A2058
Title: A multi-fidelity tensor emulator for spatiotemporal outputs: Emulation of Arctic sea ice dynamics
Authors: Yawen Guan - Colorado State University (United States) [presenting]
Abstract: Numerical models are widely used to simulate the Earth System, but they are computationally expensive and often depend on many uncertain input parameters. Their effective use requires calibration and uncertainty quantification, which typically involve running the Model across many input configurations and therefore incur substantial computational cost. Statistical emulation provides a practical alternative for efficiently exploring Model behavior. The Arctic sea ice component of the Energy Exascale Earth System Model (MPAS-Seaice) generates large spatiotemporal outputs at multiple spatial resolutions, with high-fidelity (HF) simulations being more accurate but computationally more expensive than low-fidelity (LF) simulations. Multi-fidelity (MF) emulation integrates information across resolutions to construct efficient and accurate surrogate models. A MF emulator is developed that combines tensor decomposition for dimensionality reduction, Gaussian process priors for flexible function approximation, and an additive discrepancy Model to capture systematic differences between LF and HF data. The proposed framework enables scalable emulation while maintaining accurate predictions and well-calibrated uncertainty for complex spatiotemporal fields, and consistently achieves lower prediction error and reduced uncertainty than LF-only and HF-only models in both simulation studies and MPAS-Seaice analysis.
