Emerging threatsBetter Greenland, Antarctica sheet modeling helps predict sea-level rise

The Greenland and Antarctic ice sheets will make a dominant contribution to twenty-first century sea-level rise if current climate trends continue. However, predicting the expected loss of ice sheet mass is difficult due to the complexity of modeling ice sheet behavior.

Better to understand this loss, a team of Sandia National Laboratories researchers has been improving the reliability and efficiency of computational models that describe ice sheet behavior and dynamics. The team includes researchers Irina Demeshko, Mike Eldred, John Jakeman, Mauro Perego, Andy Salinger, Irina Tezaur, and Ray Tuminaro.

Sandia Lab reports that this research is part of a five-year project called Predicting Ice Sheet and Climate Evolution at Extreme Scales (PISCEES), funded by the U.S. Department of Energy’s (DOE) Scientific Discovery through Advanced Computing (SciDAC) program. PISCEES is a multi-lab, multi-university endeavor that includes researchers from Sandia, Los Alamos, Lawrence Berkeley, and Oak Ridge national laboratories, the Massachusetts Institute of Technology, Florida State University, the University of Bristol, the University of Texas Austin, the University of South Carolina, and New York University.

Sandia’s biggest contribution to PISCEES has been an analysis tool, a land-ice solver called Albany/FELIX (Finite Elements for Land Ice eXperiments). The tool is based on equations that simulate ice flow over the Greenland and Antarctic ice sheets and is being coupled to Earth models through the Accelerated Climate for Energy (ACME) project.

“One of the goals of PISCEES is to create a land-ice solver that is scalable, fast and robust on continental scales,” said computational scientist Irina Tezaur, a lead developer of Albany/FELIX. Not only did the new solver need to be reliable and efficient, but it was critical that the team develop a solver equipped with next-generation and advanced analysis capabilities.

Tezaur said the team next needs to run the solver on new and emerging computers. They also need to be able to calibrate models and quantify uncertainties in expected sea-level rise.

“The data we get from climate scientists are usually measurements from the top surface of the ice,” she said. “To initialize an ice sheet simulation, we need information about what is happening inside and at the bottom of the ice. Determining interior and bedrock ice properties is what we call model calibration, and requires the solution of an inverse problem. A lot of our work has been in developing and implementing optimization algorithms that are able to solve these inverse problems robustly and efficiently.”