EVALUATION AND SENSITIVITY ANALYSES RESULTS 

OF THE MESOPUFF II MODEL WITH CAPTEX MEASUREMENTS 

by 

James M. Godowitch 

Atmospheric Sciences Modeling Division 

Atmospheric Research and Exposure Assessment Laboratory Research Triangle Park, North carolina 27711 

ATMOSPHERIC RESEARCH AND EXPOSURE ASSESSMENT LABORATORY 

OFFICE OF RESEARCH AND DEVELOPMENT 

U.S. ENVIRONMENTAL PROTECTION AGENCY 

RESEARCH TRIANGLE PARK, NORTH CAROLINA 27711 
EVALUATION AND SENSITIVITY ANALYSES RESULTS 

OF THE MESOPUFF II MODEL WITH CAPTEX MEASUREMENTS 

by 

James M. Godowitch 

Atmospheric Sciences Modeling Division 

Atmospheric Research and Exposure Assessment Laboratory 

Research Triangle Park, North Carolina 27711 

ATMOSPHERIC RESEARCH AND EXPOSURE ASSESSMENT LABORATORY 

OFFICE OF RESEARCH AND DEVELOPMENT 

U.S. ENVIRONMENTAL PROTECTION AGENCY 

RESEARCH TRIANGLE PARK, NORTH CAROLINA 27711 
DISCLAIMER 

The information in this document has been funded wholly or in part 

by the United States Environmental Protection Agency. It has been 

subject to the Agency's peer and administrative reviews, and has been 

approved for publication as an EPA document. 

AFFILIATION 

The author is on assignment to the Atmospheric Sciences Modeling 

Division, Atmospheric Research and Exposure Assessment Laboratory. from 

the National Oceanic and Atmospheric Administration, U.S. Department 

of Commerce. 

ii 
ABSTRACT 

The MESOPUFF II regional Lagrangian puff model has been evaluated 

and tested with the Cross-Appalachian Tracer Experiment (CAPTEX) data 

base. The model was applied to the six full-scale CAPTEX episodes in 

order to simulate the tracer plume formed from the 3-hour release of an 

inert, non-depositing perfluorocarbon tracer gas from either one of two 

selected sites. Surface tracer measurements were made at 3 hour or 6 hour 

intervals over an extensive sampling network of arcs downwind to 1100 krn 

in the northeastern U. S. and southeastern Canada. 

An operational evaluation was conducted by exercising the model 

transport and dispersion components with all default features set according 

to the user's guide. Transport in the model is simulated by a mixedlayer averaged wind field and an upper level wind field averaged from 

the mixing height to 700 mb level. Puff growth within 100 krn downwind 

is governed by horizontal and vertical dispersion parameters derived 

from expressions fitted to the standard PGT curves, while time dependent 

formulas are applied at greater distances. 

Model performance was quantitatively determined from standard statistical measures of difference and correlation between modeled and observed tracer concentrations paired in time and location. The model overpredicted peak and mean concentrations, whether paired in time and/or 

location. Modeled mean concentrations were within a factor of two of 

observed mean values in four of the experiments. The overpredictions 

are primarily attributed to an underestimation of vertical dispersion 

during neutral stability conditions which were specified during the afternoon hours after releases. Graphical maps and comparative tests between 

observed and modeled concentration pairs revealed that spatial displacements 

between the observed and modeled plumes contributed to the large scatter 

and low correlations found in the evaluation statistics. Analysis of plume 

centroid positions revealed that the greatest changes in the separation 

of the observed and modeled plumes occurred during the nocturnal periods. 

Revisions are suggested to better treat this source type in the model. 

Diagnostic model test results with optional wind fields in the model 

(e.g. surface, 850 mb single level wind fields) and various dispersion 

options are compared to those from the operational model and the observed 

data. A surface wind field transported the modeled plume considerably 

slower and generally to the left of the observed plume while the single 

level 850 mb wind field consistently shifted the modeled plume to the right 

(clockwise) of the actual plume location. Model results with the mixedlayer averaged wind field displayed the best overall performance in comparisons of the position and time of impact of the peak concentration with 

the observed plume values at the 300 krn arc. 

The 24-h peak and plume average concentration results from model test 

runs, which focused on different options and variations in key parameters 

of the the dry deposition and chemical transformation modules, are compared 

to base case values. All model runs were performed with SOx emissions 

from a realistic elevated point source. Peak S02 concentrations showed 

negligible variations when deposition or chemical transformation were omitted 

however, mean so2 concentrations in the plume were more sensitive. Mean 

and peak sulfate concentrations were more sensitive than S02 by variations 

in the surface resistance and by changes in parameters controlling the 

chemical transformation rate. 

iii 
CONTENTS 

Abstract ........................................................ . Figures ......................................................... . 

Tables .......................................................... . 

Acknowledgements ................................................ . 

1. INTRODUCTION ................................................. . 

2. DESCRIPTION OF MODEL COMPONENTS AND TECHNICAL FEATURES ....... . 

Wind Fields and Related Meteorological Parameters ......... . Dispersion Parameters ..................................... . 

Dry Deposition and Chemical Transformation Methods ........ . 

Model Grid System ......................................... . 

3. MODEL EVALUATION DATA BASE ................................... . 

Description of the Field Measurement Program .............. . 

Data Preparation for the Meteorological Processor ......... . 

4. MODEL EVALUATION PROCEDURES AND RESULTS ...................... . 

Operational Model Evaluation Analyses and Results ......... . 

Statistical Results for Mean and Peak Concentrations .. . Comparative Analyses of Plume Patterns and Positions .. . Diagnostic Model Test Results ............................. . 

5. MODEL SENSITIVITY RESULTS .................................... . 

6. SUMMARY AND CONCLUSIONS ...................................... . 

REFERENCES 

APPENDIX A Model test results for different 

puff release/sampling rates ................. . 

v 

iii 

vi 

viii 

X 

1 

4 

7 

10 

10 

12 

14 

14 

18 

30 

33 

33 

54 

64 

82 

93 

96 

99 
Number 

1 

2 

3 

4 

5 

6 

7 

8 

9 

10 

11 

LIST OF FIGURES 

Flow diagram of the MESOPUFF II modeling system ..... · · · · · · · · · · · 

Surface sampling network for the CAPTEX field program .. · · · · · · · · 

Meteorological grid in MESOPAC II for the Dayton cases 

of the CAPTEX field program .......................... · · · · · · · · · · 

Closest rawinsonde site (1 6) to each grid point in 

the MESOPAC II meteorological grid for Dayton cases ........ · · · · 

Surface meteorological stations considered in the 

MESOPAC II runs for the CAPTEX evaluation. Boundaries 

for meteorological grids are denoted (heavy solid and 

dashed lines) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . · · · · · · · · · 

Closest surface meteorological station (1 25) to 

each grid point in the MESOPAC II meteorological grid 

for Dayton cases during CAPTLX ........................ . 

Land use categories in the MESOPAC II meteorological 

grid for the Dayton cases during CAPTEX ....................... . 

Average concentrations obtained from sites with observed 

and modeled nonzero concentrations over the sampling 

periods-during a) CAPTEX #land b) CAPTEX #2 .................. . 

Same as lla-b, except for c) CAPTEX #3 and d) CAPTEX #4 

Same as lla-b, except for e) CAPTEX #5 and f) CAPTEX #7 

Cumulative frequency distributions of the model and 

observed concentrations from the entire data set .... 

Cumulative frequency distributions of model and observed 

concentrations for a) CAPTEX #l and b) CAPTEX #2 0 ••••••• . . . . . . 

Same as 13a-b, except for c) CAPTLX #3 and d) CAPT EX #4 ...... 

Same as 13a-b, except for e) CAPTEX #5 and f) CAPTEX #7 •••• 0 ••• 

Observed (0) and modeled (*) plume patterns depicted 

from sites with nonzero concentrations during; 

a) CAPTEX #l and b) CAPTEX #2 ................................. . 

Same as 8a-b, except for c) CAPTEX #3 and d) CAPTEX #4 

Same as 8a-b, except for e) CAPTEX #5 and f) CAPTEX #7 

vi 

5 

16 

19 

22 

23 

25 

29 

41 

42 

43 

44 

46 

47 

48 

56 

57 

58 
Number Figures (continued) Page 

12 Ratios of downwind distances of the model and observed 

plume centroid locations (D /D0 ) and separation 

distance between centroid pgsitions to the observed 

downwind distance (Ds/D0 ) versus time of day starting 

from the day of release. Negative and positive values 

for Ds/D0 denote the model plume position is to the 

right and left of the observed plume, respectively. 

a) CAPTEX #land b) CAPTEX #2 results ... . . . . . . . . . .. . .. . . . . . . . . . 61 

13 

14 

15 

16 

17 

Same as 9a-b, except for c) CAPTEX #3 and d) CAPTEX #4 

Same as 9a-b, except for e) CAPTEX #5 and f) CAPTEX #7 

a) Difference between the downwind distances of the 

centroid locations of the model (D ) and observed (D0 ) 

plume patterns versus time after r~lease. b) Separation distance (Ds) between model and observed 

plume centroid locations versus time after release. 

Symbols in both figures denote events for each experiment; 

CAPTEX #l (0), #2 (X), #3 (triangles), #4 (squares), 

#5 (stars), and #7 (diamonds) ................................. . 

Upper air wind speed (0) and wind direction (X) profiles 

at a) 18 GMT (i.e. 13 LST) and b) 00 GMT for CAPTEX #2 ........ . 

a) Wind speed (0) and wind direction (X) profiles and 

b) temperature profile at Dayton, Ohio from CAPTEX #3 

Tracer concentration pattern from aircraft flight legs 

at different levels during the afternoon of October 3, 1983 

during CAPTEX #3 .............................................. . 

Hourly variation of mixing height (Z·) from the 

MESOPAC II meteorological processor for Dayton, Ohio 

during September 18-19, 1983 of CAPTEX #l ..................... . 

62 

63 

65 

72 

74 

75 

81 

18 Average 24-h so2 concentration fields from the model 

base case run for 3a) Day 1 and b) Day 2. All values 

in units of JJg m- ............................................. 85-86 

19 Average 24-h sulfate concentration fields from the model 

base case for a) ~ay 1 and b) Day 2. All values 

in units of JJg m- ............................................. 87-88 

vii 
Number 

1 

2 

3 

4 

5 

6 

7 

8 

9 

10 

11 

LIST OF TABLES 

Calculation sequence of meteorological parameters 

in MESOPAC II ................................ · · · · · · · · · · · · · · · · · 

Computation sequence of the MESOPUFF II model code .. · · · · · · · · · · · · · 

Tracer release information for CAPTEX ............ · · · · · · · · · · · · · · · · 

Tracer sampling periods during each CAPTEX field experiment . · · · · · 

Upper air measurements and specifications ........... · · · · · · · · · · · · · 

Surface meteorological station information ........... · · · · · · · · · · · · 

Hourly surface observations and specifications ........... · · · · · 

Land use categories and surface roughness lengths 

for MESOPAC II . . . . . . . . . . . . . . . . . .............. · · · · · · · · · · · · · · · · 

Input control parameters and default features of 

MESOPAC II runs for CAPTEX episodes .......................... . 

Input parameters and specifications for MESOPUFF II runs ........ . 

MESOPUFF II model evaluation results: observed and 

modeled concentrations paired in time and location 

6 

8 

15 

15 

21 

24 

26 

28 

31 

32 

35 

12 Test results of modeled and observed concentrations 

13 

14 

15 

16 

17 

18 

19 

20 

paired in time and location . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37 

Selected statistical evaluation results for each event 

of the CAPTEX experiments .................................... . 

Distribution of observed and modeled concentrations 

over the entire CAPTEX data set .............................. . 

Peak observed and model concentrations 

paired in location only ...................................... . 

Peak observed and modeled concentrations paired in time only 

for the events of each CAPTEX experiments .................... . 

High-25 observed and modeled concentrations unpaired 

in time and location for each CAPTEX experiment .............. . 

Statistical results of observed and modeled concentrations 

paired in time and location from sampling arcs 

for CAPTEX #l-4 .............................................. . 

Peak observed and modeled concentrations unpaired in time 

and location for each arc from CAPTEX #l-4 .................... . 

Comparative results for different wind fields on 

peak concentration/plume transport 

at the 300 km arc for CAPTEX #l ............................... . 

viii 

39 

49 

so 

52 

53 

55 

55 

67 
Number 

21 

22 

23 

24 

25 

26 

27 

28 

29 

30 

Al 

Tables (continued) 

Comparative results for different wind fields on 

peak concentration/plume transport 

at the 300 km arc for CAPTEX #2 .............................. . 

Comparative results for different wind fields on 

at the 300 km arc for CAPTEX #3 .............................. . 

Comparative results for different wind fields on 

at the 300 km arc for CAPTEX #4 .............................. . 

Selected meteorological observations and model results 

at the release site for each CAPTEX experiment ............... . 

Results of analysis of observed upper air wind profiles 

for the CAPTEX release days .................................. . 

Peak concentrations for CAPTEX #l using 

various dispersion options ............ . 

Comparison of observed and modeled mixing heights 

Source characteristics and emission rates for all model 

sensitivity test runs ........................................ . 

Results of model sensitivity runs: Comparisons with 

24-h base case peak and mean concentrations .................. . 

Results of sensitivity runs from variations in 

select key parameters in the model ........................... . 

Differences in peak values at the initial arc 

for different puff release/sampling rates .................... . 

ix 

68 

69 

70 

71 

77 

79 

79 

83 

89 

91 

99 
ACKNOWLEDGEMENTS 

The author wishes to extend his appreciation to Terry Clark, Norman Possiel, 

and Jerome Heffter for their thorough reviews and helpful suggestions which were 

incorporated into this final report. Thanks are also expressed to Terry Clark 

for providing a copy of the CAPTEX data base and for the useful discussions 

concerning regional model evaluation methods. Appreciation is also expressed 

to James Reagan for his assistance with the land use inventory. 

X 
SECTION 1 

INTRODUCTION 

The ability of a regional-scale air quality model to reproduce 

spatial pollutant concentration fields or deposition patterns on a shortterm basis is strongly dependent upon its formulations for simulating the 

transport and dispersion processes. Models need to treat the important 

diurnal variations occurring in the mean and turbulent structure of the 

three-dimensional wind flow which directs the path of and impacts the 

spread of pollutant plumes. Thus, an evaluation of these crucial model 

components with field measurements is a critical element in establishing 

the credibity of any model. Although a comprehensive evaluation of all 

components in a model, including the chemical mechanism and removal methods, 

is highly desireable, the data necessary to undertake such an effort have 

been difficult to compile. 

Experimental field studies with certain tracer gases have provided 

valuable meteorological and concentration measurements on regional scales, 

which allow evaluations to focus on the transport and dispersion components 

of models. One of the most recent tracer data sets available for this 

purpose is the Cross-Appalachian Tracer Experiment (CAPTEX). This field 

program was was specifically designed and conducted with the intent of 

acquiring an accurate tracer data set from an extensive surface sampling 

network with concurrent upper air meteorological measurements for use in 

transport and dispersion model evaluation efforts. During the CAPTEX 

episodes, a chemically inert, non-depositing perfluorocarbon tracer gas 

was released at ground-level over a 3-h period from either one of two 

selected sites. Uncertainties often existing in emissions were minimized 

as the tracer emission rate was highly controlled and concentrations wer.e 

accurately measured above a relatively low ba~kground level. There was also 

no known interference from other sources to complicate the interpretation 

of the tracer measurements. The CAPTEX field program was conducted in the 

northeastern U.S. and southeastern Canada and the data base consists of a 

challenging set of seven experiments with measurements spanning up to two 

diurnal cycles in each episode. 

The results from a few models which have been applied to particular cases 

or to the entire CAPTEX data set have already been reported. Lee (1987) 

applied a particle-in-cell numerical model to all CAPTEX cases and relied 

heavily on various graphical analyses to investigate model performance. 

Even though plots of modeled and observed plume patterns showed relatively 

good qualitative agreement in most cases, a scatter diagram of modeled and 

observed concentration pairs showed considerable variability and no correlation. In fact, the large number of zero concentrations for either the 

observed or predicted values indicated that notable spatial plume displacements must have existed during the course of each experiement. 

The ARL (Air Resources Laboratory) Lagrangian puff model, which distributes 

mass vertically into different layers and transports the mass by different 

trajectories at each level, was evaluated in several ways with the CAPTL~ 

data base by Draxler (1987). Several model runs were performed with various 

1 
combinations of the meteorological surface and upper air data; some simulations 

applied finer spatial resolution and/or a more frequent temporal interval 

than the standard twice-daily profiles of the routine measurement network. 

Results were not conclusive as to whether improved spatial or temporal resolution in the input data produced more accurate model plume patterns. However, 

the best results for the plume trajectory were indeed found when both spatial 

and temporal resolutions were enhanced. Nevertheless, the predicted concentrations displayed order-of-magnitude differences from observed values when 

pairs were compared even when using the most highly-resolved input data. Thus, 

spatial plume displacements still were sufficient to produce large scatter and 

low correlations in concentration pairs in time and location. 

Davis et al. (1986) demonstrated the ability of a Lagrangian puff model 

(MLAM) . which allowed puffs to be vertically distributed and transported 

within seven vertical layers and also simulated decoupling from the surface, 

to explain the plume patterns in two CAPTEX episodes. While no statistical 

results were provided, the graphical displays showed the ability of this 

model to treat the considerable vertical direction shear present in one 

of the CAPTEX cases simulated. 

Most recently, a four-dimensional data assimilation technique incorporated 

into a three dimensional hydrodynamic model was also applied to two CAPTLX 

cases by Kao and Yamada (1988). who utilized it with a random-particle diffusion model. Their graphical results of concentration pairs revealed notable 

scatter. Differences between observed and simulated wind components, which 

developed with time over the modeled plume history were mainly attributed 

for the discrepancies in plume centerline positions. Spatial displacements 

were found to be larger in the latter stages of each episode. 

Clearly, the statistical and graphical analyses from these efforts revealed 

the difficulty that current models have in successfully replicating the threedimensional wind flows and dispersion processes that characterize the observed 

data, as exemplified by concentration differences and plume pattern displacements between the models and observations. 

In this report, the results of an evaluation and testing effort of the 

MESOPUFF II model (Scire et al., l984a,b) with the CAPTEX data base are 

presented. MESOPUFF II is a second generation Lagrangian puff model which 

was designed to treat transport, dispersion, chemical transformation, and 

the removal (dry and wet) processes impacting pollutant emissions from 

elevated point and/or area sources on a regional scale for short-term 

applications. Although the chemical and deposition modules were specifically 

developed for sulfur oxides and nitrogen oxides, any non-reacting and/or 

non-depositing gaseous species may be modeled by electing not to simulate 

these processes during model execution. Thus, no significant changes in 

the mode code were needed for this evaluation effort. 

The current operational version of MESOPUFF II (version 4.3) was applied 

and evaluated with the measurements obtained from six CAPTEX episodes. The 

model can take advantage of two different layer-averaged wind fields derived 

from surface and upper air data to transport a pollutant plume, while puff 

dispersion is treated with traditional dispersion parameters. Section 2 

describes the model system and provides the pertinent details about the 

methods employed in the model to simulate these processes, while Section 3 

2 
discusses the CAPTEX data base and preparation of the various input data 

for the model runs. 

Model performance was examined with various analyses techniques in 

order to investigate the model's ability to predict concentrations and 

plume patterns out to 1000 km from the tracer release sites. Thus, the 

analysis tools included, but were not limited to traditional statistical 

measures of difference and correlation between modeled and observed concentrations paired in time and/or location. While these statistical results 

provide useful quantitative information, the results of previous regional 

model evaluations with the CAPTEX data base have also shown the utility of 

various graphical analysis and more innovative quantitative measures, which 

helped clarify ·observed and modeled plume positions. Consequently, graphical 

displays are used to demonstrate qualitative spatial agreement between 

observed and simulated plumes, while analysis of plume centroid locations is 

the method applied to obtain quantitative measures of differences in the downwind position and separation of the respective plumes. In Section 4. all of 

these analysis techniques are employed in the evaluation process in order 

to obtain the best overall picture of the capabilities and limitations of 

the model for this particular application. 

Uncertainty should be considered in the analysis of model predictions. 

The uncertainty is caused by errors in the measurements, model formulation 

and model input errors, as well as the inherent uncertainty associated with 

the stochastic nature of turbulence and diffusion of a plume. The uncertainty 

is not addressed directly within the evaluation analyses. However, any 

inadequacy in the input data is pointed out where it may contribute to model 

error. Particular attention in the analyses will focus on highlighting shortcomings in the model's simulation of the transport and dispersion processes. 

Since the model evaluation with the CAPTEX data is limited to an assessment of the transport and dispersion components of the model system, a select 

group of model test runs was also undertaken to investigate the impact on 

pollutant concentrations from optional methods in the model or to changes 

to key technical parameters of the chemical transformation and dry deposition 

mechanisms. The model test runs simulated the SOx emissions from a single, 

elevated point source and apply the same meteorological fields from one of 

the CAPTEX episodes. Section 5 discusses the results of model test runs 

from comparisons of 24-h peak and average plume concentrations from each 

test simulation to those of a base case run. 

3 
SECTION 2 

DESCRIPTION OF MODEL COMPONENTS AND TECHNICAL FEATURES 

The principal program components of the model system and their 

important input/output features are depicted in Figure 1. In particular, 

separate computer codes perform the specific functions for processing 

various meteorological data (READ56, MESOPAC II), for computing pollutant 

concentrations (MESOPUFF II), and for postprocessing operations with 

the calculated concentrations from receptor sites and/or grid points 

(MESOFILE II). All of these model components were exercised during this 

evaluation and testing effort. An overview of the attributes of the 

model components is given herein and the essential details of the methods 

used to compute the parameters relevant to the transport and dispersion 

processes, and treatments of dry removal and chemical transformation are 

also presented. This information provides some background to assist in 

the interpretation of the evaluation results and sensitivity test runs. 

Complete details about the various methods in the model programs can be 

found in Scire et al. (1984a) and complete instructions for applying the 

model system and optional features are contained in Scire et al. (1984b). 

The READ56 processor program examines and reformats the twice-daily 

(i.e. 00 and 12 GMT) rawinsonde sounding measurements, and creates a 

formatted file of temperature and wind speed/direction profile data for 

each site. This program screens the profile measurements to determine 

if values at mandatory levels are missing. However, data quality assurance 

tests and inserting missing values must be performed by the user. 

MESOPAC II is the primary meteorological processor program. It 

generates hourly gridded fields of meteorological parameters from hourly 

surface meteorological observations, the upper air data files produced by 

READ56, and land use category information. Precipitation measurements are 

necessary when modeling wet episodes, otherwise these data are optional. 

Precipitation measurements were not used in this model evaluation effort 

as dry conditions existed during the CAPTEX episodes. Table 1 shows the 

execution sequence of the MESOPAC II program code and the order of calculation of meteorological parameters. The processor program is highly modular 

in that each parameter is computed within a separate su~routine. A single 

output file of gridded meteorological parameters is produced by MESOPAC II, 

which serves as the primary input file to the model program. 

