scholarly journals Lake breezes in the southern Great Lakes region and their influence during BAQS-Met 2007

2011 ◽  
Vol 11 (2) ◽  
pp. 3579-3626 ◽  
Author(s):  
D. M. L. Sills ◽  
J. R. Brook ◽  
I. Levy ◽  
P. A. Makar ◽  
J. Zhang ◽  
...  
Keyword(s):  
Air Quality ◽  
Great Lakes ◽  
Weather Prediction ◽  
Great Lakes Region ◽  
Lake Breeze ◽  
Moist Convection ◽  
Study Region ◽  
Synoptic Wind ◽  
Lake Breezes ◽  
Deep Moist Convection

Abstract. Mesoscale observations from the BAQS-Met field experiment during the summer of 2007 were integrated and manually analyzed in order to identify and characterize lake breezes in the southern Great Lakes region of North America, and assess their potential impact on air quality. Lake breezes were found to occur on 90% of study days, often occurring in conditions previously thought to impede their development. They affected all parts of the study region, including southwestern Ontario and nearby portions of southeast Michigan and northern Ohio, occasionally penetrating inland from 100 km to over 200 km. Occurrence rates and penetration distances were found to be higher than previously reported in the literature. This more accurate depiction of observed lake breezes allows a better understanding of their influence on the production and transport of pollutants in this region. The observational analyses were compared with output from subsequent runs of a high-resolution numerical weather prediction model. The model accurately predicted lake breeze occurrence in a variety of synoptic wind regimes, but selected cases showed substantial differences in the detailed timing and location of lake-breeze fronts, and with the initiation of deep moist convection. Knowledge of such strengths and weaknesses will assist with interpretation of results from air quality modelling driven by this meteorological model.

scholarly journals Lake breezes in the southern Great Lakes region and their influence during BAQS-Met 2007

2011 ◽  
Vol 11 (15) ◽  
pp. 7955-7973 ◽  
Author(s):  
D. M. L. Sills ◽  
J. R. Brook ◽  
I. Levy ◽  
P. A. Makar ◽  
J. Zhang ◽  
...  
Keyword(s):  
Air Quality ◽  
Great Lakes ◽  
Weather Prediction ◽  
Great Lakes Region ◽  
Lake Breeze ◽  
Moist Convection ◽  
Study Region ◽  
Synoptic Wind ◽  
Lake Breezes ◽  
Deep Moist Convection

Abstract. Meteorological observations from the BAQS-Met field experiment during the summer months of 2007 were integrated and manually analyzed in order to identify and characterize lake breezes in the southern Great Lakes region of North America, and assess their potential impact on air quality. Lake breezes occurred frequently, with one or more lake breezes identified on 90 % of study days. They affected all parts of the study region, including southwestern Ontario and nearby portions of southeast Lower Michigan and northern Ohio, with lake-breeze fronts occasionally penetrating from 100 km to over 200 km inland. Occurrence rates and penetration distances were found to be higher than previously reported in the literature. This comprehensive depiction of observed lake breezes allows an improved understanding of their influence on the transport, dispersion, and production of pollutants in this region. The observational analyses were compared with output from subsequent runs of a high-resolution numerical weather prediction model. The model accurately predicted lake breeze occurrence and type in a variety of synoptic wind regimes, but selected cases showed substantial differences in the detailed timing and location of lake-breeze fronts, and with the initiation of deep moist convection. Knowledge of such strengths and weaknesses aids in the interpretation of results from air quality models driven by this meteorological model.

scholarly journals Exploring the nature of air quality over southwestern Ontario: main findings from the Border Air Quality and Meteorology Study

2013 ◽  
Vol 13 (20) ◽  
pp. 10461-10482 ◽  
Author(s):  
J. R. Brook ◽  
P. A. Makar ◽  
D. M. L. Sills ◽  
K. L. Hayden ◽  
R. McLaren
Keyword(s):  
Air Quality ◽  
High Resolution ◽  
Great Lakes ◽  
The United States ◽  
Urban Heat Islands ◽  
Anthropogenic Emissions ◽  
Lake Breeze ◽  
Aerosol Formation ◽  
Air Quality Model ◽  
Quality Model

