earth-system-models

Reduced-Dimensional Neural Network Surrogate Construction and Calibration of the E3SM Land Model

Talk

A Lake Biogeochemistry Model for Global Methane Emissions: Model Development, Site-Level Validation, and Global Applicability

Abstract Lakes are important sentinels of climate change and may contribute over 30% of natural methane (CH4) emissions; however, no earth system model (ESM) has represented lake CH4 dynamics. To fill this gap, we refined a process-based lake …

Ground Heat Flux Reconstruction Using Bayesian Uncertainty Quantification Machinery and Surrogate Modeling

Abstract Ground heat flux (G0) is a key component of the land-surface energy balance of high-latitude regions. Despite its crucial role in controlling permafrost degradation due to global warming, G0 is sparsely measured and not well represented in …

Reduced-Dimensional Neural Network Surrogate Construction and Calibration of the E3SM Land Model

Talk

Uncertainty Quantification and Parameter Calibration for High-Dimensional Output Fields of Earth System Models

Poster

Modeling Perennial Bioenergy Crops in the E3SM Land Model (ELMv2)

Abstract Perennial bioenergy crops are increasingly important for the production of ethanol and other renewable fuels, and as part of an agricultural system that alters the climate through its impact on biogeophysical and biogeochemical properties 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

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

Talk

Earth System Model Improvement Pipeline via Uncertainty Attribution and Active Learning

Primary focal area: 2 (Predictive Modeling via AI): We develop methods to formally quantify uncertainties in Earth System models for the land-atmosphere coupled system. Science Challenge: Earth system models still have significant biases in …