• charlesstanier

Abdi-Oskouei et al. (2020). WRF-Chem meteorology skill for air pollution over/near Lake Michigan

Updated: Feb 26

Link at JGR: https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2019JD031971?campaign=wolacceptedarticle


Led by Maryam Abdi-Oskouei ... our work is accepted and should be out soon in the Journal of Geophysical Research - Atmospheres. The title is:"Sensitivity of meteorological skill to selection of WRF-Chem physical parameterizations and impact on ozone prediction during the Lake Michigan Ozone Study (LMOS)"


Snapshots of clouds from the GOES weather satellite and from our model.

Full author list:

M. Abdi-Oskouei, G. Carmichael, M. Christiansen, G. Ferrada, B. Roozitalab, N. Sobhani, K. Wade, A. Czarnetzki, R. B. Pierce, T. Wagner, C. Stanier


Paper highlights:

  • WRF-Chem achieved good meteorological performance around Lake Michigan, with acceptable reproduction of clouds, but inconsistencies for lake breeze

  • Campaign specific meteorological measurements by aircraft and ground-based remote sensing provide a unique test of model skill

  • The 3-km High-Resolution Rapid Refresh (HRRR) model is a useful tool for initial and boundary conditions for the air quality community


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 (HRRR) meteorology gave the best performance with the mean bias of -0.5oC for temperature, -0.6oC 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.

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