Studying glaciers . . . from Florida

May 9, 2023

3 min

Emma "Mickey" MacKie

By Emma Richards


On the surface, the University of Florida seems an unlikely place to find cutting-edge research on ice sheets.


But Emma “Mickey” MacKie says this is the perfect place for her work — thanks in large part to HiPerGator, one of the fastest supercomputers in higher education.


MacKie, an assistant professor of geological sciences and glaciologist, joined UF in August 2021 and said her decision hinged largely on access to HiPerGator and the university’s focus on machine learning and artificial intelligence technologies. MacKie uses machine learning methods to study subsurface conditions of glaciers in polar regions and access to a powerful supercomputer is crucial given the large data sets her research generates.


“I'm very happy to be in a place with lots of people who are working on different types of problems and are interested in developing these different tools,” MacKie said. “There are a number of members of my department in geology who are studying glacial geology through different lenses. And so, there's all of this complementary geological and machine learning knowledge at UF that I'm very excited to bring together.”


MacKie has set up the Gator Glaciology Lab, where she and a team of seven undergraduate students from the fields of geology, computer science, physics, math and data science are using AI to analyze what lies beneath glaciers and how they are moving and melting.


“Our work is part of a bigger effort in the glaciology community to start working on quantifying our uncertainty in future sea-level rise projections so that we can give policy makers this information.”


It’s a very difficult challenge, MacKie said, because of limited access to polar regions and the miles-thick ice covering the ground. Then there is the scale of ice sheets; Antarctica, for example, is the size of U.S. and Mexico combined.


Measurements of the topography below such glaciers are gathered using radars mounted on airplanes to “see” through ice. Her team then uses HiPerGator to simulate realistic looking topography in places where there are gaps or blank spots in the measurements. They generate hundreds of maps to represent different possible ice sheet conditions, which could be used to determine numerous possible sea level rise scenarios.


“Our work is part of a bigger effort in the glaciology community to start working on quantifying our uncertainty in future sea-level rise projections so that we can give policy makers this information,” she said.


Earlier this spring, MacKie swapped out her flip-flops for snow boots to study subsurface glacial conditions in Svalbard, which is next to northeastern Greenland. Visiting Svalbard will help her test and develop data collection and analysis techniques that could be applied to Antarctica or Greenland, which both contain large ice sheets that could have serious environmental impacts if they experience significant melting.


In Svalbard, MacKie and Norwegian researchers from the University of Bergen and the University Centre in Svalbard took seismic and radar measurements of glaciers that will be used to make estimates about conditions beneath the ice.


Among glaciers of concern is the Thwaites “Doomsday Glacier,” which is losing the most ice of any glacier in Antarctica. There are signs showing Thwaites’ ice shelf could start to break in the next few years. MacKie said it will likely be a few hundred years before the glacier could undergo significant collapse and jeopardize the West Antarctica Ice Sheet, leading to several meters of sea level rise.


The effects of Thwaites and other ice sheet melts in Antarctica and Greenland will become apparent in decades to come, with the potential for a meter of sea level rise by the end of the century, which MacKie and other researchers hope to predict more accurately.


“The state of Florida has the most to lose when sea level rises,” she said in an episode of the From Florida podcast. “And so, I think we have a lot of skin in the game and it’s really important to be studying this question here in Florida.”


To hear more about MacKie’s work, listen to From Florida at this link.



Connect with:
Emma "Mickey" MacKie

Emma "Mickey" MacKie

Assistant Professor

Mickey MacKie uses geophysical observations and machine learning techniques to study the topography, geology and hydrology of glaciers.

Cryosphere ResearchGlaciologyTopography, geology and hydrology of GlaciersMachine LearningGlaciers
Powered by

You might also like...

Check out some other posts from University of Florida

1 min

New study suggests Florida Chagas disease transmission

Researchers from the University of Florida Emerging Pathogens Institute and Texas A&M University gathered their resources to investigate the potential of vector-borne transmission of Chagas in Florida. The 10-year-long study, published in the Public Library of Science Neglected Tropical Diseases, used data from Florida-based submissions, as well as field evidence collected from 23 counties across Florida. Chagas disease is considered rare in the United States. Since it is not notifiable to most state health departments, it is quite difficult to know exactly how many cases there are and how frequently it’s transmitted. Chagas disease is caused by the protozoan parasite Trypanosoma cruzi. Nuisance blood-sucking insects known as kissing bugs spread the parasite to humans when exposure to their feces penetrates the mucus membranes, breaches the skin or gets orally ingested. Interestingly, it is believed that most companion animals, like dogs and cats, acquire the parasite from eating the kissing bug itself. The first record of kissing bugs, scientifically known as Triatoma sanguisuga, harboring T. cruzi in Florida was from an insect in Gainesville in 1988. However, kissing bugs have been calling the state home for far longer than humans have. Currently, there are two known endemic species of kissing bugs in the Sunshine State: Triatoma sanguisuga, the species invading homes, and the cryptic species Paratriatoma lecticularia, which live primarily in certain Floridan ecosystems but were not found in this study. Read more ...

