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Stephen Berman, Jia-Yeong Ku, and S. Trivikrama Rao

Abstract

A study of the temporal and spatial variations of mixing layer height over the Ozone Transport Region of the northeastern United States for the summer of 1995 is presented using meteorological data obtained from the North American Research Strategy for Tropospheric Ozone-Northeast (NARSTO-NE) 1995 field program. Rawinsonde balloon soundings made every 4 h during 13 ozone episode days during NARSTO-NE provided the principal source of upper-air data, supplemented by virtual temperature profiles from five radio acoustic sounder system sites. Forty-four weather stations provided surface data. Daytime mixing depths were estimated using a profile-intersection technique. The height of the surface inversion was used as a measure of the depth of the turbulent boundary layer at night.

For the 13 ozone episode days, the average maximum mixing depth ranged from less than 500 m offshore to greater than 2000 m inland, with most of the increase occurring within the first 100 km of the coastline. The coefficient of variation of maximum mixing depths averaged over the 13 episode days varied from 0.65 at coastal stations to 0.19 at inland locations. Greater variability at the coast may be caused by the interplay of sea-breeze circulations with synoptic wind patterns there. The rate of growth of the mixing depth between 0600 and 1000 EST (UTC − 5 h) averaged 165 m h−1 for all stations, ranging from 20–60 m h−1 at coastal sites to more than 350 m h−1 at inland stations. Ventilation coefficients were about 50% lower on ozone episode days than on nonepisode days from 0700–0900 EST.

For the ozone episode of 13–15 July a comparison was made of mixing depth estimates from three different methods: rawinsonde virtual potential temperature profiles, C2n (the atmosphere’s refractive index structure parameter), and output from running the Fifth-Generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5) version 1, a widely used nonhydrostatic mesoscale model. Estimates obtained from the three methods varied by as much as 200 m at night and by up to 500 m during the daytime. Mixing depths obtained from running MM5 were in good agreement with estimates from the other methods at Gettysburg, Pennsylvania, an inland station, but were 10%–20% too low at New Brunswick, New Jersey, a location within 30 km of the Atlantic coast. The discrepancy may be caused by the model’s 12-km grid spacing being too coarse to locate the marine–continental airmass boundary with high precision.

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S. Trivikrama Rao, Leon Sedefian, and Ulrich H. Czapski

Abstract

The primary objective of this study is to assess the effect of traffic on the turbulence structure and to infer the time and space scales of the eddies generated by the traffic. To this end, time series of wind and temperature were obtained by a three-component sonic anemometer and by copper-constantan thermo-couples adjacent to the Long Island Expressway in New York State. Eddy fluxes of heat and momentum were computed under different atmospheric conditions. Spectral distributions of these parameters were obtained using the fast Fourier transform technique. The flow characteristics in the surface layer are inferred from the wind profiles adjacent to the highway.

Results show a distinct bulge in the high-frequency range of the wind spectrum. This bulge appears only during moderate to heavy traffic conditions and with wind across the highway. This traffic-induced turbulent energy appears to be dominant at mean frequencies to 0.1–1.0 Hz corresponding to eddy sizes of the order of a few meters. Even under quite stable atmospheric conditions, no organized convection due to vehicle exhaust heat can be distinguished in the spectral structure. The aerodynamic drag due to the moving vehicles on the highway is manifested by a pronounced acceleration of wind in the lowest 8 m, especially in the cases of wind directions nearly parallel to the highway. The impact of traffic-induced turbulence on the near-roadway dispersion of air pollutants is also discussed.

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Gopal Sistla, Winston Hao, Jia-Yeong Ku, George Kallos, Kesu Zhang, Huiting Mao, and S. Trivikrama Rao

In this paper, the performance of two commonly used regional-scale Eulerian photochemical modeling systems, namely, RAMS/UAM-V and MM5/SAQM, from the regulatory or operational perspective, is examined. While the Urban Airshed Model with Variable Grid (UAM-V) is driven with the meteorological fields derived from the Regional Atmospheric Model System (RAMS), the San Joaquin Valley Air Quality Model (SAQM) used the meteorological fields derived from the Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model Version 5 (MM5). The model's performance in reproducing the observed ozone air quality over the eastern United States is evaluated for three typical high-ozone episodic events that occurred during 16–20 June, 12–16 July, and 30 July–2 August of 1995. The prevailing meteorological conditions associated with these three episodes are characterized by a slow eastward-moving high pressure system, westerly and southwesterly low-level jets, stable boundary layers, and the Appalachian lee-side trough. The results suggest that the performance of RAMS/UAM-V and MM5/SAQM systems in reproducing the observed ozone concentrations is comparable when model outputs are averaged over all simulated days. For different emissions reduction (i.e., volatile organic compound and nitrogen oxide controls) options, the response of both modeling systems, in terms of changes in ozone levels, was directionally similar, but the magnitude of ozone improvement differed from individual episode days at individual grid cells.

