raphaeldussin

Download the fonts from https://github.com/stipub/stixfonts

dirstix = "/net2/rnd/dev/stixfonts/fonts/static_ttf"
import matplotlib.font_manager as font_manager
for font in font_manager.findSystemFonts(dirstix):
    font_manager.fontManager.addfont(font)

# Set font family globally
plt.rcParams['font.family'] = 'STIX Two Text'

raphaeldussin

name: meatpotatoes
channels:
  - conda-forge
dependencies:
  - python
  - pip
  - black
  - cartopy
  - cftime
  - cmocean

raphaeldussin

import xarray as xr
import numpy as np
from matplotlib import pyplot as plt
from matplotlib import animation
import matplotlib.image as image
import cartopy.crs as ccrs
from owslib.wms import WebMapService
from matplotlib import cm
import os
from xgcm import Grid

raphaeldussin

import cmocean
import cartopy.crs as ccrs
import matplotlib.pyplot as plt

# extract temperature and depth for a given time
snapshot = CCS2.isel(time=50)
temp_snapshot = snapshot['temp']
depth_snapshot = snapshot['z_rho']

# compute temperature at 100 meters depth using xgcm.transform

raphaeldussin

import matplotlib.pyplot as plt
import cmocean

plt.figure(figsize=[10,8])

CCS2['v'].isel(time=12, yq=500).plot(x='lon_v', y='z_v',
                                     vmin=-0.25, vmax=0.25,
                                     cmap=cmocean.cm.balance,
                                     subplot_kws={'facecolor': 'grey'})

raphaeldussin

def compute_depth_layers(ds, grid, hmin=0.1):
    """ compute depths of ROMS vertical levels (Vtransform = 2) """
    
    # compute vertical transformation functional
    S_rho = (ds.hc * ds.s_rho + ds.Cs_r * ds.h) / (ds.hc + ds.h)
    S_w = (ds.hc * ds.s_w + ds.Cs_w * ds.h) / (ds.hc + ds.h)
    
    # compute depth of rho (layers) and w (interfaces) points
    z_rho = ds.zeta + (ds.zeta + ds.h) * S_rho
    z_w = ds.zeta + (ds.zeta + ds.h) * S_w

raphaeldussin

import xarray as xr
from xgcm import Grid

CCS2 = xr.open_zarr(CCS2_store, consolidated=True)

# Create xgcm grid object
grid_ccs2 = Grid(CCS2, coords={'X': {'center': 'xh', 'outer': 'xq'},
                               'Y': {'center': 'yh', 'outer': 'yq'},
                               'Z': {'center': 's_rho', 'outer': 's_w'}},
                 periodic=False)

raphaeldussin

import xarray as xr
import glob

# use glob to create a list of files to convert
filelist = glob.glob('data/CCS2_avg_*.nc')
# path to grid file
gridfile = 'grid/CCS2_grid.nc'
# output store name
store_name = 'CCS2_store'

raphaeldussin

def add_coords(ds):
    """ set coordinate variables as xarray coordinates
    
        Parameters:
            ds (xarray.Dataset): ROMS dataset
    """
    ds = ds.set_coords(['Cs_r', 'Cs_w', 'hc', 'h', 'Vtransform', 'time',
                        'lon_rho', 'lon_v', 'lon_u', 'lon_psi',
                        'lat_rho', 'lat_v', 'lat_u', 'lat_psi'])
    return ds

raphaeldussin

def rename_dims(ds):
    """ rename dimensions
    
        Parameters:
            ds (xarray.Dataset): ROMS dataset
    
    """
    ds = ds.rename({'xi_rho': 'xh', 'xi_v': 'xh', 'xi_u': 'xq', 'xi_psi': 'xq',
                    'eta_rho': 'yh', 'eta_v': 'yq', 'eta_u': 'yh', 'eta_psi': 'yq',
                    'ocean_time': 'time'