2 min

UF works with Gainesville-based Peaceful Paths to educate the public about domestic abuse and cybersecurity

Domestic abuse affects millions of people every year, often in unseen and deeply personal ways, and online threats toward victims can be particularly harmful. To address this reality locally, the University of Florida’s Center for Privacy and Security for Marginalized and Vulnerable Populations, or PRISM, works with Gainesville-based domestic abuse support center Peaceful Paths to help people stay safe in the digital world. Kevin Butler, Ph.D., the director of PRISM and the Florida Institute for Cybersecurity Research at UF, has been researching issues related to security and privacy of technologies that affect survivors of intimate partner violence for years. He and his graduate students connected with Peaceful Paths in 2022, presenting their findings on cybersecurity and demonstrating how their research may help improve online safety for vulnerable populations. They developed a pilot study, a survey and interview protocols that are now helping those in need at the center. “[We aim to] develop principles of design that will allow for a robust technology design that really mitigates harms and improves benefits for all,” Butler said about PRISM. Educating abuse survivors has been a key component of the collaboration between UF and Peaceful Paths. For example, PRISM’s team has conducted research on the effects of stalkerware, also known as spyware, which is a type of software or app designed to be installed secretly on people’s devices to monitor their activities without their consent. Abusers may use this tool to track and harass victims, and stalkerware is regularly linked to domestic violence – a fact that is not widely known. "Even the first presentation [UF] gave enhanced our advocates' knowledge of security pieces, which helps them safety plan with survivors," said Peaceful Paths CEO Crystal Sorrow. “It actually increases the safety of everyone in the community we work with when we talk about red flags, digital dating abuse and healthy relationships.” While PRISM, which is supported by the National Science Foundation, is making an impact on the local community, its overall reach is much broader. PRISM was the first academic partner in the Coalition Against Stalkerware, which includes groups such as the National Network to End Domestic Violence, the Electronic Frontier Foundation, and law enforcement agencies throughout the United States and the world.

3 min

The AI Journal: UF and other research universities will fuel AI. Here’s why

In the global AI race between small and major competitors, established companies versus new players, and ubiquitous versus niche uses, the next giant leap isn’t about faster chips or improved algorithms. Where AI agents have already vacuumed up so much of the information on the internet, the next great uncertainty is where they’ll find the next trove of big data. The answer is not in Silicon Valley. It’s all across the nation at our major research universities, which are key to maintaining global competitiveness against China. To teach an AI system to “think” requires it to draw on massive amounts of data to build models. At a recent conference, Ilya Sutskever, the former chief scientist at OpenAI — the creator of ChatGPT — called data the “fossil fuel of AI.” Just as we will use up fossil fuels because they are not renewable, he said we are running out of new data to mine to keep fueling the gains in AI. However, so much of this thinking assumes AI was created by private Silicon Valley start-ups and the like. AI’s history is actually deeply rooted in U.S. universities dating back to the 1940s, when early research laid the groundwork for the algorithms and tools used today. While the computing power to use those tools was created only recently, the foundation was laid after World War II, not in the private sector but at our universities. Contrary to a “fossil fuel problem,” I believe AI has its own renewable fuel source: the data and expertise generated from our comprehensive public academic institutions. In fact, at the major AI conferences driving the field, most papers come from academic institutions. Our AI systems learn about our world only from the data we offer them. Current AI models like ChatGPT are scraping information from some academic journal articles in open-access repositories, but there are enormous troves of untapped academic data that could be used to make all these models more meaningful. A way past data scarcity is to develop new AI methods that leverage all of our knowledge in all of its forms. Our research institutions have the varied expertise in all aspects of our society to do this. Here’s just one example: We are creating the next generation of “digital twin” technology. Digital twins are virtual recreations of places or systems in our world. Using AI, we can develop digital twins that gather all of our data and knowledge about a system — whether a city, a community or even a person — in one place and allow users to ask “what if” questions. The University of Florida, for example, is building a digital twin for the city of Jacksonville, which contains the profile of each building, elevation data throughout the city and even septic tank locations. The twin also embeds detailed state-of-the-art waterflow models. In that virtual world, we can test all sorts of ideas for improving Jacksonville’s hurricane evacuation planning and water quality before implementing them in the actual city. As we continue to layer more data into the twin — real-time traffic information, scans of road conditions and more — our ability to deploy city resources will be more informed and driven by real-time actionable data and modeling. Using an AI system backed by this digital twin, city leaders could ask, “How would a new road in downtown Jacksonville impact evacuation times? How would the added road modify water runoff?” and so on. The possibilities for this emerging area of AI are endless. We could create digital twins of humans to layer human biology knowledge with personalized medical histories and imaging scans to understand how individuals may respond to particular treatments. Universities are also acquiring increasingly powerful supercomputers that are supercharging their innovations, such as the University of Florida’s HiPerGator, recently acquired from NVIDIA, which is being used for problems across all disciplines. Oregon State University and the University of Missouri, for example, are using their own access to supercomputers to advance marine science discoveries and improve elder care. In short, to see the next big leap in AI, don’t immediately look to Silicon Valley. Start scanning the horizon for those research universities that have the computing horsepower and the unique ability to continually renew the data and knowledge that will supercharge the next big thing in AI. Read more...

View all posts