Tutorial on visualizing geoscience data with Python at AGU and AMS!

Join NCAR’s ViSR and GeoCAT teams at AGU and AMS for a tutorial titled Visualizing 2D and 3D Geoscience Data in Python.

For the AGU tutorial, be sure to click “add an event” and look for “SCIWS24 - Visualizing 2D and 3D Geoscience Data in Python” when registering. If you’ve already registered, log back into the registration site with your AGU registration information. Then click on “add sessions and events” and select “SCIWS24 - Visualizing 2D and 3D Geoscience Data in Python.”

Register directly for the AMS tutorial.

Abstract
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 tutorial 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.

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FYI: December 1 is the deadline to register for AGU Learning Workshops