I have a strong interest in (sub)mesoscale turbulence in the ocean and how it interacts with the large-scale ocean circulation and bioproductivity particularly in the Southern Ocean. I approach the problems by analyzing big data outputs from general circulation models, idealized numerical simulations and satellite observations.
PhD candidate - Physical Oceanography
Columbia University in the City of New York
Summer School - Turbulence Theory in Climate Dynamics
École de Physique des Houches, France
B.E. - Ocean Engineering
The University of Tokyo, Tokyo, Japan
xrft is a Python package for taking the discrete Fourier transform (DFT) on xarray and dask arrays. It keeps the metadata of the original dataset and provides a clean work flow of DFT. Contributed to developing the functions for detrending the data and calculating the (isotropic) power/cross spectrum.
xregrid is a Python package for aggregating and/or regridding data onto a orthogonal grid using the KDTree algorithm. xregrid is motivated by the fact that non-orthogonal grids are becoming increasingly common in general circulation models. In order to conduct physically meaningful analysis on the model outputs and compare them with satellite observations, however, we are in need of regridding the data onto orthogonal grids.
oceanmodes is a Python package for linear quasigeostrophic normal mode analysis given the background state of velocity and density profile.
Bioproductivity in the Southern Ocean
I am interested in the impact of eddy fluxes in a submesoscale eddy resolving simulation on the transport of momentum and tracers such as heat, salt, carbon and nutrients, and how bioproductivity is affected in the euphotic zone of the Southern Ocean.