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Robert E. Eskridge, Jia Yeong Ku, S. Trivikrama Rao, P. Steven Porter, and Igor G. Zurbenko

The removal of synoptic and seasonal signals from time series of meteorological variables leaves datasets amenable to the study of trends, climate change, and the reasons for such trends and changes. In this paper, four techniques for separating different scales of motion are examined and their effectiveness compared. These techniques are PEST, anomalies, wavelet transform, and the Kolmogorov–Zurbenko (KZ) filter. It is shown that PEST and anomalies do not cleanly separate the synoptic and seasonal signals from the data as well as the other two methods. The KZ filter method is shown to have the same level of accuracy as the wavelet transform method. However, the KZ filter method can be applied to datasets with missing observations and is much easier to use than the wavelet transform method.

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Christian Hogrefe, S. Trivikrama Rao, Igor G. Zurbenko, and P. Steven Porter

To study the underlying forcing mechanisms that distinguish the days with high ozone concentrations from average or nonepisodic days, the observed and model-predicted ozone time series are spectrally decomposed into different temporal components; the modeled values are based on the results of a three-month simulation with the Urban Airshed Model—Variable Grid Version photochemical modeling system. The ozone power spectrum is represented as the sum of four temporal components, ranging from the intraday timescale to the multiweek timescale. The results reveal that only those components that contain fluctuations with periods equal to or greater than one day carry the information that distinguishes ozone episode days from nonepisodic days. Which of the longer-term fluctuations is dominant in a particular episode varies from episode to episode. However, the magnitude of the intraday fluctuations is nearly invariant in time. The promulgation of the 8-h standard for ozone further emphasizes the importance of longer-term fluctuations embedded in ozone time series data. Furthermore, the results indicate that the regional photochemical modeling system is able to capture these features. This paper also examines the effect of simulation length on the predicted ozone reductions stemming from emission reductions. The results demonstrate that for regulatory purposes, model simulations need to cover longer time periods than just the duration of a single ozone episode; this is necessary not only to perform a meaningful model performance evaluation, but also to quantify the variability in the efficacy of an emission control strategy.

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Brian Eder, Daiwen Kang, S. Trivikrama Rao, Rohit Mathur, Shaocai Yu, Tanya Otte, Ken Schere, Richard Wayland, Scott Jackson, Paula Davidson, Jeff McQueen, and George Bridgers

The National Air Quality Forecast Capability (NAQFC) currently provides next-day forecasts of ozone concentrations over the contiguous United States. It was developed collaboratively by NOAA and Environmental Protection Agency (EPA) in order to provide state and local agencies, as well as the general public, air quality forecast guidance. As part of the development process, the NAQFC has been evaluated utilizing strict monitor-to-gridcell matching criteria, and discrete-type statistics of forecast concentrations. While such an evaluation is important to the developers, it is equally, if not more important, to evaluate the performance using the same protocol as the model's intended application. Accordingly, the purpose of this article is to demonstrate the efficacy of the NAQFC from the perspective of a local forecaster, thereby promoting its use. Such an approach has required the development of a new evaluation protocol: one that examines the ability of the NAQFC to forecast values of the EPA's Air Quality Index (AQI) rather than ambient air concentrations; focuses on the use of categorical-type statistics related to exceedances and nonexceedances; and, most challenging, examines performance, not based on matched grid cells and monitors, but rather over a “local forecast region,” such as an air shed or metropolitan statistical area (MSA). Results from this approach, which is demonstrated for the Charlotte, North Carolina, MSA and subsequently applied to four additional MSAs during the summer of 2007, reveal that the quality of the NAQFC forecasts is generally comparable to forecasts from local agencies. Such findings will hopefully persuade forecasters, whether they are experienced with numerous tools at their disposal or inexperienced with limited resources, to utilize the NAQFC as forecast guidance.

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