NCAR’s GeoCAT and VAPOR groups are committed to open science by developing open source, scalable, multi-platform data analysis and visualization tools that enable exploratory analysis of complex/large datasets in the scientific Python ecosystem. GeoCAT’s main focus is on analyzing/visualizing geoscience data sampled on both structured (lat-lon) and unstructured (flexible mesh) grids from various research fields such as climate, weather, atmosphere, ocean, etc. VAPOR is an open-source, community-driven, interactive, 3D visualization tool, designed to operate primarily on 3D arrays of time-varying, gridded data arising from numerical simulations. The recently released VAPOR python API brings the advanced visualization capabilities to the Python ecosystem.

This workshop will guide the participants through state-of-the-art (e.g. static plotting with Matplotlib, projections with Cartopy, etc.) and novel techniques (e.g. interactive big-data rendering with Datashader and Holoviews) in 2D/3D geoscience data visualization in the scientific Python ecosystem as well as the National Center for Atmospheric Research (NCAR’s) visualization tools such as GeoCAT-examples, GeoCAT-viz, UXarray-plot, and VAPOR.

January 27, 2024 at 8:30 AM - 12:30 PM Eastern Time (Hybrid) - Baltimore Convention Center

REGISTRATION RATES

REGISTER HERE

Course Description:

Goals for this half-day course:

• Basics of geoscience data visualization in Python:
  - Basic information about the techniques and tools that can be used for plotting data sampled on both structured (lat-lon) and unstructured (flexible) meshes in Python
• Visualization of structured (lat-lon) grids in Python:
  - Demonstration of structured (lat-lon) grids visualization using Matplotlib and Cartopy in several plotting categories through GeoCAT-examples and GeoCAT-viz
• Interactive, high-performance visualization of big data in Python
  - Introduction of novel techniques and tools such as Datashader and Holoviews for scalable, interactive visualization of very large geoscience data
• An introduction to unstructured grids (flexible mesh) visualization in Python
  - Introduction to GeoCAT’s another Python tool, Uxarray, and its plotting capabilities for data sampled on unstructured meshes
• Advanced 3D visualization techniques
  - Introduction to techniques such as 3D isosurfaces, Volume rendering, Particle visualization, flow visualization (Eg. streamlines),
  - Examples of the techniques using VAPOR

VIEW AGENDA

If you have questions regarding the course, please contact Orhan Eroglu.

Instructors: