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Title: Evaluation of a mesoscale atmospheric dispersion modeling system with observations from the 1980 Great Plains mesoscale tracer field experiment. Part I: Datasets and meterological simulations

Abstract

A mesoscale atmospheric dispersion (MAD) numerical modeling system, consisting of a mesoscale meteorological model coupled to a mesoscale Lagrangian particle dispersion model, was used to simulate transport and diffusion of a perfluorocarbon tracer-gas cloud for a surface release during the July 1980 Great Plains mesoscale tracer field experiment. Ground-level concentration (GLC) measurements taken downwind of the release site up to three days after the tracer release were available for comparison. Quantitative measures of significant dispersion characteristics obtained from analysis of the tracer cloud`s moving GLC {open_quotes}footprint{close_quotes} were used to evaluate the simulation of the MAD case. MAD is more dependent on the spatial and temporal structure of the transport wind field than is short-range atmospheric dispersion. For the tracer experiment, the observations suggest that the nocturnal low-level jet played an important role in transporting and deforming the tracer cloud. Ten two- and three-dimensional numerical meteorological experiments were devised to investigate the relative contributions of topography, other surface inhomogeneities, atmospheric baroclinicity, synoptic-scale flow evolution, and meteorological model initialization time to the structure and evolution of the low-level mesoscale flow field and thus to MAD. Results from the meteorological simulations are compared in this paper. The predicted wind fields display significant differences,more » which give rise in turn to significant differences in predicted low-level transport. The presence of an oscillatory ageostrophic component in the observed synoptic low-level winds for this case is shown to complicate initialization of the meteorological model considerably and is the likely cause of directional errors in the predicted mean tracer transport. A companion paper describes the results from the associated dispersion simulations. 76 refs., 13 figs., 6 tabs.« less

Authors:
;  [1]
  1. Colorado State Univ., Fort Collins, CO (United States)
Publication Date:
OSTI Identifier:
274059
Resource Type:
Journal Article
Resource Relation:
Journal Name: Journal of Applied Meteorology; Journal Volume: 35; Journal Issue: 3; Other Information: PBD: Mar 1996
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; METEOROLOGY; SIMULATION; LONG-RANGE TRANSPORT; MATHEMATICAL MODELS; PARTICULATES; AIR-BIOSPHERE INTERACTIONS; OKLAHOMA; DISPERSIONS

