Reading a NetCDF file with Python, Matlab and R

Visualisation tools

There are several turn-key desktop tools designed to data and image visualization of a NetCDF file like:

•  Panoply designed essentially for NetCDF files that use the Climate Forecast conventions metadata
• HDFview : able to open all NetCDF (and HDF) files

Language

In the following examples, the NetCDF file downloadable here is used.

PYTHON

1. Using the netCDF4 library:

# First, you need to install the netCDF4 library if you haven’t already
# pip install netCDF4

import netCDF4 as nc

# Specify the file path
file_path = 'sresa1b_ncar_ccsm3-example.nc'

# Open the NetCDF file
ds = nc.Dataset(file_path)

# Print the file details
print(ds)

# Access a specific variable
tas = ds.variables['tas'][:]

# Check the dimensions and attributes of the variable
print(ds.variables['tas'].dimensions)
print(ds.variables['tas'].shape)
print(ds.variables['tas'].units)

# Close the dataset after using it
ds.close()

2. Using the xarray library:

# Install xarray and netCDF4 together if you haven’t done so
# pip install xarray netCDF4

import xarray as xr

# Open the NetCDF file using xarray
ds = xr.open_dataset('sresa1b_ncar_ccsm3-example.nc')

# Print the dataset details
print(ds)

# Access a specific variable
tas = ds['tas']

# Print the values of the lat variable
print(tas.values)

# You can also access dimensions and coordinates
print(ds.dims)
print(ds.coords)

# Close the dataset (optional, handled automatically with xarray)
ds.close()

MATLAB

file_name = 'sresa1b_ncar_ccsm3-example.nc';
    var_name = 'tas';
 
    % Display global information about a netcdf file
    ncdisp(file_name);
    % About a variable or a group
   ncdisp(file_name, var_name);
       

% Get information about a netcdf file
    info = ncinfo(file_name)
    % About a variable
    var_info = ncinfo(file_name, var_name)
    % About a group
    gr_info = ncinfo(file_name, group_name)
     
     
    % Read data from a vraiable of a netcdf file
    data = ncread(file_name, var_name);
    % Or
    % data = ncread(file_name, var_name, start, count, stride) 
     
     
    % Read attribute
    var_attr = ncreadatt(file_name, var_name, 'units')

R

#Intall the NetCDF libraries: sudo apt-get install libnetcdf-dev 
#Install the ncdf package in R: install.packages("ncdf4")
 
# Charger la bibliothèque ncdf4
library(ncdf4)

# Ouvrir le fichier NetCDF
nc_data <- nc_open("sresa1b_ncar_ccsm3-example.nc")

# Afficher les informations sur le fichier
print(nc_data)

# Lire une variable spécifique (par exemple, "tas")
tas <- ncvar_get(nc_data, "tas")

# Afficher les données de la variable
print(tas)

# Obtenir les attributs de la variable "tas"
tas_attributes <- ncatt_get(nc_data, "tas")
print(tas_attributes)

# Fermer le fichier NetCDF
nc_close(nc_data)