NASA s icesat-2 mission provides unprecedented opportunities to inform the next generation of scientific discovery by providing high spatial and temporal resolution measurements of earth surface…

This is a $249,826.57 Grant For Research award from NASA to the University System of New Hampshire (UNH), through its University of New Hampshire division operating as the Office of Sponsored Research. The purpose is to enable rapid scientific discoveries from the ICESat-2 satellite's high-resolution elevation measurements of the Earth's surface. The grant aims to:

1. Develop an open-source Python package called ICEpyx for analyzing ICESat-2 data,
2. Empower domain scientists to exploit the scale and richness of ICESat-2 data through cloud and high-performance computing capabilities, and
3. Foster a community culture of collaborative, open, and reproducible scientific practices around ICESat-2 data through educational and outreach activities.

This award is not associated with a set-aside designation, and UNH has previously served as both a prime contractor and subcontractor on federal research and technical assistance projects across various agencies. The overarching goal is to support NASA's objectives to better understand the Earth's climate system.

NASA s icesat-2 mission provides unprecedented opportunities to inform the next generation of scientific discovery by providing high spatial and temporal resolution measurements of earth surface elevations. However, at present many researchers lack the necessary training and tools to implement new approaches required to maximize discovery using the large data volumes (~1 TB/day) returned by the atlas sensor. This could severely limit the scientific and societal impact of icesat-2's overall mission during a time of critical importance. We aim to enable rapid scientific discoveries from icesat-2 datasets by reducing technical and human barriers to open and reproducible research practices. We will achieve this goal by tackling the following specific objectives: (1) develop icepyx, an opensource python package for scientific analysis with icesat-2 data, CO-designed in collaboration with data access tools developed at the national snow and ICE data center (nsidc) (2) empower domain scientists to exploit the scale and richness of icesat-2 data with software and hosted deployments in large-scale computing environments (both in the cloud and at high performance computing facilities) that leverage existing and new python tools and streamline the transition for scientists to adapt their workflows to take advantage of large-scale computing (3) foster a community culture of collaborative, open, reproducible, and extensible scientific practice around icesat-2 data through the hosting of targeted educational and outreach activities and the development of open educational materials. Our software design and community development strategies are grounded in the scientific needs of domain research. By partnering with a variety of domain specialists, including cryospheric scientists, hydrologists, and biologists, we will ensure that all of our development directly meets the needs of the broader community. Among other themes, project partners are exploring the role of sea ICE on phytoplankton populations and using repeat surface elevations to compute ICE surface velocity. These research use-cases illustrate common icesat-2 data computational needs (e.g. tracking, reprojection, regridding, formatting) and serve as design constraints for icepyx. Similarly, we will conduct community development work that is tightly coupled to the needs of domain scientists. We will host targeted educational and outreach activities based on the university of washington's successful 2019 and 2020 icesat-2 hackweeks, where domain-specific questions were used to explore computational ideas while scientists developed skills in modern computational practice and explored icesat-2's datasets. We will host code development sprints to expand the icepyx codebase in support of achieving science objectives. We will also work directly with icesat-2 science team members to develop interactive, executable tutorial content based on active research projects and drawn from our team s experience in developing opensource toolkits. Expected outcomes of our work include continued development of a clearinghouse of python tools (icepyx), alignment of the icesat-2 data provider and research community around a core set of open-source tools, hosting of regular icesat-2 hackweeks targeted at engaging the broader research community in open science practices, and development of educational resources (e.g. documentation, tutorials, and real-world example workflows) that take advantage of cloud-computing capabilities. These outcomes enable big-data workflows with icesat-2 data, minimize duplication of time and effort, and accelerate our collective ability to make high-impact scientific discoveries. Through these efforts, we actively support NASA s goals to improve the ability to predict climate changes by better understanding the roles and interactions of the ocean, atmosphere, land and ICE in the climate system and promote and adopt open, reproducible scientific practices.