Citation Formats

Moran, M.D., and Pielke, R.A.. Evaluation of a mesoscale atmospheric dispersion modeling system with observations from the 1980 Great Plains mesoscale tracer field experiment. Part I: Datasets and meterological simulations. United States: N. p., 1996. Web. doi:10.1175/1520-0450(1996)035<0281:EOAMAD>2.0.CO;2.
Moran, M.D., & Pielke, R.A.. Evaluation of a mesoscale atmospheric dispersion modeling system with observations from the 1980 Great Plains mesoscale tracer field experiment. Part I: Datasets and meterological simulations. United States. doi:10.1175/1520-0450(1996)035<0281:EOAMAD>2.0.CO;2.
Moran, M.D., and Pielke, R.A.. Fri . "Evaluation of a mesoscale atmospheric dispersion modeling system with observations from the 1980 Great Plains mesoscale tracer field experiment. Part I: Datasets and meterological simulations". United States. doi:10.1175/1520-0450(1996)035<0281:EOAMAD>2.0.CO;2.
@article{osti_274059,
title = {Evaluation of a mesoscale atmospheric dispersion modeling system with observations from the 1980 Great Plains mesoscale tracer field experiment. Part I: Datasets and meterological simulations},
author = {Moran, M.D. and Pielke, R.A.},
abstractNote = {A mesoscale atmospheric dispersion (MAD) numerical modeling system, consisting of a mesoscale meteorological model coupled to a mesoscale Lagrangian particle dispersion model, was used to simulate transport and diffusion of a perfluorocarbon tracer-gas cloud for a surface release during the July 1980 Great Plains mesoscale tracer field experiment. Ground-level concentration (GLC) measurements taken downwind of the release site up to three days after the tracer release were available for comparison. Quantitative measures of significant dispersion characteristics obtained from analysis of the tracer cloud`s moving GLC {open_quotes}footprint{close_quotes} were used to evaluate the simulation of the MAD case. MAD is more dependent on the spatial and temporal structure of the transport wind field than is short-range atmospheric dispersion. For the tracer experiment, the observations suggest that the nocturnal low-level jet played an important role in transporting and deforming the tracer cloud. Ten two- and three-dimensional numerical meteorological experiments were devised to investigate the relative contributions of topography, other surface inhomogeneities, atmospheric baroclinicity, synoptic-scale flow evolution, and meteorological model initialization time to the structure and evolution of the low-level mesoscale flow field and thus to MAD. Results from the meteorological simulations are compared in this paper. The predicted wind fields display significant differences, which give rise in turn to significant differences in predicted low-level transport. The presence of an oscillatory ageostrophic component in the observed synoptic low-level winds for this case is shown to complicate initialization of the meteorological model considerably and is the likely cause of directional errors in the predicted mean tracer transport. A companion paper describes the results from the associated dispersion simulations. 76 refs., 13 figs., 6 tabs.},
doi = {10.1175/1520-0450(1996)035<0281:EOAMAD>2.0.CO;2},
journal = {Journal of Applied Meteorology},
number = 3,
volume = 35,
place = {United States},
year = {Fri Mar 01 00:00:00 EST 1996},
month = {Fri Mar 01 00:00:00 EST 1996}
}
  • A mesoscale atmospheric dispersion (MAD) numerical modeling system, consisting of a mesoscale meteorological model coupled to a mesoscale Lagrangian particle dispersion model (MLPDM), was used to simulate the emission, transport, and diffusion of a perfluorocarbon tracer-gas cloud for a surface release during a tracer field experiment. The MLPDM was run for a baseline simulation and seven sensitivity experiments. The baseline simulation showed considerable skill in predicting peak ground-level concentration (GLC), maximum cloud width, cloud arrival and transit times, and crosswind integrated exposure at downwind distances of 100 and 600 km. The baseline simulation also compared very well to simulations mademore » by seven other MAD models for the same case in an earlier study. The sensitivity experiments explored the impact of various factors on MAD, especially the diurnal heating cycle and physiographic and atmospheric inhomogeneities, by including or excluding them in different combinations. The GLC footprints predicted in sensitivity experiments were sensitive to differences in simulated meteorological fields. The observations and numerical simulations suggest that the nocturnal low-level jet played an important role in transporting and deforming the tracer cloud during this MAD experiment: the mean transport speed was supergeostrophic and both crosswind and alongwind cloud spreads were larger than can be explained by turbulent diffusion alone. The contributions of differential horizontal advection and mesoscale deformation to MAD dominate those of small-scale turbulent diffusion for this case, and Pasquill`s delayed-shear enhancement mechanism for horizontal diffusion appears to have played a significant role during nighttime transport. These results demonstrate the need in some flow regimes for better temporal resolution of boundary layer vertical shear in MAD models than is available from the conventional twice-daily rawinsonde network. 34 refs., 14 figs., 4 tabs.« less
  • The mesoscale dispersion modeling system (MDMS) described herein is under development as a simulation tool to investigate atmospheric flow and pollution dispersion over complex terrain for domains up to several hundred kilometers. The system includes a three-dimensional mesoscale meteorological model (MESO), a Lagrangian particle dispersion (LPD) model, and an Eulerian grid dispersion (EGD) model based on numerical solution of K-theory advection-diffusion equations. These two dispersion models can be used separately, or they can be linked together as a hybrid Lagrangian-Eulerian dispersion model. The MDMS has been designed for use on personal computers and workstations. This paper provides a compact descriptionmore » of the present status of the modeling system and its applications. Numerical simulations performed for a complex region of the east coast of the United States demonstrate two complementary approaches to air-pollution dispersion modeling available in the MDMS: traditional source-oriented modeling, and receptor-oriented modeling. 41 refs., 9 figs., 1 tab.« less
  • Here, the Quick Urban & Industrial Complex (QUIC) atmospheric transport, and dispersion modelling, system was evaluated against the Joint Urban 2003 tracer-gas measurements. This was done using the wind and turbulence fields computed by the Weather Research and Forecasting (WRF) model. We compare the simulated and observed plume transport when using WRF-model-simulated wind fields, and local on-site wind measurements. Degradation of the WRF-model-based plume simulations was cased by errors in the simulated wind direction, and limitations in reproducing the small-scale wind-field variability. We explore two methods for importing turbulence from the WRF model simulations into the QUIC system. The firstmore » method uses parametrized turbulence profiles computed from WRF-model-computed boundary-layer similarity parameters; and the second method directly imports turbulent kinetic energy from the WRF model. Using the WRF model’s Mellor-Yamada-Janjic boundary-layer scheme, the parametrized turbulence profiles and the direct import of turbulent kinetic energy were found to overpredict and underpredict the observed turbulence quantities, respectively. Near-source building effects were found to propagate several km downwind. These building effects and the temporal/spatial variations in the observed wind field were often found to have a stronger influence over the lateral and vertical plume spread than the intensity of turbulence. Correcting the WRF model wind directions using a single observational location improved the performance of the WRF-model-based simulations, but using the spatially-varying flow fields generated from multiple observation profiles generally provided the best performance.« less