Both processor programs were specifically designed to accept as input 

the various formatted meteorological data archived by the National Climatic 

Data Center in Ashville, North Carolina. The National Weather Service (NWS) 

upper air data (TDF5600 format) and hourly surface observations (CDl444 

format) are the expected data sets for these programs, although comparable 

observed data can be substituted if all the necessary variables have been 

measured. Hourly measurements of ceiling height, cloud cover, and nearsurface observations of temperature, pressure, wind speed and direction 

and relative humidity are required. ' 

4 
MESOPAC II 

Control Parameter 

lngut3 

MESO PUFF II 

Control Parameter 

Inputs 

MESO FILE II 

Control Parameter 

lncuu 

MESOFILE II 

Post:~rocassor Program 

REA056 Control 

Parameter lnouts 

MESOPAC II MeteoroiQ<Oical 

Preprocessor Prcqram 

MESOPUFF II DISPERSION MODEL 

~(Optional) 

Concenrrauon 

Tables 

READ 56 Ugper Air 

Preorocessor Program 

(Opuonal) 

Coneantraucn 

Tables 

Users 

Edtts 

Figure 1. Flow diagram of the MESOPUFF II modeling system. (Scire et al., 1984a) 

5 
TABLE 1 

CALCULATION SEQUENCE OF METEOROLOGICAL PARAMETERS IN MESOPAC II 

> READ USER INPUT FOR CONTROL AND TECHNICAL FEATURES 

> READ UPPER AIR PROFILE DATA (00 AND 12 GMT FOR FIRST SIMULATION DAY) 

< ITERATE OVER DAY(S) 

*COMPUTE SUNRISE/SUNSET TIMES, HOURLY SOLAR ELEVATION ANGLES 

> READ PRECIPITATION DATA (OPTIONAL) 

< ITERATE OVER HOURS 

> READ HOURLY SURFACE METEOROLOGICAL STATION OBSERVATIONS 

>IF HOUR IS 00 GMT, READ NEXT 12 GMT UPPER AIR PROFILE 

>IF HOUR IS 12 GMT, READ NEXT 00 GMT UPPER AIR PROFILE 

* CALCULATE SURFACE WIND FIELD AT GRID POINTS 

* CALCULATE PGT STABILITY CLASS AT GRID POINTS 

* CALCULATE SENSIBLE HEAT FLUX (H) AT GRID POINTS 

* CALCULATE FRICTION VELOCITY (U*) AT GRID POINTS 

* CALCULATE MIXING HEIGHT (Zi) AT GRID POINTS 

* CALCULATE OBUKHOV LENGTH (L) AT GRID POINTS 

* CALCULATE CONVECTIVE VELOCITY (W*) AT GRID POINTS 

* CALCULATE LOWER WIND FIELD AT EACH GRID POINT 

* CALCULATE UPPER WIND FIELD AT EACH GRID POINT 

* OUTPUT/STORE ALL GRIDDED METEOROLOGICAL PARAMETERS 

< END OF HOUR ITERATION 

< END OF DAY ITERATION 

* CLOSE FILES 

* END PROGRAM EXECUTION 

6 
MESOPUFF II computes hourly surface pollutant concentrations on a 

Cartesian grid and/or at user-specified, nongridded receptor sites. The 

model applies a Gaussian puff superposition technique to simulate a 

continuous plume by a series of individual puffs. The puff release and 

sampling rates, and source and emission information must be supplied by 

the user. Each puff is individually transported and its mass is subjected 

to dispersion, deposition (dry and/or wet) and chemical transformation. 

Table 2 reveals the overall execution sequence of the MESOPUFF II code 

and the order of simulation of the physical processes. Options exist 

that permit one or more of the removal mechanisms to be omitted or for 

input values to override default values of key technical parameters. 

The MESOFILE II postprocessor package is capable of performing 

various analyses of individual or multiple concentration files produced 

by the model. Time-averaging of concentrations may be performed in an 

evaluation effort or statistical results can be computed to investigate 

variations in concentration fields produced by different model runs. 

The latter function is particularly useful when conducting model 

sensitivity studies in a comparison of different results to a base case. 

WIND FIELDS AND RELATED METEOROLOGICAL PARAMETERS 

Two different layer-averaged wind fields are generated by MESOPAC II 

in the default mode. A mixed-layer averaged wind field is determined from 

hourly surface observations and twice-daily upper air profile data in order 

to represent the mean boundary layer flow pattern between the surface and 

mixing height (Zi). An upper wind field is determined over the layer from 

Zi to the 700 mb height. The user may override these default fields by 

selecting alternate wind fields according to particular input specifications 

(see Scire et al., 1984b). Optional wind fields include; a single level 

wind field for surface, 850 mb, 700 mb, or 500 mb levels, or vertically 

averaged winds from Zi to 850 mb or to 500 mb. A single wind field model 

is also possible by specifying the same wind field selection as the lower 

and upper level wind fields. 

The methodology to determine the layer-averaged wind fields consists 

of several steps. Surface wind components (us, vs) are determined at 

each grid point from the hourly surface station observations with the inverse 

distance-squared (l/d2) technique. An alignment weighting factor is also 

applied which gives greater consideration to measurements at sites more 

directly upwind or downwind of a grid point. The 00 GMT and 12 GMT rawinsonde 

profiles are assumed to be representative of neutral/unstable conditions and 

stable conditions, respectively. With the appropriate rawinsonde profile, 

layer-averaged wind speed and direction are computed from all measurements 

between the surface and the current Zi. Then the ratio of the layer-averaged 

and surface wind speeds <Rws), and the angular difference between the layeraveraged and surface wind directions (d8) at the rawinsonde site are determined 

Finally, the mixed-layer averaged horizontal wind components (Uml•Vml) at a 

grid point for a particular hour are computed by applying Rws and d8 from the 

closest rawinsonde site to the spatially-interpolated surface wind speed and 

direction, respectively, at that grid point. 

The layer-averaged upper wind field is determined by linear interpolation 

in time between soundings and averaging all data over the layer from Zi 

7 
TABLE 2 

COMPUTATION SEQUENCE OF THE MESOPUFF II MODEL CODE 

>READ INPUTS FOR TECHNICAL OPTIONS, GRID SIZE, SOURCES/&~ISSIONS 

> READ THE GRIDDED WIND FIELDS FOR INITIAL HOUR OF SIMULATION 

< ITERATE OVER THE HOURS FOR THE SIMULATION 

> READ OTHER GRIDDED METEOROLOGICAL PARAMETERS FOR CURRENT HOUR 

> READ GRIDDED WIND FIELDS FOR NLXT HOUR 

* INITIALIZE CONCENTRATION ARRAYS 

< PERFORM PUFF ITERATIONS 

* FOR NEW EMITTED PUFF - COMPUTE PLUME RISE 

< PERFORM PUFF SAMPLING ITERATIONS 

* TRANSPORT THE PUFF 

* COMPUTE AND APPLY DISPERSION PARAMETERS TO PUFF, ru~D 

TRANSFER MASS IF IN 3-LAYER MODE 

* CALCULATE AND APPLY CHEMICAL TRANSFORMATION RATE(S) 

* CALCULATE AND APPLY WET REMOVAL 

* CALCULATE AND APPLY DRY DEPOSITION 

* SAMPLE PUFF TO COMPUTE CONCENTRATION CONTRIBUTION 

AT GRID POINTS/NONGRIDDED RECEPTOR LOCATIONS 

< END PUFF SAMPLING ITERATIONS 

< END PUFF ITERATIONS 

* CALCULATE PUFF CONCENTRATIONS FOR NEXT HOUR'S CHEMISTRY 

*CALCULATE MULTI-HOUR AVERAGE CONCENTRATIONS, IF SPECIFIED 

* PRINT/STORE MODELED CONCENTRATIONS 

< END HOUR ITERATIONS 

* END PROGRAM EXECUTION 

8 
to the 700 mb height. The upper level wind components (Uul• Vul) are 

derived at each grid point by the l/d2 method with the summation of contri 

butions over the rawinsonde sites. 

The appropriate wind field for puff transport is automatically 

selected by a comparison of the puff center height (Zp) and the current 

Zi on an hourly basis The source height and any plume rise are summed 

t~ obt~in Zp. For Zp<Zi, a puff is advected with the lower level 

w~nd f~eld. If Z >Zi, the upper wind field is used to transport the 

puff and its grow~h is governed by stability class 5 (i.e. PGT class E by 

default). Puff splitting is not performed by this model. However, when 

the multi-layer model feature is exercised, puff mass can be transferred 

between the mixed-layer and upper layer. For example, the amount of mass 

removed from the mixed-layer depends on the fractional change of Zi since 

its peak value. This model feature is usually selected with the surface 

depletion method for dry deposition in an attempt to account for the large 

difference of boundary layer resistance to mixing at night compared to daylight hours. 

The mixing height has particularly important roles in this model 

because it is involved in both transport, as just discussed, and in 

dispersion processes. Since Zi is the demarcation level defining the 

vertical extent of the mixed-layer averaged wind field and the starting 

height of averaging for the upper level wind field, variations in Zi 

can lead to possibly notable differences in puff transport, especially 

when strong vertical shears in speed andjor direction exist. As in many 

models, Zi is also the critical height scale in vertical dispersion 

calculations. Thus, it is essential to model performance that the temporal 

behavior and spatial variations of Zi be simulated realistically. 

During the daylight hours, convective and mechanical mixing heights 

are computed with the greater of the two values being selected as Zi 

at each grid point. The convective mixing height (Zic) is strongly 

controlled by the surface sensible heat flux (H = w'T') and the temperature 

structure aloft. The behavior of H is highly dependent on the incoming 

solar radiation and the observed cloud cover. Eqs. (1) and (2) are used 

to compute Zic and the temperature discontinuity (~T) at the mixed-layer 

top, respectively, at the next hour (t+l) over an hourly time step (dt). 

2 (Zic + 2H(l+E)dt/~ 

t 

~T = (2 E ~ H dt)~ 

t+l 

+ ~T /~ 

t+l 

(l) 

(2) 

The potential temperature lapse rate (~) is determined over a 200 m layer 

(default) above Zic· An entrainment coefficient (E) is included in an 

effort to parameterize an additional contribution to zic growth from 

downward transport of warmer air with a default value forE of 0.15. 

A daytime mechanical mixing height (Zim) is computed from the 

surface friction velocity (U*) and the Brunt-Vaisala frequency (Nb) 

according to; 

9 
where f is the Coriolis parameter. During nocturnal hours, the 

mixing height is defined solely by Zim• which has an even stronger 

dependency on U* according to the empirical expression in Eq. 4. 

The current default value for C is 2400. 

The friction velocity is a function of the surface wind speed, 

surface roughness length (Z0 ), and a stability adjustment factor 

(Scire et al. ,1984a). The land use type for each grid point should 

( 3) 

(4) 

be accurately specified because Z0 is assigned internally based on 

representative values for the broad land use types of Sheih et al. (1979). 

DISPERSION PARAMETERS 

Each puff in the model is horizontally symmetric with a Gaussian 

distribution. Puff growth is governed by the horizontal and vertical 

dispersion parameters, ay and az. Values of these parameters are 

computed by power law functions which were derived from fits of the 

Turner (1970) curves. The form of these functions is given by; 

a = A Xb (5) 

where A and b vary with stability class and are different for ay and az 

(Scire et al., 1984b). Eq. (5) is applied to puff growth out to downwind 

distances (X) of 100 km (default). Thereafter, puff growth is determined 

with the time-dependent formulas of Heffter (1965). The crossover distance 

where the change in methods occurs may be overidden. An optional feature 

in the model uniformly disperses puffs throughout the mixed-layer depth 

immediately after being released. 

The stability class for each grid point is determined each hour 

according to the Turner (1964) method. Since these PGT stability 

classes are defined according to cloud cover, ceiling height, solar' 

elevation angle, and the surface wind speed, values can vary across the 

model grid each hour. Stability classes range from 1 (A very unstable) 

to 6 (F- moderately stable). 

DRY DEPOSITION AND CHEMICAL TRANSFORMATION METHODS 

Although the tracer gas which is the subject of this evaluation 

effort is nondepositing and chemically inert, the methodologies that 

simulate dry removal processes and determine the transformation rates in 

MESOPUFF II are described because the results of the sensitivity analyses 

in Section 5 are obtained from variations to the default methods. 

10 
Both of these physical processes are highly complex in the atmosphere 

and revisions to model formulations are often performed as new experimental 

information becomes available. Methods to simulate these processes must be 

species dependent. While MESOPUFF II is capable of simulating SOx and 

NOx simultaneously, the information contained in this overview is limited 

to this model's treatment of so2 and a secondary product, fine sulfate (S04 ). 

Dry deposition has received greater recognition over the past decade 

as an important removal process of pollutants over regional and larger scales 

Consequently, more resources have been devoted to obtaining experimental 

dry deposition measurements of certain pollutants (Hales et al., 1987), 

which has provided more information to improve our understanding of deposition processes and has advanced the development of deposition parameterization methods. There has also been a notable evolution in the treatment 

of dry deposition in models from the simple technique of specifying a 

constant deposition velocity of a specific pollutant, as in the first 

generation of MESOPUFF (Benkley and Bass, 1979) to a physically realistic 

method which attempts to account for the spatial and temporal variations 

in meteorological parameters and surface features that influence dry 

removal processes. Currently. atmospheric and surface resistances are 

commonly employed to compute spatially-averaged deposition velocities for 

grid cells by consideration of the proportion of various land use types 

within each cell (Walcek, et al., 1986). 

The dry deposition method in MESOPUFF II is also parameterized by a 

deposition velocity (Vd). In this scheme the removal processes consist 

of the vertical turbulent diffusion of pollutants through a turbulent 

atmospheric surface layer and a laminar sublayer, which is followed by 

uptake into the vegetative or surface material. Individual resistances 

are used to represent the ability of a species to transfer through the 

atmosphere and surface cover. The deposition velocity is computed as the 

inverse of the sum of individual resistances according as follows; 

·(6) 

where ra is the aerodynamic resistance, rb is the quasi laminar 

boundary layer resistance in the proximity of the canopy or surface 

interface and rs is the surface resistance. Values of ra and rb are 

temporally and spatially variable since both are dependent upon the 

meteorological conditions and land use. These aerodymamic resistances 

are computed from; 

(k U*)- 1(ln(z/Z0 ) - Sh 

(kU*)- 1kB-l 

(6a) 

(6b) 

where Sh is a stability correction factor and B is a surface transfer 

function. The value of kB-l for S02 is 2.6. However, rb is assumed 

to have a constant value of 1000 s/m for S04. Specifications for other 

modeled pollutants are given in the user guide (Scire et al., 1984b). 

11 
Surface resistances for so2 are a function of land use and stability 

class. The default values are specified internally in the module for 

summer conditions only and are the same as those in Sheih et al. (1979). 

For so4 , the total resistance is determined by the sum of ra and rb 

because rs is currently assigned to be zero in the module. 

In the multi-layer mode of the model, only puff mass within the mixed 

layer is subjected to dry deposition. In contrast, the source depletion 

method is exercised when the single layer mode of the model is selected. 

The treatment of chemical transformation in the atmosphere has also 

shown great advances. There is a hierarchy of methods to simulate chemical 

reactions and their rates that vary from the linear treatments with fixed 

transformation rates to sophisticated chemical mechanisms containing 

numerous reactions which require considerable computer resources. 

Chemical conversion of so2 to so4 in MESOPUFF II is controlled 

by a transformation rate which is computed from a parameterized expression. 

Scire et al. (1984a) described the photochemical model mechanism and 

analyses of the model simulation results which lead to defining the 

primary variables that dominated the transformation rates. Expressions 

for transformation rates were developed from statistical regression 

analyses of many photochemical model run results for a range of conditions. 

In particular, the hourly transformation rate (k) for S02 to sulfate 

for the daytime period is computed from; 

+ (7) 

where R is total solar radiation (kwatt/m2 ), 0 3 is the background 

ozone concentration (ppm), Sis the stability class, and RH is relative 

humidity(%). These parameters were found to be the dominant variables 

from regression analysis of the photochemical model results. Thus, 

chemical conversion of so2 is enhanced in the model under conditions of 

high solar radiation, strong dispersion, high background o3 , and high 

humidity. The default background 0 3 concentration in the model is 

currently 80 ppb, although the model is capable of accepting measured 

03 concentrations at sites within the model domain. Model run results 

in Scire et al. (1984a) indicated values for k were 2-3% per hour during 

the daytime, which were comparable to existing experimental results from 

field studies (Wilson, 1981). During the nocturnal period, the so2 

oxidation rate is set to 0.2% h- 1 . Equations comparable to (7) have 

also been developed for NOx transformation rates. 

GRID SYSTEM 

The grids for MESOPAC II and MESOPUFF II are based on a Cartesian 

coordinate reference frame. Since it is not constructed on a latitudelongitude framework, alignment differences between N-S grid lines and 

the true N-S direction lines defined by longitude can become serious for 

grid domains larger than a few hundred kilometers, especially at middle 

and high latitude regions. An approach used to minimize the impact of 

12 
this effect on the grid system for the CAPTEX region will be noted later. 

A meteorological grid defines the set of grid points where the 

meteorological parameters are computed by MESOPAC II. Currently, the 

computer code limits the size to 40 x 40 grid indices. The computational 

grid in MESOPUFF II can be defined to be the same size as the meteorological 

grid or a subset of it. When a puff travels beyond the computational grid, 

it is eliminated from further consideration in concentration calculations. 

A sampling grid defines the set of gridded receptor points where concentrations are computed and this grid may be identical to or a subset of the 

computational grid. The model is also capable of computing concentrations 

at so-called nongridded receptor locations. This model feature can be 

particularly useful in a model evaluation, such as in this application to 

the CAPTEX tracer sampling sites, since measurement networks are not designed 

according to a uniformly spaced grid. Model execution time is also reduced 

significantly by restricting concentration calculations to the nongridded 

receptor locations with an option to omit calculations for the sampling 

grid. The grid size and grid point spacing must be defined by the user in 

each application. Additional details and an example configuration of the 

model grid sjstems are presented in Scire et al. (1984b). 

13 
SECTION 3 

MODEL EVALUATION DATA BASE 

DESCRIPTION OF THE FIELD MEASUREMENT PROGRAM 

The field study phase of CAPTEX consisted of seven individual tracer 

releases from either Dayton, Ohio or Sudbury, Ontario over the period 

from mid-September to late October 1983. Information about each tracer 

experiment is given in Table 3. With the exception of experiment #6, which 

was very short to permit the start up of the next release from Sudbury, 

the amount of tracer gas emitted for these experiments was comparable. All 

releases were from ground level and a constant emission rate is assumed 

over a 3-hour period during each full-scale experiment. 

The first four tracer releases were undertaken from Dayton and the 

release periods were during afternoon hours (Table 3). In contrast, both 

Sudbury releases were conducted at night. Nevertheless, the meteorological 

conditions at both sites permitted strong vertical mixing and the prevailing 

wind pattern in each case provided the desired transport of the tracer 

plume across the study region. Dayton releases were performed when the 

region was under the influence of large high pressure systems. At the 

release site, wind flows were from the southwest or west and mostly fair 

or partly cloudy sky conditions existed. The Sudbury releases occurred 

after cold front passages with northwesterly winds and mostly cloudy skies. 

Brown et al. (1985) provides detailed synoptic maps and discusses the 

weather conditions for each CAPTEX episode. 

The field study region during CAPTEX encompassed the northeastern 

U. S. and southeastern Canada. The surface sampling network shown in 

Figure 2 was designed to encompass this area. It consisted of an array of 

individual arcs deployed at approximately 100 km intervals extending from 

300 km to about 1100 km from of Dayton. Each sampling site was designated 

by a 3-digit number (e.g. 302); the leading digit (3) signifying the arc 

number in hundreds of kilometers and the next two digits (02) representing 

a site's relative position along each arc with numbers increasing from 

south to north. 

The experimental measurement plan was to commence sampling concurrently 

at all sites along a given arc prior to the expected arrival of the tracer 

plume and to obtain measurements over the entire duration of plume passage. 

Each site was equipped with an automatic sequential sampler that was preset 

to collect tracer concentrations over a prescribed period. The tracer 

sampling system is described by Ferber et al. (1986). Tracer sampling 

began at the nearest arc soon after the start of a release, and at 3-h or 

6-h intervals later at subsequent arcs. The sampling interval was set to 

3-h at sites on the 300-km arc for Dayton releases and at some Canadian 

sites after the Sudbury releases to provide better temporal resolution near 

the release point. All other measurements were generally made over 6-h 

intervals. A maximum of six consecutive samples were obtained at each site, 

14 
TABLE 3 

TRACER# RELEASE INFORMATION FOR CAPTEX 

EXPT SITE DATE TIME AMOUNT RELEASED RATE 

(#) (1983) (LST) (kg) (g/s) 

1 DAYTON* 9/18 1200-1500 208 19.26 

2 DAYTON 9/25 1205-1505 201 18.61 

3 DAYTON 10/2 1400-1700 201 18.61 

4 DAYTON 10/14 1100-1400 199 18.44 

5 SUDBURY 10/25-6 2245-0145 180 16.67 

6 DAYTON 10/28 1030-1100 32 2.96 

7 SUDBURY 10/29 0100-0400 183 16.94 

* Released from Wright-Patterson Air Force Base, otherwise at 

Dayton International Airport (DAY). 

# Tracer used was perfluoromonomethylcyclohexane (C7H14) 

TABLE 4 

TRACER SAMPLING PERIOD FOR EACH CAPTEX FIELD EXPERIMENT 

EXPT START SAMPLING STOP SAMPLING$ DURATION 

(#) (DATE-TIME (LST) (DATE/TIME (LST) (hours) 

1 9/18-1400 9/20-0800 42 

2 9/25-1300 9/28-0400 63 

3 10/02-1600 10/04-1900 51 

4 10/14-1300 10/16-1000 45 

5 10/26-0300 10/28-0300 48 

6* 10/28-1100 10/29-0800 21 

7** 10/28-0100 10/30-0800 33 

$ Sampling end time for most sites up through the 1000 km arc. 

*Canadian sites were not put in operation in anticipation of #7. 

** One site continued sampling until 11-31/1500 

15 
• • 152 

052 

0 

854 

• • 853 

756 0 • 108 

• 912 107 654 • • 106 

• 0 

556 910 

0 

0 II 

0 614 0 810 

00 710 0 I-' 

0\ 0 908 

612 009 

0 0 

0 70B BOB 

610 

0 

412 0 007 

0 608 0 

50B 706 806 

G 0 

410 0 0 0 0314 0 0 

320 310 316 312 0 506 

4 08 

0 0 

310 406 504 • 

0 

• 604 

502 

0 

Figure 2. Surface sampling network for the CAPTEX field program. 
so measurements spanned either 18 or 36 hours. In most cases this sampling 

strategy was successful since the arrival and departure times of the tracer 

plume, and peak concentrations could be determined at each arc to within 

the averaging interval of the measurements. Table 4 lists the start time 

and most common ending time of sampling to reveal the overall duration of 

each experiment. Measurements at a few sites on the most distant arcs 

continued even later than those posted in Table 4. The sampling period for 

all experiments, with the exception of #6, extended over at least one diurnal 

cycle. Measurement periods for the four Dayton experiments covered episodes 

of approximately two full days before the actual tracer plume departed the 

sampling network. 

