Data Visualization in Python: Leveraging Community Tools for Earth System Science Across Scales

Data visualization is important at all steps of the scientific process, from exploratory data analysis to publication, scientific communication, and application. The ever increasing volume and complexity of Earth System science data and associated tools, infrastructure, and technologies necessitates the use of state of the art analysis and visualization tools and techniques. A wealth of tools and resources for these purposes are available in the broader scientific Python ecosystem and associated projects. The ability to leverage these tools effectively and engage with the surrounding communities and resources is emerging as a core competency for students, researchers, and practitioners working in and around Earth System science and is critical for open science.

This half-day short course guides participants through a range of tools, techniques, and resources (e.g. Project Pythia, GeoCAT projects) for visualization of Earth System science data across scales leveraging open-source, community software from the scientific Python ecosystem (e.g. Matplotlib, Cartopy, Holoviews, Geoviews, UXarray). In particular, we focus on some of the more advanced features and techniques that address common challenges and use cases for Earth System science across scales such as: domain specific visualization types and specialty plots; animations; interactive and high-performance visualization tools and technologies; visualization of multiple disparate data sources; working with data on unstructured grids and meshes; and customization options.

Instructors for the course are from the U.S. National Science Foundation National Center for Atmospheric Research GeoCAT team. GeoCAT is committed to open science by developing open source, scalable, multi-platform data analysis and visualization tools and resources that enable analysis and visualization of geoscience datasets in the scientific Python ecosystem.

Participants are expected to have basic knowledge of Python syntax and familiarity with Matplotlib figure structure as covered in Project Pythia Foundations.

105th AMS Annual Meeting
New Orleans Ernest N. Morial Convention Center
January 12, 2025 at 8:00 AM - 12:00 PM Central Time (Hybrid)

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Course Description:

Coding skills and expertise to support data visualization are critical to Earth System science, from exploratory data analysis to scientific communication, and yet training in these areas is often lacking. These challenges are compounded by the growing size and complexity of data (e.g. data on global high resolution meshes from Earth System model simulations), rapid evolution in technology, and the corresponding changes to infrastructure, workflows, and software. This course will introduce participants to data visualization concepts, state of the art tools and techniques, and raise awareness of resources and community efforts in these areas.

By the end of the course participants will:

  • Have increased awareness of the tools and resources available to support their data analysis and visualization needs
  • Understand when to use different packages for data analysis and visualization
  • Recognize some of the common challenges and pain points and how to address them
  • Be able to visualize outputs from models such as the Community Earth System Model (CESM) and the Model for Prediction Across Scales (MPAS) directly without the need for preprocessing or regridding

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If you have questions regarding the course, please contact Katelyn FitzGerald.

Instructors:

Julia Kent
Julia Kent

NSF NCAR

Philip Chmielowiec
Philip Chmielowiec

NSF NCAR

Katelyn FitzGerald
Katelyn FitzGerald

NSF NCAR

Orhan Eroglu
Orhan Eroglu

NSF NCAR

Anissa Zacharias
Anissa Zacharias

NSF NCAR