Abstract. This paper serves as an overview and discusses the main findings from the Border Air Quality and Meteorology Study (BAQS-Met) in southwestern Ontario in 2007. This region is dominated by the Great Lakes, shares borders with the United States and consistently experiences the highest ozone (O3) and fine particulate matter concentrations in Canada. The purpose of BAQS-Met was to improve our understanding of how lake-driven meteorology impacts air quality in the region, and to improve models used for forecasting and policy scenarios. Results show that lake breeze occurrence frequencies and inland penetration distances were significantly greater than realized in the past. Due to their effect on local meteorology, the lakes were found to enhance secondary O3 and aerosol formation such that local anthropogenic emissions have their impact closer to the populated source areas than would otherwise occur in the absence of the lakes. Substantial spatial heterogeneity in O3 was observed with local peaks typically 30 ppb above the regional values. Sulfate and secondary organic aerosol (SOA) enhancements were also linked to local emissions being transported in the lake breeze circulations. This study included the first detailed evaluation of regional applications of a high-resolution (2.5 km grid) air quality model in the Great Lakes region. The model showed that maxima in secondary pollutants occur in areas of convergence, in localized updrafts and in distinct pockets over the lake surfaces. These effects are caused by lake circulations interacting with the synoptic flow, with each other or with circulations induced by urban heat islands. Biogenic and anthropogenic emissions were both shown to play a role in the formation of SOA in the region. Detailed particle measurements and multivariate receptor models reveal that while individual particles are internally mixed, they often exist within more complex external mixtures. This makes it difficult to predict aerosol optical properties and further highlights the challenges facing aerosol modelling. The BAQS-Met study has led to a better understanding of the value of high-resolution (2.5 km) modelling for air quality and meteorological predictions and has led to several model improvements.

scholarly journals Impact of model grid spacing on regional- and urban-scale air quality predictions of organic aerosol

2010 ◽  
Vol 10 (12) ◽  
pp. 30347-30379 ◽  
Author(s):  
C. A. Stroud ◽  
P. A. Makar ◽  
M. D. Moran ◽  
W. Gong ◽  
S. Gong ◽  
...  
Keyword(s):  
Air Quality ◽  
Great Lakes ◽  
Secondary Organic Aerosol ◽  
Chemical Transport ◽  
Organic Aerosol ◽  
Great Lakes Region ◽  
Grid Spacing ◽  
Aerosol Composition ◽  
Resolution Model ◽  
Bear Creek

Abstract. Regional-scale chemical transport model predictions of urban organic aerosol to date tend to be biased low relative to observations, a limitation with important implications for applying such models to human exposure health studies. We used a nested version of Environment Canada's AURAMS model (42-to-15-to-2.5 km nested grid spacing) to predict organic aerosol concentrations for a temporal and spatial domain corresponding to the Border Air Quality and Meteorology Study (BAQS-Met), an air-quality field study that took place in the southern Great Lakes region in the summer of 2007. The use of three different horizontal grid spacings allowed the influence of this parameter to be examined. A domain-wide average for the 2.5 km domain and a matching 15 km subdomain yielded very similar organic aerosol averages (4.8 vs. 4.3 μg m−3, respectively). On regional scales, secondary organic aerosol dominated the organic aerosol composition and was adequately resolved by the 15 km model simulation. However, the shape of the organic aerosol concentration histogram for the Windsor urban station improved for the 2.5 km simulation relative to those from the 42 and 15 km simulations. The model histograms for the Bear Creek and Harrow rural stations were also improved in the high concentration "tail" region. As well the highest-resolution model results captured the midday 4 July organic-aerosol plume at Bear Creek with very good temporal correlation. These results suggest that accurate simulation of urban and large industrial plumes in the Great Lakes region requires the use of a high-resolution model in order to represent urban primary organic aerosol emissions, urban VOC emissions, and the secondary organic aerosol production rates properly. The positive feedback between the secondary organic aerosol production rate and existing organic mass concentration is also represented more accurately with the highest-resolution model. Not being able to capture these finer-scale features may partly explain the consistent negative bias reported in the literature when urban-scale organic aerosol evaluations are made using coarser-scale chemical transport models.

scholarly journals An assessment of atmospheric mercury in the Community Multiscale Air Quality (CMAQ) model at an urban site and a rural site in the Great Lakes Region of North America

2012 ◽  
Vol 12 (15) ◽  
pp. 7117-7133 ◽  
Author(s):  
T. Holloway ◽  
C. Voigt ◽  
J. Morton ◽  
S. N. Spak ◽  
A. P. Rutter ◽  
...  
Keyword(s):  
Air Quality ◽  
Great Lakes ◽  
Numerical Models ◽  
Atmospheric Mercury ◽  
Rural Site ◽  
Urban Site ◽  
Base Case ◽  
Mercury Species ◽  
Great Lakes Region ◽  
Local Emissions

