Internal Variability

Distribution of the LES concentration predictions in the input parameter space

PPMLES – Perturbed-Parameter ensemble of MUST Large-Eddy Simulations

his dataset contains an ensemble of large-eddy simulations of atmospheric pollutant dispersion reproducing the MUST field experiment for varying wind meteorological conditons.

Reliability diagrams of the surrogate uncertainty estimates.

Uncertainty-aware surrogate modeling for urban air pollutant dispersion prediction

This paper tells the construction and validation of a surrogate model for atmospheric pollutant dispersion. We show that the selected approach is able to embed accurately the uncertainty at stakes.

Sensitivity of the mean concentration to the wind direction and to the friction velocity.

EnKF workshop 2024: Reduced-cost EnKF for parameter estimation of microscale atmospheric pollutant dispersion models

In this presentation, we implement and validate a reduced-cost EnKF that estimate meteorological forcing parameters, such as wind direction, for large-eddy simulations of microscale pollutant dispersion.

Atmospheric microscale internal variability effect on pollutant concentration.

Assessing the Internal Variability of Large-Eddy Simulations for Microscale Pollutant Dispersion Prediction in an Idealized Urban Environment

This paper provides a methodology to assess the effect of atmospheric microscale internal variability on time statistics. It is then applied to the validation of a LES model of the MUST field experiment.