Sensitivity of Meteorological Skill to Selection of WRF‐Chem Physical Parameterizations and Impact on Ozone Prediction During the Lake Michigan Ozone Study (LMOS)

Abstract Ozone concentrations in excess of health‐based standards occur along the coastline of Lake Michigan. A complex pattern of ozone precursor emissions interfaces with a complex meteorological environment, presenting a challenge for air quality management and simulation. Precursors are transported into a shallow, stable boundary layer over the lake. This is followed by ozone formation and transport back onshore through a combination of synoptic and lake breeze winds. In this study, we use measurements during the Lake Michigan Ozone Study 2017 (LMOS) to quantitatively evaluate the Weather Research and Forecasting with Chemistry (WRF‐Chem) model at 4 km horizontal resolution for key features of high ozone episodes over Southern Lake Michigan, with a focus on meteorological performance. WRF‐Chem showed good performance and successful reproduction of meteorological fields and clouds. Lake breeze model skill was inconsistent, with both good and poor performance depending on site and day. The combination of Noah land surface model and High‐Resolution Rapid Refresh meteorology gave the best performance with the mean bias of −0.5 °C for temperature, −0.6 °C for dewpoint temperature, and −0.3 m/s for wind speed along the western coast of Lake Michigan during the daytime. For ozone, WRF‐Chem was biased low (−4.4 ppb mean bias for daytime ozone) and underestimated hourly peak ozone. In some cases, ozone bias can be attributed to transport and lake breeze errors. Average ozone concentration showed minor (<2 ppb) sensitivity to changes to meteorology initial and boundary conditions or the land surface model.