FLACS CFD air quality model performance evaluation with Kit Fox, MUST, Prairie Grass, and EMU observations

Hanna, Steven R.; Hansen, Olav R.; Dharmavaram, Seshu

doi:10.1016/j.atmosenv.2004.05.041

Cited by 215 publications

(117 citation statements)

References 16 publications

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“…Many authors have utilised this approach to analyse model performance against the MUST data (e.g. Warner et al, 2006;Milliez and Carissimo, 2007) while other authors have used the Arcmax approach for the MUST data (Hanna et al, 2004a(Hanna et al, , 2006(Hanna et al, , 2007(Hanna et al, , 2008, and for full scale urban tracer data, e.g. Madison Square Garden (Hanna et al, 2004b) and JointUrban2003 (Allwine et al, 2004).…”

Section: A C C E P T E D Article In Pressmentioning

confidence: 99%

Evaluation of results of a numerical simulation of dispersion in an idealised urban area for emergency response modelling

Donnelly

Lyons

Flassak

2009

Atmospheric Environment

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Donnelly, R.P. , Lyons, T.J. and Flassak, T. (2009) Evaluation of results of a numerical simulation of dispersion in an idealisedThis is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. M A N U S C R I P T A C C E P T E D ARTICLE IN PRESSEvaluation of results of a numerical simulation of dispersion in an idealised urban area for emergency response modelling. AbstractWinMISKAM is evaluated from an emergency response perspective. Comparisons are made between ground level concentrations observed during selected Mock Urban Setting Test (MUST) field trials and predictions generated by the model. The model was driven by 5 minute averaged on-site meteorological data, and used minimum grid spacing of 0.5 m in both the horizontal and vertical. The code was found to perform well, with 46% of all predictions (paired in time and space) and 83% of arc maxima predictions within a factor of two of observed concentrations. The model was found to perform better for neutral cases than stable cases with 27% of stable case predictions and 57% of neutral case predictions within a factor of two when compared in time and space.

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Section: A C C E P T E D Article In Pressmentioning

confidence: 99%

Evaluation of results of a numerical simulation of dispersion in an idealised urban area for emergency response modelling

Donnelly

Lyons

Flassak

2009

Atmospheric Environment

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“…Several of the statistical performance measures recommended by Hanna et al (2005) are used to assess the performance of our model. They are: the fraction of predictions within a factor of two or five (FAC2 or FAC5), fractional bias (FB), geometric mean bias (MG), and normalized mean square error (NMSE).…”

Section: Modal-data Comparisonmentioning

confidence: 99%

A Validation of FEM3MP with Joint Urban 2003 Data

Chan

Leach

2007

Journal of Applied Meteorology and Climatology

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Under the sponsorship of the U.S. DOE and DHS, we have recently developed a computational fluid dynamics (CFD) model for simulating airflow and dispersion of chemical/biological agents released in urban areas. Our model, FEM3MP, is based on solving the three-dimensional, time-dependent Navier-Stokes equations with appropriate physics submodels on massively parallel computer platforms. It employs finite-element discretization for effective treatment of complex geometries and a semi-implicit projection scheme for efficient timeintegration. A simplified CFD approach, using both explicitly resolved and virtual buildings, was can be a cost-effective tool for simulating urban dispersion problems.

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“…These typically include, the normalized mean square error (NMSE), the fraction of predictions within a factor of 2 of the observations (FAC2), the fractional bias (FB), the geometric mean bias (MG) and the geometric variance (VG) (see Appendix A for definitions). In the absence of any universally agreed performance criteria, when authors wish to compare their results to those of others, they generally cite the criteria for an 'acceptable model' proposed by Chang and Hanna (e.g., [16][17][18][19][20][21][22]), which are summarized in Table 2. The Chang and Hanna criteria were based on their experience in conducting a large number of model evaluation exercises [23].…”

Section: Performance Metricsmentioning

confidence: 99%

A Review of Methodology for Evaluating the Performance of Atmospheric Transport and Dispersion Models and Suggested Protocol for Providing More Informative Results

Herring

Huq

2018

Fluids

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Many models exist for predicting the atmospheric transport and dispersion of material following its release into the atmosphere. The purpose of these models may be to support air quality assessments and/or to predict the hazard resulting from releases of harmful materials to inform emergency response actions. In either case it is essential that the user understands the level of predictive accuracy that might be expected. However, contrary to expectation, this is not easily determined from published comparisons of model predictions against data from dispersion experiments. The paper presents and reviews the methods adopted and issues involved in comparing the predictive performance of atmospheric transport and dispersion models to experimental data, by reference to a number of experimental data sets and comparison results. It then presents an approach which is designed to make the performance of atmospheric dispersion models more transparent, through clearly defining the basis on which the comparison is made, and comparing the performance of the chosen model to that of a reference model. Such an approach establishes a clear baseline against which the accuracy of models can be evaluated and the performance benefits of more sophisticated approaches quantified. The use of a simple analytic reference model applicable to continuous ground level releases in open terrain and urban areas is shown as a proof-of-principle.

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FLACS CFD air quality model performance evaluation with Kit Fox, MUST, Prairie Grass, and EMU observations

Cited by 215 publications

References 16 publications

Evaluation of results of a numerical simulation of dispersion in an idealised urban area for emergency response modelling

Evaluation of results of a numerical simulation of dispersion in an idealised urban area for emergency response modelling

A Validation of FEM3MP with Joint Urban 2003 Data

A Review of Methodology for Evaluating the Performance of Atmospheric Transport and Dispersion Models and Suggested Protocol for Providing More Informative Results

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