Geoscientists often spend significant research time identifying, downloading, and refining geospatial data before they can use it for analysis. Exploring interdisciplinary data is even more challenging because it may be difficult to evaluate data quality outside of one’s expertise. QGreenland, a newly funded EarthCube project, is designed to remove these barriers for interdisciplinary Greenland-focused research and analysis via an open data, open platform Greenland GIS tool. QGreenland will combine interdisciplinary data (e.g., glaciology, human health, geopolitics, hydrology, biology, etc.) curated by an international Editorial Board into a unified, all-in-one GIS environment for offline and online use. The package is designed for the open source GIS platform QGIS. QGreenland will include multiple levels of data use: 1) a fully downloadable base package ready for offline use, 2) additional disciplinary and/or high-resolution data extension packages for select download, and 3) online-access-only data to facilitate especially large datasets or updating time series. Software development has begun and we look forward to discussing techniques to create the best open access, reproducible methods for package creation and future sustainability. We also now have a beta version available for experimentation and feedback from interested users and the Editorial Board. The version 1 public release is slated for fall 2020, with two subsequent annual updates. As an interdisciplinary data package, QGreenland is designed to aid collaboration and discovery across fields. Along with discussing QGreenland development, we will also provide an example use case to demonstrate the potential utility of QGreenland for researchers, educators, planners, and communities.

The rapid acceleration of Greenland Ice Sheet mass loss over, particularly the last two decades, is well documented.However, limits in early remote sensing restricted the details with which we could examine local changes on an ice-sheet-wide scale, particularly in areas of slow motion, along shear margins and complex coastal terrain. We explore the localcharacter of rapid contemporary change marine-terminating glaciers using satellite-derived ice sheet surface velocities,glacier terminus advance/retreat history, and surface elevation-change data from the 1980s to the present. Widespread glacierterminus retreat is a strong and more consistent climate response indicator than velocity change, but local changes in velocityare critical indicators of rapid ice sheet reconfiguration. Ice thickness changes related to changing ice dynamics often providethe first evidence of processes that initiate outlet glacier retreats and mass loss, such as the development of sub-ice shelfcavities and subglacial hydrology changes. Reconfiguration is observed locally as narrowing zones of fast-flow, ice flowrerouting, shear margin migration, and likely glacier outlet abandonment. These patterns are apparent in all ice sheet sectorsand observable from space-borne instruments. The rapid reconfiguration now well underway in Greenland has wide-rangingimplications, including expected changes in subglacial hydrology, ice discharge, freshwater flux to the ocean, and transport ofnutrients and sediment. Lacking detailed observations of earlier deglaciations and current limits on ice-sheet modelcapabilities, the expanding details of these combined observational records may provide a valuable analog for studying pastice sheet dynamics and projecting future ice loss.

Southeastern Greenland (SEG) provides a complex habitat area consisting of dozens of deep fjords that connect land-based ice with the open ocean. Within these fjords, glacial ice mixes with sea ice and intricate topography can create niche local conditions. This area is important for a number of species, including polar bears, and better understanding of both land ice and floating glacial ice as biological habitat motivates the need to study the physical environment itself. Studying SEG, however, posed a variety of challenges, including difficult access for in-situ work or instrument deployment, cloudy conditions that can obscure optical satellite instruments, and steep, complex terrain that can complicate identification of surface conditions. Here, we discuss our work to leverage several remote sensing products to determine the geospatial patterns of landfast sea ice and solid glacial ice during 2015-2019 in five SEG fjords with high polar bear use. We further connect these data with measurements of solid glacial ice discharge and glacial and terrestrial freshwater flux across SEG. The landfast sea ice season in our focus fjords is quite short, extending on average only ~2-4 months, and including substantial variability. Because of the fjord connections to marine-terminating glaciers, however, solid glacial ice creates a potential alternative ice platform on the fjord surfaces that can complement the short sea ice season. Challenges remain in automating this type of surface classification, and we discuss how our manual digitization work can be leveraged to support other ongoing efforts to create machine learning surface identification algorithms.