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Argo Online School

The Argo Online school is a set of videos and hands-on jupyter notebooks to describe the minimum requiremets to use, and understand, the Argo data. You can access the content as here in a JubyterBook, or download them and use in your local machine. In that case, you should create a python enviroment to use these notebooks. To create, and activate, the enviroment AOS

conda env create -f environment.yml
conda activate AOS

This enviroment already includes argopy stable version.

Data

If you download the notebooks you should create a ./Data* folder where include the files used for the examples. The files in the Data folder can be dowloaded from here or directly from its source using wget:

Daily NOAA OI SST V2 High Resolution Dataset for 2009:

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

Data from float 6900772

wget ftp://ftp.ifremer.fr/ifremer/argo/dac/coriolis/6900772/*

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

Further reading

As a very useful first aproach to python, you can use An Introduction to Earth and Environmental Data Science and Research computing in earth Sciences developed by Ryan Abernathey and Kerry Key.

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


Before proceding, let’s check if you really need this course, and try to answer the following questions

  • what is a WMO number ?

  • what is the difference between Delayed and Real Time data mode ?

  • what is an adjusted parameter ?

  • what a QC flag of 3 means ?

If you don’t answer to more than 1 questions, please keep reading (or watching). Even though if you answered all the questions but you ara not very familiar with python, netCDF, or argopy, you may find interesting the content of this course