Exploration of the impact of nearby sources on urban atmospheric inversions using large eddy simulation

Details

Location
North America, Central America and the Caribbean
Objectives
Objective 3
Year
2017

Description

The Indianapolis Flux Experiment (INFLUX) aims to quantify and improve the effectiveness of inferring greenhouse gas (GHG) source strengths from downstream concentration measurements in urban environments. Mesoscale models such as the Weather Research and Forecasting (WRF) model can provide realistic depictions of planetary boundary layer (PBL) structure and flow fields at horizontal grid lengths (Δx) down to a few km. Nevertheless, a number of potential sources of error exist in the use of mesoscale models for urban inversions, including accurate representation of the dispersion of GHGs by turbulence close to a point source.Here we evaluate the predictive skill of a 1-km chemistry-adapted WRF (WRF-Chem) simulation of daytime CO2 transport from an Indianapolis power plant for a single INFLUX case (28 September 2013). We compare the simulated plume release on domains at different resolutions, as well as on a domain run in large eddy simulation (LES) mode, enabling us to study the impact of both spatial resolution and parameterization of PBL turbulence on the transport of CO2. Sensitivity tests demonstrate that much of the difference between 1-km mesoscale and 111-m LES plumes, including substantially lower maximum concentrations in the mesoscale simulation, is due to the different horizontal resolutions. However, resolution is insufficient to account for the slower rate of ascent of the LES plume with downwind distance, which results in much higher surface concentrations for the LES plume in the near-field but a near absence of tracer aloft. Physics sensitivity experiments and theoretical analytical models demonstrate that this effect is an inherent problem with the parameterization of turbulent transport in the mesoscale PBL scheme. A simple transformation is proposed that may be applied to mesoscale model concentration footprints to correct for their near-field biases. Implications for longer-term source inversion are discussed.