Comparing emulation methods for a high‐resolution storm surge model

Abstract

Realistic simulations of complex systems are fundamental for climate and environmental studies. Large computer systems are often not sufficient to run sophisticated computational models for large numbers of different input settings. Statistical surrogate models, or emulators, are key tools enabling fast exploration of the simulator input space. Gaussian processes have become standard for computer simulator emulation. However, they require careful implementation to scale appropriately, motivating alternative methods more recently introduced. We present a comparison study of surrogates of the Sea, Lake, and Overland Surges from Hurricanes (SLOSH) simulator-the simulator of choice for government agencies-using four emulation approaches: BASS; BART; SEPIA; and RobustGaSP. SEPIA and RobustGaSP use Gaussian processes, BASS implements adaptive splines, and BART is based on ensembles of regression trees. We describe the four models and compare them in terms of computation time and predictive metrics. These surrogates use proven and distinct methodologies, are available through accessible software, and quantify prediction uncertainty. Our data cover millions of response values. We find that SEPIA and RobustGaSP provide exceptional predictive power, but cannot scale to emulate experiments as large as the one considered in this paper as effectively as BASS and BART.

Spatio‐temporal downscaling emulator for regional climate models

“…Previous work on statistical emulators from Castruccio et al (2014), Overstall and Woods (2016), Mearns et al (1999), O'Hagan (2006) and Hernanz et al (2022) have been used on climate models' projections and on computer experiment output. Moreover, spatio‐temporal models have been used as statistical emulators for storm surge models (Hutchings et al, 2023), for modeling precipitation during tropical cyclones Kleiber et al (2022) and to calibrate flood hazard models (Roth et al, 2022). In this work, we describe how to use a spatio‐temporal statistical model with varying coefficients (VC), as a downscaling emulator for a RCM.…”