Abstract. Quantitative analysis of three atmospheric mercury species – gaseous elemental mercury (Hg0), reactive gaseous mercury (RGHg) and particulate mercury (PHg) – has been limited to date by lack of ambient measurement data as well as by uncertainties in numerical models and emission inventories. This study employs the Community Multiscale Air Quality Model version 4.6 with mercury chemistry (CMAQ-Hg), to examine how local emissions, meteorology, atmospheric chemistry, and deposition affect mercury concentration and deposition the Great Lakes Region (GLR), and two sites in Wisconsin in particular: the rural Devil's Lake site and the urban Milwaukee site. Ambient mercury exhibits significant biases at both sites. Hg0 is too low in CMAQ-Hg, with the model showing a 6% low bias at the rural site and 36% low bias at the urban site. Reactive mercury (RHg = RGHg + PHg) is over-predicted by the model, with annual average biases >250%. Performance metrics for RHg are much worse than for mercury wet deposition, ozone (O3), nitrogen dioxide (NO2), or sulfur dioxide (SO2). Sensitivity simulations to isolate background inflow from regional emissions suggests that oxidation of imported Hg0 dominates model estimates of RHg at the rural study site (91% of base case value), and contributes 55% to the RHg at the urban site (local emissions contribute 45%).

scholarly journals A Synoptic Climatology of Spring Dryline Convection in the Southern Great Plains

2020 ◽  
Vol 35 (4) ◽  
pp. 1561-1582 ◽  
Author(s):  
Trevor Mitchell ◽  
David M. Schultz
Keyword(s):  
United States ◽  
Great Plains ◽  
Weather Prediction ◽  
Synoptic Climatology ◽  
Specific Humidity ◽  
Moist Convection ◽  
Southern Great Plains ◽  
South Central ◽  
Deep Moist Convection ◽  
Upper Level

AbstractA dataset of drylines within a region of the southern Great Plains was constructed to investigate the large-scale environments associated with the initiation of deep moist convection. Drylines were identified using NOAA/NWS Weather Prediction Center surface analyses for all April, May, and June days 2006–15. Doppler radar and visible and infrared satellite imagery were used to identify convective drylines, where deep, moist convection was deemed to have been associated with the dryline circulation. Approximately 60% of drylines were convective, with initiation most frequently occurring between 2000 and 2100 UTC. Composite synoptic analyses were created of 179 convective and 104 nonconvective dryline days. The composites featured an upper-level long-wave trough to the west of the Rockies and a ridge extending across the northern and eastern United States. At the surface, the composites featured a broad surface cyclone over western Texas and southerly flow over the south-central states. Convective drylines featured more amplified upper-level flow, associated with a deeper trough in the western United States and a stronger downstream ridge than nonconvective drylines up to 5 days preceding a dryline event. By the day of a dryline event, the convective composite features greater low-level specific humidity and higher CAPE than the nonconvective composite. These results demonstrate that synoptic-scale processes over several days help create conditions conducive to deep, moist convection along the dryline.

scholarly journals Exploring the nature of air quality over southwestern Ontario: main findings from the border air quality and meteorology study

2013 ◽  
Vol 13 (4) ◽  
pp. 11111-11166
Author(s):  
J. R. Brook ◽  
P. A. Makar ◽  
D. M. L. Sills ◽  
K. L. Hayden ◽  
R. McLaren
Keyword(s):  
Air Quality ◽  
High Resolution ◽  
Great Lakes ◽  
The United States ◽  
Urban Heat Islands ◽  
Anthropogenic Emissions ◽  
Lake Breeze ◽  
Aerosol Formation ◽  
Air Quality Model ◽  
Quality Model

Abstract. This paper serves as an overview and discusses the main findings from the Border Air Quality and Meteorology Study (BAQS-Met) in southwestern Ontario in 2007. This region is dominated by the Great Lakes, shares borders with the United States and consistently experiences the highest ozone (O3) and fine particulate matter in Canada. The purpose of BAQS-Met was to improve our understanding of how lake-driven meteorology impacts air quality in the region, and to improve models used for forecasting and policy scenarios. Results show that lake breeze occurrence frequencies and inland penetration distances were significantly greater than realized in the past. Due to their effect on local meteorology, the lakes were found to enhance secondary O3 and aerosol formation such that local anthropogenic emissions have their impact closer to the populated source areas than would otherwise occur in the absence of the lakes. Substantial spatial heterogeneity in O3 was observed with local peaks typically 30 ppb above the regional values. Sulphate and secondary organic aerosol (SOA) enhancements were also linked to local emissions being transported in the lake breeze circulations. This study included the first detailed evaluation of regional applications of a high resolution (2.5 km grid) air quality model in the Great Lakes region. The model showed that maxima in secondary pollutants occur in areas of convergence, in localized updrafts and in distinct pockets over the lake surfaces. These effects are caused by lake circulations interacting with the synoptic flow, with each other or with circulations induced by urban heat islands. Biogenic and anthropogenic emissions were both shown to play a role in the formation of SOA in the region. Detailed particle measurements and multivariate receptor models reveal that while individual particles are internally mixed, they often exist within more complex external mixtures. This makes it difficult to predict aerosol optical properties and further highlights the challenges facing aerosol modelling. The BAQS-Met study has led to a better understanding of the value of high resolution (2.5 km) modeling for air quality and meteorological predictions and has led to several model improvements.

