James Varndell Using Jupyter notebooks to document and support climate and meteorology data

Discover how Jupyter notebooks are revolutionizing climate and meteorology data documentation and support, providing an end-to-end workflow and interactive web applications for users of all skill levels.

Key takeaways
  • The Climate Data Store (CDS) is a web-based data portal with 190,000 registered users, 139 data sets, and daily data serving capacity of 100TB, aiming to provide access to climate data for a wide range of users.
  • The typical climate data workflow involves accessing data, processing, and visualizing it, with users seeking to calculate long-term averages, trends, and climatic indices.
  • The CDS uses Jupyter notebooks to document and support climate data, providing an end-to-end workflow through a single interface, from data access to visualization, and offering interactive web applications for less technical users.
  • The Climate Change Service (C3S) and Atmosphere Monitoring Service (CAMS) provide global information for climate change adaptation and mitigation policies, and air pollution, health, solar energy, and other topics.
  • Jupyter notebooks help provide documentation and code for efficient explanation of processes, with accompanying use cases, improving reproducibility of results and engaging users with climate data.
  • The CDS uses a common data model to harmonize data, enabling comparison of different data sets, and provides a simple web interface for selecting data facets, as well as a full API catalog.
  • The Climate and Atmosphere Datastore (CADS) is being improved to use JupyterHub and JupyterLab, replacing the current bespoke web-based Python editor.
  • Jupyter notebooks will be used for data documentation and support, with tools for processing, visualizing, and combining large data sets, and providing high-level APIs for easier interaction.
  • The CDS and CADS aim to provide a user-friendly interface for exploring dataset contents, with caching and reproducibility features to reduce memory issues and improve performance.
  • The CDS is in the process of modernizing its system to make use of Jupyter technologies, seeking to provide a more straightforward and consistent interface for accessing and working with climate data.