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Collaborative Computational Resource Development around ICESat-2 Data: the icepyx Community and Library
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  • Jessica Scheick,
  • Kelsey Bisson,
  • Tian Li,
  • Wei Ji Leong,
  • Anthony Arendt
Jessica Scheick
University of New Hampshire

Corresponding Author:jbscheick@gmail.com

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Kelsey Bisson
Oregon State University
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Tian Li
University of Bristol
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Wei Ji Leong
Victoria University of Wellington
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Anthony Arendt
University of Washington
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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.