Current Projects at CReSIS

Lead Institution: Oregon State University
KU-PI: John Paden, Co-I's: Emily Arnold, Rick Hale, Fernando Rodriguez-Morales
Sponsor: NSF
10/01/2021 to 09/30/2026

https://coldex.org/ 

SF COLDEX is a multi-institution collaboration to explore Antarctica for the oldest possible polar ice samples and analyze those samples to understand the evolution and future of Earth’s climate system. It will also create and deliver novel educational and professional development programs for teachers, faculty and early career scientists, develop and implement programs to help make polar science more diverse and inclusive, and transfer scientific knowledge to stakeholders and the public. NSF COLDEX is funded by the U.S. NSF Science and Technology Center Program and supported by the NSF Office of Polar Programs through Award number OPP 2019719. 

NSF COLDEX research includes exploration of interior East Antarctica using radar and novel “rapid access” tools to find locations to collect a continuous 1.5 million year ice core, roughly doubling the length of the existing continuous record. NSF COLDEX will also collect and analyze much older ice along the Antarctic ice sheet margin, conduct ice sheet modelling to help understand the history and distribution of the oldest ice, and develop new laboratory capabilities for analyzing and dating old ice.

NSF COLDEX education programs are bringing ice core science to K-12 and college level instructors through several summer professional development programs. A center-wide REU program and other research opportunities provide cutting edge research experiences for undergraduates. Opportunities for graduate students and postdoctoral research are available at a number of NSF COLDEX partner institutions.  NSF COLDEX also organizes professional development workshops for early career scientists, specialized technical workshops, and a research scholarship program. These activities are open to individuals from NSF COLDEX participating institutions and other colleges and universities.

NSF COLDEX aims to broaden participation in polar science by both recruiting members of underrepresented groups in STEM to join all of our programs, and a targeted effort to develop a more inclusive scientific culture. 

Knowledge Transfer in NSF COLDEX focuses on bringing climate change knowledge to the public and a variety of other stakeholders, on understanding how the scientific knowledge we generate is disseminated through the media, through social networks, and in other forums, and on new exploration technology.

PI: Carl Leuschen
Sponsor: Heising Simons
04/01/2019-03/31/2026

The primary goal of the project is to improve our knowledge of the bedrock topography of Helheim Glacier. Bed topography is a primary input for ice sheet models, and filling in existing gaps will improve modelling results and understanding of ice sheet processes near the terminus. Previous airborne radar sounding measurements of Helheim Glacier from large fixed-wing manned aircraft have been unable to completely map the bed topography, especially near the terminus where the glacier is rapidly changing. Previous airborne survey using lightweight UAS over Russell Glacier have shown the utility of a high-frequency (operating near 30 MHz) radar sounder operating on a compact UAS in mapping the bed when compared to previous surveys.

PI: Emily Arnold
Sponsor: NSF
08/01/2019-07/31/2026

The ice sheet mass loss being observed in Greenland and Antarctica directly contributes to global Sea Level Rise (SLR). By the end of this century, scientists predict that changes in the polar ice sheets could contribute anywhere from tens of centimeters to almost two meters in SLR. This large uncertainty in future SLR predictions is due, in part, to insufficient measurements of bedrock topography and surface crevasses in the most critical regions of the ice sheets. These measurements are used by scientists in ice sheet models to predict contributions to SLR. The observational gaps in bedrock topography and surface crevasses limit scientists abilities to accurately model changes in the dynamic ice sheets. This project addresses this data need by equipping a small drone helicopter with a radar suite to produce fine-grid measurements of ice thickness, bed topography, and crevasses in critical regions of the ice sheet. Rising seas will have huge social and economic impacts on the entire global population especially to the estimated 150 million people living in coastal regions at elevations within 1 m of current sea level. The uncertainties in SLR predictions greatly inhibit our ability to properly plan for and adapt to our changing climate. The broader impacts of this work are not limited to reducing uncertainty in SLR predictions. This project also involves the training of post-secondary students in developing next-generation remote sensing technologies to better prepare them for 21st century careers. By integrating research and education, post-secondary students will gain practical experience via classroom design, build, and test projects. Through these projects, students will be exposed to the environmental and social issues that are driving the need for this new technology. The intellectual merits of this work encompass both the technological development of the new sensor-platform and the glaciological studies this tool will enable. The primary technological research goal is to extend the application of drones in environmental remote sensing by: 1) using a novel approach for antenna integration and multi-pass distributed array processing that overcomes major payload limitations of small drones, and 2) demonstrating an autonomous platform that is easier to operate yet has sufficient payload capabilities and is robust enough to conduct measurements in polar environments. The vehicle’s flight capabilities will enable crevasse mapping and bed topography data collection with a combined spatial extent and resolution that will allow scientists to study: 1) the effects of measurement resolution on modeling ice sheet dynamic processes; 2) the significance of bed topography on glacial behavior at multiple time scales; and, 3) crevassing mechanisms and correlating crevasse attributes to calving events.

PI: John Paden

Sponsor: National Science Foundation

09/01/2021-08/31/2024

Earth’s polar ice sheets play a critical role in shaping sea level over geological time, yet ice-sheet response to contemporary climate change remains highly uncertain. Forty years of spaceborne observations reveal the recent acceleration in mass loss of the ice sheets through measured change in elevation, gravity, and ice-flow variation. It remains difficult, however, to use these satellite observations to predict future behavior, as they are the surface expression of non-unique subsurface processes. Airborne radar sounder measurements offer the potential to constrain non-unique ice-sheet surface dynamics because they can map out subsurface parameters (ice temperature/rheology, crystal-orientation fabric, englacial velocity, bed roughness, bed thermal state, and subglacial hydrology) on an ice-sheet-wide scale. These more advanced applications of radar data require joint interpretation of geometric and radiometric properties of radar data on a large scale.  However, five decades of radar data collection by multiple organizations deploying a range of systems with data distributed under inconsistent data policies and processing methods leads to siloed research resulting in lower efficiency and increased time to science. Open Polar Radar (OPoRa) brings together many of the data providers with the largest datasets and leverages an expert science team of collaborators in applied mathematics, radar engineering, glaciology, and artificial intelligence (AI), to produce standardized AI-ready data products, search services, and user tools firmly based on Findable Accessible Interoperable and Reusable (FAIR) principles to improve accuracy and reduce uncertainty in sea-level projection.

The OPoRa team covers 83% of Antarctica data and nearly complete Greenland and polar sea-ice coverage. For the first time, these datasets will be placed in common formats and made available through a common interface with a common set of tools for scientists via an end-user driven process.