The acquisition of upper air meteorological data on more frequent 

temporal and finer spatial scales was also an important ingredient of the 

CAPTEX field program. During the experimental periods the National Weather 

Service rawinsonde sites in the CAPTEX region launched four rawinsondes 

daily at 6-hour intervals, instead of the routine twice-daily soundings. 

These supplemental soundings were made at 06 and 18 GMT. Even though the 

meteorological processor was not designed to accept these profiles as 

input, Zi observations from these soundings may be compared to 

modeled values and the intermediate wind profiles are also useful in 

diagnosing and interpreting the causes of model variations. There were 

10 additional upper air sites deployed in the region during this 

experimental program to provide greater spatial density of the rather 

sparse NWS rawinsonde network. Rawinsonde soundings were also performed 

during the tracer release periods at both release sites. 

Several research aircraft were specially-equipped with modified 

tracer samplers for the CAPTEX studies. Sampling flights were conducted 

to obtain the horizontal dimensions of the tracer plume at various levels 

at different downwind distances and aircraft soundings were conducted to 

investigate the vertical distribution of tracer. The aircraft flight paths 

for each experiment and listings of the tracer concentrations measured 

along each flight path are provided by Ferber et al. (1986). Since the 

aircraft tracer measurements represented spatially-averaged concentrations 

sampled over several minutes along a flight path at various heights above 

ground, these measurements will not be directly used in the quantitative 

statistical analysis of the model results. However, the aircraft 

measurements provided valuable information about the tracer plume 

position, and its spatial dimensions at various times and distances from 

the release point. The aircraft data can be helpful in an examination 

of modeled and observed plume locations and in qualitative assessments 

of modeled and observed concentrations when possible. Results of analyses 

of the horizontal and vertical distribution of the aircraft tracer data 

have been presented by Raynor et al. (1984) and Stunder et al. (1986), 

respectively. 

The tracer measurements collected at each sampling site were subjected 

to quality assurance audits and tests (Lagomarsino et al., 1987). Tracer 

concentrations were provided in units of femtoliters per liter (fl 1- 1 ) 

which is equivalent to parts per.l015 . Accardi~~ to Ferber et al. (1986), 

an ambient background concentrat~on of 3.4 fl 1 was subtracted from all 

tracer measurements. The final data base contained concentrations to the 

nearest 1 fl 1-l at each site with accompanying date/time (GMT) information, 

17 
and sampling interval (3 or 6 hours). The data base contained no entries 

for sampling periods when tracer concentrations were not collected at a site 

or when measurements were reiected by quality assurance procedures. A 

conversion factor of 1 fl 1- - 1.56xlo-ll g m 3 was applied to modeled 

concentrations for their evaluation against observations. 

DATA PREPARATION FOR THE METEOROLOGICAL PROCESSOR PROGRAM 

Prior to the selection of surface stations and data preparation for 

the model evaluation runs, a meteorological grid for MESOPAC II was 

designed with sufficient size and adequate resolution to cover the CAPTEX 

region. It was also decided to use different grid sizes for the Dayton 

and Sudbury cases. The meteorological grid was set to 30 x 19 for the 

Dayton cases and 30 x 24 for both Sudbury releases. However, the grid 

point spacing of 37 km was the same for both grids. Therefore, the grid 

domain covered an 1100 km x 700 km area for the Dayton cases and an 

1100 km X 888 km region for the Sudbury cases. The selection of the grid 

point spacing was partly based on the resolution of the land use inventory 

which will be discussed later. This combination of grid size and the grid 

point spacing provided sufficient coverage and spatial resolution of the 

study region. Figure 3 shows the meteorological grid for the Dayton cases. 

The release site is situated a sufficient distance from grid boundaries and 

the domain extends eastward to include the 1000 km arc. The northern boundary of the grid extended to 47°N for the Sudbury cases. These grid sizes 

appeared to stretch the applicability of this model grid system to a maximum 

limit due to the convergence of longitude lines with latitude. Differences 

in alignment of grid and longitude lines, taking the overall domain into 

consideration, were minimized by defining the N-S grid lines in the middle 

of the model domain to be parallel with longitude lines. Thus, alignment 

differences increased slowly toward the E-W boundaries. 

A magnetic tape of the CAPTEX data base contained the rawinsonde 

data, surface tracer concentrations, aircraft tracer data, ancillary 

meterological measurements from several towers, and terrain heights 

over the CAPTEX region according to the format specifications documented 

in Ferber et al. (1986). 

The rawinsonde sounding measurements at the release sites and the 

regular NWS upper air network sites were processed for input to MESOPAC II. 

Since a survey of the rawinsonde measurements from the 10 additional 

sounding sites revealed that winds were consistently missing for many 

levels within the boundary layer, these sites were not included in the 

meteorological processor runs. The wind and temperature records for each 

sounding were combined from separate blocks on the tape. An additional 

complication was that the significant wind and temperature reporting 

levels did not necessarily correspond, as temperatures were often detected 

at fewer levels. Consequently, an upper air profile with temperatures and 

winds at common levels up to 500 mb was constructed by deriving values by 

linear interpolation at heights where the other parameter was measured. 

The formatted upper air data files were reviewed to insure that soundings 

existed at 00 and 12 GMT for all days in the simulation period required to 

model each experiment. These files were also examined to make sure values 

existed at all mandatory levels (i.e. 1000, 850, 500 mb) because the MESOPAC II 

code ceases execution when an upper air profile or data are missing. Table 5 

18 
\ 

0 

... 

._PI 41.ocf 

r-~~--------------------1 

Figure 3. 

0 

YSB 

Meteorological grid in MESOPAC II for the Dayton cases 

of the CAPTEX field program. 
contains information about the upper air measurements required as input to 

MESOPAC II. These upper air data were subjected to various quality control/ 

assurance tests during processing and archival procedures (Ferber et al., 1986) 

Figure 4 displays the closest rawinsonde station to each grid point by a 

number from 1 to 6. There were six rawinsonde sites available for the Dayton 

cases. It is evident from Figure 4 that each site is assumed to represent 

a rather large section of the model grid, ranging from 300 km to over 400 km 

in most directions. 

The hourly surface meteorological observations at all regularly 

reporting stations in the northeastern United States and for several 

stations in Ontario were also obtained, as the processor cannot compute 

fields of meteorological parameters without hourly surface measurements. 

Since the number of stations available was much greater than MESOPAC II's 

limit of 25 sites, a single group of stations was selected and their 

observations were prepared for model input. Figure 5 shows the full set 

of stations selected for the model evaluation. These sites were chosen in 

order to cover the entire CAPTEX region and to also provide a relatively 

uniform intersite spacing across the region. The hourly observations at 

each release site were included as input for the experiments with a release 

from that site. Table 6 lists the entire group of stations whose observations 

were use as input for the model runs. A set of 25 stations was used in all 

cases, however, a few sites were only used in the Dayton experiments and 

other stations were substituted for the Sudbury cases. In particular, 

stations closer to a release location were selected in an attempt to provide 

better definition of the flow pattern around the time of release. For 

example, two stations in Indiana and one in Michigan were included in the 

Dayton cases, but these stations were excluded from the model runs for the 

Sudbury releases in lieu of sites closer to Sudbury. Although the dimensions 

of arrays in the program code could be easily increased to accommodate data 

at additional stations, the purpose of the operational evaluation was to 

exercise the code as specified in the user guide. Figure 6 reveals that 

the greater number of surface sites is translated into finer spatial resolution than that for the upper air stations. 

There are notable elevation differences among the stations in Table 6. 

The relatively level terrain across Ohio and Ontario gives way to higher 

elevations and complex terrain variations among the stations across 

Pennsylvania and New York. Nevertheless, elevation data are not required 

by MESOPAC II since flat terrain is assumed by this model. 

The MESOPAC II code contains no provisions for missing data and execution 

stops if it detects missing data or an error occurs in the date/time information. Therefore, it is also imperative that the hourly surface observation 

files be carefully scrutinized for missing data and that editting corrections 

be performed before model execution. Fortunately, only a small fraction of 

observations were missing from the 25 selected sites. In most cases a single 

hour of observations was missing, although 2 or 3 consecutive hours of missing 

data occurred occasionally. In all instances, values were estimated by linear 

interpolation from observations taken immediately before and after the missing 

hour(s). Table 7 presents the surface meteorological variables required as 

input to MESOPAC II. The information about each variable is taken from CD144 

(Card Deck 144) format specifications. The files of hourly observations were 

also reviewed and values were derived when a single variable was missing. 

20 
TABLE 5 

UPPER AIR MEASUREMENTS AND SPECIFICATIONS# 

VARIABLE UNITS RESOLUTION 

Pressure mb 0.1 mb 

Height m, MSL* 1 m 

Temperature degrees (OK) 0.1° 

Wind speed m/s 0.1 m/s 

Wind direction degrees (0) 1 0 

#Units and resolution of the format requirements in MESOPAC II. 

* altitude above mean sea level 

21 
N 

N 

S TA TT 011 IIU~C U OF CLOS!: ST RAIIIIISOIIOE STAT f ON TO EACit GRIO POT NT 

HULTIPLY ALL VALUES aY 10 •• 0 

1? 6 6 6 6 6 6 6 6 6 6 6 6 ~ 5 5 5 ~ s 5 5 5 5 3 3 3 3 1 1 3 

' 1-

1::1 \ 6 6 

' + 1-

17 \ 6 "' 

\ . 16 \ 6 

\ • + 

1~ \ 6 6 

\ • + 

n ' o ~> \ • + 

1l \ 6 6 

\ . 12 \ 6 6 

' • + 

11 \ 6 6 

\ + + 

1-J \ 6 6 

' + + ~ \ 6 6 

\ • + 

(~ \ 1 1 

' 1- + 

7 ' 1 

' + + 0 \ 

' • + 

5 \ 

\ + 

~ \ 1 

\ + + 

J \ 

\ + + 

l \ 

+ 

6 6 

+ 

f, 6 

+ 

6 6 

+ 

6 6 

<i 6 

+ 

6 6 + + 

6 6 

• 

6 l 

+ + 

6 6 

+ 

6 6 

+ 

1 + + 

+ .+ 

1 

• 

+ + 

1 1 

+ + 

1-

+ • 

1 1 

+ 

6 

+ 

6 

• 

6 

+ 

6 

+ 

6 

+ 

6 

+ 

6 

+ 

6 

+ 

6 

+ 

I 

+ 

+ 

1 

+ 

+ 

+ 

6 

+ 

6 

+ 

6 

+ 

6 

+ 

6 

t 

6 

+ 

6 

6 

+ 

6 

+ 

6 

+ 

1 

+ 

1 

• 

1 

+ 

+ 

1 

+ 

6 

+ 

6 

+ 

6 

+ 

6 

+ 

6 

+ 

6 

• 

6 

6 

+ 

6 

+ 

6 

+ 

+ 

t 

+ 

• 

1 

+ 

+ 

6 

+ 

6 

+ 

6 

+ 

6 

• 

6 

+ 

6 

+ 

6 

t 

6 

6 

• 

6 

+ 

1 

+ 

1 

+ 

1-

+ 

1 

t 

+ 

6 

6 

+ 

6 

+ 

6 

+ 

6 

+ 

6 

+ 

6 

t 

6 

+ 

6 

t 

6 

+ 

6 

+ 

t 

1 

t 

+ 

1 

t 

1 

+ 

+ 

6 

+ 

6 

t 

6 

t 

6 

t 

6 

• 

6 

+ 

6 

+ 

6 

+ 

~ 

+ 

1 

• 

4 

+ 

4 

+ 

1 

+ 

1 

+ 

+ 

1 

\ + t + t + + + + t 

\ 1 1 1 1 1 

' + + + t t + t + + 

+ 

6 

6 

+ 

6 

+ 

6 

t 

6 

• 

6 

• 

6 

+ 

6 

+ 

c 

4 

• 

4 

4 

+ 

4 

+ 

4 

+ 

4 

+ 

4 

+ 

4 

6 

+ 

6 

+ 

6 

6 

+ 

6 

+ 

6 

+ 

6 

+ 

6 

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----------------------------------------------------------------------------------------- 2 3 

Figure h. 

5 6 1 r 9 10 11 12 11 14 15 16 17 1a 19 20 21 22 21 24 25 26 21 23 Z9 30 

Closest rawinsonde site (l - 6) to each grid point in 

the MESOPAC II meteorological grid for Dayton cases. 
• • 

Figure 5. 

• CMH 

• 

DUJ 

• 

• 

ELM 

• 

!PT 

Surface meteorological stations considered 

runs for the CAPTEX 

in the MESOPAC II 

evaluation. Boundaries 

grids 

for meteorological 

are denoted (heavy solid and dashed lines). 
TABLE 6 

SURFACE METEOROLOGICAL STATION INFORMATION 

LOCATION SITE ID 

Albany, NY ALB 

Altoona, PA AOO 

Avoca, PA AVP 

Buffalo, NY BUF 

Cleveland, OH CLE 

Dayton, OH DAY 

Dubois, PA DUJ 

Elmira, NY ELM 

Erie, PA ERI 

Flint, MI FNT 

Ft. Wayne, IN FWA 

Grand Rapids,MI GRR 

Harrisburg, PA CXY 

Indianapolis,IN IND 

Messina, NY MSS 

Newark, NJ EWR 

Philadelphia, PA PHL 

Pittsburgh, PA PIT 

Parkerburg, WV PKB 

*Sault Ste Marie,MI SSM 

Syracuse, NY SYR 

Toledo, OH TOL 

Williamsport, PA IPT 

Youngtown, OH YNG 

Canadian Sites: 

London, ONT. YXU 

*Ottawa, ONT. YOW 

*Sudbury, ONT. YSB 

Trenton, ONT. YTR 

Alternate Site: 

#Columbus, OH CMH 

LATITUDE 

(DEG. N) 

42.75 

40.30 

41.33 

42.93 

41.42 

39.90 

41.18 

42.17 

42.08 

42.97 

41.00 

42.90 

40.22 

39.75 

44.93 

40.70 

39.88 

40.50 

39.27 

46.47 

43.12 

41.60 

41.25 

41.27 

43.05 

45.32 

46.62 

44.12 

40.00 

LONGITUDE 

(DEG. W) 

73.80 

78.32 

75.53 

78.73 

81.87 

84.20 

78.90 

76.90 

80.18 

83.75 

85.20 

85.50 

76.85 

86.25 

74.85 

74.17 

75.25 

80.22 

81.57 

84.37 

76.12 

83.80 

76.92 

80.67 

81.09 

75.67 

80.80 

77.53 

82.88 

ELEVATION 

(m ASL) 

89. 

448. 

289. 

215. 

245. 

306. 

556. 

291. 

225. 

234. 

252. 

245. 

107. 

246. 

65. 

9. 

8. 

374. 

194. 

221. 

124. 

211. 

160. 

362. 

278. 

126 

348. 

81. 

254. 

* applied in the Sudbury cases only in place of FWA, IND, YNG 

# Substituted for DAY in a test case only 

24 
N 

lJl 

HESOPUFF VERSIOH 4.0 LEVEL 870421 

STATIOII truttBER OF CLOSEST StmFACE HET. STATiotl TO EACII GRID POUlT 

HULTIPLY All VALUES OY 10 MM 0 

19 ' 14 14 14 14 12 12 12 12 12 25 25 25 25 25 24 24 24 24 24 24 24 24 17 17 17 17 17 17 17 17 

' + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + 

18 ' 14 14 14 14 12 12 12 12 12 25 25 25 25 25 25 24 24 24 24 24 24 24 24 17 17 17 I7 I7 I7 I7 

\ + + + + + + + + + + + • + + + • + + + + + + + + + + + + + + 

17 \ 14 I4 14 14 12 12 12 12 12 25 25 25 25 25 25 24 24 24 24 24 24 24 24 17 17 17 17 17 17 17 

\ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + 

16 \ 14 14 14 14 12 12 12 12 12 25 25 25 25 25 25 4 4 24 24 24 24 24 24 21 21 17 17 I7 1 1 

' + + + + + • .. + + + + + + + + + • .. + + + + + + + .. + + + 

15 ' 14 14 14 14 12 12 12 12 12 25 25 25 25 25 25 4 4 4 24 24 24 24 21 21 21 21 1 1 1 1 

\ + .. + • + + + + + + + + + + + + + + + .. + + + + + + + + + 

14 \ 14 14 14 14 12 12 12 12 12 25 25 25 25 25 25 4 4 4 4 4 24 21 21 21 21 21 1 1 1 1 

\ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + 

13 \ 14 14 14 14 14 I2 12 12 12 25 25 25 25 25 25 4 4 4 4 4 21 21 21 21 21 21 1 1 1 1 

\ + + + • • t + • • t • + • + + + .. + + + + + + .. + + + + + + 

12 \ 14 14 14 14 14 12 12 12 I2 25 25 25 25 25 10 10 4 4 4 4 9 9 21 21 21 21 I 1 1 1 

' + + + + + + + + + 

11 ' 14 14 14 14 14 12 12 12 12 

' + + + + .. + + .. + 

10 ' 14 14 14 14 22 22 22 22 22 

• + + + .. + + + 

5 25 25 10 10 10 10 4 

+ + + + + + + + 

5 5 5 10 10 10 10 10 

\ + + + + + t t .. 

9 \ 13 13 13 13 22 22 22 22 

\+ + + + + + 

8 \ 13 13 13 13 13 22 22 22 

' + + + + + + + • 

7 ' 13 13 13 13 13 22 22 22 

\ + • + + + • t • 

6 \ 13 13 13 13 13 7 7 22 

\ + t + • • • + • 

5 \ 15 15 13 13 7 7 7 7 

' • • + 4 \ 15 15 15 

+ 

7 

+ 

7 

+ 

5 

+ 

5 

+ 

5 

• 

5 

+ 

7 

+ 

5 

+ 

5 

• 

5 

+ 

5 

• 

5 

+ 

5 

+ 

5 

+ + + + + 

5 23 23 10 10 

+ + + + + 

5 23 23 23 8 

+ .. t t + 

5 5 23 23 2J 8 

+ + + + + + 

5 5 19 19 19 19 

+ + + + + + 

5 19 . 19 19 19 19 

+ + + + + + + + 

7 20 20 20 19 19. 19 19 

\ + • + 

3 ' 15 15 15 

' + • + 2 \ 15 15 15 

' + + + 

1 ' 15 15 15 

+ 

7 

+ 

7 

+ 

7 

+ 

7 

+ 

+ 

7 

+ 

7 

+ 

7 

+ 

7 

+ 

+ 

7 

+ 

7 

• 

7 

• 

7 

+ '+ + + + + • + + + 

7 7 20 20 20 20 20 19 19 19 • • + + + + + • + + 

7 7 20 20 20 20 20 20 20 19 

+ + + • + + + + + • 

7 7 20 20 20 20 20 20 20 20 

' + + + + + + + + + + + 

+ 

8 

+ 

8 

+ 

8 

+ 

8 

• 

2 

+ 

2 

+ 

2 

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8 16 16 16 16 

+ + + • • 

8 16 16 16 16 

+ 

3 

+ 

3 

+ 

3 

+ 

3 

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3 

+ 

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+ 

3 

+ 

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+ + + + 

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+ + + + 

3111111 

+ 

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+ 

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+ 

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+ 

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+ 

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+ 

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+ 

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• 

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2 16 16 16 

+ + • • 

2 6 6 6 

+ • + + 

2 6 6 6 

• 

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+ 

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+ + + + + + + 

3 J 3 11 11 11 1I 

+ + + + + + + 

6 3 J 11 11 11 11 

+ + + + + + + 

6 18 18 18 11 11 11 

+ + + + + + + 

6 18 18 18 18 11 11 

+ 

2 

+ 

2 

+ 

2 

• 

2 

+ 

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+ 

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+ 

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+ 

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+ 

t 

6 

+ 

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+ 

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+ 

+ + + + + + + + 

6 6 18 18 18 18 18 11 

+ + + + + + + + 

6 16 16 18 16 18 16 18 

• + + + + + + + 

6 16 18 16 18 16 18 16 

+ + + + + + + + + 

-----------------------------------------------------------------------------------------------------------------------

1 2 J 4 5 6 7 6 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 JO 

Figure 6. Closest surface meteorological station (l-25) to each grid point 

of the MESOPAC II meteorological grid for Dayton cases during CAPTEX. 
TABLE 7 

HOURLY SURFACE OBSERVATIONS AND SPECIFICATIONS 

VARIABLE UNITS 

Wind speed knots 

Wind direction degrees (0) 

Temperature Fo 

Pressure (station) Inches Hg 

Relative humidity % 

Cloud cover Tenths (xlO) 

Ceiling height Ft, AGL# 

Weather code 

(Precip. type)* 

* Card Deck 1444 specifications 

# height above ground level 

26 

RESOLUTION 

1 

10° 

1 

0.01 

1 

1 

100 
However, no quality assurance tests were performed on the surface observations 

since various quality control procedures are routinely conducted during the 

data archival process by the National Climatic Data Center. 

It should also be stated that these surface observations do not represent 

actual time-averaged measurements over 1-hour periods. The hourly observations 

are actually taken over a relatively short interval prior to each hour. It 

is particularly notable that wind direction is recorded only to the nearest 

10°. There is no random number technique in MESOPAC II to generate a value 

for the units place and observed directions are multiplied by 10 in the model. 

While wind speed is reported to the nearest 1 knot, observed wind speeds less 

than 3 knots are rare due to instrument response limitations. These light 

wind conditions are usually reported as calm (i.e. zero wind speed). 

The land use type must also be provided at each grid point in the 

meteorological domain. A list of the land use categories and their 

associated surface roughness lengths built into the preprocessor code 

are given in Table 8. Since land use information was not part of the 

CAPTEX data base, land use types were obtained from an existing in-house 

land use inventory (Page,l980). Briefly, this inventory contained the 

percentage contributions of 12 different land use types for cells 

covering 1/6° latitude by 1/4° longitude areas (i.e. approximately 

18.5 km square grids). The land use cell whose coordinates were closest 

to each grid point was determined and the land use type exhibiting the 

largest percentage was selected to represent the land use at each grid 

point. At most grid points, a single land use type was dominant with 

percentages greater than 70%. There were a few cases when the agriculture 

(Category 1) and forest (Category 4 or 5) categories were the major land 

use types and exhibited nearly equivalent percentages. Category 2 (see 

Table 8) was selected as a representative compromise in these situations 

because only one land use category could be specified for each grid 

point. It is acknowledged that this is a simplification to the realworld where the landscape usually exhibits various land uses on subgrid 

scale of this model. 

Figure 7 displays the grid for Dayton experiments with the land use 

categories. The principal water bodies (12) include the Great Lakes and 

Atlantic Ocean. Agricultural cropland (1) dominates Ohio while forested (5) 

regions cover central Pennsylvania, and parts of New York state and Ontario. 

