News

September 2025 Collaborator Highlight: Navigating the New Arctic

About the Project The National Science Foundation announced the 10 Big Ideas for Future NSF Investments in 2016, a strategic set of long-term research priorities aimed at catalyzing bold advances in science and engineering. Among them was the Navigating the New Arctic (NNA) program, an initiative designed to tackle one of the most urgent and… Read more »

Permafrost Grown: Farmers and Researchers Co-Produce Knowledge on Permafrost-Agriculture Interactions

Highlight: “Farming in Alaska is like farming on another planet” – Local Farmer working with the Permafrost Grown project. The Unseen Challenge Beneath Alaska’s Farms Rising temperatures, extended warm seasons, and a growing number of frost-free days are shifting the geographic range of crop cultivation, contributing to expanded agricultural activity across Alaska. Farming in remote… Read more »

August 2025 Collaborator Highlight: QGreenland

About the Project The QGreenland project, funded by the National Science Foundation, is a mapping tool hosted by the National Snow and Ice Data Center (NSIDC) at the University of Colorado Boulder’s Cooperative Institute for Research in Environmental Sciences (CIRES). The free tool supports interdisciplinary Greenland-focused research, teaching, collaboration, and decision making by combining key… Read more »

New Dataset Explores Permafrost Coastline Erosion Dynamics at Drew Point, Alaska

ADC Dataset Feature

  “…when ice is present underground, it occupies space. The melting of this ice leads to ground subsidence, which creates issues such as coastal erosion, infrastructure instability, agricultural changes, landslides, and more.” Background and Research Expertise Like many researchers, Dr. Melissa Ward Jones found Arctic science by accident. As a first-generation college student and the… Read more »

July 2025 Collaborator Highlight: Cyber2A

  Artificial intelligence (AI) and machine learning (ML) play an increasingly crucial role in Earth science teaching and research by accelerating large data analyses, data interpretation, enhancing predictive models, and making complex environmental processes more accessible to students and researchers alike. The NSF-funded Cyber2A project is a collaboration between Arizona State University (ASU), Woodwell Climate… Read more »

New Dataset Using Deep Learning to Predict Permafrost Thaw Damage in the Arctic with Elias Manos

Background Born and raised in New England, Elias Manos was not familiar with the Arctic, but he had a deep interest in learning about this unfamiliar place. His academic background in geography more commonly dealt with geospatial data science, particularly analyzing satellite/aerial imagery with machine learning. While Manos was still an undergraduate, he began collaborating… Read more »

Applications Open for NSF AI/ML Curriculum Development Workshop (Cyber2A)

  We are excited to announce the upcoming second “Scaling Impact: Co-Creating a Shared Framework for Teaching AI and Machine Learning with Applications in Arctic Research” workshop, to be held from October 20-24, 2025, in beautiful Santa Barbara, CA! Overview Artificial intelligence (AI) and machine learning (ML) play an increasingly crucial role in Earth science teaching and research… Read more »

June 2025 Collaborator Highlight: Permafrost Discovery Gateway

Highlight: Permafrost thaw is expected to cost Alaska $37-51 billion in building and road damages by 2050 The Permafrost Discovery Gateway (PDG) is an online data visualization platform hosted by the Arctic Data Center that provides openly accessible permafrost conditions across the Arctic region for researchers, educators, and the public. The PDG leverages satellite imagery… Read more »

Updated Large Model Output Policy at the Arctic Data Center

Computational models are growing in their capacity to consume large datasets and create complex, fine-scale outputs that sometimes reach multiple terabytes in size. Although in theory model output can be regenerated by re-running the model, doing so may require access to high-performance supercomputing, making reproduction costly and impractical. Therefore, when the model output data have… Read more »

New Dataset and Paper Exploring the Influence of Goose Herbivory on Litter Decomposition in the Yukon-Kuskokwim River Delta, Alaska

Highlight: “Saunders emphasized the importance of having the work from her project funded and supported by the National Science Foundation and state agencies, highlighting the great value of investing in research like hers and resources like the ADC” Background and Research Expertise Prior to the Arctic, Taylor Saunders spent a few years immersed in the… Read more »