This repository contains a collection of notebooks that demonstrate various techniques for loading and processing data. The goal is to have an easy and fast access to code that can be reused in different projects.
How to load CESM2 Large Ensemble (CESM2-LE) data from AWS.
How to access CMIP6 data hosted on Google Cloud. (Subset, faster method)
How to access CMIP6 data from ESGF nodes using rooki. (Subset and regrid, sometimes slow)
How to access data downloaded and hosted in IRI library and other sources that support OPeNDAP.
How to calculate the E and C index following the method of Takahashi et al. (2011).
If you feel more comfortable using your computer instead of the cloud, you can run the notebooks locally by using the provided env.yml file (or just installing the missing packages if you already have an environment).
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Download the conda-installer that suits your OS from here
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Install mamba (faster than conda)
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Create a new environment using the
env.ymlfile with the following command:mamba env create -f env.yml
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Activate the environment:
conda activate climate
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Launch Jupyter Lab or use Visual Studio Code to open the notebooks.