There are a few grid points defined as urban land use (11). The spatial 

pattern in Figure 7 was also found to closely correspond with the coarser 

grid scale land use map presented by Sheih et al. (1979). 

27 
TABLE 8 

LAND USE CATEGORIES AND SURFACE ROUGHNESS LENGTHS FOR MESOPAC II 

CATEGORY 

1* 

2* 

3 

4 

5* 

6 

7 

8 

9 

10 

11* 

12* 

NOTE: 

LAND USE DESCRIPTION ROUGHNESS LENGTH Z0 (m) 

crops and pasture 

crops, woodland, and 

grazing land 

irrigated crops 

grazed forest and woodland 

ungrazed forest and woodland 

subhumid grassland and semiarid 

grazing land 

open woodland grazed 

desert shrubland 

swamp 

marshland 

urban 

water 

0.20 

0.30 

0.05 

0.90 

1. 00 

0.10 

0.20 

0.30 

0.20 

0.50 

1. 00 

0.0001 

Contents of table taken from Sheih et al. (1979) 

* land use types input at grid points in the model domain 

28 
N 

I.D 

NESOPAC VERSIOII 1.1 LEVEL 660326 

UtiO USE CATEGORIES FOR EACII GRID POitiT 

MULTIPLY ALL VALUES BY 10 MM 0 

19 ' 12 lZ 12 

' • • + 

18 ' 12 2 2 

\ + + + 

17 \ 12 2 2 

\ • • + 

16 \ 2 2 2 

\ + + + 

15 \ 2 2 2 

' + • + 14 \ 2 2 2 

' + • + 

13 ' 12 2 2 

\ + + + 

12 \ 12 1 1 

' + 

11 ' 1 

\ + 

10 \ 1 

\ + 

9 ' 1 

' + 8 \ 1 

' + 7 \ 1 

\ . 6 ' 1 

\ + 

5 \ 1 

\ + 

4 ' 1 

\ t3 \ 1 

' t2 ' 1 

' t- 1 \ 1 

' 

+ 

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+ 

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+ 

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+ 

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+ 

1 

+ 

+ 

1 

+ 

1 

+ 

1 

+ 

1 

+ 

1 

+ 

1 

+ 

1 

+ 

1 

+ 

1 

+ 

1 

+ 

1 

+ 

2 

+ 

2 

+ 

2 

+ 

2 

+ 

2 

• 

2 

• 

2 

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• 

1 

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1 

+ 

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+ 

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+ 

1 

+ 

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1 

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2 

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5 5 12 12 12 12 12 12 12 

+ + + .. + .. • + + 

5 12 12 12 12 12 2 12 12 

+ + + + + + + + + 

5 12 12 12 12 1 1 1 1 

+ + + + + + + • + 

2 12 12 12 12 1 1 1 1 

+ + + • + + + + + 

12 1 1 12 12 1 1 1 1 

+ + + • + + + + + 

1 2 1 12 12 1 1 1 1 

+ + + + + + + + + 

2 2 1 12 1 1 1 1 1 

+ + + + + + + + • 

1 1 1 1 1 1 1 1 12 

5 5 5 5 5 5 5 

+ • + + + + + 

5 5 5 5 5 5 5 

+ + + + + + + 

1 12 1 1 2 2 2 

+ + + + + + + 

1 1 1 1 1 1 12 

+ + + + + + + 

1 1 12 12 12 12 12 + + + .. .. .. + 

12 12 12 12 12 12 12 .. • .. .. + .. • 

2 2 1 1 1 2 2 

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t .. t t 

5 2 2 2 

t .. .. .. 

2 2 5 2 

t t t .. 

2111111 

t + t t 

1 11 12 lZ t • .. • 

2 2 12 12 t .. t t 

5 5 12 12 

.. t t + 

5 12 12 12 

t t ... + 

5 12 12 12 

+ t .. ... 

----------------------------------------------------------------------------------------------------------------------- 1 2 4 5 6 7 8 9 10 11 12 13 14 15 16 17 16 19 20 21 22 23 24 25 26 27 28 29 30 

Figure 7. Land use categories in the MESOPAC II meteorological grid 

for the Dayton cases during CAPTEX. 
SECTION 4 

MODEL EVALUATION PROCEDURES AND RESULTS 

The MESOPUFF II modeling system was applied to the six full-scale 

CAPTEX experimental cases. Experiment #6 was omitted in this model 

evaluation effort because it was limited to a half-hour release with few 

nonzero measured concentrations over the sampling network. All model runs 

and data analyses were performed on a Sperry Univac 1182 computer system. 

The important input variables and standard features specified in the 

MESOPAC II processor runs are given in Table 9. All MESOPAC II runs began 

at hour 00 EST (midnight, Eastern Standard Time) of a release day and the 

number of simulation hours was sufficient to cover the entire sampling 

period of each experiment. All technical default features in the operational model runs were applied according to the user guide (Scire et al., 

1984b). The data files of hourly surface observations from 25 selected 

stations, the maximum number permitted, were input in each case and data 

files of upper air measurements for 6 and 7 rawinsonde sites were used for 

Dayton and Sudbury cases, respectively. The gridded meteorological fields 

generated by the processor were stored on a single disk file in each case 

and an output file was also produced with results printed at two hour 

intervals for use in analysis and interpretation of model results. The 

MESOPAC II program required about 400,000 bytes of computer core during 

execution and computational times varied from 400 to 600 seconds for these 

episodes spanning two to three simulation days. 

The input values and specifications for the MESOPUFF II model runs are 

presented in Table 10. Due to the conservative nature of the tracer, the 

wet/dry deposition and transformation processes were not simulated. The 

computational grid in the model was defined to be identical to the 

meteorological grid. The emission rate (g s- 1 ) was slightly different 

in each case as individual rates were computed from the actual amount of 

tracer emitted over the release period (see Table 3). The tracer gas 

existed under ambient temperature and exhibited neutral bouyancy. Thus, 

no plume rise occurred. The height of the release nozzle was specified 

to be l m above the surface in all model runs. 

The selection of rates for puff release and puff sampling is an 

important element for any puff model because sufficient puff overlap must 

occur under all wind speeds encountered in an application for the model 

to properly simulate plumes. The results of several model test runs 

conducted with various combinations of rates are listed in Appendix A. 

Results showed that individual peak concentrations at 300 krn arc sites 

differed by 3% or less from the average peak value computed over all test 

runs. Since these results indicated that modeled concentrations were 

not sensitive to combinations of rates between 2 and 12 puffs h 1 at the 

nearest arc, the puff release rate and puff sampling rate were both set to 

4 h 1 in all model runs. However, an optional feature was selected for 

these model runs which allowed the puff sampling rate to increase, if 

necessary, in order to insure sufficient puff overlap. The start time for 

30 
TABLE 9 

INPUT CONTROL PARAMETERS AND DEFAULT FEATURES 

OF MESOPAC II RUNS FOR CAPTEX EPISODES 

FEATURE 

METEOROLOGICAL GRID 

GRID POINT SPACING 

TIME STEP 

SIMULATION PERIOD 

REFERENCE TIME ZONE 

METEOROLOGICAL STATIONS 

UPPER AIR STATIONS 

WIND FIELDS ,(default) 

OUTPUT FIELDS 

COMPUTER REQUIREMENTS 

31 

SPECIFICATION 

30 x 19 (Dayton), 30 x 24 (Sudbury) 

37 km 

1 hour 

VARIABLE start at 00 EST on the day 

of release and go to end of sampling 

period (e.g. range from 56 to 87 h) 

Eastern Standard Time (EST) 

25 hourly surface sites 

6 - Dayton , 7 - Sudbury cases 

Mixed-layer average (Sfc. to Zi), 

upper layer average (Zi to 700 mb) 

Storage on disk file, printer output 

at 2-hour intervals 

400,000 bytes; 10 minutes CPU time 

on a Sperry Univac 1182 computer 
TABLE 10 

INPUT PARAMETERS AND SPECIFICATIONS FOR MESOPUFF II RUNS 

TRACER EMISSIONS 

COMPUTATIONAL GRID 

TIME STEP 

PUFF RELEASE RATE 

PUFF SAMPLING RATE 

WET/DRY DEPOSITION/CHEMICAL 

TRANSFORMATION 

PUFF DISPERSION 

Sfu~PLING GRID CALCULATIONS 

COMPUTATION REQUIREMENTS 

32 

3-hour release at constant rate 

Source Height 1 m; neutral buoyancy 

IDENTICAL TO METEOROLOGICAL GRID 

1 hour 

4 per hour 

4 per hour 

PROCESSES NOT SIMULATED 

aty and a 2 according to PGT curves 

b 100 kffi;tirne dependent expressions 

of Heffter (1965) at greater distances 

deactivated; calculations at 

nongridded site coordinates only 

400,000 bytes of core 
model execution corresponded with the beginning hour for each release. 

The model code was modified slightly to stop new puffs from being 

emitted after 3 hours. Thereafter, only existing puffs were tracked and 

sampled during the remainder of the simulation period. Hourly tracer 

concentrations (g/m3 ) were computed at the coordinates of all operational 

tracer measurement sites in the model domain, instead of at sampling 

grid points. This feature reduced the execution time of individual model 

runs to less than two minutes for this application. 

In order to compare the modeled results with the surface tracer 

measurements, the MESOFILE II postprocessor program was applied in order 

to compute 3-h or 6-h average concentrations from the model output file 

over the same time periods as the measurements and modeled concentrations 

were also converted into the same units as the measurements (fl 1 1 ). 

OPERATIONAL MODEL EVALUATION ANALYSES AND RESULTS 

Sets of statistical measures of differences (residuals) and correlation 

between observed and modeled concentration pairs are presented from time 

and/or space pairings in order to provide quantitative evidence of model 

performance. Concentration pairs with both observed and modeled values 

equal to zero were excluded in the calculation of the statistical measures 

because neither the observed nor the modeled plumes had an impact in these 

cases; 1088 out of 1895 pairs were in this category. In addition, analyses 

of observed plume concentration patterns at individual time periods revealed 

a large number of concentrations of 1-2 fl 1- 1 ; some at sites separated 

from the main plume distribution by adjacent sites which exhibited zero 

concentrations. Specifically, measurements at these isolated locations 

were believed to be anomolous since there was considerable uncertainty as 

to whether a measured concentration so close to the natural background 

really indicated an actual impact by the tracer plume. Potential error 

in the analytical procedures used to determine concentrations might be 

attributed for some of these values above background (Ferber et al., 1986). 

However, instead of eliminating all such extremely low values, a screening 

procedure redefined 73 values to be zero where an observed concentration 

of~ 2 fl 1-l occurred at any outlying site separated from the tracer 

plume pattern. Other observed conce~trations ~ 2 fl 1-l at sites 

next to locations with nonzero tracer concentrations were not changed in 

the data set since it was deemed reasonable to assume that the tracer plume 

had indeed impacted such locations. Therefore, the final evaluation data 

set contained all paired values that formed the union of both the perceived 

actual and predicted plumes. As a consequence of applying these screening 

criteria, the full data set was composed of 734 concentration pairs from 

the six modeled experiments. 

Statistical Results For Mean and Peak Concentrations 

Statistical results were computed from observed and modeled concentration pairs matched in time and location for each experiment and over the 

entire data set. These criteria provide a stringent test of model performance and a critical test of model skill as each predicted concentration was compared to the measured value at the same site and for the same 

time period. 

33 
The results in Table 11 reveal that MESOPUFF II overpredicted mean 

concentrations in each case. Nevertheless, the predicted mean concentration (P) was within a factor of two of the observed mean value (0) 

in experiments #2,#4, and #7 and for the entire data set. The overall 

mean residual (d) was -33.8 fl 1-1, while individual values ranged from 

-58.3 fl 1-l for CAPTEX #l to a low of 12.8 fl 1-l in CAPTEX #2. The 

most significant model overprediction occurred in CAPTEX #3 as P was five 

times greater than 0; however, the observed mean concentration in CAPTEX #3 

was considerably lower than the mean values of the other experiments. 

Results of additional analyses will be presented later in an effort to 

explain this large discrepancy. 

Since no absolute standards have been established for defining acceptable 

model performance, statistical results like those in Table 11 are primarily 

useful in an intercomparison of different models. However, comparable 

statistics for other models have yet to appear. Nevertheless, results of 

several statistical measures in Table 11 did indicate that considerable 

scatter existed among the paired concentrations. The standard deviations 

of the residuals (SDd) are much larger than the observed mean concentrations. Furthermore, there is greater variability in the modeled results 

as exemplified by the standard deviations of the modeled concentrations 

(SDP), which are greater than corresponding standard deviations for 

observed values (SD0 ). The results for the average absolute residual (AAR) 

and root mean square error (RSME), when compared to observed concentrations, 

also indicate that notable scatter exists between modeled and observed 

concentrations. In addition, the Pearson correlation coefficient (R) is 

also generally near zero which reveals no linear relationship among the 

concentration pairs for these individual data sets and over the entire 

data set. 

Similar results for the statistical measures were also obtained by 

Policastro et al. (1986) when the predicted results of eight regional 

models, including MESOPUFF II, were evaluated in time and space against 

measurements from two different tracer field studies. Large scatter 

and low correlations were generally found between model and observed 

results, and most models also displayed a tendency to overpredict mean 

concentrations. Consequently, scatter plots of observed versus modeled 

concentrations showed many pairs where either the observed or the predicted 

value was zero (Policastro et al., 1986; Draxler, 1987; Lee, 1987). Thus, 

it was evident that the modeled plume was either displaced away from 

particular sites where the actual tracer was measured or modeled concentrations impacted the particular sites at different times that the observed 

plume. Some statistical measures were strongly sensitive to these circumstances and the ensuing results reflected situations when plume displacements 

occurred. In particular, significant scatter (e.g. large values for d, 

AAR, and RMSE) and low correlations were obtained when observed and modeled 

plumes exhibit little or no overlap, even though modeled mean concentrations 

may have compared favorably with observed mean values (Policastro, et al., 

1986). However, the statistical measures could only provide partial information concerning regional model performance and more innovative analyses, 

to be shown, are certainly required to provide better quantitative information to assist in assessing and understanding the causes of model/measured 

differences. 

34 
TABLEll 

MESOPUFF II MODEL EVALUATION RESULTS: OBSERVED AND MODELED 

CONCENTRATIONS PAIRED IN TIME AND LOCATION 

STATISTIC$ CAPTEX EXPERIMENT 

#l #2 #3 

N 143 247 124 

0 22.6 45.7 10.0 

SDO ±138.1 ±172.0 ±31.4 

p 80.9 58.5 49.9 

SDP ±252.8 ±231.1 ±163.2 

d -58.3 12.8 39.9 

SDd ±165.5 ±295.5 ±168.2 

AAR 71.8 95.7 57.1 

RMSE 174.9 295.2 172.2 

R 0.80 -0.05 -0.07 

#4 #5 #7 

96 68 56 

54.9 41.7 79.7 

±172.2 ±112.7 ±135.4 

90.5 86.0 113.5 

±226.5 ±166.8 ±214.8 

-35.7 -44.4 ~33.8 

±294.6 ±178.4 ±283.0 

123.6 103.2 185.5 

295.2 182.6 282.5 

-0.08 0.23 -0.27 

$ - units are fl/1, except for N and R 

N - number of concentration pairs 

ALL 

734 

38.6 

±143.3 

72.4 

±218.6 

~33.8 

±244.6 

95.7 

246.7 

0.14 

0 = mean observed concentration , P = mean modeled concentration 

SD = standard deviation about the mean 

d = average residual = 0 P 

AAR = average absolute residual 

RMSE = root mean square error 

R = Pearson correlation coefficient 

35 
Objective tests between the concentration pairs were performed in order 

to provide additional quantitative comparative results which could provide 

a better overall picture of the model's capabilities to simulate the 

spatial plume pattern over the time frame of these experiments. In 

particular, comparative test results that demonstrate the relative amount 

of correspondence between modeled and observed plumes could provide relevant 

information about the abilities of the transport and dispersion components 

of the model to simulate the movement and growth experienced by the tracer 

plume. Table 12 contains results in the form of percentages for certain 

comparative tests on the concentration pairs. One of the interesting 

tests is the percentage of pairs where both observed and modeled values 

are nonzero (Tl). High percentages for Tl demonstrates that a substantial 

overlap must have existed between the modeled and observed plumes for the 

sampling periods of an experiment, which also suggests the overall speed 

and path, and growth of the plume was accurately simulated. Conversely, 

low percentages would reveal that the area of intersection between the 

respective plumes was rather small which implies inadequate treatment of 

plume transport/dispersion by the model. The percentages for Tl in Table 12 

vary among these cases with the highest being 46.9% for CAPTEX #4. Tl 

was less than 20% for experiments #l, #3, #5, and #7 which indicated 

rather small areas of intersection for the observed and modeled plumes 

during these cases. 

Additional evidence of spatial displacements between the respective 

plumes is provided by test results showing the percentages when either the 

observed (T2) or the predicted (T3) concentration was zero while its 

counterpart was nonzero. Low percentages for T2 and T3 would suggest 

a strong spa_tial correspondence of the respe-ctive tracer plumes. However, 

these results show a notable number of pairs where either the observed 

or predicted concentration was zero. In fact, results indicate that either 

T2 or T3 was greater than 50% in some experiments with most values 

for T2 and T3 above 30%. The best combination of T2 and T3 is found for 

CAPTEX #4. which also displayed the highest value for Tl. Finally, 

the results for T4, the percentage of cases where observed concentrations 

were greater than modeled values, vary with values ranging from about 35% 

to 54%. Results from the T4 test are sometimes used as indicators of the 

performance of dispersion in a model. For example, when T4 is significantly 

greater than 50%, it might be suggested that the modeled plume exhibited 

less horizontal spread than the observed plume. Nevertheless, T4 results 

are difficult to interpret in this manner and are also complicated by the 

potential effects from both transport and dispersion. Even though the model 

certainly overpredicted the mean concentrations, as shown by the earlier 

statistical results, spatial displacements due to differences in the speed 

and/or the directional components of transport between the model and 

observed plumes are believed to be the principal factors responsible for 

the variations in T4 results among these cases. 

Mean concentrations and selected statistical measures for each experiment 

are presented in Table 13 to illustrate model behavior on an event by 

event basis. An examination of Table 13 indicates that observed mean 

concentrations generally exhibited an increase with time and then gradually 

decreased toward the last sampling period. This temporal trend reflects 

the arrival of the tracer plume accompanied by generally high concentrations 

36 
TABLE 12 

TEST RESULTS OF MODELED AND OBSERVED CONCENTRATIONS 

PAIRED IN TIME AND LOCATION 

CAPTEX EXPERIMENT 

TEST #1 #2 #3 #4 #S #7 ALL 

N 143 247 124 96 68 56 734 

T1 (%) 16.8 33.6 16.1 46.9 19.1 16.1 26.4 

(P&O >0) 

T2 (%) 52.4 32.0 33.9 27.1 48.5 37.5 37.6 

(0=0, P>O) 

T3 (%) 30.8 34.4 50.0 26.0 32.4 46.4 36.0 

(P=O, 0>0) 

T4 (%) 35.7 53.0 54.0 44.8 35.3 48.2 46.7 

(O>P) 

37 
TABLE 13 

SELECTED STATISTICAL EVALUATION RESULTS FOR EACH EVENT 

OF THE CAPTEX EXPERIMENTS 

EX.PT MM/DD-HR N 0 p d AAR NNO NNP T1 T4 

(LST) (fl/1) (fl/1) (fl/1) (fl/1) (%) (%) 

1 9/18-14 4 5.8 59.0 -53.2 53.2 2 0 25. 0. 

1 9/18-17 5 552.2 1012.8 -460.5 615.5 0 1 75. so. 

1 9/18-20 15 23.7 155.9 -131. 3 140.7 3 4 53. 40. 

1 9/18-23 4 0.8 29.0 -28.2 29.8 2 2 0. so. 

1 9/19-02 21 16.6 61.8 -45.1 75.5 8 10 14. 52. 

1 9/19-05 3 0. 118.7 -118.7 118.7 3 0 0. 0 

1 9/19-08 26 4.5 49.2 -44.7 52.5 16 6 8. 31. 

1 9/19-14 26 3.2 38.1 -34.8 41.3 17 9 0. 35. 

1 9/19-20 26 2.0 36.6 -34.6 38.1 17 7 8. 31. 

1 9/20-02 14 2.4 13.0 10.6 15.0 7 5 7. 36. 

2 9/25-13 4 0.2 51.0 -50.8 51.2 3 1 0. 25. 

2 9/25-16 5 0.2 827.6 -827.4 827.8 4 1 0. 20. 

2 9/25-19 6 45.7 419.0 -373.3 464.0 3 2 17. 33. 

2 9/25-22 14 130.4 155.8 -25.4 285.9 5 8 7. 57. 

2 9/26-01 8 311.6 118.8 192.9 421.4 4 2 25 38. 

2 9/26-04 24 125.6 33.3 92.3 150.1 6 13 21. 71. 

2 9/26-10 33 32.6 32.7 -0.1 50.0 9 13 30. 70. 

2 9/26-16 36 21.0 33.6 12.6 42.3 10 10 42. 47. 

2 9/26-22 37 17.8 17.2 0.6 23.1 9 11 43. 54. 

2 9/27-04 32 17.7 8.6 9.1 21.9 8 13 31. 59. 

2 9/27-10 25 11.7 8.7 3.0 16.7 6 8 36. 52. 

2 9/27-16 10 5.1 9.7 -4.6 13.8 6 1 30. 40. 

3 10/02-16 1 1.0 0. 1.0 1.0 0 1 0. 100. 

3 10/02-19 4 18.0 1.5 16.5 17.5 2 2 0. 50. 

3 10/02-22 6 50.8 257.5 -206.7 308.0 4 1 0. 17. 

3 10/03-01 16 3.6 118.8 -115. 1 122.4 7 9 0. 56. 

3 10/03-04 4 5.0 5.5 -0.5 10.5 1 3 0. 75. 

3 10/03-07 29 6.9 39.5 32.6 45.2 11 14 10. 48. 

3 10/03-13 27 6.7 28.9 -22.3 32.8 8 10 30. 48. 

3 10/03-19 15 12.3 49.1 -36.9 49.1 5 5 27. 40. 

3 10/04-01 12 12.6 4.7 7.9 12.6 4 7 8. 67. 

3 10/04-07 5 12.0 0. 12.0 12.0 0 5 0. 100. 

3 10/04-13 5 1.8 0. 1.8 1.8 0 5 0. 100. 

38 
TABLE 13 (CONTINUED) 

EXPT DATE/TIME N 0 p d AAR NNO NNP T1 T4 

4 10/14-13 1 0. 67.0 -67.0 67.0 1 0 0. 0. 

4 10/14-16 7 133.9 167.6 -33.7 301.4 5 2 0. 29. 

4 10/14-19 5 276.6 521.0 -244.4 784.4 3 1 20. 20. 

4 10/14-22 16 47.8 230.0 -72.2 138.7 3 7 38. 62. 

4 10/15-01 9 30.1 77.0 -46.9 102.0 3 3 33. 33. 

