A Statistical Evaluation of WRF-LES Trace Gas Dispersion Using Project Prairie Grass Measurements

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Authors

Alex Rybchuk , Caroline B. Alden, Julie K. Lundquist, Gregory B. Rieker

Abstract

In recent years, new measurement systems have been deployed to monitor and quantify methane emissions from the natural gas sector. Large-eddy simulation (LES) has complemented measurement campaigns by serving as a controlled environment in which to study plume dynamics and sampling strategies. However, with few comparisons to controlled-release experiments, the accuracy of LES for modeling natural gas emissions is poorly characterized. In this paper, we evaluate LES from the Weather Research and Forecasting (WRF) model against measurements from the Project Prairie Grass campaign, surface layer similarity theory, and the Gaussian Plume Model. Using WRF-LES, we simulate continuous emissions from an ensemble of 30 near-surface trace gas sources in two stability regimes: strong and weak convection. We examine the impact of grid resolutions ranging from 6.25 m to 52 m in the horizontal dimension on model performance. We evaluate performance in a statistical framework, calculating fractional bias and conducting Welchs t-tests. WRF-LES accurately simulates observed surface concentrations at 100 m and beyond under strong convection; the magnitude of factional bias is less than 30% for the moderate- and fine-resolution simulations. However, in weakly convective conditions with strong winds, WRF-LES substantially overpredicts concentrations – the magnitude of fractional bias often exceeds 30%, and all but one t-test fails. Despite the good performance of dispersion in the strongly convective atmosphere, we find that both the strongly and weakly convective boundary layers disagree with empirical wind and temperature Monin-Obukhov similarity theory profiles that are often used to evaluate LES within the atmospheric surface layer.

DOI

https://doi.org/10.31223/osf.io/uevsx

Subjects

Atmospheric Sciences, Oceanography and Atmospheric Sciences and Meteorology, Physical Sciences and Mathematics

Keywords

Dispersion, Large eddy simulation, Natural gas, WRF

Dates

Published: 2020-08-17 11:03

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License

CC BY Attribution 4.0 International

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