Limit global warming to 1.5°C and halve the land ice contribution to sea level this century
Berkeley Lab-developed BISICLES contributes to an international study
May 5, 2021
By Linda Vu
Glaciers and ice sheets currently contribute to half of the global sea level rise. Now an international collaboration of 84 scientists, including two from Lawrence Berkeley National Laboratory (Berkeley Lab), predict that sea level rise from the melting of ice could be halved this century—from today to 2100—if we meet the Paris Agreement target of limiting global warming to 1.5°C. A paper describing this work appears today in Nature.
Led by Tamsin Edwards of King's College London, the study combined a large number of computer models, including some carried out using the Berkeley Lab-developed BISICLES model, with statistical techniques to explore the land ice contribution to sea-level in the 21st century arising from the world’s glaciers and the Greenland and Antarctic ice sheets. These predictions will also inform the Intergovernmental Panel on Climate Change’s (IPCC) Sixth Assessment report, which will be published later this year.
“Ahead of COP26 (26th UN Climate Change Conference) this November, many nations are updating their pledges to reduce greenhouse gas emissions under the Paris Agreement. Global sea level will continue to rise, even if we halt all emissions now, but our research suggests that we could limit the damage: if pledges were far more ambitious, central predictions for the sea-level rise from melting ice would be reduced from 25 cm to 13 cm in 2100, with a 95% chance of being less than 28 cm rather than the current upper end of 49 cm. This would mean a less severe increase in coastal flooding,” said Edwards.
For this study, Edwards and her collaborators used a larger and more sophisticated set of climate and ice models than ever before, combining nearly 900 simulations from 38 international groups to improve their understanding of uncertainty about the future. Their research predicts that if we limit global warming to 1.5°C, Greenland ice sheet losses would reduce by 70% and glacier losses by half, compared with current emissions pledges. For Antarctica, the predictions are the same for different emissions scenarios because it is currently unclear whether snow falling in the cold interior of the ice sheet will offset melting at the coasts. However, under a “pessimistic” storyline, with much more melting than snowfall, Antarctic ice losses could be five times larger.
“Antarctica is the ‘wildcard of sea level rise: difficult to predict and critical for the upper end of projections,” said Edwards. “In a pessimistic storyline, where Antarctica is very sensitive to climate change, we found there is a 5% chance of the land ice contribution to sea-level rise exceeding 56 cm in 2100 even if we limit warming to 1.5°C. Coastal flood management must therefore be flexible enough to account for a wide range of possible sea level rise until new observations and modeling can improve the clarity of Antarctica’s future.”
“This is the first time that it’s been possible to do a community-wide set of experiments that represent realistic projections of what might happen, based on realistic climate scenarios, and have enough models to make it statistically valid,” said Dan Martin, a Berkeley Lab computational scientist and co-author on the paper.
He adds that “when the last IPCC report was published almost 10 years ago, performing fully-resolved Antarctic ice sheet simulations with the confidence that we have right now was only something we dreamed about. We’ve come this far largely through a community-wide effort, like the U.S. Department of Energy’s investment in better algorithms, better math, better codes, better implementation of parallel codes, and more access to supercomputers like the National Energy Research Scientific Computing Center’s (NERSC’s) Cori.”
Martin notes that one of the codes contributing to more realistic projections of land ice contributions to global sea level rise is the BISICLES ice sheet model, which he co-developed over the last decade with collaborators at the University of Bristol and Swansea University. For this study, Martin and his team used BISICLES to model the Antarctic land ice contribution to global sea level rise under various climate scenarios, while collaborators at the University of Bristol used the code to explore the land ice contributions from Greenland. Martin ran his simulations on the Cori system, which is located at Berkeley Lab.
Modeling ice sheets requires supercomputers — it’s not something you can do on a laptop computer — and BISICLES allows researchers to perform these massive simulations in a computationally efficient way. The key to BISICLES’s ability to more accurately simulate the evolution of ice sheets in Antarctica and Greenland is adaptive mesh refinement, which dynamically increases the computational resolution specifically at locations where the ice sheets are changing most rapidly. This allows researchers to capture the physics in the regions that control the overall evolution of an ice sheet, like fast-moving ice streams, retreating edges, and grounding lines (the point at which ice sheets transition from grounded ice to floating ice shelves) — features that can migrate over continental scales. Meanwhile, regions that aren’t changing quickly are modeled at lower resolution. Before tools like BISICLES, full-continent simulations were generally limited to low-resolution models because of computational restrictions.
“What we’ve learned in a decade of modeling the Antarctic ice sheet is that you need very fine resolution at places like the grounding lines to get this right; if you don’t have sufficient resolution at the grounding lines in Antarctica you can often get the wrong answer,” said Martin.
DOE’s Scientific Discovery through Advanced Computing (SciDAC) program, this study includes 5 other DOE co-authors, and also incorporated land ice simulations of Antarctica and Greenland performed with the DOE-funded, Los Alamos- and Sandia-developed MPAS-Albany Land Ice code.
“Two years out of undergrad, I never imagined that I would be contributing to such a large intercomparison project that will inform the IPCC report. It’s important work and will have a great impact on science and our future,” said Courtney Shafer, a numerical modeling post-baccalaureate fellow in Berkeley Lab’s Computational Research Division (CRD) and co-author on the paper.
This work inspired Shafer to pursue a Ph.D. in Geology with an emphasis in computational science and glaciology. A first-generation college student and recently named DOE Computational Science Graduate (CSGF) Fellow, Shafer will begin her graduate studies at the University at Buffalo this fall.
This article utilizes materials from a King's College press release.
About NERSC and Berkeley Lab
The National Energy Research Scientific Computing Center (NERSC) is a U.S. Department of Energy Office of Science User Facility that serves as the primary high-performance computing center for scientific research sponsored by the Office of Science. Located at Lawrence Berkeley National Laboratory, the NERSC Center serves almost 10,000 scientists at national laboratories and universities researching a wide range of problems in climate, fusion energy, materials science, physics, chemistry, computational biology, and other disciplines. Berkeley Lab is a DOE national laboratory located in Berkeley, California. It conducts unclassified scientific research and is managed by the University of California for the U.S. Department of Energy. »Learn more about computing sciences at Berkeley Lab.