4 10/15-04 24 58.8 51.8 7.1 70.1 4 5 58. so. 

4 10/15-07 6 27.0 62.3 -35.3 69.0 3 0 33. 17. 

4 10/15-10 16 9.6 33.2 -23.6 26.3 5 0 69. 19. 

4 10/15-16 8 13.2 11.2 2.0 14.0 2 3 38. 62. 

4 10/15-22 9 8.8 7.3 1.5 7.2 1 4 44. 67. 

4 10/16-04 10 0. 0. 10 10 

5 10/26-03 4 86.2 0. 86.2 86.2 0 4 0. 100. 

5 10/26-09 9 181.1 176.8 4.3 181.1 2 4 33. 56. 

5 10/26-15 14 57.5 118.5 -61.0 175.1 6 5 14. 43. 

5 10/26-21 12 2.8 130.5 127.7 128.7 6 2 33. 17. 

5 10/27-03 13 0.6 74.5 -73.8 74.2 10 1 8. 8. 

5 10/27-09 10 0.6 2.0 1.4 2.4 7 2 0. 20. 

5 10/27-15 3 1.3 0. 1.3 1.3 0 3 0. 100. 

5 10/27-21 1 1. 0. 1. 1. 0 1 0. 100. 

7 10/28-23 0 0. 0. 

7 10/29-02 3 1. 0. 1. 1. 0 3 0. 100. 

7 10/29-05 3 35.7 190.7 -155.0 155.0 2 0 33. 0. 

7 10/29-08 14 25.6 220.8 -195.2 234.6 8 2 21. 14. 

7 10/29-11 4 179.5 8.0 171.5 187.5 1 3 0. 75. 

7 10/29-14 16 75.9 107.3 -31.4 179.7 6 6 25. 44. 

7 10/29-20 11 196.0 63.2 132.8 259.2 2 9 0. 82. 

7 10/30-02 3 32.7 83.3 -50.7 116.0 2 1 0. 33. 

NN0 , NNR - number of observed ' predicted zero concentrations. 

T1 P nd 0 both > 0 

T4 - 0 > p 

39 
at the closest arc or sites a few hours after release, and this peak was 

followed by an general decrease in the mean concentration due to the plume 

being dispersed as it traveled across the sampling region. Modeled concentrations also exhibited a similar temporal pattern, although the time 

variation of mean model values was often out of phase with the time series 

of observed mean values. The residuals were usually negative as the model 

appears to overpredict in most events. The largest biases were usually 

found during an early time period when concentrations also happen to be 

highest. Differences in the time and location of impact of the peak 

concentration are attributed for these significant departures between the 

observed and modeled mean concentrations. The results for the number of 

observed (N0 ) and predicted (N ) concentrations being zero coupled 

with the low Tl results indica~e important spatial plume displacements. 

In fact, during some events there was no intersection of the respective 

plumes (i.e. Tl = 0). Low values of Tl were more common during the early 

events and also near the end of an experiment. Differences in the time of 

initial impact of the respective plumes at the first arc (or closest sites 

for the Subdury cases) can produce low Tl values soon after release. At 

the later stages of an experiment a more rapid departure of the observed 

plume from the sampling region or large spatial displacements between the 

plume patterns existing on the sampling domain was also believed to lead 

to small fractions in Tl. 

Averaged concentrations for each event were also computed separately from 

observed and modeled concentrations (excluding any zero values) to assess 

differences in magnitude between the plumes with time. The results are 

presented as a function of time after release in Figure Sa-f. For CAPTEX 

#l-4 (Figures Sa-d), the highest observed and modeled average plume concentration occurred within 12 h after release as a result of plume impact at 

the 300 km arc sites. The modeled values (X) replicated the time history 

and magnitudes of observed (O) concentrations best in #2 and #4. For a few 

events there were very few or no observed nonzero concentrations, which 

was responsible for the values near or on the abscissa. These results also 

show the overall decrease in average plume concentrations with time. 

Concentration standard deviations were comparable to mean values for most 

events. The results for CAPTEX #5 and #7 (Fig. Se-f) did not exhibit concentrations at early periods as high as the Dayton cases; probably because the 

plumes did not intersect sites or an arc as close to release point as in the 

Dayton cases. Despite the log scale for concentration, it appeared that 

average modeled concentrations from these calculations were more often higher 

than average observed values, which suggests that peak concentrations were 

overpredicted, although more definitive information about model performance 

at peak concentration levels will be presented later. 

Cumulative frequency distributions were determined to establish the 

relative agreement between the observations and predicted values across 

the range of concentrations. Although frequency distributions do not 

demonstrate information about model skill, since values are not paired in 

time or location, the results can provide evidence about how well the modeled 

concentrations replicate the magnitude and overall distribution of observed 

values. The results from the entire data set in Figure 9 concur with the 

earlier tests that large numbers of either observed or modeled concentrations 

in the evaluation data set were zero. The cumulative frequency curve for 

observed concentrations lies above that for the modeled values. The 

40 
1 Q A 

,.--..... 

" 10 3 

....._,. 

-

z 

0 

1-- 10 2 

<( 

c:::: 

1--

z 

w 

u 

z 10 1 

0 

u 

10 ° 

10 A 

,.--..... 

" 10 

3 

z 

0 

X 

0 

X 

X 

0 

0 

0 

a CAPT EX 

X MODEL 

0 

X X 

X 

X X X 

0 

X 

0 

0 

0 0 

0 

10 20 .30 40 

TIME AFTER RELEASE (h) 

b CAPTEX 2 

I I I I I I I I I -

X MODEL ~ 0 OBSERVE~ 

~ 

1-- 10 2 j <( 

10' <iil ~ 9 R J 

c:::: 

1--

z 

w 

u 

z 

0 

u 

100 

0 

f~~~~~c~I~I_LI ~!~I~I~I~~~I_L! ~~~~~~~~~~~I_L! ~~~~~~~I_LI ~~~~~~~·~ Figure 8. 

10 20 .30 40 50 60 

TIME AFTER RELEASE (h) 

Average concentrations obtained from sites with observed 

and modeled nonzero concentrations over the sampling periods 

during a) CAPTEX #l and b) CAPTEX #2. 

41 
10. 

...--... 

'-..._ 10 3 

.._ 

.....__.. 

z 

0 

I- 10 2 

<{ 

Ct:: 

Iz 

w 

u 

z 10 I 0 

u 

10 ° 

10 • 

...--... 

'-..._ 10 3 

z 

0 

I- 10 2 

<{ 

Ct:: 

1--

z 

w 

u 

z 

0 

u 

10 I 

0 

I I 

0 

X 

X 

c CAPTEX 3 

X 

0 

10 20 30 

TIME AFTER RELEASE (h) 

I I 

X 

X 

0 0 

d CAPTEX 4 

X 

0 

X 

0 

MODEL 

J 

0 J --, 

0 

I," !,;I ,, " 40 50 

I I I I I -

3 

_J 

MODEL j OBSERVE~ 

:::j 

-J 

_J 

l 

l 

J 

~ 

1001 L ~t~_L~I ~~~~~·~· ~'~'_LI~I ~~~·~'_Ll~I~I~I~'~~·~I~I_LI~j 0 10 20 30 40 50 

TIME AFTER RELEASE (h) 

Figure 8. Same as 8a-b, except for c) CAPTEX #3 and d) CAPTE\ #4 

42 
e CAPTEX 5 

10 4 

I I I I I I I I I I -

,........._ 

X MODEL ~ 0 OBSERVED 

"- 10 3 

--=1 

3 - J ........... 

z X 

0 X 

I- 10 2 0 

<( X ..., 

C!::: ., 

J I- j z 

w 

u 

z 10 1 

0 ~ 

u 0 

0 X ~ 

10 ° t 0 

0 J ,,,... I I I I I I I I I I I I I I I I "'I I .,;... I I /' 

0 10 20 30 40 '' - 50 

TIME AFTER RELEASE (h) 

10 4 f CAPT EX 7 

I I I I I I I I I I I = -i 

i 

i 

X MODEL J 

J ,........._ 0 OBSERVE~ 10 3 

"- =1 

- J ...__, X 

z X 0 0 j 0 6 * I- 10 2 

<( --=> 

0 C!::: ~ I- I 

z X 

w J 

u 

z 10 1 J 

0 

u ~ 

J 

10 ° ..... I I I I I I I I I I I I I I I I I 

0 - 5 10 15 20 25 

TIME AFTER RELEASE (h) 

Figure 8. Same as 8a-b, except for e) CAPTEX #5 and f) CAPTE..X #7 

43 
.c:-

.c:-

~ 

~ 

"---../80 

>-

u 

z 

w 

=:) 60 

0 

w 

0:::: 

LL / / 

w4o --- > 

r 

<{ 

_J 

~ 

:L20 -

::=> 

(_) 

/ / 

/ / 

/ / 

/ / 

/ 

/ 

/ 

/ 

CAPT EX 

/ 

/ 

/ 

/ 

/ 

MESOPUFF II (clashed) 

OBSERVED (solid) 

OL-~--L_LJ~Ji~~----L_~I_JI_LILILILIIui ____ L-~I_JI_LI~I~I~II~~-----L-~~~~~ 

10° 10 10 2 10 3 10 4 

CONCENTRATION ( fl/1) 

Figure 9. Cumulative frequency distributions of the model and observed 

concentrations from the entire data set. 
separation between the curves increased from 1 to 10 fl l- 1 , which 

indicated that a greater number of observed values exist at these low 

concentrations compared to modeled results. The separation remains about 

the same between 10 and 100 fl 1- 1 . However, the gap between the curves 

closed rapidly above 100 fl 1-l as a relatively greater number of modeled 

values occur at higher concentrations. 

Individual cumulative concentration distributions are shown in 

Figures lOa-f to illustrate the variability in the distributions among these 

experiments. The best overall agreement between the cumulative distribution 

curves of observed and modeled concentrations appeared in experiments #2,4, 

and #7. CAPTEX #2 and #4 also happened to exhibit the best results for 

plume overlap (i.e. highest Tl values in Table 13) among these experiments. 

The frequency distribution results of observed and modeled values 

in Table 14 quantitatively reinforce the previous cumulative distribution 

findings. These results that reveal a relatively large number of observed 

concentrations still existed at 1 fl l- 1 , however, there was no basis to 

eliminate or modify these values since all were found at sites on the edge 

of the observed plume. These results also verify that larger numbers of 

observed values occurred at low concentrations. A crossover point appeared 

at about 25 fl 1- 1 , as the frequencies of modeled values were greater at 

higher concentrations. In fact, these results provided strong evidence 

that the model overpredicted the highest concentrations because twice as 

many modeled values are found in the intervals above 100 fl 1-l observed 

values. 

The ability of a model to predict the highest concentration should 

certaiply be an important aspect of an evaluation effort, since models 

are often applied in order to assess peak concentrations in regulatory 

situations. In the evaluation for peak concentrations, results were 

determined from observed and modeled values paired in time only or location 

only. In· fact, there were very few cases where the modeled peak concentration occurred at the same site and time as the observed peak concentration, 

which is not unexpected in view of the spatial plume displacements 

reported earlier. 

Table 15 contains the results for peak observed and modeled concentrations paired in location only. This evaluation framework allows peak 

observed and modeled concentrations to occur at different time periods 

at a given site. These results show that the model overpredicted peak 

concentrations for all experiments. Except for CAPTEX #3, the peak 

modeled concentrations were within a factor of two of peak observed values. 

The smallest negative residuals are found in CAPTEX #2 and #4. In these 

experiments, the results for Tl in Table 12 indicated that plume overlap 

was higher and the other test results were more favorable than in the other 

cases. The largest overpredictions of peak concentrations occurred in 

CAPTEX #l and #3. As reported earlier, the mean observed concentration 

for CAPTEX #3 was unusually low in relation to the other cases. Results of 

analysis of peak concentrations at the 300 km sites, where the highest 

observed concentrations occurred for the Dayton cases, revealed that the 

main portion of the observed plume did indeed pass to the west of the 

300 km arc in this case. This explains the low observed peak and mean 

concentrations for this experiment and the reason for the significant 

45 
a CAPTEX #1 100r-~~ilniTIT--,-,-rrnTn=~==~~-~-~-~~~~-~F--~-~-TT-.IIinl ~~~~ 

,--..,. 

~ 

'---"'so 

>-

u 

z 

w 

:J 60 0 

w 

0::: 

u... 

WJ.O 

> 

l-

<r: 

__] 

:J 

~20 

:J 

(.) 

100 

,--..,. 

~ 

'---"'so 

>-

u 

z 

w 

:J"'O ow 

e:::: 

u... 

WJ.O 

> 

!--

<r: 

__] 

:J 

:220 

:J 

u 

0 

10 ° 

/ 

-

I I 

/ 

/ 

/ 

/ 

/ 

/ 

/ 

/ 

I I I I I 

10 1 

b 

/ 

/ 

I I 

I 

/ 

/ 

I 

MESOPUFF II (dashed) 

OBSERVED (solid) 

CAPT EX J!. r;2 

' I I' I 

MESO PUFF II (dashed) 

OBSERVED (solid) 

t I I II I I ,I I I I I I I I I 

10 2 10 3 10 • 

CONCENTRATION ( fl/1) 

Figure 10. Cumulative frequency distributions of model and observed 

concentrations for a) CAPTEX #l and b) CAPTLX #2. 

46 
,..-.... 

~ 

.......... 80 

>-

u 

z 

w 

:::J 60 a 

w 

0:::: 

u.... 

w40 

> 

1-

<t: 

_J 

:::J 

220 

:::J 

(_) 

,..-.... 

~ 

.......... 80 

>-

u 

z 

w 

:::J 60 a 

w 

n::: 

u.... 

~40 

1-

<t: 

_J 

:::J 

220 

:::J 

(_) 

___ ., ~--

.· 

I 

/ 

/ 

/ 

/ 

/ 

/ 

/ 

/ 

MESO PUFF II (dashed) 

OBSERVED (solid) 

/ 

/ 

/ 

/ 

~/ 

/ 

MESO PUFF II (dashed) 

OBSERVED (solid) 

Figure 10. Same as lOa-b, except for c) CAPTEX #3 and d) CAPTLX #4 

47 
_......._ 

~ 

'-"'so 

>-

u 

z 

w 

~60 0 

w 

a::: 

u.... 

I 

I 

MESO PUFF II (dashed) 

OBSERVED (solid) 

f CAPTEX #7 

100~~,~,~~~~~~---,~TTTn"~l~-f-rTTr;a~~~~~~,,,~"nT" 

_......._ 

~ 

'-"so 

>-

u 

z 

w 

~"'0 ow 

a::: 

u.... 

1-

<:( 

__J 

~ 

:220 

=> 

u 

/ 

/ 

/ 

/ 

/ 

MESOPUFF II (dashed) J 

OBSERVED (solid) 

oL-~-L'~'~'~'~--L'-L' ~~~'U'~--L--~~~~~~~~ ~~ ~~~~~~~~~ 

10° 10 1 10 2 10 3 10" 

CONCENTRATION (fl/1) 

Figure 10. Same as lOa-b, except for e) CAPTEX #5 and f) CAPTLX #7 

48 
TABLE 14 

DISTRIBUTION OF OBSERVED AND MODELED CONCENTRATIONS 

FOR ENTIRE CAPTEX DATA SET 

CONCENTRATION OR NUMBER OF VALUES 

INTERVAL (fl/1) OBSERVED MODELED 

0 1437 1425 

------------------------------------------------------ 1 68 36 

2 53 50.4% 25 34.8% 

3-5 57 49 

5-10 53 so ------ ------ 11-15 29 30 

16-25 51 36.9% 49 40.9% 

26-50 47 67 

50-100 42 46 

------ ------ 100-150 14 24 

151-200 11 25 

201-250 8 10.7% 16 20.2% 

251-300 3 12 

301-400 7 12 

401-500 6 6 ------ ------ 501-600 2 4 

601-701 0 4 

701-800 1 0.9i 2 2.8% 

801-900 0 3 

900-1000 1 0 

------ ------

1001-2001 5 1.1% 8 2.1% 

>2001 0 2 

------ ------

49 
TABLE 15 

PEAK OBSERVED AND MODELED CONCENTRATIONS PAIRED IN LOCATION ONLY 

E..XPT N 0 p d AAR RMSE R T4 (O>P) 

# (fl/1) (fl/1) (fl/1) (fl/1) (fl/1) (%) 

1 42 66.1 176.4 -110. 3 141.3 277.4 0.83 31.0 

±251.2 ±427.0 ±257.6 

2 58 86.3 133.2 -46.9 180.6 482.6 -0.09 60.3 

±229.3 ±406.2 ±84.5 

3 43 17.7 109.0 -91.4 115.4 256.2 -0 .ll 34.9 

±48.6 ±231. 7 ±242.2 

4 26 111.0 151.7 -40.7 208.7 451.8 -0.12 57.7 

±262.6 ±345.8 ±458.8 

5 25 95.2 178.8 83.6 126.0 196.4 0.61 20.0 

±169.0 ±225.4 ±181.4 

7 28 lll. 3 173.9 -62.6 236.5 344.2 -0.22 42.9 

±171. 5 ±263.2 ±344.7 

ALL 69 197.4 391.1 193.6 326.0 579.9 0.22 29.0 

±315.7 ±526.3 ±550.6 

50 
overpredictions was because the modeled plume directly intercepted this arc. 

Other results in Table 15 also reveal large scatter and low correlations 

between peak pairs matched in space. The absolute value of residuals and 

RMSE are large relative to observed peak values and correlation coefficients 

are generally small and negative. 

A comparative analysis of peak concentrations was also performed 

for observed and modeled values paired in time only. With this framework, 

the highest observed concentration is compared with the peak modeled value 

from any site for the same time period. Table 16 contains the results for 

the events of each experiment. Travel time is also given as the number 

of hours from the start time of release to the beginning hour of each 

sampling interval. Clearly, in most of the events the modeled peak concentrations were greater than observed values, as exemplified by the large 

number of negative residuals. An encouraging result, however, is that the 

highest modeled concentration within an experiment occurred at the same 

time as the corresponding observed peak value in #1,#4, and #5. This 

result suggests that there was apparently good agreement in the transport 

speed and direction between the modeled and actual plumes during the initial 

hours after release. On the otherhand, highest modeled peak concentrations 

for experiments #2 and #7 occurred much earlier than the observed highest 

values in these cases. Since these results are unpaired in space, it is 

also interesting to note that a survey of all 60 events revealed that in 

only 3 cases the observed and modeled peak concentrations during a particular event were found at the same site. However, there were 21 events 

where the peak values occurred at different sites along the same arc. 

Larger displacements obviously existed in another 25 events where the peak 

observed and modeled values were located at sites on different arcs. 

Finally, the relative positions of peak concentration pairs in the remaining 

11 cases were indeterminant since either the observed or modeled value was 

zero. These results also reveal that the model generally overpredicted 

peak values and notable time and/or spatial displacements also existed 

between observed and modeled peak concentrations. 

Statistical results in Table 17 were computed over the high-25 

observed and modeled concentrations fully unpaired in time and location 

for each experiment and for the overall data set. These results are also 

not unexpected based on the previous analyses of the peak concentrations 

and frequency distributions. The model consistently overpredicted for this 

group of concentrations even when values are completely unpaired. The 

absolute values of the bias were less than the average peak observed 

concentrations for experiments #2, #4, and #7- Since time and location 

constaints are irrelevant in this comparison, the peak concentration differences given in Table 17 were not likely attributed to transport speed 

and direction variations of the observed and modeled plumes. These 

results and those in previous tables for peak concentrations suggest that 

dispersion of the modeled plumes may not be as great as that experienced 

by the actual tracer plumes. Results of analysis of additional model runs 

to be discussed later will attempt to confirm this hypothesis and identify 

the underlying cause(s). 

The configuration of the sampling network presented an opportunity 

to investigate the four Dayton experimental results separately from the 

Sudbury cases. Consequently, a statistical analysis was performed on this 

51 
TABLE 16 

PEAK Of1SEI<VElJ Atm ~HlllELEO f:ONCENTI!AT IONS PAIRED IN TIME FOR EACH EVENT OF THE CAPTEX EXPERIMENTS 

EVENT 

£' 3 ll 5 6 7 8 9 10 11 12 

CAPTEX #1 --------------------------------------------------------------------- AVE + SO 

TlATE/TIME ( 00/IIR) 18/11\ ln/17 lfl/ 2ll lH/23 19/02 19/05 19/08 19/ 14 19/20 20/02 

TIME FIWM RELEASE (h) 2 5 n 11 14 17 20 26 32 38 

Peak Obs. ( fl /l) 22 1586 121 2 89 0 47 16 11\ 12 191 + 492 

Peak l~odeled ( tl /l) 153 2367 862 67 283 224 2£'4 242 197 60 468 + 668 

RESIDUAL (Op - Pp) -131 -7B1 -741 -65 -194 -224 -177 -226 -183 -1\8 -277 + 262 

CAPTEX #2 

TlAI17111TtlOO/IIR) 25/13 25/16 25/19 25/22 26/01 26/04 26/10 26/16 n;22 27 ;o4 27/10 27/16 

TIME FROM RELEASE (h) 1 4 7 lll 13 lfi 22 28 34 40 46 5£' 

Peak Obs. ( f 1 /l) 1 1 228 1348 1575 1399 200 96 73 96 43 44 425 + 618 

Peak 1100ELED ( fl /l) 156 2767 14 30 1()£'0 381 413 245 214 144 50 27 26 573 + 779 

RESIDUAL (Op - Pp) -155 -2766 -1202 328 1194 986 -45 -118 -71 46 16 18 -148 + 1017 -

Vl 

N CAPTEX #3 

DATE/TIME ( 00/IIR) 02/16 02/19 02/22 03/01 03/04 03/07 03/13 03/19 04/01 04/07 04/13 

TIME FROM RELEASE (h rs) 2 5 13 ll 14 17 23 29 35 41 47 

Peak Obs. (fl/l) l 7l 304 21 1S 63 68 Hi2 79 28 3 74 + 89 

Peak 110DELED ( fl /1) 0 4 874 1416 22 261\ 201 294 28 0 0 282 + 426 

RESIDUAL (Op - Pp) 67 -570 -1395 -7 -201 -133 -132 51 2B 3 -208 + 433 

CAPTEX #4 

D7CIT7TTI1E ( DD/1/R) 14/13 l'f/Tii 14719 14;22 15/01 15/04 15/07 15/lU 15/16 15/22 16/04 

TIME FIWt1 HELEASE (h) 2 5 8 11 14 17 20 23 29 35 41 

Peak Obs. ( fl /l ) 0 935 1350 248 216 210 156 40 37 28 0 293 + 439 

Peak /100ELED (fl/1) 67 B30 1448 687 491 39£' 221 14 7 51 35 0 397 + 426 

RESIDUAL (Op - Pp) -67 105 -98 -439 -275 -182 -65 -107 -14 -7 0 -104 + 142 

CAPTEX #5 

DATE/TIHE (lJD/IIR) 26/03 26/09 26/15 26/21 27/03 27/09 27 /l /21 

TIME FROM I<ELEASE (h) ll 10 11i 22 28 34 40 46 

Peak Ohs. ( f l/1 ) 167 41J0 384 33 125 10 2 1 148 + 181 

Peak 110DELED ( fl /l ) 0 794 4713 382 272 5 0 0 241 + 277 

I~ESIDUAL (Om - Pm) 11i7 -331J -91J -31J9 -11J7 5 2 1 - 93 + 178 

CAPTEX #7 

DATE/TIME ( DO/IIR} 28/23 29/02 29/05 29/08 29/11 29/lll 29/20 30/02 

TIME FROM RELEASE (h) -2 l I] 7 10 13 19 25 

Peak Ohs. ( fl I 1 ) l l 107 309 277 ~46 553 91J 236 + 224 

Peak HODEL ED ( fl /l) 0 () £'99 1041 32 578 li52 £'30 354 + 351 

RESIDUAL (Op - Pp) 1 1 -192 -732 245 -32 - 99 -132 -118 + 280 
TABLE 17 

HIGH-25 OBSERVED AND MODELED CONCENTRATIONS UNPAIRED 

IN TIME AND LOCATION FOR EACH CAPTEX EXPERIMENT 

EXPT 0 p P25/025 d 

(£fJ1) (flJf) (fl/1) 

1 121 ±311 379 ± 502 3.1 -259 ± 237 

2 341 ± 437 470 ± 578 1.4 129 ± 240 

3 43 ± 59 230 ± 300 5.3 187 ± 246 

4 196 ± 293 319 ± 352 1.6 -123 ± 146 

5 113 ± 161 230 ± 204 2.0 -117 ± 86 

7 178 ± 152 253 ± 258 1.4 75 ± 118 

ALL 637 ± 436 1010 ± 559 1.6 -373 ± 222 

± one standard deviation 

53 
subset of concentration pairs to compare observed and modeled concentrations 

for each arc from Dayton cases. The results for mean concentrations in 

Table 18 were derived from paired values at all sites along each arc from 

CAPTEX #l-4. These results confirm that the largest overpredictions occurred 

at the closest arc with the largest negative residuals at the 300 and 400 km 

arcs. The mean observed concentration at the 300 km arc was significantly 

greater than values at other arcs by as much as a factor of 10. Another 

notable result is that observed mean values appear to display no strong 

trend with downwind distance between the 400 km and 1000 km arc over these 

cases. The modeled mean concentrations, on the otherhand, definitely exhibit 

a gradual decrease with distance. The most significant differences between 

the respective mean values existed from the 400 km to 600 km arcs. 

