098039