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- Author or Editor: Christopher P. Loughner x
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Abstract
The continually changing atmospheric conditions over densely populated coastal urban regions make it challenging to produce models that accurately capture the complex interactions of anthropogenic and environmental emissions, chemical reactions, and unique meteorological processes, such as sea- and land-breeze circulations. The purpose of this study is to determine and identify the influence of synoptic-scale wind patterns on the development of local-scale sea-breeze circulations and air quality over the New York City (NYC), New York, metropolitan area. This study utilizes column-integrated nitrogen dioxide observations made during the Long Island Sound Tropospheric Ozone Study (LISTOS) field campaign, ground-level ozone observations, the HRRR numerical weather prediction model, and trajectory model simulations using the NOAA HYSPLIT model. A cluster analysis within the HYSPLIT modeling system was performed to determine that there were six unique synoptic-scale transport pathways for NYC. Stagnant conditions or weak transport out of the northwest resulted in the worst air quality for NYC. Weak synoptic-scale forcings associated with these conditions allowed for local-scale sea-breeze circulations to develop, resulting in air pollution being able to recirculate and mix with freshly emitted pollutants.
Significance Statement
The purpose of this work is to understand how synoptic-scale wind patterns influence air quality and sea-breeze circulations in the New York City, New York, metropolitan area. This work shows that clean air can be imported into the region from rural New England and over the Atlantic Ocean, whereas polluted air can be transported into the region from the northwest and southwest. This work also shows the importance of the strength in synoptic-scale forcings in the development of sea-breeze circulations. Weak synoptic-scale winds allow for strong sea-breeze circulations to develop over all coastlines in the New York City region, resulting in air pollutants recirculating and mixing with freshly emitted air pollution and contributing to poor air quality.
Abstract
The continually changing atmospheric conditions over densely populated coastal urban regions make it challenging to produce models that accurately capture the complex interactions of anthropogenic and environmental emissions, chemical reactions, and unique meteorological processes, such as sea- and land-breeze circulations. The purpose of this study is to determine and identify the influence of synoptic-scale wind patterns on the development of local-scale sea-breeze circulations and air quality over the New York City (NYC), New York, metropolitan area. This study utilizes column-integrated nitrogen dioxide observations made during the Long Island Sound Tropospheric Ozone Study (LISTOS) field campaign, ground-level ozone observations, the HRRR numerical weather prediction model, and trajectory model simulations using the NOAA HYSPLIT model. A cluster analysis within the HYSPLIT modeling system was performed to determine that there were six unique synoptic-scale transport pathways for NYC. Stagnant conditions or weak transport out of the northwest resulted in the worst air quality for NYC. Weak synoptic-scale forcings associated with these conditions allowed for local-scale sea-breeze circulations to develop, resulting in air pollution being able to recirculate and mix with freshly emitted pollutants.
Significance Statement
The purpose of this work is to understand how synoptic-scale wind patterns influence air quality and sea-breeze circulations in the New York City, New York, metropolitan area. This work shows that clean air can be imported into the region from rural New England and over the Atlantic Ocean, whereas polluted air can be transported into the region from the northwest and southwest. This work also shows the importance of the strength in synoptic-scale forcings in the development of sea-breeze circulations. Weak synoptic-scale winds allow for strong sea-breeze circulations to develop over all coastlines in the New York City region, resulting in air pollutants recirculating and mixing with freshly emitted air pollution and contributing to poor air quality.
Abstract
Wintertime cold air outbreaks are periods of extreme cold, often persisting for several days and spanning hundreds of kilometers or more. They are commonly associated with intrusions of cold polar air into the midlatitudes, but it is unclear whether the air mass’s initial temperature in the Arctic or its cooling as it travels is the determining factor in producing a cold air outbreak. By calculating air parcel trajectories for a preindustrial climate model scenario, we study the role of the origin and evolution of air masses traveling over sea ice and land and resulting in wintertime cold air outbreaks over central North America. We find that not all Arctic air masses result in a cold air outbreak when advected into the midlatitudes. We compare trajectories that originate in the Arctic and result in cold air outbreaks to those that also originate in the Arctic but lead to median temperatures when advected into the midlatitudes. While about one-third of the midlatitude temperature difference can be accounted for by the initial height and temperature in the Arctic, the other two-thirds are a result of differences in diabatic heating and cooling as the air masses travel. Vertical mixing of cold surface air into the air mass while it travels dominates the diabatic cooling and contributes to the cold events. Air masses leading to cold air outbreaks experience more negative sensible heat flux from the underlying surface, suggesting that preconditioning to establish a cold surface is key to producing cold air outbreaks.
Significance Statement
Wintertime cold air outbreaks can cause temperatures to plummet tens of degrees below freezing over the northern United States, with the potential to damage agriculture, infrastructure, and human health. Accurate predictions under climate change could help mitigate these effects, but there is disagreement over whether cold air outbreaks have declined in line with the already-observed global warming trend or persisted in spite of it. Focusing on cold air outbreaks that originate from the Arctic, we find that there must be additional cooling of the traveling air mass by mixing with very cold surface air as it moves south over North America in order to result in a cold outbreak.
Abstract
Wintertime cold air outbreaks are periods of extreme cold, often persisting for several days and spanning hundreds of kilometers or more. They are commonly associated with intrusions of cold polar air into the midlatitudes, but it is unclear whether the air mass’s initial temperature in the Arctic or its cooling as it travels is the determining factor in producing a cold air outbreak. By calculating air parcel trajectories for a preindustrial climate model scenario, we study the role of the origin and evolution of air masses traveling over sea ice and land and resulting in wintertime cold air outbreaks over central North America. We find that not all Arctic air masses result in a cold air outbreak when advected into the midlatitudes. We compare trajectories that originate in the Arctic and result in cold air outbreaks to those that also originate in the Arctic but lead to median temperatures when advected into the midlatitudes. While about one-third of the midlatitude temperature difference can be accounted for by the initial height and temperature in the Arctic, the other two-thirds are a result of differences in diabatic heating and cooling as the air masses travel. Vertical mixing of cold surface air into the air mass while it travels dominates the diabatic cooling and contributes to the cold events. Air masses leading to cold air outbreaks experience more negative sensible heat flux from the underlying surface, suggesting that preconditioning to establish a cold surface is key to producing cold air outbreaks.
Significance Statement
Wintertime cold air outbreaks can cause temperatures to plummet tens of degrees below freezing over the northern United States, with the potential to damage agriculture, infrastructure, and human health. Accurate predictions under climate change could help mitigate these effects, but there is disagreement over whether cold air outbreaks have declined in line with the already-observed global warming trend or persisted in spite of it. Focusing on cold air outbreaks that originate from the Arctic, we find that there must be additional cooling of the traveling air mass by mixing with very cold surface air as it moves south over North America in order to result in a cold outbreak.
Abstract
The Hybrid Single-Particle Lagrangian Integrated Trajectory model (HYSPLIT) is a state-of-the-science atmospheric dispersion model that is developed and maintained at the National Oceanic Atmospheric Administration’s Air Resources Laboratory. In the early 2000s, HYSPLIT served as the starting point for development of the Stochastic Time-Inverted Lagrangian Transport (STILT) model that emphasizes backward-in-time dispersion simulations to determine source regions of receptors. STILT continued its separate development and gained a wide user base. Since STILT was built on a now outdated version of HYSPLIT and lacks long-term institutional support to maintain the model, incorporating STILT features into HYSPLIT allows these features to stay up to date. This paper describes the STILT features incorporated into HYSPLIT, which include a new vertical interpolation algorithm for WRF-derived meteorological input files, a detailed algorithm for estimating boundary layer height, a new turbulence parameterization, a vertical Lagrangian time scale that varies in time and space, a complex dispersion algorithm, and two new convection schemes. An evaluation of these new features was performed using tracer release data from the Cross Appalachian Tracer Experiment and the Across North America Tracer Experiment. Results show that the dispersion module from STILT, which takes up to double the amount of time to run, is less dispersive in the vertical direction and is in better agreement with observations when compared with the existing HYSPLIT option. The other new modeling features from STILT were not consistently statistically different than existing HYSPLIT options. Forward-time simulations from the new model were also compared with backward-in-time equivalents and were found to be statistically comparable to one another.
Abstract
The Hybrid Single-Particle Lagrangian Integrated Trajectory model (HYSPLIT) is a state-of-the-science atmospheric dispersion model that is developed and maintained at the National Oceanic Atmospheric Administration’s Air Resources Laboratory. In the early 2000s, HYSPLIT served as the starting point for development of the Stochastic Time-Inverted Lagrangian Transport (STILT) model that emphasizes backward-in-time dispersion simulations to determine source regions of receptors. STILT continued its separate development and gained a wide user base. Since STILT was built on a now outdated version of HYSPLIT and lacks long-term institutional support to maintain the model, incorporating STILT features into HYSPLIT allows these features to stay up to date. This paper describes the STILT features incorporated into HYSPLIT, which include a new vertical interpolation algorithm for WRF-derived meteorological input files, a detailed algorithm for estimating boundary layer height, a new turbulence parameterization, a vertical Lagrangian time scale that varies in time and space, a complex dispersion algorithm, and two new convection schemes. An evaluation of these new features was performed using tracer release data from the Cross Appalachian Tracer Experiment and the Across North America Tracer Experiment. Results show that the dispersion module from STILT, which takes up to double the amount of time to run, is less dispersive in the vertical direction and is in better agreement with observations when compared with the existing HYSPLIT option. The other new modeling features from STILT were not consistently statistically different than existing HYSPLIT options. Forward-time simulations from the new model were also compared with backward-in-time equivalents and were found to be statistically comparable to one another.
Abstract
Urban heat island (UHI) effects can strengthen heat waves and air pollution episodes. In this study, the dampening impact of urban trees on the UHI during an extreme heat wave in the Washington, D.C., and Baltimore, Maryland, metropolitan area is examined by incorporating trees, soil, and grass into the coupled Weather Research and Forecasting model and an urban canopy model (WRF-UCM). By parameterizing the effects of these natural surfaces alongside roadways and buildings, the modified WRF-UCM is used to investigate how urban trees, soil, and grass dampen the UHI. The modified model was run with 50% tree cover over urban roads and a 10% decrease in the width of urban streets to make space for soil and grass alongside the roads and buildings. Results show that, averaged over all urban areas, the added vegetation decreases surface air temperature in urban street canyons by 4.1 K and road-surface and building-wall temperatures by 15.4 and 8.9 K, respectively, as a result of tree shading and evapotranspiration. These temperature changes propagate downwind and alter the temperature gradient associated with the Chesapeake Bay breeze and, therefore, alter the strength of the bay breeze. The impact of building height on the UHI shows that decreasing commercial building heights by 8 m and residential building heights by 2.5 m results in up to 0.4-K higher daytime surface and near-surface air temperatures because of less building shading and up to 1.2-K lower nighttime temperatures because of less longwave radiative trapping in urban street canyons.
Abstract
Urban heat island (UHI) effects can strengthen heat waves and air pollution episodes. In this study, the dampening impact of urban trees on the UHI during an extreme heat wave in the Washington, D.C., and Baltimore, Maryland, metropolitan area is examined by incorporating trees, soil, and grass into the coupled Weather Research and Forecasting model and an urban canopy model (WRF-UCM). By parameterizing the effects of these natural surfaces alongside roadways and buildings, the modified WRF-UCM is used to investigate how urban trees, soil, and grass dampen the UHI. The modified model was run with 50% tree cover over urban roads and a 10% decrease in the width of urban streets to make space for soil and grass alongside the roads and buildings. Results show that, averaged over all urban areas, the added vegetation decreases surface air temperature in urban street canyons by 4.1 K and road-surface and building-wall temperatures by 15.4 and 8.9 K, respectively, as a result of tree shading and evapotranspiration. These temperature changes propagate downwind and alter the temperature gradient associated with the Chesapeake Bay breeze and, therefore, alter the strength of the bay breeze. The impact of building height on the UHI shows that decreasing commercial building heights by 8 m and residential building heights by 2.5 m results in up to 0.4-K higher daytime surface and near-surface air temperatures because of less building shading and up to 1.2-K lower nighttime temperatures because of less longwave radiative trapping in urban street canyons.
Abstract
Meteorological and air-quality model simulations are analyzed alongside observations to investigate the role of the Chesapeake Bay breeze on surface air quality, pollutant transport, and boundary layer venting. A case study was conducted to understand why a particular day was the only one during an 11-day ship-based field campaign on which surface ozone was not elevated in concentration over the Chesapeake Bay relative to the closest upwind site and why high ozone concentrations were observed aloft by in situ aircraft observations. Results show that southerly winds during the overnight and early-morning hours prevented the advection of air pollutants from the Washington, D.C., and Baltimore, Maryland, metropolitan areas over the surface waters of the bay. A strong and prolonged bay breeze developed during the late morning and early afternoon along the western coastline of the bay. The strength and duration of the bay breeze allowed pollutants to converge, resulting in high concentrations locally near the bay-breeze front within the Baltimore metropolitan area, where they were then lofted to the top of the planetary boundary layer (PBL). Near the top of the PBL, these pollutants were horizontally advected to a region with lower PBL heights, resulting in pollution transport out of the boundary layer and into the free troposphere. This elevated layer of air pollution aloft was transported downwind into New England by early the following morning where it likely mixed down to the surface, affecting air quality as the boundary layer grew.
Abstract
Meteorological and air-quality model simulations are analyzed alongside observations to investigate the role of the Chesapeake Bay breeze on surface air quality, pollutant transport, and boundary layer venting. A case study was conducted to understand why a particular day was the only one during an 11-day ship-based field campaign on which surface ozone was not elevated in concentration over the Chesapeake Bay relative to the closest upwind site and why high ozone concentrations were observed aloft by in situ aircraft observations. Results show that southerly winds during the overnight and early-morning hours prevented the advection of air pollutants from the Washington, D.C., and Baltimore, Maryland, metropolitan areas over the surface waters of the bay. A strong and prolonged bay breeze developed during the late morning and early afternoon along the western coastline of the bay. The strength and duration of the bay breeze allowed pollutants to converge, resulting in high concentrations locally near the bay-breeze front within the Baltimore metropolitan area, where they were then lofted to the top of the planetary boundary layer (PBL). Near the top of the PBL, these pollutants were horizontally advected to a region with lower PBL heights, resulting in pollution transport out of the boundary layer and into the free troposphere. This elevated layer of air pollution aloft was transported downwind into New England by early the following morning where it likely mixed down to the surface, affecting air quality as the boundary layer grew.
Abstract
A series of meteorological measurements with a small uncrewed aircraft system (sUAS) was collected at Oliver Springs Airport in Tennessee. The sUAS provides a unique observing system capable of obtaining vertical profiles of meteorological data within the lowest few hundred meters of the boundary layer. The measurements benefit simulated plume predictions by providing more accurate meteorological data to a dispersion model. The sUAS profiles can be used directly to drive HYSPLIT dispersion simulations. When using sUAS data covering a small domain near a release and meteorological model fields covering a larger domain, simulated pollutants may be artificially increased or decreased near the domain boundary because of inconsistencies in the wind fields between the two meteorological inputs. Numerical experiments using the Weather Research and Forecasting (WRF) Model with observational nudging reveal that incorporating sUAS data improves simulated wind fields and can significantly affect mixing characteristics of the boundary layer, especially during the morning transition period of the planetary boundary layer. We conducted HYSPLIT dispersion simulations for hypothetical releases for three case study periods using WRF meteorological fields with and without assimilating sUAS measurements. The comparison of dispersion results on 15 and 16 December 2021 shows that using sUAS observational nudging is more significant under weak synoptic conditions than under strong influences from regional weather. Very different dispersion results were introduced by the meteorological fields used. The observational nudging produced not just an sUAS-nudged wind flow but also adjusted meteorological fields that further impacted the mixing calculation in HYSPLIT.
Abstract
A series of meteorological measurements with a small uncrewed aircraft system (sUAS) was collected at Oliver Springs Airport in Tennessee. The sUAS provides a unique observing system capable of obtaining vertical profiles of meteorological data within the lowest few hundred meters of the boundary layer. The measurements benefit simulated plume predictions by providing more accurate meteorological data to a dispersion model. The sUAS profiles can be used directly to drive HYSPLIT dispersion simulations. When using sUAS data covering a small domain near a release and meteorological model fields covering a larger domain, simulated pollutants may be artificially increased or decreased near the domain boundary because of inconsistencies in the wind fields between the two meteorological inputs. Numerical experiments using the Weather Research and Forecasting (WRF) Model with observational nudging reveal that incorporating sUAS data improves simulated wind fields and can significantly affect mixing characteristics of the boundary layer, especially during the morning transition period of the planetary boundary layer. We conducted HYSPLIT dispersion simulations for hypothetical releases for three case study periods using WRF meteorological fields with and without assimilating sUAS measurements. The comparison of dispersion results on 15 and 16 December 2021 shows that using sUAS observational nudging is more significant under weak synoptic conditions than under strong influences from regional weather. Very different dispersion results were introduced by the meteorological fields used. The observational nudging produced not just an sUAS-nudged wind flow but also adjusted meteorological fields that further impacted the mixing calculation in HYSPLIT.