The results for the peak concentrations in Table 19 are similar to those 

for mean values over these arcs. The peak observed and modeled values were 

computed from the highest concentration at each of the sites along the arcs 

for these cases. These results show that model overpredictions of peak 

concentrations were also certainly largest at the 300 km arc. While the 

peak observed concentration at the 300 kill arc is considerably larger than 

peak values at any of the other arcs, there is also an indication of a 

secondary peak in the results for the 700 km arc. This feature was believed 

to be attributable to fumigation of elevated tracer material to the ground 

during the radid growth of the mixing height to higher levels over the 

morning period of the day after release. 

Comparative Analyses of Plume Patterns and Positions 

The graphical results in Figure lla-f are shown to give qualitative 

displays of the overall observed and simulated plume patterns for each of 

the modeled CAPTEX experiments. The overall spatial patterns of the 

observed and modeled plumes are depicted by symbol(s) at the sites that 

experienced a nonzero observed (0) and/or modeled (*) concentration(s) 

during any sampling event of an experiment. The sites where both nonzero 

observed and predicted concentrations occurred represent an overlap region 

of the actual and modeled tracer plumes over the entire course of a 

particular experiment. 

During CAPTEX #l-4 (Figures lla-d) with releases from Dayton, both 

modeled and observed plumes crossed the 300 km arc in northern Ohio, 

although some spatial displacement in the positions of plume impact are 

evident even at this arc. The modeled plume appeared to overlap the 

observed tracer plume very well at the 300 km arc during CAPTEX #l 

(Figure lla), however, the observed plume traveled north of the modeled 

plume as it passed across Lake Ontario and upper New York state before 

exiting the sampling region. The modeled plume during CAPTEX #2 (Figure llb) 

intercepted the 300 km arc to the left (i.e. counterclockwise) of the 

observed plume, however, there appears to be better overall spatial agreement in the plume patterns farther downwind in this case. 

In contrast, the modeled plumes were shifted to the right (clockwise) 

of the observed plumes at the 300 km arc during CAPTEX #3 and #4 in 

Figures llc and lld, respectively. The spatial discrepancies between the 

respective plumes are particularly noticeable from the 300 km to 500 km arcs 

during CAPTEX #3. In fact, the observed plume nearly missed the 300 km arc 

54 
TABLE 18 

STATISTICAL RESULTS OF OBSERVED AND MODELED CONCENTRATIONS 

PAIRED IN TIME AND LOCATION FROM SAMPLING ARCS FOR CAPTEX #l-4 

ARC N NN 0 p d AAR T4 (O>P) 

(SITES) (PAIRS) (fl/1) (fl/1) (fl/1) (fl/1) (%) 

300 16 91 140.8 230.3 -89.5 321.8 41.8 

400 9 71 12.0 110.7 -98.7 109.5 23.9 

500 12 75 18.7 55.4 -36.7 53.7 30.7 

600 10 78 15.2 34.3 -19.2 41.5 41.0 

700 10 93 18.8 27.0 -8.2 39.3 55.9 

800 13 112 16.8 14.1 2.7 27.0 67.5 

900 8 63 12.2 12.5 -0.3 22.1 60.3 

1000 3 27 13.7 13.4 0.3 17.6 63.0 

TABLE 19 

PEAK OBSERVED AND MODELED CONCENTRATIONS 

UNPAIRED IN TIME AND LOCATION FROM CAPTEX #l-4 

ARC N NN 0 p d AAR T4 

cd;1) (d/1) (fl/1) (fl/1) (%) 

300 12 12 439.0 1041.7 -602.7 983.5 16.7 

±658.2 ±924. 8 ±1136. 8 

400 8 8 61.1 386.1 -307.0 307.0 0.0 

±69.8 ±328.6 ±354.8 

500 9 9 71.7 170.4 -98.8 107.7 22.2 

±59.1 ±95.7 ±94.2 

600 9 9 75.2 113.3 38.1 64.6 22.2 

±63.6 ±78.9 ±65.6 

700 9 9 84.8 135.2 -50.4 123.6 33.3 

±74.2 ±82.6 ±132.6 

800 12 12 71.0 59.3 11.7 53.5 58.3 

±41.4 ±53.5 ±75.2 

900 6 6 62.5 70.7 -8.2 80.8 50.0 

±34.3 ±111. 5 ±125.5 

1000 2 2 55.5 123.0 -67.5 67.5 0.0 

±37.5 ±73.5 ±36.1 

55 
"<> 

0 

0 

... 

~---~a~_:C.:_A.:_PT.:_E:_X~#-1_R_Es_u_L_T_s _____ • /( .1.oa' 

R 

b CAPTEX #2 RESULTS 

R 

Jf J4.Cq' 2~---..L ___ .....i.:_ ___ ~~L3"-.....LL--------; 

. 

~ ~ ~ 

Figure 11. Observed (0) and modeled (*) plume patterns depicted from sites 

with nonzero concentrations during a) CAPTEX #l and b) CAPTEX #2 

56 
c CAPTEX #3 RESULTS 

• 0 

0 

R 

.. 

0 

Q 

0 d CAPTEX #4 RESULTS " ~----____ ____::._ __________ • /147.oc' 

R 

------~------L_------~~B_d_ __ ----------~~H~W 

<> 

.. 

"' 

Figure 11. Same as 11a-b, except for c) CAPTEX #3 and d) CAPTEX #4 

57 
e CAPTEX #5 RESULTS 

R 

~--~----L---~~_.J1__j_ _______ 1&/{ ,8.w 

.. 

'b 

0 

.,; 

-y-----f _c_A_PT_E_X__:_#_7_R_E_s_u_L_Ts _____ ~ /{ .r.w 

R 

0 

0 0 

0 

.,; 

.. 

.. 

------~------L_------~~~d_------------~&/{~-(1(1' 

0 

.. 

.. Figure 11. Same as lla-b, except for e) CAPTEX #5 and f) CAPTEX #7 

58 
during #3, as the bulk of it apparently traveled over extreme northwestern 

Ohio. Clearly, the best overall spatial agreement between the plumes 

existed during CAPTEX #4. Results of analysis of winds to be shown later 

will indicate that vertical wind direction shear was comparatively smaller 

on this case than in the other Dayton episodes. 

Figures lle-f show the plume patterns during CAPTEX #5 and #7 for the 

Sudbury releases. There was an interesting difference between these cases 

as the modeled plume traveled to the right (clockwise looking downwind) of 

the observed plume during CAPTEX #5 and to the left (counterclockwise) of 

the observed plume during #7. There is also evidence that the spatial 

separation between the respective plumes increased with distance downwind 

for these two cases. However, no firm conclusions can be reached about 

the relative spatial agreement between the plumes at any particular 

time period within an experiment from Figure lla-f since each showed only 

the overall spatial 'footprint' of the modeled and observed plumes over 

a particular experimental episode. Individual graphical maps of the 

concentration distributions, too numerous to display herein, are needed 

to demonstrate the patterns of the observed and modeled plumes at each time 

period. 

Another analysis technique that has emerged to assess spatial displacements between modeled and observed plume patterns relies on plume centroid 

positions. With this technique, the difference in relative plume positions 

and plume separation can be explored. A centroid location of a plume is 

defined herein as the density-weighted maximum concentration coordinate 

position (Xc,Yc). The plume centroid positions for the modeled and 

observed plumes were determined at each time period from concentrations 

at sites with Eq. (8). 

~ xj•Cj I~ cj 

~ Yj.cj 1 ~ cj 

(8a) 

(8b) 

In Eq. 8, xj-Yj are the latitude-longitude coordinates of each site (j) 

with a nonzero concentration (C), where C represents either an observed or 

modeled concentration over a particular time period (t). The summation is 

performed over all sites separately with the observed and modeled plumes. 

Using the results of Eq. 8, the downwind distances of the observed (D0 ) 

and predicted (Dp) plume centroid locations with respect to the particular 

release site were determined. In addition, the results of Eq. (8) were also 

applied in order to compute the separation distance (Ds) between the 

observed and modeled plume centroid positions. 

These distance parameters have been advocated by Clark et al. (1988) 

in an assessment of long range model performance. For example, the statistical and test results presented earlier may not be able to distinguish 

between the performance of two different models in situations where both 

calculate zero concentrations at the same sites. That is, one model's 

plume pattern may slightly miss sampling sites, while the plume from another 

model may be displaced by a much greater distance from the same measurement 

sites. With these plume distance parameters, the downwind distance ratio 

59 
(Dp/D0 ) and a normalized separation distance ratio (Ds/D0 ) can 

be applied to more rigorously assess and distinguish between the performance 

of different models. For example, values of Dp/D0 that are greater 

than unity indicate the modeled plume traveled faster than the observed 

plume, while ratios less than unity signify the modeled plume was transported 

slower than the observed plume. On the otherhand, the values of Ds could 

implicate the speed and/or direction components of transport. However, if 

both plumes were the same distance downwind (i.e. Dp/D0 =1), a separation 

between the respective plumes would be entirely attributable to directional 

errors by the model. 

The results of these ratios for each CAPTEX episode are presented in 

Figure 12a-f. Values have been plotted at the mid-point in time of 

each sampling interval. Focusing on the CAPTEX #l-4 (Fig. 12a-d), most of 

the values of Dp/D0 are less than 1, which reveals the modeled plumes 

traveled slower than the observed plumes. In particular, the evidence 

in some of these cases showed that the modeled plume tended to travel 

more slowly than the actual plume during the first overnight period. The 

sign convention adopted for the ratio of Ds/D0 in these figures 

specifies whether the modeled plume centroid was to the left (minus) or to 

the right (positive) of the observed tracer plume. The most dramatic 

shifts in Ds/D0 also occurred during the nocturnal hours of the first 

night. During the stable night hours, large vertical shears in both speed 

and direction are expected to develop in association with the nocturnal 

low level jet. In addition, graphical maps of plume concentration patterns 

during the morning periods of the second day in these cases also verified 

that the leading edge of the observed plume was impacting sites along arcs 

considerably farther downwind than the modeled plume. 

An examination of the MESOPUFF II code revealed that the modeled plume 

was always transported by the lower wind field (mixed layer averaged) even 

during the nocturnal hours. Transport of the modeled plume was not switched 

to the upper layer wind field because with a surface-based nonbouyant 

release as in this application, Zp always remained less than Zi. Thus, 

even though the mixed layer depth dropped to relatively low values at night, 

Zi continued to be greater than Zp. Plume transport by the mixed layer 

averaged field, which at night is representative of the wind flow over a 

relatively shallow layer, also explains why the observed tracer probably 

outpaced the modeled plume during the nocturnal period. At night when 

significant vertical shears in speed and direction are prevalent, the 

mixed layer averaged winds were certainly slower than upper level wind 

speeds which more likely advected the observed tracer plume. In addition, 

plume separation was also magnified because larger differences in wind 

direction between these layers often exist during stable conditions at 

night. Examinations of nocturnal wind profiles during the CAPTEX 

episodes revealed notable vertical shears in both speed and direction, 

although there was variability from among the cases. 

The results for the two Sudbury cases where the releases were at night 

under moderate winds behind cold fronts differed somewhat from the previous 

cases and each other. The results for CAPTEX #5 in Figure 12e were closer 

to ideal as higher winds and smaller vertical shears were responsible for 

transporting the rather narrow plumes rapidly off the U. S. east coast 

(see Figure 8e for plume patterns). Results for CAPTEX #7 in Figure 12f are 

60 
1.5 

1.0 

0 

~ .5 

c:: 

0.0 

-.5 

-1.0 

12 

CAPTEX 

0 

X X ---------------------------------------------- X 

X X X X X 

0 0 0 0 0 

0 0 ° ----------------------------------------------

I I, I I I, I I, I I I I, I 

20 00 OA. 08 12 16 20 00 OA. 03 12 

14 18 22 02 06 10 14 18 22 02 06 10 

1.5-

0 

~.5 

£::!::: 

0.0 

-.5 

TIME (LST) 

b CAPTEX 2 

I I I' I' I I I' I I' I' I I I 

Dp/Do 

o - D,/00 ~ 

X 3 

------------------------------x-----x-----)(---j 

X X X X X X 1 ______________________________________________ _] 

0 0 ~ 0 J 

~ 

0 

0 

0 0 0 

0 0 J 

-1.0 I lr I I, I I I I I I I I I I I I I, I I I I I I I I I, I I I I 

04 08 12 16 20 00 04 03 12 

0~ 06 10 14 18 22 02 06 10 

12 16 

14 18 

TIME (LST) 

Figure 12. Ratios of downwind distances of the model and observed 

plume centroid locations (D /D0 ) and separation 

distance between centroid pgsitions to the observed 

downwind distance (Ds/D0 ) versus time of day starting 

from the day of release. Negative and positive values 

for Ds/D0 denote the model plume position is to the 

right and left of the observed plume, respectively. 

a) CAPTEX #l and b) CAPTEX #2 results. 

61 
1.5 

1.0 

0 

::;: .5 

a:: 

-.5 

CAPTEX 3 

X 0 

X 

X X -----------------;c--------x------------------

0 X 

X 

0 0 

0 

4 ----------------------------------------------~ 

0 0 0 j 0 

-1.0U-~~~~~~LLLULW~~~~~~LLLL~~~~~~~~~~~~~ 12 16 20 00 04 08 16 20 00 08 12 

14 18 22 o: 06 10 14 18 22 02 06 10 

TIME (LST) 

d CAPTEX 4 

X 

1.5 

X X 

1.0 ----------------------------------------------

0 

X X X X 

X 

0 X 

0 0 

-----------------------------------------------3 

0 0 0 0 0 0 j 

04 08 12 16 20 00 04 08 12 

14 18 22 02 06 10 14 18 22 oz 06 10 

TIME (LST) 

Figure 12. Same as 12a-b, except for c) CAPTEX #3 and d) CAPTEX #4 

62 
1.0 

0 

':;: .5 

0:::: 

0.0 

-.5 

2.0 

1.5 

X 

-----------------------X-----~---------------- X 

X 

0 

0 0 _______________________ Q _____________________ _ 

0 

04 08 12 20 00 04 08 12 16 20 

02 06 10 14 18 22 02 06 10 14 18 22 

TIME (LST) 

f CAPTEX 7 I 

X X 0 

X 

X 

---------x------------------------------------

0.0 ----------------------------------------------

0 0 

-.5 

0 0 0 

00 

-1.0~' Ll LLLLLLLLLLLLLLLLLLLLLLLLLLLLLL~LLLLLLLL~~~ I I I, I, I, I I I I I I I I I I, I I I I I, 

00 04 08 12 16 20 00 04 08 12 16 

02 06 10 14 18 22 02 06 10 14- 18 22 

TIME (LST) 

Figure 12. Same as 12a-b, except for e) CAPTEX #5 and f) CAPTEX #7 

63 
in agreement with the overall plume patterns shown earlier in Figure llf 

as the modeled plume traveled to the left (looking downwind) of the observed 

plume and at a faster pace, which was a departure from the other cases. 

The non-normalized values of these parameters are presented in 

Figure 13 to show the actual difference between Dp and D0 and the 

magnitude of Ds. The results have been plotted against time after 

release for all episodes. A notable feature is that the largest differences in downwind distance between the respective plume centroid locations appeared from 12-24 hours after releases with values around 200 krn. 

This time frame also coincided with the nocturnal period for the Dayton 

cases. The largest values of Ds were also found during this time period 

as values near 300 km occurred among these cases. Some caution must 

be exercised when interpreting the results for the later time periods 

because the bulk of the observed plume probably already moved beyond the 

sampling domain. Consequently, greater uncertainty exists with these 

points as some values may not accurately reflect the true differences 

between the respective plumes as the observed plume centroids were 

derived from plume remnants still being sampled at the farthest 

arcs from the release locations. Nevertheless, these results have 

provided valuable quantitive information about the magnitude of spatial 

plume displacements and helped focus on the probable causes for deviations 

in plume transport by the model. 

DIAGNOSTIC TEST RUN RESULTS 

Additional processor and model runs were conducted in order to 

exercise some of the optional selections for the wind field and dispersion 

methods and to compare these results with those already obtained from the 

operational default model runs. It was decided to conduct the diagnostic 

runs for the Dayton cases only with the emphasis in the analysis on the 

peak concentration results at the 300 krn arc. This test strategy was 

selected in order to uncover the extent of the differences in the plume 

impact location and timing for the various wind fields and to identify 

the cause of the model overpredictions of peak concentrations which were 

pronounced at the 300 krn arc sites. A single optional feature was exercised 

in each of the diagnostic runs while all other default parameters and 

methods remained unchanged. The input surface and upper air data files 

were identical to those in the default runs. 

Although MESOPAC II contains options for several different wind fields, 

it was decided to limit the diagnostic runs to two alternative wind fields; 

single-level wind fields for the surface and the 850mb levels. Either of 

these wind flows might be selected in certain model applications. Winds at 

the 850 mb level are generally representative of the flow at the top of the 

daytime mixing layer, and it is expected to provide a strong contrast from 

the transport provided by a surface wind flow. MESOPAC II processor runs 

were performed to produce meteorological files for each case with these 

wind field selections. 

Of particular interest are differences in the location and travel time 

for the peak concentration and its magnitudeat the 300 km arc for the 

different wind fields and how the results compare with those of the observed 

plume. Tables 20-23 present the comparative results for CAPTEX #l-4, 

64 
DOWNWIND DIFFERENCE 

400 I I 

0 

t:. 

200 0 * 0 

0 0 0 ,.--.... 0 

E x? 0 

t:. 

.:::t. X X XO )!(0 X 0 t:. ........... X X 0 0 0 t:. 

* X 

0 0 0 2 X *t:. 

I 

a. IE! 0 t:. 

0 

0 * 

0 

0 

0 0 

-400 I I 101 I I I I 

0 10 20 30 40 50 

HOURS AFTER RELEASE 

SEPARATION DISTANCE 

400 I I I I I I I I I I I I I I I I I I I I 

0 0 J 

0 

0 ~ l 300 l .c. 0 

0 XI 

,.--.... 0 l 

E 0 * 0 J 

2;,0o t:. X _j 

J 

"' 0 0 X 0 A J 

X t:. X I 

A X -tr.c. l 

100 )60 X xo X 0 Q X l t:. I 

* 0 l 

0 o *o J 

0 * J 0 I I 0 I I I I I I I I I I I I I I I I 

0 10 20 30 40 50 

HOURS AFTER RELEASE 

Figure 13. a) Difference in the downwind distances of the centroid 

positions of the modeled (D ) and observed (D0 ) plume 

patterns versus time after ?elease. b) Separation distance (D ) 

between modeled and observed plume centroid locations versus s 

time after release. Symbols in both figures denote events for 

each experiment; CAPTEX #l (0), #2 (X), #3 (triangles), 

#4 (squares), #5 (stars), and #7 (diamonds). 

65 
respectively. The individual results will be discussed separately in 

this section. The azimuth angle of each site with respect to true north 

are also given to help quantify the angular difference in the relative 

positions of plume impacts with the different wind fields. The position 

of each site in these tables is consistent with the configuration of this 

arc, as shown earlier in Figure 2, with site numbers increasing from right 

(east) to the left (west). 

Table 24 presents the hourly NWS surface wind observations and results 

of certain parameters from the operational model runs for the release period. 

This table is provided with the intention of giving supplemental information 

for the interpretation of the model results. Surface winds in Table 24 do 

indeed show that the Dayton releases all occurred under primarily southwesterly 

wind flows. Consequently, for this wind flow and with the configuration 

of the sampling arc, a modeled plume impacting a site to the right (left) 

of the observed plume location on the 300 krn arc would indicate a greater 

influence by a more westerly (southerly) component in the wind field. 

The results in Table 20 for CAPTEX #l indicate that the location and 

timing of impact of the peak concentration with the mixed layer (default) 

wind field compares favorably with the observed results. Site 316 was 

the location of impact for both the observed and model default peak concentration and the transport times were also the same at 5 h after the start 

of release. In contrast, the surface wind field caused the modeled peak 

concentration to occur much later and at a site slightly to the left of 

the observed results. The 850mb winds transported the modeled plume 

at about the same speed as the observed plume but directed it to the right 

of the observed peak concentration location. These results are to be 

expected when wind direction becomes more westerly with height which was 

evident from the rawinsonde profiles; the wind flow at 850mb had a greater 

westerly component than the surface winds. It appears that winds averaged 

over the mixed layer simulated the observed transport very well during the 

afternoon period in this case. 

