Description

Workshop attendees will learn how to utilize new software that allows users to harness the cloud-optimization of the Zarr data format with existing NetCDF/HDF5 datasets by following along with example code and data.

Learning Objectives

Gain familiarity with:
– XArray, Matplotlib, and Jupyter notebooks
– Zarr, NetCDF/HDF
– fsspec-reference-maker (ReferenceFileSystem), a project that allows Zarr-like access to existing NetCDF/HDF/GRIB2 data without needing to convert to Zarr.

Prerequisites

Participants should have an introductory understanding of Python.

Software

No software installation is needed. A link to interactive code samples in the cloud will be provided for attendees to follow along, requiring only a web browser (such as Chrome, Firefox, Safari, or Edge).

Instructor: Lucas Sterzinger

Instructor Bio

Lucas is a 5th year PhD student in the UC Davis Atmospheric Science Graduate Group studying cloud physics. He became involved in Big Data/Open Data software development during the summer of 2021 as an intern in the National Center for Atmospheric Research’s (NCAR) Summer Internship in Parallel Computational Science (SIParCS) program.

Location: Zoom. Please register to receive Zoom link.

Registration: https://registration.genomecenter.ucdavis.edu/events/maptimeDavisAccessingNetCDFwithPythonZarr/register/

Cost: Free of charge.