read_sla_currents.py

import netCDF4 as nc
import matplotlib.pyplot as plt
from mpl_toolkits.basemap import Basemap
import cartopy.crs as ccrs
import numpy as np
import geopandas as gpd
from matplotlib.animation import FuncAnimation
from dayssince2utc import time 

file_path = 'data/SAGA__SSHA_GEOVEL__60N_88N__2011_2020_rev_ext_alongtrack.nc'
ncfile = nc.Dataset(file_path, 'r')

sla = ncfile.variables['sla'][:, :, :]
ug = ncfile.variables['ug'][:, :, :]
vg = ncfile.variables['vg'][:, :, :]
mdt = ncfile.variables['mdt20112020'][:,:]
lat = ncfile.variables['lat'][:]
lon = ncfile.variables['lon'][:]
# print(time)
# print(ncfile.variables)

temp_mean_sla = np.mean(sla, axis=0)
# sla = sla[0,:,:]

ncfile.close()

###### plot single time step

# fig, ax = plt.subplots(1, 1, figsize=(15, 5))
# # world = gpd.read_file(gpd.datasets.get_path('naturalearth_lowres'))
# # world.boundary.plot(ax=ax1, linewidth=1, edgecolor='black', transform=ccrs.PlateCarree())

# m = Basemap(projection='npstere', lon_0=0, lat_0=90, boundinglat=60, ax=ax)
# x, y = m(lon, lat)

# m.pcolormesh(x, y, sla, cmap='viridis', ax=ax)
# m.colorbar(ax=ax)
# ax.quiver(x, y, ug, vg, scale=10, color='red', alpha=0.5)

# m.drawcoastlines(ax=ax)
# # ax.coastlines(color="0.1")
# # ax.set_title(f'{sla.name} [m]')
# ax.set_xlabel('Longitude')
# ax.set_ylabel('Latitude')
# ax.set_aspect('equal')
# plt.tight_layout()
# plt.show()