Ozone distributions over southern Lake Michigan: comparisons between ferry-based observations, shoreline-based DOAS observations and model forecasts

Abstract

Abstract. Air quality forecast models typically predict large summertime ozone abundances over water relative to land in the Great Lakes region. While each state bordering Lake Michigan has dedicated monitoring systems, offshore measurements have been sparse, mainly executed through specific short-term campaigns. This study examines ozone abundances over Lake Michigan as measured on the Lake Express ferry, by shoreline differential optical absorption spectroscopy (DOAS) observations in southeastern Wisconsin and as predicted by the Community Multiscale Air Quality (CMAQ) model. From 2008 to 2009 measurements of O 3 , SO 2 , NO 2 and formaldehyde were made in the summertime by DOAS at a shoreline site in Kenosha, WI. From 2008 to 2010 measurements of ambient ozone were conducted on the Lake Express, a high-speed ferry that travels between Milwaukee, WI, and Muskegon, MI, up to six times daily from spring to fall. Ferry ozone observations over Lake Michigan were an average of 3.8 ppb higher than those measured at shoreline in Kenosha, with little dependence on position of the ferry or temperature and with greatest differences during evening and night. Concurrent 1-48 h forecasts from the CMAQ model in the upper Midwestern region surrounding Lake Michigan were compared to ferry ozone measurements, shoreline DOAS measurements and Environmental Protection Agency (EPA) station measurements. The bias of the model O 3 forecast was computed and evaluated with respect to ferry-based measurements. Trends in the bias with respect to location and time of day were explored showing nonuniformity in model bias over the lake. Model ozone bias was consistently high over the lake in comparison to landbased measurements, with highest biases for 25-48 h after initialization.

Quantifying errors in surface ozone predictions associated with clouds over the CONUS: a WRF-Chem modeling study using satellite cloud retrievals

“…Therefore, an O 3 action alert would have been issued if the CNTR simulation results were used, which would result in a false alarm. The example shown here emphasizes the important roles of clouds in the Great Lakes region where large O 3 biases have been reported previously in air quality forecasts (e.g., Cleary et al, 2015). The correction of clouds both over the lakes and in the upstream regions (mostly large cities located to the west-southwest of the lakes) significantly reduces the O 3 bias.…”

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

“…Skill for air pollution relevant meteorology in the southern Great Lakes has been extensively studied (see McNider et al, , Sills et al, , and Odman et al, citations therein). Assessments of photochemical grid model (PGM) skill for ozone over the southern Great Lakes are more limited and often done as new measurements or model updates emerge (e.g., Cleary et al, ; Fast & Heilman, ; Makar et al, ; Qin et al, ). Fast and Heilman () simulated summer 1999 at 12 km resolution with the RAMS/Pagasus modeling system, achieving good performance for 1 hr peak ozone in many locations around Lake Michigan.…”

“…Recent CMAQ‐based model assessments have shown high bias for peak ozone metrics including daily averaged 1 hr maximum, afternoon ozone, MDA8 ozone, or MDA8 ozone on days above 60 ppb (Cleary et al, , with 12 km and Qin et al, , with 4 km horizontal resolution). However, the three highest resolution PGMs used during LMOS 2017 were biased low for peak ozone, including the operational NAM‐CMAQ forecast (12 km), a WRF/CMAQ model run (12 km) using typical regulatory modeling configuration, and Weather Research and Forecasting with Chemistry (WRF‐Chem; 4 km) (Abdioskouei et al, ).…”

“…During the LAP experiment, high concentrations of reactive nitrogen (NO y ) and Volatile Organic Compounds (VOC) were observed over the lake (Foley et al, 2011). More recently, measurements aboard the Lake Express Ferry during the ozone seasons of 2008-2010 confirmed an ozone enhancement averaging 4 ppb over the lake relative to a land monitor at Kenosha, WI (Cleary et al, 2015). Similarly, higher concentration of ozone over the water was measured for the Chesapeake Bay Loughner et al, 2014;Sullivan et al, 2018), and for Lake Erie and Lake St. Clair (Levy et al, 2010).…”

Responses to Reviewer 3

“…Among meteorological parameters, clouds can be one of the key factors because they greatly modulate the ultraviolet radiation that is critical for O 3 formation. However, they remain one of the largest sources of uncertainties in air quality modeling as Dabberdt et al (2004) pointed out a decade ago. Accurate cloud predictions in numerical weather models are still challenging, and it has not yet been quantified how much errors in cloud prediction impact surface O 3 predictions.…”