scholarly journals Prediction of Lake-Effect Snow Using Convection-Allowing Ensemble Forecasts and Regional Data Assimilation

2017 ◽  
Vol 32 (5) ◽  
pp. 1727-1744 ◽  
Author(s):  
Seth Saslo ◽  
Steven J. Greybush
Keyword(s):  
Data Assimilation ◽  
Great Lakes ◽  
Forecast Error ◽  
Weather Prediction ◽  
The United States ◽  
Ensemble Prediction ◽  
Great Lakes Region ◽  
Prediction System ◽  
Ensemble Prediction System ◽  
Lake Effect

Abstract Lake-effect snow (LES) is a cold-season mesoscale convective phenomenon that can lead to significant snowfall rates and accumulations in the Great Lakes region of the United States. While limited-area numerical weather prediction models have shown skill in prediction of warm-season convective storms, forecasting the sharp nature of LES precipitation timing, intensity, and location is difficult because of model error and initial and boundary condition uncertainties. Ensemble forecasting can incorporate and quantify some sources of forecast error, but ensemble design must be considered. This study examines the relative contributions of forecast uncertainties to LES forecast error using a regional convection-allowing data assimilation and ensemble prediction system. Ensembles are developed using various methods of perturbations to simulate a long-lived and high-precipitation LES event in December 2013, and forecast performance is evaluated using observations including those from the Ontario Winter Lake-Effect Systems (OWLeS) campaign. Model lateral boundary conditions corresponding to weather conditions beyond the Great Lakes region play an influential role in LES precipitation forecasts and their uncertainty, as evidenced by ensemble spread, particularly at lead times beyond one day. A strong forecast dependence on regional initial conditions was shown using data assimilation. This sensitivity impacts the timing and intensity of predicted precipitation, as well as band location and orientation assessed with an object-based verification approach, giving insight into the time scales of practical predictability of LES. Overall, an assimilation-cycling convection-allowing ensemble prediction system could improve future lake-effect snow precipitation forecasts and analyses and can help quantify and understand sources of forecast uncertainty.

scholarly journals Daily Precipitation Fields Modeling across the Great Lakes Region (Canada) by Using the CFSR Reanalysis

2018 ◽  
Vol 57 (10) ◽  
pp. 2419-2438 ◽  
Author(s):  
Dikra Khedhaouiria ◽  
Alain Mailhot ◽  
Anne-Catherine Favre
Keyword(s):  
Great Lakes ◽  
Linear Model ◽  
Random Fields ◽  
Generalized Linear Model ◽  
Daily Precipitation ◽  
Weather Prediction ◽  
Gaussian Random Fields ◽  
Great Lakes Region ◽  
Spatiotemporal Random Fields ◽  
Model Output Statistics

AbstractReanalyses, generated by numerical weather prediction methods assimilating past observations, provide consistent and continuous meteorological fields for a specific period. In regard to precipitation, reanalyses cannot be used as a climate proxy of the observed precipitation, as biases and scale mismatches exist between the datasets. In the present study, a stochastic model output statistics (SMOS) approach combined with meta-Gaussian spatiotemporal random fields was employed to cope with these caveats. The SMOS is based on the generalized linear model (GLM) and the vector generalized linear model (VGLM) frameworks to model the precipitation occurrence and intensity, respectively. Both models use the Climate Forecast System Reanalysis (CFSR) precipitation as covariate and were locally calibrated at 173 sites across the Great Lakes region. Combined with meta-Gaussian random fields, the GLM and VGLM models allowed for the generation of spatially coherent daily precipitation fields across the region. The results indicated that the approach corrected systematic biases and provided an accurate spatiotemporal structure of daily precipitation. Performances of selected precipitation indicators from the joint Commission for Climatology (CCl)/CLIVAR/JCOMM Expert Team on Climate Change Detection and Indices (ETCCDI) were good and were systematically improved when compared to CFSR.

