<jupyter_start><jupyter_text>Sverdrup Balance in observations<jupyter_code>import numpy as np
import xarray as xr
import cartopy.crs as ccrs
import cartopy.feature as cfeature
import matplotlib.pyplot as plt
%matplotlib inline<jupyter_output><empty_output><jupyter_text>In this assignment, we are going to compute the Sverdrup streamfunction from the wind stress. As a reminder, the Sverdrup balance is\begin{equation}    \beta V = \frac{\vec{\nabla} \times \vec{\tau}}{\rho}\end{equation} Download the zonal and meridional GODAS momentum flux (=wind stress in [N/m$^2$]) files for one year from the GODAS website at https://psl.noaa.gov/data/gridded/data.godas.html (via 'List of *.nc files'>'See list'>'Save Link as') and use their time average from here on.<jupyter_code># loading and inspecting
data = '/Users/Andre/Downloads'
uflx = xr.open_dataset(f'{data}/uflx.2020.nc')
vflx = xr.open_dataset(f'{data}/vflx.2020.nc')
taux = uflx.uflx.mean('time')
tauv = vflx.vflx.mean('time')
uflx<jupyter_output><empty_output>