Mathematical models are crucial for understanding how and why glaciers move and change over time. Because satellites like NASA’s MODIS have collected extensive measurements of the changing West Antarctic Ice Sheet (including PIG) over decades, scientists can apply well-understood mathematical equations describing the physics of glaciers to investigate the causes and likely outcome of these changes.
“We started our models where Pine Island Glacier was about 10 years ago; then we adjusted ocean conditions in the region so that the grounding line retreat in our models reflects satellite measurements since then,” says Stephen Cornford of the University of Bristol, a co-author of the paper. “Then we computed grounding line retreat 50 years into the future under different scenarios.”
The team relied on three different models to do this work: Elmer/Ice, BISICLES and Úa. According to Cornford, Elmer/Ice—an open-source finite element software package for modeling the flow of ice sheets and glaciers —provides the most accurate and physically complete model. He notes that this model allows researchers to capture small-scale, non-hydrostatic features like ice bridges, but is also extremely computationally expensive to run. Úa uses a simpler model designed to capture the essential physics of ice flow, which makes it computationally less expensive, while the BISICLES model is somewhat between the other two in physical fidelity and computational cost.
All three models allow researchers to consider regions of interest—like the retreating edge of an ice-sheet—at sub-kilometer spatial resolution, while employing computationally cheaper coarser resolution in areas that don’t need such fine detail. This allows an accurate, high-resolution view of phenomena like ice streams and grounding-line migration, at a relatively low computational cost.
According to Cornford, BISICLES is unique in that it can readily modify its computational meshes as the ice sheet evolves, permitting calculations further into the future. Berkeley Lab mathematicians have been leading developers of this technique, known as adaptive mesh refinement.
“BISICLES is much faster to run than Elmer/Ice, largely because it employs a slightly less accurate but computationally far simpler description of the ice physics, but partly because of the high performance methods it inherits from Berkeley Lab’s Chombo toolkit,” says Cornford, who co-developed the code with Dan Martin from Berkeley Lab. “That meant that we were able to run a number of additional experiments. These additional runs gave us supplementary evidence to support our argument.”
"In spite of the simplified mathematical formulation, the BISICLES calculations compare very favorably with results from the more expensive Elmer/Ice code for the physical examples we are interested in," say Martin, a Berkeley Lab computational scientist. “It’s exciting to see BISICLES being used in this way and contributing to these kinds of results, this is a validation that the code is a useful tool for understanding ice sheet behavior.”
In addition to Cornford and Gudmundsson, other co-authors on the paper include L. Favier, G. Durand, O. Gagliardini, F. Gillet-Chaulet, T. Zwinger, A.J. Payne, and A.M. Le Brocq.
BISICLES was developed with funding from Advanced Scientific Computing Research (ASCR) in the Department of Energy’s Office of Science under the Scientific Discovery through Advanced Computing (SciDAC) Program and the UK Natural Environment Research Council. Computational scientists at Berkeley Lab (Dan Martin, Esmond Ng, and Sam Williams) formed a collaboration with climate scientists at the Los Alamos National Laboratory (William Lipscomb and Stephen Price), which led to the Predicting Ice Sheet and Climate Evolution at Extreme Scales (PISCEES) project, a SciDAC applications partnership.
(http://crd.lbl.gov/news)
Published on Feb 28, 2014, This BISICLES simulation shows the collapse of Antarctica's Pine Island Glacier (in the top left of this simulation) over 200 years. At around 2230, Thwaites Glacier (center-right) begins to collapse as well. Colors indicate ice flow speed, varying from no flow (blue) at the edges up to 4 km per year (red) where Pine Island and Thwaites Glaciers meet the ocean. High resolution is concentrated around and moves with the grounding line (in cyan) as it travels across much of the region.
Mathematical models are crucial for understanding how and why glaciers move and change over time. Because satellites like NASA’s MODIS have collected extensive measurements of the changing West Antarctic Ice Sheet (including PIG) over decades, scientists can apply well-understood mathematical equations describing the physics of glaciers to investigate the causes and likely outcome of these changes.
“We started our models where Pine Island Glacier was about 10 years ago; then we adjusted ocean conditions in the region so that the grounding line retreat in our models reflects satellite measurements since then,” says Stephen Cornford of the University of Bristol, a co-author of the paper. “Then we computed grounding line retreat 50 years into the future under different scenarios.”
The team relied on three different models to do this work: Elmer/Ice, BISICLES and Úa. According to Cornford, Elmer/Ice—an open-source finite element software package for modeling the flow of ice sheets and glaciers —provides the most accurate and physically complete model. He notes that this model allows researchers to capture small-scale, non-hydrostatic features like ice bridges, but is also extremely computationally expensive to run. Úa uses a simpler model designed to capture the essential physics of ice flow, which makes it computationally less expensive, while the BISICLES model is somewhat between the other two in physical fidelity and computational cost.
All three models allow researchers to consider regions of interest—like the retreating edge of an ice-sheet—at sub-kilometer spatial resolution, while employing computationally cheaper coarser resolution in areas that don’t need such fine detail. This allows an accurate, high-resolution view of phenomena like ice streams and grounding-line migration, at a relatively low computational cost.
According to Cornford, BISICLES is unique in that it can readily modify its computational meshes as the ice sheet evolves, permitting calculations further into the future. Berkeley Lab mathematicians have been leading developers of this technique, known as adaptive mesh refinement.
“BISICLES is much faster to run than Elmer/Ice, largely because it employs a slightly less accurate but computationally far simpler description of the ice physics, but partly because of the high performance methods it inherits from Berkeley Lab’s Chombo toolkit,” says Cornford, who co-developed the code with Dan Martin from Berkeley Lab. “That meant that we were able to run a number of additional experiments. These additional runs gave us supplementary evidence to support our argument.”
"In spite of the simplified mathematical formulation, the BISICLES calculations compare very favorably with results from the more expensive Elmer/Ice code for the physical examples we are interested in," say Martin, a Berkeley Lab computational scientist. “It’s exciting to see BISICLES being used in this way and contributing to these kinds of results, this is a validation that the code is a useful tool for understanding ice sheet behavior.”
In addition to Cornford and Gudmundsson, other co-authors on the paper include L. Favier, G. Durand, O. Gagliardini, F. Gillet-Chaulet, T. Zwinger, A.J. Payne, and A.M. Le Brocq.
BISICLES was developed with funding from Advanced Scientific Computing Research (ASCR) in the Department of Energy’s Office of Science under the Scientific Discovery through Advanced Computing (SciDAC) Program and the UK Natural Environment Research Council. Computational scientists at Berkeley Lab (Dan Martin, Esmond Ng, and Sam Williams) formed a collaboration with climate scientists at the Los Alamos National Laboratory (William Lipscomb and Stephen Price), which led to the Predicting Ice Sheet and Climate Evolution at Extreme Scales (PISCEES) project, a SciDAC applications partnership.
(http://crd.lbl.gov/news)
http://www.youtube.com/watch?v=lTj_rUsL-a0list