When does boundary-condition uncertainty outweigh thermal and vegetation effects in street canyon flow? A global sensitivity analysis of input uncertainty
Abstract
Computational Fluid Dynamics (CFD) is increasingly used to resolve wind, heat, and pollution patterns in cities with high fidelity but high computational cost. Thermal effects and vegetation are often neglected despite being important drivers, yet their influence may be masked by variability from other uncertain inputs. This work determines how precisely model parameters and boundary conditions must be known for these effects to govern output uncertainty in the velocity, temperature, and concentration fields of a two-dimensional street canyon. A global Sobol analysis of 24 parameters is made tractable by a surrogate trained on Reynolds-Averaged Navier--Stokes (RANS) simulations, combining principal component analysis (PCA) with multilayer perceptrons (MLPs). Two ventilation regimes assess the variance due to thermal and vegetation parameters as uncertainty in all other inputs is progressively reduced. At typical uncertainty levels, turbulence closure constants and inflow turbulence profiles govern variability in all three fields in both regimes. Under weak ventilation, solar forcing becomes the main source of temperature variability once the remaining uncertainties are halved, and of concentration variance once they are reduced to a quarter (about ±11% for the dominant closure constant and ±12% for the emission rate). In contrast, vegetation contributes significantly at typical uncertainty levels. Under strong ventilation, however, the canopy never overtakes the closure constants, even when the dominant one is known to ±5%. Spatially, both effects peak at road level and along canyon walls, which influence outdoor exposure and indoor infiltration, suggesting that high-resolution exposure studies should account for them.
Related
- Threshold Sensitivity and Reference Uncertainty in Sentinel-1 Inundation Mapping: The July 2021 Mahad Flood
- Towards improved integration of hydrological uncertainty and hydraulic model sensitivity in flood hazard mapping
- Quantifying Uncertainty in Climate Sensitivity Metrics Using Large Ensemble Observational Datasets
- Evolution of the Antarctic Ice Sheet from 2000–2300 and beyond: model sensitivity and uncertainty analysis using MPAS-Albany Land Ice
- Fixed-ground multisensor monitoring resolves longitudinal vegetation condition and fuel-state structure in Southern California chaparral and oak scenes
BibTeX
@misc{catala2026when,
title = {{When does boundary-condition uncertainty outweigh thermal and vegetation effects in street canyon flow? A global sensitivity analysis of input uncertainty}},
author = {Albert Moreno Català and Joan Calafell Sandiumenge and Nikolaj T. Mücke and Jan Mateu Armengol},
howpublished = {arXiv},
year = {2026},
month = oct,
doi = {10.48550/arxiv.2610.32631},
eprint = {2610.32631},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2610.32631},
note = {CC BY-NC-ND 4.0},
}
RIS
TY - UNPB
TI - When does boundary-condition uncertainty outweigh thermal and vegetation effects in street canyon flow? A global sensitivity analysis of input uncertainty
AU - Albert Moreno Català
AU - Joan Calafell Sandiumenge
AU - Nikolaj T. Mücke
AU - Jan Mateu Armengol
PY - 2026
DA - 2026/10/23
PB - arXiv
DO - 10.48550/arxiv.2610.32631
UR - https://arxiv.org/abs/2610.32631
AB - Computational Fluid Dynamics (CFD) is increasingly used to resolve wind, heat, and pollution patterns in cities with high fidelity but high computational cost. Thermal effects and vegetation are often neglected despite being important drivers, yet their influence may be masked by variability from other uncertain inputs. This work determines how precisely model parameters and boundary conditions must be known for these effects to govern output uncertainty in the velocity, temperature, and concentration fields of a two-dimensional street canyon. A global Sobol analysis of 24 parameters is made tractable by a surrogate trained on Reynolds-Averaged Navier--Stokes (RANS) simulations, combining principal component analysis (PCA) with multilayer perceptrons (MLPs). Two ventilation regimes assess the variance due to thermal and vegetation parameters as uncertainty in all other inputs is progressively reduced. At typical uncertainty levels, turbulence closure constants and inflow turbulence profiles govern variability in all three fields in both regimes. Under weak ventilation, solar forcing becomes the main source of temperature variability once the remaining uncertainties are halved, and of concentration variance once they are reduced to a quarter (about ±11% for the dominant closure constant and ±12% for the emission rate). In contrast, vegetation contributes significantly at typical uncertainty levels. Under strong ventilation, however, the canopy never overtakes the closure constants, even when the dominant one is known to ±5%. Spatially, both effects peak at road level and along canyon walls, which influence outdoor exposure and indoor infiltration, suggesting that high-resolution exposure studies should account for them.
ER -