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Ariel F. Stein
and
John C. Wyngaard

Abstract

Atmospheric dispersion models are widely used to estimate the impact of nonreactive pollutant releases into the atmosphere. Most such models predict the ensemble-average concentration field, the average over a large collection of releases under similar externally imposed conditions. The stochastic nature of pollutant dispersion in the atmospheric boundary layer (ABL) makes pollutant concentrations vary greatly from one sampling period to another under the same meteorological conditions, however. Therefore, if the sampling time is not sufficiently long, the values predicted by even a perfect model will inevitably differ from mean values measured in the atmosphere. The ratio of their root-mean-square difference and the ensemble-average concentration is called the inherent uncertainty. This work investigates the relationship between inherent uncertainty in laboratory and ABL flows. This relationship provides a way to use laboratory measurements to estimate the inherent uncertainty in ABL flows. For a given averaging time, it is shown that the inherent uncertainty in laboratory flows is smaller than in the ABL under the same stability and statistical conditions. This result is illustrated with the Willis–Deardorff convection tank data to show that the values of the inherent uncertainty in pollutant dispersion from a near-surface source in the ABL exceed 50% for an averaging time on the order of 1 h.

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Fong Ngan
and
Ariel F. Stein

Abstract

A long-term archive of meteorological data using the Weather Research and Forecasting (WRF) Model was created to provide data that are compatible with the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) dispersion model and to serve as initial and boundary conditions for simulations at a finer resolution. On the basis of these WRF data, generated with a variety of planetary boundary layer (PBL) schemes and nudging options, the HYSPLIT model was run to simulate four controlled tracer experiments—the Cross Appalachian Tracer Experiment (CAPTEX), the Across North America Tracer Experiment (ANATEX), a 1980 release in Oklahoma City, Oklahoma (OKC80), and the Metropolitan Tracer Experiment (METREX)—covering different time periods with diverse durations, including a summer day, several days in autumn, three months during winter, and one full year, respectively. The evaluation of the WRF results utilizing conventional observations showed a similar statistical performance for the different PBL schemes. Given the limited information the meteorological evaluation alone can provide, the authors used the dispersion evaluation with measurements from multiple tracer experiments to gain further insight into the most appropriate WRF configuration to generate reasonable data for dispersion applications. The dispersion simulations that were based on WRF data generated equal or slightly better statistical performance than did those driven by the North American Regional Reanalysis (NARR) dataset. The statistical comparison showed a mixed impact for the dispersion results driven by the nonnudged and nudged WRF data. The main advantage of the WRF data is the availability of hourly meteorological data from 1980 to the present and the inclusion of additional variables that are relevant to atmospheric dispersion and are not available from NARR. This WRF dataset will be accessible online, providing additional capabilities for using different meteorological inputs and a variety of options to compute the HYSPLIT mixing parameters.

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Ariel F. Stein
,
Bruce B. Hicks
,
LaToya Myles
, and
Margaret Simon

Abstract

For over 75 years, the National Oceanic and Atmospheric Administration’s Air Resources Laboratory (NOAA ARL) has been at the forefront of federal meteorological and climate research. As the Special Projects Section (SPS) of the U.S. Weather Bureau (USWB), the laboratory pioneered the development of atmospheric trajectory modeling, initially used in studies related to nuclear weapons following World War II. Model development was guided by observations following weapons tests, assisted by later experiments using a wide variety of atmospheric tracers. Today’s familiar Gaussian plume dispersion model, previously in nascent form, was developed and promoted with ARL research, as was the much later and widely used HYSPLIT model. Much of ARL’s early research was focused on the challenges presented by the complex terrain surrounding nuclear installations, often addressed with high-spatial-resolution meteorological measurements, atmospheric tracers, and site-specific models. ARL has since extended boundary layer research to increasingly complex landscapes, such as forests, agricultural lands, and urban areas, and has expanded its research scope to air quality, weather, and climate applications based on the knowledge and experience developed throughout its long history. Examples of these research endeavors include the establishment of the U.S. Climate Reference Network, fundamental contributions to the development of the National Air Quality Forecast Capability, and foundational participation in the National Atmospheric Deposition Program. ARL looks forward to continuing to refine scientific understanding from field experiments, including coupling ground-based experimentation with modeling, and sustained observations, in order to facilitate the transfer of knowledge into practical applications of societal relevance.

Open access
Christopher P. Loughner
,
Benjamin Fasoli
,
Ariel F. Stein
, and
John C. Lin

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.

