OSSE_pCO2

This repository contains introductory training material on climate and weather modelling, focussing on Observation System Simulation Experience (OSSE), based on the article:

Denvil-Sommer, A., Gehlen, M., and Vrac, M.: Observation system simulation experiments in the Atlantic Ocean for enhanced surface ocean pCO2 reconstructions, Ocean Sci., 17, 1011–1030, https://doi.org/10.5194/os-17-1011-2021, 2021.

Base requirements

• Python 3

NOTE: this code uses Pytorch, which on some laptops is not compatible with python versions >3.12 (for example if you are running a Mac with intel processors). If the installation of pytorch fails, you will need to use a different version of python (more details below).

The instructions below will install the necessary packages

Getting started

1. Clone this repository into a directory

git clone https://github.com/lcimoli/OSSE_pCO2.git

2. Download the data set from:

Denvil-Sommer, A. (2024). Dataset for OSSE exercise at ICCS Summer School 2024 Cambridge [Data set]. Zenodo. https://doi.org/10.5281/zenodo.12567970

It is easiest to download Data_SS.zip and unzip it into the same directory as the code so that the .csv files are alongside the notebook file.

3. To setup the Notebook, we recommend running it in a virtual environment:

   python3 -m venv .venv
   source .venv/bin/activate
   pip install -r requirements.txt
   

NOTE: If you get an error about pytorch, you will need to use a different python version when creating the virtual environment. First check what versions are available with

ls /usr/local/bin/python*

Then, pick a version previous to 3.13 (if available) and run

/usr/local/bin/python3.XX -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt

Where XX should be changed with your python version (e.g. python3.11).

If a previous version of python is not available, you will need to install it. The easiest way is probably to use pyenv, i.e.

brew install pyenv; pyenv install 3.12 . 

Alternatively, you can use conda to create an environment (this might take some time to setup):

1. first install miniforge https://conda-forge.org/download/

2. then create a new environment using

   conda create -n my-env "python==3.12"

3. then pip install inside of this

Once the requirements have been installed, you can load the notebook using your favourite mechanism. For example, using Jupyter lab you can do:

  jupyter-lab

and then choose the SOCAT_20082010_AtlOcean_ADS_05062024.ipynb notebook.

If you are using VScode, you can select the version of python when you create a virtual environment.

Credits

Originally created by Anna Denvil-Sommer. Reviewed by Laura Cimoli.