Sensitivity of WRF Surface Fluxes to Boundary Layer and Land Surface Parameterizations During Persistent Cold Air Pools in the Western US

Stable atmospheric boundary layers are associated with a decrease in boundary layer height and decreased turbulent mixing which causes an increase in air pollution concentrations. This phenomena is prevalent throughout the intermountain west where cold air pools (CAPs) exist throughout the day and can last for weeks. During persistent CAP events, particulate matter concentrations in the atmosphere accumulate and reach levels that are harmful to human health. While numerical weather prediction models can capture the synoptic weather patterns associated with CAP formation and destruction, the models have difficulty capturing the small scale turbulent mixing processes. Therefore having an impact on predictions of heat, moisture, and momentum exchanges from the surface to the atmosphere and the turbulent mixing of pollutants in the atmospheric boundary layer. The surface atmosphere exchange is over-estimated during the CAP event, which leads to an under-prediction in pollutant concentrations. This is because the empirical data used to develop the turbulence parameterizations in numerical weather prediction models are based on experimental surface flux data collected in flat, idealized terrain.

This paper will present results from a Weather Research and Forecasting (WRF) sensitivity analysis where simulated surface fluxes are compared to observations collected in the Salt Lake Valley, Utah. The observations of turbulent fluxes come from a previously published study [Holmes et al. 2015], which found a correlation between decreased turbulent mixing and increased pollutant concentrations during wintertime CAPs. Hourly momentum, latent heat, and sensible heat fluxes from the WRF model are evaluated using the observations. Different land surface models (LSM) and planetary boundary layer (PBL) parameterizations impact the WRF surface flux results, therefore a sensitivity analysis is needed to select the best performing PBL and LSM configuration. This analysis is done with the observations to assess the uncertainty in surface fluxes from WRF using different PBL and LSM parameterizations. Results using five PBL schemes and two LSM in WRF will be presented. Future work will use the best performing WRF results in an air quality model to evaluate the simulated pollutant concentrations during wintertime CAP events.