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.
Large-Eddy Simulation
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.
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.
EGU2024: Surrogate-based data assimilation for microscale atmospheric pollutant dispersion
Poster presentation of a data assimilation workflow for microscale pollutant dispersion. The use of a surrogate model enables real-time data assimilation and large ensemble size while also providing an estimation of the uncertainties involved.
[PhD Thesis] Assessing and reducing uncertainty in large-eddy simulation for microscale atmospheric dispersion
Poster presentation of a data assimilation workflow for microscale pollutant dispersion. The use of a surrogate model enables real-time data assimilation and large ensemble size while also providing an estimation of the uncertainties involved.
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.
HARMO21: Sensitivity analysis of microscale pollutant dispersion large-eddy simulations for observation network design
In this presentation, we investigate the sensitivity of microscale dispersion large-eddy simulations to inflow boundary conditions, such as wind direction. This analysis constitutes a first step in the construction of a data assimilation workflow.