Mathematician uses DOE Early Career Research Award to capture more real-world data

Sandia researcher Pete Bosler aims to improve the fidelity by which complex computer simulations can be guided by very fine examinations of real-world data.

His proposal’s information-packed title, “High performance adaptive multiscale simulation with data-driven scale-selective subgrid parameterizations,” refers to multiscale simulations that, integrated, could include individual raindrops, supercell thunderstorms and the entire global atmosphere, guided by data currently thought too fine to be used, that is, too small to be seen on a data grid, or in other words, currently subgrid.

The proposal earned Pete a 2022 DOE Early Career Research Award.

“Peter’s research plan lays out a highly innovative approach to achieving more accuracy from our simulations of complex domains like climate and plasmas,” Sandia manager Andy Salinger said. “As our computing resources for these mission application areas increase, there is a shift in the boundary between those phenomena we can resolve with our highest fidelity models. Those too fine-scaled need to be represented with heuristic models derived from experience. Peter will develop new algorithms that will intelligently choose which heuristic models are most appropriate to capture the unresolved processes.”

Read the full Sandia LabNews story.