The results in Table 21 for CAPTEX #2 are certainly somewhat different 

from the CAPTEX #l in the relative positions of plume impact. During this 

experiment the model default peak concentration intercepted the arc much 

faster and to the left of the location of the observed peak value. In fact, 

several 'model-specific' sampler sites were included in the model run in 

an effort to better define the modeled plume position in this case. The 

default peak occurred at a site about 25° to the west (left) of the 

observed peak. Mixed layer averaged wind directions at Dayton in Table 24 

were indeed more southerly than the surface winds, which indicated why the 

modeled plume moved to the left of the observed plume position, but this 

did not explain why the mixed layer averaged wind possessed a greater 

southerly component. However, the afternoon and the regular evening 

(00 GMT) wind profiles at Dayton in Figure 14 appeared to show why the 

modeled plume behaved in this manner. The 00 GMT profile ,which was used 

to determine the modeled winds, revealed that wind direction backed with 

height from 230° at the surface to 250° near 1000, while the sounding 

at 18 GMT indicated that wind direction displayed the more typical veering 

with height during the release period. Consequently, d8 derived from the 

surface and layer-averaged directions was positive from the 00 GMT 

profile, which produced the stronger southerly component found in the mixed 

66 
TABLE 20 

COMPARATIVE RESULTS FOR DIFFERENT YIND FIELDS ON 

PEAK CONCENTRATION/PLUME TRANSPORT AT THE 300 KM ARC FOR CAPTEX #1 

RELEASE - 9/18 (1200 

320 

AZIMUTH (0) (24.5) 

0 1 

D~~JTIME$ 18/1700 

TRAVEL TIME 

MODEL WIND 

DEFAULT 

SURFACE 

850 mb 

*(h) 5 

FIELD 

0 

176 

18/2300 

11 

0 

- 1500 LST) 

SITE NUMBER 

318 316 314 

(36.2) (42.5) (45.3) 

425 1586 197 

18/1700 18/1700 18/1700 

5 5 5 

116 2367 1568 

18/1700 18/1700 18/1700 

5 5 5 

4456 752 163 

18/2000 18/2300 19/0200 

8 11 14 

0 0 0 

$ TIME IS THE START HOUR OF THE SAMPLING I~TERVAL 

312 

(55.4) 

0 

0 

0 

1961 

18/1700 

5 

* TIME INTERVAL FROM THE START OF RELEASE &~D TO BEGINNING OF 

OF SAMPLING INTERVAL 

67 

310 

(60.5) 

0 

0 

0 

642 

18/1700 

5 
TABLE 21 

COMPARATIVE RESULTS FOR DIFFERENT YIND FIELDS ON 

PEAK CONCENTRATIONS/PLUME TRANSPORT AT THE 300 KM ARC FOR CAPTEX #2 

RELEASE 9/25 (1205-1505 LST) 

SITE NUHBER 

324* 323* 322* 321* 320 318 316 314 312 310 

AZI.( 0 ) ( 1.5) (4.7) (10.8)(16.7)(24.5)(36.2)(42.5)(45.3)(55.4)(60.5) 

g~~JTIME TRAVEL TIME (h) 

MODEL WIND FIELD 

DEFAULT 9 320 2767 

26/01 25/16 25/16 

13 4 4 

SURFACE 12 79 286 

26/07 26/07 26/07 

19 19 19 

850 mb 0 0 0 

* 'Model-specific' sites 

64 1575 768 407 12 10 

26/04 26/02 26/04 26/01 26/04 26/04 

16 14 16 13 16 16 

1430 390 20 0 0 0 0 

25/19 25/22 26/04 

7 10 16 

459 1106 1324 873 656 92 74 

26/10 26/10 26/13 26/13 26/16 26/19 26/19 

22 22 25 25 28 31 31 

0 0 0 533 1002 303 0 

25/19 25/22 2·5/22 

7 10 10 

only 

68 
TABLE 22 

COMPARATIVE RESULTS FOR DIFFERENT YIND FIELDS ON 

PEAK CONCENTRATIONS/PLUME TRANSPORT AT THE 300 KM ARC FOR CAPTEX #3 

RELEASE - 10/02 (1400-1700 LST) 

SITE NUHBER 

320 318 316 314 3-12 310 308 306 

AZI. (0) (24.5) (36.2) (42.5) (45.3) (55.4) (60.5) (68.8) (74.4) 

g~~~HR 304 0 2 0 0 0 0 0 

02/2200 03/0100 

TIME (h) 8 11 

MODEL WIND FIELD -·-----------------------------------------------------------------------

DEFAULT 0 0 102 38 1416 524 8 0 

02/2200 02/2200 03/01 02/2200 03/0100 

8 8 11 8 11 

SURFACE 258 10 3 11 0 0 0 0 

03/0400 03/0400 03/0700 03/0700 

14 14 17 17 

850 mb 0 0 0 0 0 14 754 1357 

03/0100 03/0100 03/0100 

11 11 11 

69 
TABLE 23 

COMPARATIVE RESULTS FOR DIFFERENT WIND FIELDS ON 

PEAK CONCENTRATIONS/PLUME TRANSPORT FOR THE 300 KM ARC FOR CAPTEX #4 

RELEASE - 10/14 (1100-1400 LST) 

SITE NUHBER 

320 318 316 314 312 310 308 306 304 302 

AZI.( 0 ) 24.5 36.2 42.5 45.3 55.4 60.4 68.8 77.4 83.9 93.1 

Omax 0 0 0 

DAY/HR 

TRAVEL TIME (h) 

MODEL WIND FIELD 

DEFAULT 0 0 0 

SURFACE 65 799 1859 

15/07 15/01 15/01 

20 14 14 

850 mb 0 0 0 

M missing measurements 

0 

0 

1492 

15/04 

17 

0 

70 

9 

15/19 

8 

0 

231 

15/04 

17 

0 

1350 

14/19 

8 

0 

119 

15/04 

17 

0 

33 

14/19 

8 

1448 

14/19 

8 

0 

0 

0 

145 

14/16 

5 

0 

0 

M 

0 

0 

626 

14/16 

5 

M 

0 

0 

81 

14/19 

8 
SITEDATE 

TABLE 24 

SELECTED METEOROLOGICAL OBSERVATIONS AND MODEL RESULTS 

AT THE RELEASE SITE OF EACH CAPTEX EXPERIMENT 

SFC OBS. MODEL ML WINDS$ 

HR ws WD SPEED DIR PGT TEMP 

(LST) (m/s) (Degx10) (m/s) (De g) CLASS (oF) 

(DAY-9/18) 

#1 12 7.7 22 13.4 224.4 4 86 

13 9.3 24 16.0 245.0 4 87 

14 8.8 21 15.3 216.7 4 89 

15 8.2 22 14.3 224.8 4 89 

CLOUD 

COVER 

(tenths) 

0 

4 

4 

4 

-------------------------------------------------------------------------

(DAY-9/25) 

#2 12 4.1 24 9.4 230.1 3 66 10 (250)* 

13 5.2 20 12.8 189.5 4 68 10 (250)* 

14 6.2 22 15.6 206.6 4 70 10 (250)* 

15 3.6 22 10.1 205.2 4 69 10 (100)* 

--------------------------------------------------------------------------

(DAY-10/2) 

#3 14 7.2 24 17.3 266.0 4 81 0 

15 5.7 22 13.7 248.7 4 82 0 

16 4.1 23 10.1 258.5 3 81 0 

17 5.2 23 12.4 257.6 4 81 0 

--------------------------------------------------------------------------

(DAY-10/14) 

#4 11 7.7 25 14.8 269.4 4 49 0 

12 7.2 26 14.5 280.9 4 51 0 

13 7.2 24 14.9 264.2 4 53 0 

14 8.2 25 16.3 271.9 4 55 0 _______________________________________ .,. _________________________________ _ 

(SUD-10/25-26) 

#5 23 4. 6 32 4.6 319.9 4 37 8 (11)* 

00 3.6 32 3.6 319.9 4 37 8 (16)* 

01 5.2 33 5.2 329.8 4 39 8 (18)* 

02 5.7 31 5.6 310.0 4 39 8 (13)* 

---------------------------------------------------------------------------

(SUD-10/29) 

#7 01 8.2 33 17.9 326.8 4 32 4 

02 6.2 33 13.0 326.9 4 32 8 (30)* 

03 3.1 33 8.8 339.7 4 30 8 (24)* 

04 6.2 33 13.0 326.9 4 30 4 

$ Mixed layer (ML) averaged winds at the grid point nearest release site 

* Ceiling height in hundreds of feet above ground 

71 
STATION 72429 DATE: 9/25/83 TIME18 GMT 

.3000 

\ 

\ 

19 

-J I 

l:l 2000 fo 

o:l: ' ' 

E ' 

0 

- I 

/ 

1- ,0' 

::r: >' 

