Bio SOSE data for the Southern Ocean:

• SOSE data
• bioSOSE

using xarray to load files and manipulate files

Data Files for BSOSE are here: BSOSE iteration 122 data stored on engaging: /nfs/cnhlab004/alir/bsose_i122/

With Ali Oct 25th

• set up miniconda python 3 on engaging in my home directory

Load the environment.yml file conda activate seasonal_cycle

When plotting use plt.show() for XQuartz viewer

import xarray as xr #learn the xarray functions for quick computing from dask.diagnostics import ProgressBar import cmocean import matplotlib.pyplot as plt

u_file = "bsose_i122_2013to2017_1day_Uvel.nc" v_file = "bsose_i122_2013to2017_1day_Vvel.nc"

u = xr.open_mfdataset(u_file, parallel=True, chunks={'time': 10}) #chunk the big dataset into pieces for parallelized computing v = xr.open_mfdataset(v_file, parallel=True, chunks={'time': 10})

inspect data and variables

u.Z u.Z.values

u.UVEL.values #etc

select a subset of the data to use

u_slice = u_.sel(time=slice('2013-01-01',' 2014-01-02'), YC=slice(-80,-60)).isel(Z=1) u_slice_1time = u_slice.isel(time=1)

u_slice_1time.UVEL.plot() plt.show()

u_slice_yr = u.sel(time=slice('2013-01-01',' 2014-01-02'), YC=slice(-80,-60)).isel(Z=1) u_slice_yr_avg = u_slice_yr.mean(dim='time')

with ProgressBar(): u_slice_yr_avg.UVEL.plot() plt.show()