Using Argo Data#

As indicated in the introduction, the third component of the Argo Online School is hands-on, and it is based on Jupyter Notebooks:

The hands-on component of the Argo Online School#

You can access the hands-on content as here, in a web-page, built using JubyterBook, or download the Jupyter Notebooks and use them in your local machine.

The hands-on component of the Argo Online School was developed using JupyterLab, since it contains a complete environment for interactive scientific computing which runs in your web browser. Jupyter is an open-source python project, and as a very useful first approach to python and JupyterLab, you can use An Introduction to Earth and Environmental Data Science and Research computing in earth Sciences developed by Ryan Abernathey and Kerry Key.

In case that you decide to download and run the python Jupyter Notebooks in your local machine, you should create a python environment. Since using some of the packages may give problems due to compatibility issues between conda-forge packages and packages contained in the default conda channels, we will recommend to set up channel_priority: strict and give priority to the conda-forge channel over the default channels when installing stuff. There are two ways of doing it. Either you always specify conda install -c conda-forge or you create a .condarc file in your home with this content:

channels:
  - conda-forge
  - defaults
channel_priority: strict

An environment should either use conda-forge or not, from creation to destruction. Do not mix and match. If you created it without using the conda-forge channel, then do not add it to the mix halfway. In practice, we always create an environment with conda-forge unless in very specific cases where we found incompatibilities.

To create and activate the AOS environment, that already includes the last stable version of argopy, the python library for Argo data, you should:

conda env create -n AOS -f environment.yml 
conda activate AOS

If by any chance, a library is not included in the environment.yml file, you should install it using, for instance:

conda install netcdf4
conda install xarray
conda install seawater

Data used in the Argo Online School#

If you download the notebooks you should create a ./Data* folder to include the files used for the examples. The files in the Data folder can be downloaded directly from its source using wget, for instance:

for the Daily NOAA OI SST V2 High-Resolution Dataset for 2019:

wget ftp://ftp2.psl.noaa.gov/Datasets/noaa.oisst.v2.highres/sst.day.mean.2019.nc

for the data from float 6901254:

wget ftp://ftp.ifremer.fr/ifremer/argo/dac/coriolis/6901254/*`

or for the data in the North Atlantic for the 11th November 2019

wget ftp://ftp.ifremer.fr/ifremer/argo//geo/indian_ocean/2019/11/20191111_prof.nc`

However we recomend to download the data from here to use exactly the same dataset and therefore to be able to reproduce precisely the notebooks here. Once you have downloaded the data, the ./Data folder should look like:

ArgoCycle

Further reading#

For the full description of the formats and files produced by the Argo Data Assembly Centres (DACs), see the Argo user’s manual, the Argo Quality Control Manual for CTD and Trajectory Data or the The Argo data management handbook

More information can be found in the Argo Steering Team web page or the Argo Data Management team documentation

License for this book#

All content in this book (ie, any files and content in the content/ folder) is licensed under the Creative Commons Attribution-ShareAlike 4.0 International (CC BY-SA 4.0) license.