Collaborative Computational Resource Development around ICESat-2 Data:
the icepyx Community and Library
Abstract
Cryospheric data is increasing in size, demanding highly computational
analyses. Open science principles, including collaboration, enable
efficient, tested, reproducible, and diverse computational resource
development. The ICESat-2 science community continues to coalesce around
these ideals through contributions to icepyx, a community and
open-source Python library for obtaining and working with large
(~500 GB/day) data products from the ICESat-2
satellite/ATLAS laser altimeter. Our presentation will focus on the
history, motivation, and process of creating this community, developing
shared computational tools, and collating a set of example workflows
within Jupyter Notebooks focused on ICESat-2 data. We will present new
and in-the-works examples and features of the library, including
enhanced pre-data-download visualizations, collaborative developments
for multi-mission and -sensor data access, and data read-in/merging
functionality. We will also highlight the community building events
(including hackweeks) that drive this group and showcase some of the
research supported and enabled by this software library.