Open access
Ariel F. Stein
,
Glenn D. Rolph
,
Roland R. Draxler
,
Barbara Stunder
, and
Mark Ruminski

Abstract

A detailed evaluation of NOAA’s Smoke Forecasting System (SFS) is a fundamental part of its development and further refinement. In this work, particulate matter with a diameter less than or equal to 2.5-μm (PM2.5) concentration levels, simulated by the SFS, have been evaluated against satellite and surface measurements. Four multiday forest fire case studies, one covering the continental United States, two in California, and one near the Georgia–Florida border, have been analyzed. The column-integrated PM2.5 concentrations for these cases compared to the satellite measurements showed a similar or better statistical performance than the mean performance of the SFS for the period covering 1 September 2006–1 November 2007. However, near the surface, the model shows a tendency to overpredict the measured PM2.5 concentrations in the western United States and underpredict concentrations for the Georgia–Florida case. Furthermore, a sensitivity analysis of the model response to changes in the smoke release height shows that the simulated surface and column-integrated PM2.5 concentrations are very sensitive to variations in this parameter. Indeed, the model capability to represent the measured values is highly dependent on the accuracy of the determination of the actual injection height and in particular to whether the smoke injection actually occurred below or above the planetary boundary layer.

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Jennifer Hegarty
,
Roland R. Draxler
,
Ariel F. Stein
,
Jerome Brioude
,
Marikate Mountain
,
Janusz Eluszkiewicz
,
Thomas Nehrkorn
,
Fong Ngan
, and
Arlyn Andrews

Abstract

Three widely used Lagrangian particle dispersion models (LPDMs)—the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT), Stochastic Time-Inverted Lagrangian Transport (STILT), and Flexible Particle (FLEXPART) models—are evaluated with measurements from the controlled tracer-release experiments Cross-Appalachian Tracer Experiment (CAPTEX) and Across North America Tracer Experiment (ANATEX). The LPDMs are run forward in time driven by identical meteorological inputs from the North American Regional Reanalysis (NARR) and several configurations of the Weather Research and Forecasting (WRF) model, and the simulations of tracer concentrations are evaluated against the measurements with a ranking procedure derived from the combination of four statistical parameters. The statistical evaluation reveals that all three LPDMs have comparable skill in simulating the tracer plumes when driven by the same meteorological inputs, indicating that the differences in their formulations play a secondary role. Simulations with HYSPLIT and STILT demonstrate the benefit of using customized hourly WRF fields with 10-km horizontal grid spacing over the use of 3-hourly NARR fields with 32-km horizontal grid spacing. All three LPDMs perform better when the WRF wind fields in the planetary boundary layer are nudged to NARR, with FLEXPART benefitting the most. Case studies indicate that the nudging corrects an overestimate in plume transport speed possibly caused by a positive bias in WRF wind speeds near the surface. All three LPDMs also benefit from the use of time-averaged velocity and convective mass flux fields generated by WRF, but the impact on HYSPLIT and STILT is much greater than on FLEXPART. STILT backward runs perform as well as their forward counterparts, demonstrating this model’s reversibility and its suitability for application to inverse flux estimates.

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Glenn D. Rolph
,
Roland R. Draxler
,
Ariel F. Stein
,
Albion Taylor
,
Mark G. Ruminski
,
Shobha Kondragunta
,
Jian Zeng
,
Ho-Chun Huang
,
Geoffrey Manikin
,
Jeffery T. McQueen
, and
Paula M. Davidson

Abstract

An overview of the National Oceanic and Atmospheric Administration’s (NOAA) current operational Smoke Forecasting System (SFS) is presented. This system is intended as guidance to air quality forecasters and the public for fine particulate matter (≤2.5 μm) emitted from large wildfires and agricultural burning, which can elevate particulate concentrations to unhealthful levels. The SFS uses National Environmental Satellite, Data, and Information Service (NESDIS) Hazard Mapping System (HMS), which is based on satellite imagery, to establish the locations and extents of the fires. The particulate matter emission rate is computed using the emission processing portion of the U.S. Forest Service’s BlueSky Framework, which includes a fuel-type database, as well as consumption and emissions models. The Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model is used to calculate the transport, dispersion, and deposition of the emitted particulate matter. The model evaluation is carried out by comparing predicted smoke levels with actual smoke detected from satellites by the HMS and the Geostationary Operational Environmental Satellite (GOES) Aerosol/Smoke Product. This overlap is expressed as the figure of merit in space (FMS), the intersection over the union of the observed and calculated smoke plumes. Results are presented for the 2007 fire season (September 2006–November 2007). While the highest FMS scores for individual events approach 60%, average values for the 1 and 5 μg m−3 contours for the analysis period were 8.3% and 11.6%, respectively. FMS scores for the forecast period were lower by about 25% due, in part, to the inability to forecast new fires. The HMS plumes tend to be smaller than the corresponding predictions during the winter months, suggesting that excessive emissions predicted for the smaller fires resulted in an overprediction in the smoke area.

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