Improving the Quasi-Biennial Oscillation (QBO) through Surrogate - Accelerated Parameter Optimization and Vertical Grid Modification
This project aims to improve the
Energy Exascale Earth System Model (E3SM),
a model development and simulation project that investigates energy science using code optimized for supercomputers. We use
machine learning
techniques in our research to improve model biases in E3SM due to the quasi-biennial oscillation (QBO), a regular variation of the winds high above the equator and cause changes in the tropical stratosphere.
| Keywords | convection, convective parameterization, E3SM, mesoscale convection, MMF, model bias, modeling, parameter optimization, quasi-biennial oscillation (QBO), structure and composition, surrogate models, tropical convection |
|---|---|
| TYPE | Project |
Principal Investigator (PI)
Jim Benedict
Lead Institution
Other Collaborators
National Center for Atmospheric Research
Equatorial zonal mean zonal wind for (a) observations, (b) E3SM with default vertical grid, and (c) E3SM with a smoothed vertical grid. (Image credit: Los Alamos National Laboratory)