surrogate-modeling

Efficient Probabilistic Prediction and Uncertainty Quantification of Tropical Cyclone–Driven Storm Tides and Inundation

This study proposes and assesses a methodology to obtain high-quality probabilistic predictions and uncertainty information of near-landfall tropical cyclone–driven (TC-driven) storm tide and inundation with limited time and resources. Forecasts of …

Using a Surrogate-Assisted Bayesian Framework to Calibrate the Runoff-Generation Scheme in the Energy Exascale Earth System Model (E3SM) v1

Runoff is a critical component of the terrestrial water cycle, and Earth system models (ESMs) are essential tools to study its spatiotemporal variability. Runoff schemes in ESMs typically include many parameters so that model calibration is necessary …

Hit Twice by the Curse of Dimensionality; Spatio-Temporal Land Model Calibration using Karhunen-Loeve and Sparse Polynomial Chaos Expansions

Poster

surrogate-modeling

Efficient Probabilistic Prediction and Uncertainty Quantification of Tropical Cyclone–Driven Storm Tides and Inundation

Using a Surrogate-Assisted Bayesian Framework to Calibrate the Runoff-Generation Scheme in the Energy Exascale Earth System Model (E3SM) v1

Hit Twice by the Curse of Dimensionality; Spatio-Temporal Land Model Calibration using Karhunen-Loeve and Sparse Polynomial Chaos Expansions

Quantifying and Reducing Uncertainty in the E3SM Land Model using Surrogate Modeling

Dimensionality Reduction and Physics-Informed Neural Networks for Climate Land Models

Breaking Down the Computational Barriers to Real-Time Urban Flood Forecasting

Dimensionality Reduction and Physics-Informed Recurrent Neural Networks for Climate Land Models

Physics-informed Machine Learning for Uncertainty Quantification in E3SM Land Model

Physics-informed Machine Learning for Uncertainty Quantification in Land Models

A Novel Modeling Framework to Secure Efficiency and Accuracy in Real-Time Ensemble Flood Forecasting