scholarly journals Examination of Nudging Schemes in the Simulation of Meteorology for Use in Air Quality Experiments: Application in the Great Lakes Region

2019 ◽  
Vol 58 (11) ◽  
pp. 2421-2436 ◽  
Author(s):  
M. Talat Odman ◽  
Andrew T. White ◽  
Kevin Doty ◽  
Richard T. McNider ◽  
Arastoo Pour-Biazar ◽  
...  
Keyword(s):  
Air Quality ◽  
Great Lakes ◽  
Large Scale ◽  
Lake Michigan ◽  
Forecast Errors ◽  
Great Lakes Region ◽  
Air Quality Model ◽  
Quality Model ◽  
Four Dimensional Data Assimilation ◽  
The Impact

AbstractHigh levels of ozone have been observed along the shores of Lake Michigan for the last 40 years. Models continue to struggle in their ability to replicate ozone behavior in the region. In the retrospective way in which models are used in air quality regulation development, nudging or four-dimensional data assimilation (FDDA) of the large-scale environment is important for constraining model forecast errors. Here, paths for incorporating large-scale meteorological conditions but retaining model mesoscale structure are evaluated. For the July 2011 case studied here, iterative FDDA strategies did not improve mesoscale performance in the Great Lakes region in terms of diurnal trends or monthly averaged statistics, with overestimations of nighttime wind speed remaining as an issue. Two vertical nudging strategies were evaluated for their effects on the development of nocturnal low-level jets (LLJ) and their impacts on air quality simulations. Nudging only above the planetary boundary layer, which has been a standard option in many air quality simulations, significantly dampened the amplitude of LLJ relative to nudging only above a height of 2 km. While the LLJ was preserved with nudging only above 2 km, there was some deterioration in wind performance when compared with profiler networks above the jet between 500 m and 2 km. In examining the impact of nudging strategies on air quality performance of the Community Multiscale Air Quality model, it was found that performance was improved for the case of nudging above 2 km. This result may reflect the importance of the LLJ in transport or perhaps a change in mixing in the models.

scholarly journals Impact of model grid spacing on regional- and urban- scale air quality predictions of organic aerosol

2011 ◽  
Vol 11 (7) ◽  
pp. 3107-3118 ◽  
Author(s):  
C. A. Stroud ◽  
P. A. Makar ◽  
M. D. Moran ◽  
W. Gong ◽  
S. Gong ◽  
...  
Keyword(s):  
Air Quality ◽  
Great Lakes ◽  
Secondary Organic Aerosol ◽  
Chemical Transport ◽  
Organic Aerosol ◽  
Great Lakes Region ◽  
Grid Spacing ◽  
Aerosol Composition ◽  
Resolution Model ◽  
Bear Creek

Abstract. Regional-scale chemical transport model predictions of urban organic aerosol to date tend to be biased low relative to observations, a limitation with important implications for applying such models to human exposure health studies. We used a nested version of Environment Canada's AURAMS model (42- to- 15- to- 2.5-km nested grid spacing) to predict organic aerosol concentrations for a temporal and spatial domain corresponding to the Border Air Quality and Meteorology Study (BAQS-Met), an air-quality field study that took place in the southern Great Lakes region in the summer of 2007. The use of three different horizontal grid spacings allowed the influence of this parameter to be examined. A domain-wide average for the 2.5-km domain and a matching 15-km subdomain yielded very similar organic aerosol averages (4.8 vs. 4.3 μg m−3, respectively). On regional scales, secondary organic aerosol dominated the organic aerosol composition and was adequately resolved by the 15-km model simulation. However, the shape of the organic aerosol concentration histogram for the Windsor urban station improved for the 2.5-km simulation relative to those from the 42- and 15-km simulations. The model histograms for the Bear Creek and Harrow rural stations were also improved in the high concentration "tail" region. As well the highest-resolution model results captured the midday 4 July organic-aerosol plume at Bear Creek with very good temporal correlation. These results suggest that accurate simulation of urban and large industrial plumes in the Great Lakes region requires the use of a high-resolution model in order to represent urban primary organic aerosol emissions, urban VOC emissions, and the secondary organic aerosol production rates properly. The positive feedback between the secondary organic aerosol production rate and existing organic mass concentration is also represented more accurately with the highest-resolution model. Not being able to capture these finer-scale features may partly explain the consistent negative bias reported in the literature when urban-scale organic aerosol evaluations are made using coarser-scale chemical transport models.

Sign in / Sign up

Export Citation Format

Share Document