SIParCS 2023 - Ian Franda
Ian Franda, University of Wisconsin Madison
Python Data Analysis and Visualization for Unstructured Grids Data
Project Raijin was awarded by NSF EarthCube in order to develop community-owned, sustainable, scalable tools for data analysis and visualization that can operate on unstructured climate and global weather data at global storm-resolving resolutions. The development of Project Raijin leverages the scientific Python ecosystem, particularly the Xarray and Dask packages, and the Pangeo community. During the SIParCS 2023 summer internship, the intern will have the opportunity to work in a novel research and development project by helping implement various data analysis and visualization workflows for unstructured grids such as example plotting scripts for different unstructured grid datasets, Jupyter Notebook based training modules, UXarray usage examples, and computational functions. The student will explore and learn about data visualization and analysis in geosciences using commonly used Python tools such as Matplotlib, Cartopy, and Holoviews. The student will also learn high performance computing (HPC) principles through use of NCAR’s HPC clusters as well as using parallelization and optimization packages such as Dask, Numba, and Datashader. Most or all of the student’s work will be made publicly available through our open-development model, which will in turn help the intern create a strong Python portfolio in data analysis and visualization.
Mentors: Orhan Eroglu, Anissa Zacharias
Slides and poster