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darc-training-2025

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Practical for NERC/NCEO/DARC Training course on data assimilation and its interface with machine learning 2025

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# NERC/NCEO/DARC Training course on data assimilation and its interface with machine learning 2026
Practical material for NERC/NCEO/DARC Training course on data assimilation and its interface with machine learning 2026 in Reading

## On Google Colab (Recommended)
This year, the DARC training course is splitted into foundation and advanced course. In the foundation course, this repository covers:
- Building blocks of DA: [Streamlit](https://alisonfowler-da-training-oi-1-optimal-interpolation-3dxab6.streamlit.app/) and [Jupyter Notebook](https://colab.research.google.com/github/darc-reading/darc-training-2025/blob/main/Control_DA_components.ipynb)
- Reanalysis: [Jupyter Notebook](https://colab.research.google.com/github/darc-reading/darc-training-2025/blob/main/reanalysis.ipynb)

In the advanced course, we provide practicals for
- Variational DA: [Jupyter Notebook](https://colab.research.google.com/github/darc-reading/darc-training-2025/blob/main/Controls_L96_Var.ipynb) and [JEDI instructions](JEDI_SABER_exps.pdf)
- EnKF DA: [Jupyter Notebook](https://colab.research.google.com/github/darc-reading/darc-training-2025/blob/main/Controls_L96_Enkf.ipynb), [Optional Notebook](https://colab.research.google.com/github/darc-reading/darc-training-2025/blob/main/Controls_L63_Enkf.ipynb) and [JEDI instructions](JEDI_LETKF_exps.pdf)
- [Machine learning and DA](https://colab.research.google.com/drive/1resUNqp3HHIwV-Ra-tli5Lgu4Qft-ZEB)

## Running on your own laptop locally
To run practicals on your local laptop, we recommend configure the Python environment using `conda`. Once you installed `conda`, you can launch the Jupyter notebook with the following command in your terminal or anaconda command prompt:
```bash
# create a new conda envrionment and install required packages
conda create -n da_course conda-forge::numpy conda-forge::scipy conda-forge::matplotlib conda-forge::cartopy conda-forge::ipywidgets conda-forge::jupyter conda-forge::xarray conda-forge::dask conda-forge::netCDF4 conda-forge::bottleneck conda-forge::kagglehub
# activate the conda environment
conda activate da_course
# launch jupyter notebook
jupyter notebook
```

# Setting up connections to Reading Academic Computing Cluster (RACC) -- in-person only
Advanced course participants will obtain a temporary RACC account. To utilise the computing resources on the computing cluster, users must connect to RACC via `ssh`.
```bash
ssh -Y -J USERNAME@arc-ssh.reading.ac.uk USERNAME@racc.rdg.ac.uk
```

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