Coastal Glacier Retreat Is Linked to Climate Change – Is It Up With That?
UNIVERSITY OF TEXAS IN AUSTIN
Many of the world’s coastal glaciers are melting faster than ever before, but exactly what is causing the large-scale retreat is difficult to determine because of natural fluctuations in the environment around the glaciers. Now, researchers at the University of Texas Institute of Geophysics (UTIG) and Georgia Tech have developed a method that they say has decoded why coastal glaciers are retreating, and in turn, how much of it could be due to human-caused climate change. Determining the role humans play in coastal glaciers – which melt directly into the sea – could pave the way for better predictions of sea level rise.
So far, scientists have tested this method only in computer models using simplified glaciers. They found that even modest global warming caused most glaciers to melt or retreat.
The next step, the researchers say, is for scientists to simulate the coastal glaciers of a real ice sheet that, like Greenland, contains enough ice to raise sea levels by about 22 feet (7 meters). That would reveal whether they’re retreating due to climate change and help predict when big ice loss might happen next.
“The method we are proposing is a roadmap towards making confident statements about the role of human [in glacial retreats],” said glaciologist John Christian, a postdoctoral researcher at the University of Texas at Austin and Georgia Tech. “Those statements can then be communicated to the public and policymakers and help them make decisions.”
Published July 13 in the magazine Cryosphere, this method is unique because it treats the rapid retreat of glaciers as an individual probabilistic event, like a wildfire or tropical storm. For a major retreat to occur, a glacier must retreat past its “stabilization threshold,” usually a steep rise in the underlying bed that helps slow its flow. The probability of that happening varies depending on the local climate, and ocean conditions change with natural fluctuations and anthropogenic warming. Even small variations can cause large changes in glacier behavior, making them difficult to predict and leading to cases where glaciers are found retreating right next to those that aren’t.
That’s why the final report of the Intergovernmental Panel on Climate Change found there was still so much uncertainty about coastal glaciers, said co-author and UTIG glaciologist Ginny Catania. to say whether their retreat is due to anthropogenic climate change or natural climate variability.
New research shows how to overcome uncertainty by providing a methodology that explains differences between glaciers and natural climate variability, while examining the impact of background trends such as warming up globally. According to Catania, this study means they can now attribute the mass retreat of coastal glaciers to climate change and not just natural variability.
“And that was the first time someone did it,” she said.
To test the methodology, the team ran thousands of simulations over the past 150 years with and without global warming. The simulations show that even modest warming significantly increases the probability of glacier retreat across the entire ice sheet.
When the scientists ran the models without human-caused climate change, they found it was unlikely that many glaciers would begin to recede within years afterward.
In contrast, since 2000, nearly all (200) of Greenland’s 225 coastal glaciers have been in various states of retreat.
“This study provides us with a toolbox to determine the role of humans in the loss of ice from Greenland and Antarctica, confidently saying it’s not just a coincidence,” said Georgia glaciologist. Tech and co-author Alex Robel said.
The study of coastal glaciers builds on previous work to understand the human role in the retreat of mountain glaciers – which is now well established. The latest research was funded by UTIG and the National Science Foundation. UTIG is a research branch of UT Austin’s Jackson School of Geosciences.
JOURNEYS
Cryosphere
DOI
RESEARCH METHODS
Simulation / Computational Modeling
ARTICLE TITLE
https://doi.org/10.5194/tc-16-2725-2022
ARTICLE PUBLICATION DATE
July 13, 2022