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the-coding-club

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Explore the pathway toward scaled-up scientific analysis with Earthdata in the cloud. These activities focus on the community with limited knowledge of the AWS cloud, which is still the majority.

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# The PO.DAAC Coding Club

Toward scaling up scientific analyses with Earthdata/PO.DAAC in the cloud.

1. [The very first step toward using cloud from knowing nothing about cloud](https://github.com/podaac/the-coding-club/blob/main/notebooks/Earthdata_webinar_20220727.ipynb)
1. [Demonstrate using Fortran in the cloud by running MITgcm](https://github.com/podaac/the-coding-club/blob/main/notebooks/Run_MITgcm_on_a_large_EC2.ipynb)
1. [Investigating the Efficiency of File Formats for SWOT Data on the Cloud](https://github.com/podaac/the-coding-club/blob/main/notebooks/File_Performance.ipynb)
1. [The one-stop cloud solution: SWOT-dashboard as an example](https://nbviewer.org/github/podaac/the-coding-club/blob/main/notebooks/SWOT_SSH_dashboard.ipynb) (notebooks/SWOT_SSH_dashboard.ipynb)

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1. Grace Handbook
   1. [Using GRACE-FO mascon data to analyze Terrestrial Water Storage anomalies of the Colorado River Basin](https://github.com/podaac/the-coding-club/blob/main/notebooks/GRACE_handbook_tutorial_01_tws_riverbasin_v01.ipynb)

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1. Tutorials
   * ECCO [Compute global mean ocean energy imbalance from ECCO Version 4 Release 4](https://github.com/podaac/the-coding-club/blob/main/notebooks/Compute_ECCO_global_mean_energy_imbalance.ipynb)
   * [EC2 jupyterlab setup](https://github.com/podaac/the-coding-club/blob/main/notebooks/EC2-Jupyter-Setup.md)
   * NASA-SSH [Using Dask to parallel process the global mean sea level anomaly using PO.DAAC data in the cloud](https://github.com/podaac/the-coding-club/blob/main/notebooks/MEaSUREs-SSH-dask.ipynb)
   * [Build a notebook with podaac data to support a field campaign in real time: SASSIE as an example](https://github.com/podaac/the-coding-club/blob/main/notebooks/sassie_campaign.ipynb)

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