ASTE data ——Sea surface height

In the Arctic Cap, the visualization of Sea surface height（SSH) like this:

The detailed code:

import numpy as np

import xarray as xr

import matplotlib.pyplot as plt

import cartopy.crs as ccrs

import sys

from xmitgcm import llcreader

sys.path.append('/home/ifenty/ECCOv4-py')

import ecco_v4_py as ecco

import matplotlib.path as mpath

import cartopy.feature as cfeature

import matplotlib.ticker as mticker

from mpl_toolkits.basemap import Basemap

import netCDF4 as nc

## Set top-level file directory for the ECCO NetCDF files

## =================================================================

# base_dir = '/home/username/'

base_dir = '/home/ifenty/ECCOv4-release'

## define a high-level directory for ECCO fields

ECCO_dir = base_dir + '/Release3_alt'

## LOAD NETCDF FILE

## ================

# directory containing the file

data_dir=  'C:/Users/34740/Desktop/ASTE data/'

# filename

fname = 'ETAN.0012.nc'

# load the file

ds = xr.open_dataset(data_dir + fname).load()

print('time: ')

time=ds.tim

sla=ds.ETAN.isel(i1=115)

sla_new=[]

lon_new=[]

lat_new=[]

i1=115

for i in range(8,10):

    file_path = data_dir +'ETAN.000%d.nc'%(i)

    file_obj = nc.Dataset(file_path)

    sla= file_obj.variables['ETAN'][i1,:]

    lats= file_obj.variables['lat'][:]

    lons= file_obj.variables['lon'][:]

    sla_new.append(sla)

    lon_new.append(lons)

    lat_new.append(lats)

   

for i in range(10,17):

    file_path = data_dir +'ETAN.00%d.nc'%(i)

    file_obj = nc.Dataset(file_path)

    sla= file_obj.variables['ETAN'][i1,:]

    lats= file_obj.variables['lat'][:]

    lons= file_obj.variables['lon'][:]

    sla_new.append(sla)

    lon_new.append(lons)

    lat_new.append(lats)

sla_new=np.array(sla_new)

sla_new=np.where(sla_new,sla_new,np.nan)

lon_new=np.array(lon_new)

lat_new=np.array(lat_new)

plt.figure(figsize=(10,10),dpi=500)

m=Basemap(projection='npstere',boundinglat=60,lon_0=0,resolution='l')

m.drawcoastlines()

m.fillcontinents()

for i in range(9):

    im=m.pcolormesh(lon_new[i],lat_new[i],sla_new[i],shading='nearest',cmap=plt.cm.jet,latlon=True)

m.drawparallels(np.arange(60,82,5),labels=[0,0,0,0])

m.drawmeridians(np.arange(0,361,20),labels=[0,0,1,1])

m.drawmapboundary()

ax=plt.gca()                                                                                                                                                                                                                                                                                      cb=m.colorbar(im,"right",size="5%",pad="10%")

cb.set_label('m',loc='bottom',rotation=1)

plt.title('Arctic cap ssh(201108)',pad=20)

plt.savefig("Arctic cap ssh(201108).png",dpi=500)

plt.show()

However, the result is not exactly correct, we need to use the following equation to correct SSH: