bay breeze
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Abstract A novel algorithm is developed for detecting and classifying the Chesapeake Bay breeze and similar water-body breezes in output from mesoscale numerical weather prediction models. To assess the generality of the new model-based detection algorithm (MBDA), it is tested on simulations from the Weather Research and Forecasting (WRF) model and on analyses and forecasts from the High Resolution Rapid Refresh (HRRR) model. The MBDA outperforms three observation-based detection algorithms (OBDAs) when applied to the same model output. Additionally, by defining the onshore wind directions based on model land-use data, not on the actual geography of the region of interest, performance of the OBDAs with model output can be improved. Although simulations by the WRF model were used to develop the new MBDA, it performed best when applied to HRRR analyses. The generality of the MBDA is promising, and additional tuning of its parameters might improve it further.


2021 ◽  
pp. 118669
Author(s):  
Vanessa Caicedo ◽  
Ruben Delgado ◽  
Winston Luke ◽  
Xinrong Ren ◽  
Paul Kelley ◽  
...  
Keyword(s):  

2020 ◽  
Vol 237 ◽  
pp. 03015
Author(s):  
Zhifeng Yang ◽  
Ruben Delgado ◽  
Belay Demoz ◽  
John Sullivan ◽  
Guillaume Gronoff ◽  
...  

This study focuses on the distribution of ozone (O3) concentration near the Chesapeake Bay, USA (hereafter CB) by integrating observations and model simulations. The motivation of this work is to understand reasons causing the horizontal and vertical distribution of pollutants (mainly O3) near the CB. The O3 exceedance over the CB happens very frequently during summer and the Maryland Department of Environment intends to find out the reasons in order to make policy-related decision. The observation data used in this study are from the Ozone Water-Land Environmental Transition Study-2 (OWLETS-2) field campaign, including observations from O3 lidar, Doppler wind lidar, ozonesonde. The mesoscale model employed is Weather Research and Forecasting model coupled with chemistry (WRF-Chem) version 3.9.1. The anthropogenic emission dataset is from National Emission Inventory 2011 (NEI-2011), including various emission species, e.g., CO, NOX, SO2, NH3, PM2.5, PM10, etc. The meteorological initial and boundary conditions are from the Northern American Regional Reanalysis (NARR) dataset, which is a high-resolution combined model and assimilated dataset from the National Centers for Environmental Prediction (NCEP). There are several findings of this study based on the model simulations and ground-based observations. Actually, at the beginning of study, we considered two different versions of anthropogenic emissions from NEI-2005 and NEI-2011 developed by the Environment Protection Agency (EPA). EPA added the anthropogenic emissions over CB from boats and ships while updating from NEI-2005 to NEI-2011. For model performance evaluation, we employed AirNow surface hourly O3 mixing ratio diurnal variation and compared it with model simulations. For instance, at Essex site near Baltimore City, observed O3 has a strong diurnal variation, with minimum (25 ppbv) just after sunrise (05:00 EST), and with maximum (75 ppbv) around afternoon (15:00 EST). Even the model simulation has a good agreement with the observation, it underestimates the mean O3 mixing ratio by about 15-20 ppbv. Both the surface and 700 mb level horizontal spatial distribution of O3 indicate the higher O3 concentration over the north-middle CB, with surface O3 mixing ratio of 40-50 ppbv and 700 mb level O3 mixing ratio of 60 ppbv, which means the surface O3 was lifted up after production. The vertical profiles of wind of both model and Doppler wind lidar match very well, indicating that the model captured the vertical variation of wind. However, the vertical profiles of O3 from model simulation, ozonesonde, and O3 lidar suggests that model simulation underestimated the O3 from surface to 4.5 km. In addition, the model simulation captured the vertical mixing of O3 from surface to 2 km, while misses the O3 variation above 2 km. In order to study the influence of bay breeze on the O3 small scale transport, three vertical cross sections through the CB from west to east at the northern, middle, and southern CB. The results show that higher O3 concentration above the CB. The bay breeze over the southern CB is stronger than the northern CB. The planetary boundary layer height over the CB is dramatically lower than the surrounding land in the day, which contributes to the surface higher O3 concentration over the CB.


2019 ◽  
Vol 198 ◽  
pp. 351-365 ◽  
Author(s):  
Gina M. Mazzuca ◽  
Kenneth E. Pickering ◽  
David A. New ◽  
Joel Dreessen ◽  
Russell R. Dickerson

2016 ◽  
Vol 144 (2) ◽  
pp. 553-573 ◽  
Author(s):  
Young-Hee Ryu ◽  
James A. Smith ◽  
Elie Bou-Zeid ◽  
Mary L. Baeck

Abstract Low-level convergence induced by land surface heterogeneities can have substantial influence on atmospheric convection and rainfall. Analyses of heavy convective rainfall in the Baltimore–Washington metropolitan area are performed using the Weather Research and Forecasting (WRF) Model, coupled with the Princeton Urban Canopy Model (PUCM) that resolves urban subfacet heterogeneity. Analyses center on storms that produced heavy rainfall and record urban flooding in Baltimore on 1 June 2012. The control simulation using PUCM shows a better performance in reproducing the surface energy balance and rainfall than the simulation using a traditional slab model for the urban area. Sensitivity experiments are carried out to identify the role of the land surface heterogeneities, arising from land–water and urban–nonurban contrasts in the Baltimore–Washington metropolitan area, on heavy rainfall from organized thunderstorm systems. The intersection of low-level convergence zones from thunderstorm downdrafts and from the bay breeze from the Chesapeake Bay enhances the upward motion of preexisting convective storms. The larger sensible heating from the urban area modifies the low-level temperature and wind fields, which in turn modifies the bay breeze. The enhanced moisture supply in the deepened bay-breeze inflow layer due to urban heating promotes intense convection and heavy rainfall in conjunction with the enhanced upward motion at intersecting convergence zones. This study suggests that better representations of surface heat and moisture fluxes in urban areas along major water bodies are required to better capture the timing and location of severe thunderstorms and heavy rainfall.


2014 ◽  
Vol 53 (7) ◽  
pp. 1697-1713 ◽  
Author(s):  
Christopher P. Loughner ◽  
Maria Tzortziou ◽  
Melanie Follette-Cook ◽  
Kenneth E. Pickering ◽  
Daniel Goldberg ◽  
...  

AbstractMeteorological 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.


2012 ◽  
Vol 72 (3-4) ◽  
pp. 335-353 ◽  
Author(s):  
Ryan M. Stauffer ◽  
Anne M. Thompson ◽  
Douglas K. Martins ◽  
Richard D. Clark ◽  
Daniel L. Goldberg ◽  
...  
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2012 ◽  
Vol 51 (10) ◽  
pp. 1775-1793 ◽  
Author(s):  
Christopher P. Loughner ◽  
Dale J. Allen ◽  
Da-Lin Zhang ◽  
Kenneth E. Pickering ◽  
Russell R. Dickerson ◽  
...  

AbstractUrban 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.


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