l:l ~ \ 

L.U 1000 \ 

Q ::r: I 

I 

0 

~ \ 

\ 

\ 

~~~ 

~D 

ol -'?--~~ I '::; - r 

~ 2 .... ! 110 I I ? 

0 50 100 150 200 250 JOO 

SPEED {m/s) , DIRECTION {0 ) bottom axis 

STATION 72429 

-...J 

l:l 2000 

o:l: 

E 

-

l.!.J 

:c 

1000 

250 270 280 290 

SPEED (m/s) , DIRECTION (0 ) bottom axis 

Figure 14. Upper air wind speed (O) and wind direction (X) profiles 

at a) 18 GMT (i.e. 13 LST) and b) 00 GMT for CAPTEX ~2. 

72 
layer averaged wind directions in Table 24 for this case. Another wind 

profile from a rawinsonde launch at 20 GMT was also very similar to the 

18 GMT profile, so the vertical variation in wind direction exhibited in 

the 00 GMT sounding did not occur during the time period of the tracer 

release. This case demonstrated the impact on model results when the 

upper air data were not representative of the conditions at an earlier 

time. It is apparent that better model results might have been obtained 

if one of the upper air profiles taken during the release period was 

substituted for the 00 GMT profile, or if the model was capable of using 

rawinsonde data at more frequent time intervals. 

The largest spatial difference in the location of plume impact 

between the observed plume and modeled plume with the mixed layer averaged 

winds occurred in CAPTEX #3 (Table 22). The exact location and magnitude 

of the actual tracer peak concentration could not be accurately judged 

in this case since the bulk of the tracer plume definitely traveled to the 

west of this arc. Some of the tracer plume impacted site 320 located on 

the western end of the arc. It is estimated from Table 22 results that the 

peak concentration location from the model default run was shifted at least 

30° to the right of the position where the observed plume may have passed 

at this downwind distance. The 00 GMT wind profile at Dayton in Figure 15 

reveals that significant vertical shear in direction existed within the 

mixed-layer in this case, as wind directions varied from 200° at the 

surface to almost 270° at Zi. This large vertical variation in 

direction also explains the large differences in plume impact time and 

location between the model runs with surface and 850 mb wind fields. The 

release period for #3, being slightly later in the afternoon compared to 

the other Dayton releases, may also have contributed to the variations 

in the plume's trajectory and dispersion. In particular, tracer gas 

emitted near the end of the release period at 17 LST had much less time to 

be mixed through the boundary layer as convective turbulence is already 

less vigorous and is rapidly decreasing during the late afternoon hours. 

Tracer measurements from aircraft flights provided additional 

valuable information about the impact of vertical direction shear coupled 

with the timing of the release for CAPTEX #3 on the transport and 

dispersion of the tracer plume. An aircraft flight leg was conducted 

across northern Ohio at 1500 m around midnight. A tracer plume was 

discovered at this level with the highest concentration being 1466 fl 1-l 

in the same relative position as modeled peak concentration from the 

mixed layer wind fields. However, the real suprise occurred from the tracer 

measurements from aircraft flight legs over southeastern Pennsylvania 

during the afternoon of the next day, October 3. The vertical cross-section 

in Figure 16 showed evidence of a coherent tracer plume aloft with a 

concentration as high as 2961 fl 1- 1 . Clearly, this portion of the 

tracer plume was transported by westerly winds which existed in the upper 

part of the boundary layer. Additionally, for concentrations to be so 

high, this plume section had experienced little boundary layer-based 

turbulent activity, which would have dispersed it and fumigated it to the 

surface. Surface sampling sites measured zero concentrations in this area. 

The multi-layer Lagrangian model by Davis et al. (1987), which contained 

seven vertical layers up to nearly 3000 m, displayed much greater success 

in simulating the broad spread and decoupling of the tracer plume pattern 

due to the large vertical shears during this episode. 

73 
STATION 72429 DATE: 10/ 3/83 TIMEOO GMT 

.3000 

I 

I 

Q 0- __ 

,..... 

...l 

c..:l 2000 

< 

E 

'-' 

t I 

- I 

c..:l p t;;J I 

- 1000 I 

- Q 

6 

__ ..o ' 

0 ---+----.--

t " ? ~ 110 ? It I 

200 220 2.10 250 280 JOO 320 

SPEED (m/s) 1 DIRECTION ( 0 ) bottom axis 

STATION 72429 DATE: 10/ 3/83 TIMEOO GMT 

JOOO I I I I l I ' I I I I ''' 

,..... 

...l \ c..:l 2000 

< ) 

~ E \. '-' 

!-

--

c..:l I t;;J 

- 1000 J -

O ' • r 1 I I I I I I I I I I I I I I I I I' I I I I 

-10 -5 0 5 10 15 20 25 JO 

TEMPERATURE (OC) 

Figure 15. a) Wind speed (0) and wind direction (X) profiles and 

b) temperature profile at Dayton, Ohio from CAPTLX #3 

74 
..J 

tiJ 

I: 

...... 

~ 

t..l 

Q 

:::1 

!-

!-

..J 

<:: 

COHCEHTRAT!OH CFL/L) 

R E L E AS E 3 3 0 CT Z 1Z 

32 

ZB 

24 e a oo a 

28 

a e a a 

16 e e a a 1 

BB ea e a a 

8 

e 

4 -----------------------AVERAGE-suRfAcf-HffGHf ___________________________ _ 

B 48 41 42 43 45 

LATITUDE 

Figure 16. Tracer concentration pattern from aircraft flight legs at different 

levels during the afternoon of October 3, 1983 during CAPTEX ~3. 

(Ferber et al., 1986) 

75 
The results for CAPTEX #4 in Table 23 reveal that the default model 

plume exhibited relatively good correspondence in time and position with 

the observed peak concentration. The modeled peak occurred within 10° 

to the right of site where the observed plume impacted and the respective 

travel times were in agreement. Both results also show that the 

tracer plume was narrow in this case. The results for the single layer 

wind fields were similar to those in #l and #2; the modeled plume 

using surface wind fields traveled to the right and slower than the 

observed plume and the 850 mb winds caused the modeled plume to impact 

to the right of the observed peak concentration position. 

Although the experiments from Sudbury were not examined in these model 

test runs, it is of interest to assess the plume impact locations for these 

two cases, especially on the north side of Lake Ontario. For CAPTEX #5, 

the observed and modeled plumes (Figure 8e) impacted sites 752 and 652, 

respectively. which were both about 400 km from Sudbury and just north of 

Lake Ontario (Figure 2). More importantly, the difference in azimuth angle 

with respect to Sudbury between these sites was about 8°. In CAPTEX #7, 

the observed plume traveled to the right of the modeled plume (Figure llf) 

and the angle difference in azimuth angle for the sites in this case was 

about 13°. Interestingly, in these cases and in some of the Dayton cases 

the angular separation of the respective plumes was comparable to the 

resolution of the surface wind direction observations. 

The upper air wind profile data collected during the release periods 

and at the regular 00 GMT launch time were analyzed to further explore 

reasons why modeled speeds and directions differed from those inferred from 

the actual tracer plume measurements out to the 300 km arc. The results 

in Table 25 were determined from profiles at Dayton and for Buffalo (BUF) 

to represent the Sudbury cases. The notable values are the ratio of the 

mixed-layer averaged to surface wind speeds (WSml/WS 0 ) and difference 

between the wind directions. In particular, most of the afternoon wind 

speed ratios were lower than values at 00 GMT. Wind direction differences 

in Table 25 also tended to be larger at 00 GMT than in the earlier profiles. 

Stronger turbulent mixing in the afternoon period likely reduced vertical 

shears in speed and direction within the mixing layer, however, vertical 

variations appeared to become stronger by evening. The changes over the 

time period of these profiles were also consistent with the results reported 

by Shreffler (1982). From analysis of a large wind profile data base, he 

found that the diurnal variations of wind speed ratio and wind direction 

difference over the mixed layer exhibited minimum values during the 

afternoon period with gradual increases during the evening to maxima at 

night. Thus, the mixed layer averaged fields computed by the model are 

believed to be slightly overestimating transport speeds during the daytime 

period, however, this feature was difficult to assess with the 3-h averaging 

period for these cases. On the otherhand, there was some evidence of an 

effect on wind direction in the model as the previous results indicated 

that the default model plumes were shifted slightly to the right of the 

observed plumes in CAPTEX #4 (Table 23) and CAPTEX #l (Table 20). 

The other important feature to be examined is the significant model 

overprediction of peak concentrations reported earlier. The same dispersion 

method, as outlined in Section 2, was applied in these model runs with the 

76 
TABLE 25 

RESULTS OF ANALYSIS OF OBSERVED UPPER AIR WIND PROFILES 

FROM THE CAPTEX RELEASE DAYS 

EXPT SITE DATE-TIME ws 1 WDml wsml WDB-WDml WD -WDz· z. 

(MM/DD-GMT) (mis) (De g) WSo ( eg) (8eg) ~ (mY 

1 DAY 9/18-1800 12.5 229.0 2.4 1.0 -12.0 1254 

9/18-2000 13.1 239.0 2.0 -19.0 -27.0 1855 

9/19-0000 12.7 221.5 1.8 11.5 -22.0 1675 

2 DAY 9/25-1800 5.3 220.0 1.7 -20.0 -21.6 1294 

9/26-0000 7.5 237.9 3.0 12.1 11.8 1439 

3 DAY 10/2 -1800 4. 9 258.3 1.1* -26.0* -39.0* 1808 

10/3 -0000 7.3 226.4 2.4 -26.4 -55.0 1732 

4 DAY 10/14-2000 9.2 249.2 1.5 -9.2 -30.6 1217 

10/15-0000 8.0 239.8 2.0 -19.8 -38.6 972 

5 BUF 10/26-1800 9.8 290.1 1.4 9.9 12.4 2293 

10/27-0000 11.7 315.0 1.7 -25.0 -30.0 2070 

7 BUF 10/29-1800 8.5 335.5 1.2 14.5 6.5 1254 

10/30-0000 6.2 330.5 3.1 -0.5 -8.1 1175 

NOTE: 

wsml - mixed-layer mean wind speed from observed profile data 

WDml mixed-layer mean wind direction from observed values 

wso - surface observed wind speed at the rawinsonde site 

WDo - surface observed wind direction at the rawinsonde site 

WDzi - observed wind direction at the mixing height 

zi - observed mixing height; winds averaged up to this level 

* Missing observed surface wind; values at next higher level applied; 

this result may slightly underestimate the actual condition. 

77 
different fields. In the three Dayton cases where the peak concentration 

was readily resolved (Tables 20, 21, and 23), model predictions with the 

default wind scheme were greater than observed peak values by varying 

amounts. Since dispersion is dependent on travel time after 100 km in 

the model, modeled peak values differed for the various wind fields. 

Focusing on the default model results in Tables 20-23, the overpredictions 

were smaller for #l (Table 20) and #4 (Table 23) where model transport 

times agreed with observed values. The most sizeable overprediction of the 

peak concentration by the default model run occurred in CAPTEX #2 (Table 21) 

as the modeled plume arrived much earlier than the observed plume. 

Differences in the width of modeled and observed plumes were difficult 

to assess even for the site spacing of this network, however, the results 

at 300 km suggested that modeled and observed plumes exhibited comparable 

horizontal spread. Nevertheless, the consistent model overprediction 

strongly implied that dispersion was greater for the observed plumes. 

Since puff growth is controlled by dispersion parameters, whose variations 

are dependent on stability class, the results for PGT class in Table 24 

are illustrative of a possible cause for the model overpredictions. Neutral 

stability (PGT class 4) was often found during these afternoon hours when 

unstable conditions might be expected, although based on the observed wind 

speeds the specification of a neutral stability class appears appropriate. 

A further examination of processor output revealed stability class 4 was 

indeed prevalent at the grid points in Ohio during the afternoon hours. 

Consequently, the initial growth of the model plume, particularly in the 

vertical dimension, was much more limited due to the significantly slower 

increase in the dispersion parameters under neutral stability when compared 

to that under the unstable PGT classes (Turner, 1970). In particular, the 

coefficients of the power law curve for az for neutral stability in the 

model were derived from a fit to the so-called D2 curve in Pasquill (1974), 

which is the neutral curve for the vertical dispersion parameter in Turner 

(1970). However, greater vertical dispersion in the model would have 

been produced under the Dl curve for neutral stability in Pasquill (1974). 

In any event, the principal cause for overprediction by the model in this 

application was attributed to underestimation of vertical dispersion. More 

evidence to support this explanation will be given next from additional 

model test runs. 

Diagnostic model test runs were also performed to assess the impact 

on peak concentrations by applying optional variations to the default 

dispersion method or selecting the uniform vertical mixing feature in the 

model. Results in Table 26 for CAPTEX #l were representative of those 

found in model runs for the other Dayton cases. The peak concentrations 

at the plume centerline with the uniform vertical mixing option were lower 

than values from the default model run. Since the observed peak concentration was 1586 fl 1 1 in CAPTEX #l (see Table 20), the peak value using 

the vertical mixing option was certainly more comparable and suggested 

that distributing the plume vertically over the depth of the mixed layer 

was more representative in this case. In fact, a further examination of 

operational model out~ut indicated that az was much less than zi 

at the 300 km arc, wh~ch revealed the modeled plume had not yet become 

well-mixed even out at this distance. Thus, it is evident that more rapid 

growth of az in the model would have provided an improvement in the 

prediction of peak concentrations. 

78 
TABLE 26 

PEAK CONCENTRATIONS FOR CAPTEX #l USING VARIOUS DISPERSION OPTIONS 

SITE NUMBER 

MODEL RUN 320 318 316 314 312 

DEFAULT METHODS* 0 116 2367 1568 0 

UNIFORM VERTICAL 0 69 1446 980 0 

MIXING OPTION@ 

CROSSOVER DISTANCE# 0 133 2586 1722 0 

AT 50 km 

CROSSOVER DISTANCE# 0 126 3075 2020 0 

AT 10 km 

* PGT dispersion curves applied out to 100 km, time dependent growth 

according to Heffter (1965) at greater distances. 

@ Puffs vertically distributed over the mixed-layer after release 

instead of a 2 growth. 

# Downwind distance where puff dispersion changes from PGT curves to 

time dependent method. 

TABLE 27 

COMPARISON OF OBSERVED AND MODELED MIXING HEIGHTS 

ALL PAIRS 0 < cc ::5 8/10 0 < cc :::; 4/10 

TIME (GMT) 18 00 18 00 18 00 

N 59 73 38 49 18 28 

ziO (m) 1456. 1479. 1368. 1369. 1300. 1307. 

±533. ±496. ±437. ±431. ±453. ±409. 

ziP (m) 1145. 1166. 1244. 1191. 1355. 1313. 

±317. ±326. ±270. ±339. ±324. ±331. 

d (m) 311. 312. 124. 177. -56. -6. 

AAR (m) 468. 471. 336. 402. 283. 340. 

R 0.22 0.15 0.35 0.22 0.56 0.34 

O>P (%) 66.1 67.1 57.9 59.2 44.4 39.3 

F2 (%) 84.7 89.0 92.1 95.9 88.9 100. 

cc = cloud cover 

F2 = percent of observed and modeled values within a factor of 2 

79 
Additional results in Table 26 revealed that reducing the crossover 

distance caused even higher peak concentrations compared to the default 

distance (i.e. 100 km). Clearly, these results indicated that the time 

dependent dispersion formulas provided even slower growth than that offered 

by PGT class 4 in this application. 

Since it was noted earlier that accurate specification of Zi was also 

important to both transport and dispersion in this model, a brief examination of the modeled mixing height is warranted. The diurnal variation 

of Zi at the grid point closest to Dayton over the two day period of 

CAPTEX #l is depicted in Figure 17 to illustrate the typical temporal 

behavior and magnitude of mixing height derived by the MESOPAC II processor. 

The most dramtic change in Zi occurred around sunset when a switch in 

methods takes place. Mechanical Zi's at night were generally much lower 

than the daytime convective Zi's which were primarily controlled by the 

variation in the sensible heat flux. However, the term containing the 

thermal gradient aloft in Eq. 1 also appears to be counteracting the 

surface sensible heat flux term in this case. This effect is attributed 

to the gradual decreases in zi in the late afternoon hours prior to the 

substantial drop observed at sunset. 

Of particular interest is how well the modeled mixing heights compare 

to observed values. Therefore, a data set of observed and modeled Zi's 

was developed. An observed Zi, defined as the height of the elevated 

temperature inversion base, was paired against a modeled value from the 

closest grid point to a rawinsonde site at the same hour. Observed 

values were easily obtained from the temperature profiles because a 

strong inversion was present during the CAPTEX episodes (e.g. Figure 15). 

Statisitical results were computed for Zi pairs at 18 and 00 GMT. For 

the latter time, however, it was decided that the modeled convective Zi 

at 23 GMT was appropriate to compare with an observed value since sunset 

had already occurred by 00 GMT at some sites. 

The results in Table 27 contain the results for both time periods for 

separate categories of cloud cover. The model performed best under clear 

to partly cloudy conditions which generally prevailed, as the bias (d) was 

smaller and the correlation was higher than for the mostly cloudy cases. 

It is apparent that the underpredicted Zi for the few cases when overcast 

conditions prevailed. Finally, no strong conclusions about the general 

applicability of this method to model zi should be drawn because the data 

set was relatively small and represented a rather limited set of temporal 

cases and meterological conditions. 

80 
-E 

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00 10 20 06 16 

TIME OF THE DAY (HOURS) 

Figure 17. Hourly variation of mixing height (Zi) from the MESOPAC II 

for Dayton, Ohio for September 18-19, 1983 of CAPTEX #l. 

02 
SECTION 5 

MODEL SENSITIVITY RESULTS 

Flexibility built into the design of model code can be advantageous to 

the testing of various model components. MESOPUFF II contains considerable 

flexibility which allows certain changes in methods or variations in technical parameters to occur through input values (Scire et al., 1984b). 

Nevertheless, the intent of this testing effort was not to conduct a comprehensive sensitivity study of the various model components. Practical 

considerations of time and computer costs necessitated a limit to the 

number of model test runs for selected model components. It was decided 

to place major emphasis of this sensitivity analysis on the dry deposition 

and chemical transformation algorithms, which were not exercised in the 

CAPTEX evaluation effort. Furthermore, no evaluation of the methods for 

these processes was possible during the development effort that led to 

this version of the model. Finally, there was a desire to report for the 

first time the impact from some of the options in this model. 

The main purpose of this sensitivity effort was to investigate the 

impact on surface concentrations for a typical short-term averaging 

period (i.e. 24 h) from selected changes in methods available in the 

model or from differences in particular key technical parameters involved 

in the two model components. Differences in concentrations between the 

test cases and a model base case are emphasized herein because Morris et al. 

(1988) already examined the responses of deposition velocity and transformation rates of the modeled pollutant species to ranges in atmospheric 

parameter variations, land use types, and for differences in technical 

parameters involved in these model components. 

Although various types of sensitivity methods are available (Gelinas 

and Vayk, 1979), the test procedure adopted for this effort consisted of 

varying a single option or parameter in a model test run while holding all 

other inputs and model features the same as those in a base case. This 

testing strategy permitted a comparative assessment of the relative impact 

of the variation in each test run to the base case results. Consequently, 

all model test runs were performed with the same input meteorological fields; 

namely, the gridded results produced by MESOPAC II in the default mode 

for CAPTEX #l. 

The identical source characteristics and emissions from a single 

realistic elevated point source were input to each model run. Table 28 

contains the source information and emission rates used in all model runs. 

The location of this single source was set to the same grid coordinates 

as the Dayton tracer release site. The elevated source height and strong 

buoyancy of the plume also exercises plume rise and fumigation methods in 

the model. A single source was chosen because the analysis and interpretation of the effects on ground-level concentrations from one point source are 

more straightforward and model runs are less expensive than for multiple 

sources. These test runs focused on computing so2 and sulfate (so4 ) 

concentrations with the emission rates specified in Table 28. 

82 
TABLE 28 

SOURCE CHARACTERISTICS AND EMISSION RATES 

FOR ALL MODEL SENSITIVITY TEST RUNS 

Point source location - Grid coordinates of Dayton tracer release site 

Stack height - 304 m AGL 

Stack diameter - 8 m 

Exit velocity 22 m/s 

Exit temperature 407 K 

so2 emission rate - 7064 g/s 

so4 emission rate 53 gjs 

83 
Several other aspects of the model base case and test runs should also 

be identified. All model runs commenced at midnight and model execution 

continued for a 48 h period. Source emissions in Table 28 were continuous 

over the 2-day simulation period, which was of sufficient duration for the 

source plume to travel across the entire model domain while being subjected 

to the various physical processes. Additionally, pollutant concentrations 

were computed at grid points on the model sampling grid which was set to 

the same size as the meteorological grid in the CAPTEX application. It 

was desireable to analyze concentrations on the denser, uniform model grid 

in order to take advantage of the capabilities of the MESOFILE II postprocessor program. Computational procedures were specially designed into this 

program to perform various analyses on different gridded concentration 

fields from independent model runs. 

The methods described in Section 2 for dry deposition and chemical 

transformation were applied in the model base case run. The 24-h average 

concentration fields of so2 from the model base case run for Day 1 and 2 

are displayed in Figures l8a and 18b, respectively. The results in Figure 18a 

show that the plume had reached the eastern edge of the model grid by the 

end of Day 1. The 24-h average plume patterns on both days are similar 

because of prevailing southwesterly winds within the mixed-layer with stronger 

westerly winds in the upper layer field. The highest so2 concentrations 

are found close to the source and values generally decrease with distance 

downwind due to the dispersion, and both deposition and transformation 

processes reducing so2 levels in the plume. 

The 24-h sulfate concentration patterns for the two simulation days from 

the base case run in Figure l9a and 19b are identical to those for so2 , 

except so4 concentration levels are considerably lower. However, in 

contrast to the results for so2 , highest sulfate concentrations are found 

several hundred kilometers downwind of the source on both days. This is 

a consistent feature for some pollutants, such as sulfate, which is primarily 

formed from chemical reactions during transport across a region. 

Since the plume patterns from all model test runs were also identical 

to the base case distributions because the same transport and dispersion 

conditions were applied in all cases, concentration differences were 

examined from the set of grid points defining the plume pattern. Thus, 

analyses by the postprocessor was restricted to the grid points with nonzero 

concentrations. The results consist of percent deviations of a test case 

concentration (Ct) from a corresponding model base case value (Cb). 

The results of peak and plume average concentrations for so 2 and 

so4 over the two 24-h periods from initial model test runs are given in 

Table 29. The peak concentration was defined as the highest value found 

from the entire gridded plume pattern over the time period, while average 

plume concentrations were computed from all nonzero values. These initial 

test runs were conducted to examine the impact on concentrations when one 

of these physical processes was not modeled, which represents an extreme 

situation .. The resul~s in Table_2~ show minor differences in peak so 2 concentrat~ons when e~ther depos~t~on or transformation processes were 

omitted. This is to be expected since peak so2 concentrations were generally found close to the source where these processes have not yet had much 

84 
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5 6 7 6 9 10 11 ll 15 16 17 111 19 zo Zl zz 

Average 24-h so2 concentration fields from the model bas~ case run 

for a) Day 1 and b) Day 2. All values in units of pg mZl 24 Z5 Z6 Z7 Zll 10 
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TABLE 29 

RESULTS OF MODEL SENSITIVITY RUNS: COMPARISONS WITH 

24-HOUR BASE CASE PEAK AND MEAN CONCENTRATIONS 

MODEL RUN 

BASE CASE 

No Dep. only 

No Trans£. only 

No Vert. Gauss. 

Distribution* 

1-layer mode* 

BASE CASE 

No Dep. only 

No Trans£. only 

No Vert. Gauss. 

Distribution* 

1-layer mode* 

VARIATION IN 

PEAK SO 

ccb ct);cb (%) 

DAY 1 DAY 2 

-1.6 -0.6 

1.2 -0.5 

168.5 -97.7 

-0.1 0.0 

PEAK so4 

(Cb - Ct)/Cb (%) 

-8.4 -28.5 

91.3 89.3 

22.6 21.5 

0.0 0.0 

VARIATION IN 

PLUME AVERAGE S02 

(Cb - Ct)/Cb (%) 

DAY 1 DAY 2 

-15.5 -24.6 

-7.2 -8.8 

3.2 25.9 

-2.4 -2.9 

PLUME AVERAGE S04 

(Cb - Ct)/Cb (%) 

-8.6 -17.4 

93.1 94.0 

14.7 26.5 

-1.7 1.9 

NOTE: Cb - base case concentrat~on 

Ct - test case concentratlon 

* Both deposition and transformation applied as in default mode 

89 
impact on so 2 . However, there was a greater effect on the average S02 

concentrat~ons since these values were derived over the entire plume pattern 

For example, in the model run where no deposition was permitted, the average 

plume concentration on Day 2 was nearly 25% higher than the base case concentrations. The results in the case with no S02 loss by chemical transformation indicated that the mean plume concentrations were less than 10% 

greater than the base case. On the otherhand, it is evident from Table 29 

that transformation has a much greater impact on so4 , as peak concentrations 

without transformation were around 90% lower than those in the base case. 

In this simulation, the peak so4 concentrations were located from 500-

700 krn downwind of the source position. 

Other results in Table 29 are from the model test run with no vertical 

Gaussian dispersion (i.e. uniform vertical mixing). In this case, peak S02 

concentrations were particularly sensitive to the type of vertical 

dispersion technique. Peak values were substantially higher than those in 

the base case using the Gaussian vertical dispersion parameter because the 

plume became distributed immediately through the entire mixed-layer under 

this optional method. Since this option feature produced higher peak 

concentrations and slightly greater deposition near the source, lower mean 

plume concentrations were obtained. For Day 2, the impact on the mean 

concentration is comparable, except in an opposite sense to the results 

without deposition. Peak and mean so4 concentrations were reduced 

under this dispersion option. In particular, the peak S04 concentration 

for both days was more than 20% lower than the base case values. In contrast, 

there appeared to be little impact on peak and mean concentrations in the 

1-layer model mode where the source depletion method for dry deposition 

was applied as pollutant mass over the entire vertical extent of the plume 

was subjected to dry removal. 

Additional model test runs were performed to determine the impact 

of prescribed changes in rs for so2 and sulfate. The processor 

results indicated that PGT class 4 (neutral) was often determined to 

represent the stability during the afternoon periods. The surface 

resistances for so2 for the various land use categories is 100 s/m for 

the unstable classes and 300 sjm for neutral stability. During the 

daytime period, rs is generally the dominant resistance to pollutant 

uptake since the sum of the two atmospheric resistances are often much 

less than rs. A model run was performed with rs redefined to be 

100 s/m for neutral class, which essentially was an attempt designate these 

cases as being unstable in the model. However, the results in Table 30 

show that the effects of this change are rather small on the peak and 

plume average concentrations of so 2 and so4 . On the otherhand, 

the results for a test run where the default value of rs for so4 was 

modified from its default value of 1000 sjm to 100 sjm reveal comparable 

impacts on peak and mean so4 concentrations. No differences occurred 

in so2 values, but the peak and plume average so4 concentrations 

for this model run were between 15-20% lower than base case values. The 

current default rs value limits the maximum Vd for sulfate to 0.1 em s-1, 

which might be too low based on some experimental results and the analysis 

reported by Morris et al. (1988). Thus, a refinement in the formulation 

for rs for so4 appears to be warranted. 

The background ozone concentration (0 3bg) is an important parameter 

90 
TABLE 30 

RESULTS OF SENSITIVITY RUNS FROM VARIATIONS 

IN SELECT KEY TECHNICAL PARAMETERS IN THE MODEL 

MODEL RUN 

BASE CASE 

modified rs (S02) 

modified rs (S04 ) 

03bg = 40 ppb 

03bg = 120 ppb 

stack zs = 150m 

VARIATION IN 

PEAK SO 

(Cb - Ct)/tb (%) 

DAY 1 

1.8 

0 

-0.3 

0.3 

-147.7 

DAY 2 

0.01 

0 

-0.2 

0.1 

-210.3 

VARIATION IN 

PLUME AVERAGE SOz 

(Cb - Ct)/Cb (%) 

DAY 1 DAY 2 

4.5 4.4 

0 0 

-1.5 -1.7 

1.2 1.4 

-37.2 -20.3 

----------------------------------------------------------------------- PEAK SO 

(Cb - Ct)/~b (%) 

BASE CASE 

modified rc(so2) 1.2 2.7 

modified rs(S04) 17.0 18.2 

03bg = 40 ppb 19.0 18.0 

03bg = 120 ppb -16.0 -15.0 

stack zs = 150 m 21.0 30.1 

NOTE: o3bg - background ozone concentration 

r - surface resistance 

z: - height above ground of stack top 

91 

PLUME AVERAGE so4 

(Cb Ct)/Cb (%) 

1.4 

15.8 

19.1 

-16.1 

1.1 

2.3 

18.5 

18.2 

-15.2 

4.4 
in the determination of the transformation rate (k). Clearly, ozone 

generally exbihits a strong diurnal variation and large differences 

in ozone levels occur between air masses. Consequently, model test runs 

were conducted to assess concentration differences to a ±50% variation 

in o3b from its current default value of 80 ppb. In fact, k is larger 

by a f§ctor of two when o3b - 120 ppb compared to 40 ppb with all other 

parameters being equal (Mor~is et al., 1987). The results for these model 

runs in Table 30 reveal little effect on so2 , however, the changes in 

so4 peak and mean concentrations are more important. Rather clean and 

polluted air masses are represented by o3bg being 40 and 120 ppb, 

respectively. Peak and plume average so4 concentrations in the test 

cases appeared to be equally affected, as results with 03bg = 40 ppb 

were 18-19% lower and those with o3b ~ 120 ppb were 15-16% higher 

than base case values. Thus, the suffate concentration levels were fairly 

sensitive to variations in o3b values with this transformation method, 

Therefore, representative ozon~ levels from measurements made within the 

model domain should be input for particular applications. 

The height of a pollutant release has a strong influence on the 

ground-level concentrations; the rationale for higher stacks during the 

past two decades was that peak concentration reductions would be produced 

with higher stack heights (zs). A model run was performed with 

zs = 150 m, which is approxiately one-half the height of the stack used 

in the base case. The final results shown in Table 30 reveal that 

peak so2 concentrations indeed were considerably higher on both days 

compared to base case values, while increases in the plume mean so2 

concentrations were not as dramatic. A notable result with the lower 

stack, however, is that peak sulfate values were 21% and 30% lower than 

base case peak values on Day 1 and 2, respectively. Thus, the change in 

stack heights may also have had an impact on secondary pollutant levels. 

It is recognized that these results represent only a small subset of a 

much larger group of possible model test runs which could explore the 

effects more features and variations in the numerous parameters incorporated 

into the current model. However, these limited set of model runs present 

a clearer picture of the impact on modeled concentrations when an important 

process is excluded or when certain key technical parameters in the dry 

deposition and chemical transformation methods are modified. More evaluation 

and testing efforts of this modeling system are certainly advocated. 

92 
SECTION 6 

SUMMARY AND CONCLUSIONS 

The MESOPUFF II regional Lagrangian model has been evaluated and tested 

with measurements from six full-scale CAPTEX episodes to assess its ability 

to simulate long-range transport and dispersion of an inert, non-depositing 

tracer plume. A neutrally-buoyant tracer gas was released over a 3-hour 

period from ground-level during four cases from Dayton, Ohio and during two 

cases from Sudbury, Ontario under fair weather conditions. 

The results revealed that the model overpredicted both mean and peak 

concentrations. The overpredictions were most pronounced for the Dayton 

releases at the first two sampling arcs. Since differences in horizontal 

plume spread were not evident during the first day of transport, it was 

concluded that the primary cause for the model overpredictions was an underestimation of vertical plume growth for neutral stability, which was the 

stability class most often specified during the afternoon release periods. 

It is suggested that a different dispersion formula for the Gaussian vertical dispersion parameter for neutral conditions (the Dl curve established 

by Pasquill (1974)) be incorporated and tested within the current framework 

of the model. This revision would provide for more rapid vertical plume 

spread with the default Gaussian dispersion distance-dependent scheme under 

neutral conditions, a stability class frequently selected from the widelyused methodology by this model and others. 

The statistical results also showed that large scatter and low correlations occurred between modeled and observed concentrations paired in time 

and space for both mean and peak values. This reflected the inability of 

this model, like other similar models, to accurately replicate the speed 

and/or direction of the tracer plume. Thus, the large concentration differences where observed and modeled plumes did not overlap were primarily 

attributed to trajectory errors. However, the statistical analyses did not 

provide sufficient information for an assessment of the causes for model 

errors in transport. 

Graphical displays and a technique to det~rmine plume centroid positions 

which indicated the size of the spatial plume differences, greatly assisted 

in characterizing model trajectory errors. Spatial displacements of varying 

amounts were evident from graphical maps of modeled and observed plume patterns with time. Plume centroid positions, derived as the concentrationweighted locations from non-zero values at 6-hour intervals, were used in 

quantifying differences in the downwind distance and the separation distance 

between observed and modeled plumes. Specifically, results from MESOPUFF II 

indicated that the observed plume moved faster and/or along a different path 

during the nocturnal period and was generally found further downwind of the 

modeled plume by the second daytime period in these episodes. The plume 

separation distance, the difference in centroid locations between the observed and modeled plumes, ranged from 100-300 km during these cases at downwind distances of 500-1000 km. The most rapid increase in plume separation 

also occurred during the nocturnal periods. 

93 
The CAPTEX tracer emissions consisted of non-buoyant, ground-level 

releases. For this source type, puff heights in MESOPUFF II were always 

less than the mixing height which caused modeled plumes to be continually 

transported by the lower layer wind field. This feature is believed to be 

a shortcoming of the model design, especially during the nocturnal period 

when greater vertical shears in speed and direction often prevail. It was 

concluded from analyses of the plume centroid positions that the modeled 

plumes must have been advected by slower winds derived over the shallow 

mixed layer at night, while observed plumes had been transported along a 

different trajectory by faster winds at higher levels. In the case of an 

elevated source emitting a buoyant plume which rises to even higher levels, 

the model would have switched the plume transport at night to the upper 

layer wind field when the mixing height dropped below the height of the puff 

center. Based on these results, model applications for multi-day simulations 

of ground-level, non-buoyant point emissions are not recommended. The model's 

treatment for this source type could be improved if the height of the puff 

center after release was redefined to be one-half of its vertical dimension 

and this revised puff center height reached a limit when vertical puff growth 

extended up to the mixing height. 

Four other regional-scale models have also been applied on two or all 

of the CAPTEX episodes with results being reported in the literature. These 

models contained greater sophistication in transport (e.g. more vertical 

layers) and different dispersion techniques. Unfortunately, comparable 

statistical measures and plume displacement parameters were not reported 

for three of the four models and an extensive comparison could not be made. 

Nevertheless, the available results for the other models also displayed 

large variabilities when observed and modeled concentrations were compared 

and concentration differences were primarily attributed to spatial discrepancies in plume patterns due to trajectory errors. 

The most extensive results with CAPTEX data were reported by Draxler (1987) 

who tested a Lagrangian puff model which utilized several wind layers and 

permitted puff splitting. Observed-modeled plume separation distances with 

this model appeared to be smaller than those for MESOPUFF II, especially for 

the cases exhibiting the greatest speed and directional shears. However, 

plumes simulated by MESOPUFF II appeared to be displaced to the same side 

with respect to the observed plumes (i.e. either to the right or left) as 

those with the multi-layer model. _Draxler (1987) reported that average 

spatial displacements for the 24-42 hour period after each release varied 

from 90-189 km among the CAPTEX episodes, while individual separation distances with MESOPUFF II were found to be 100-300 km as noted above. It must 

be noted, however, that Draxler's model runs included rawinsonde profile 

data obtained at 6-hour intervals during CAPTEX. Better temporal resolution 

of flow fields was translated into reduced trajectory errors when the more 

frequent upper-air profile data and higher spatial resolution of observed 

data were included in his model simulations. These supplemental profiles 

were not used in the MESOPUFF II model simulations since they are not 

available on a routine basis for model applications. 

Qualitatively, the results from MESOPUFF II appeared to be competitive 

with those of the other models. Therefore, radical changes of MESOPUFF II 

and its processors are probably not warranted that could eliminate its 

advantages of being computationally practical and easy to use for single 

94 
sources. Indeed, the model should be expected to perform better for a 

ground-level point source if revisions identified earlier are instituted. 

The feasibility of puff splitting within the current model's framework 

should also be explored as a step toward better addressing directional 

shear-induced dispersion. 

Any firm judgment of the comparative capabilites of the models for 

general application was not possible based on the reported CAPTEX results. 

If conclusions could have been made, they would necessarily be tempered by 

the rather small number of cases, the specific source characteristics, and 

the narrow set of meteorological scenarios during CAPTEX. Consequently, a 

simultaneous evaluation of MESOPUFF II and a hierarchy of other models using 

an agreed upon set of evaluation measures with a broader data base(s), which 

should include elevated point source data, is certainly needed to provide 

definitive evidence of relative model performance. In the interim, the 

MESOPUFF II model should continue to be considered a useful modeling tool 

for short-term, regional applications. 

Diagnostic tests of optional features in the model provided distinct 

differences in plume transport and dispersion from the default methods. 

The mixed-layer averaged wind field (i.e. default lower level wind field) 

was found to be superior to single level wind fields at the surface or 

850 mb height in simulating the impact time and location of the tracer 

plume at the 300 km arc. Results suggested that it should remain as the 

preferred wind field for representing boundary layer transport when applying 

this model. Model test run results with the uniform vertical mixing option 

indicated that peak concentrations were much closer to observed values than 

those from the default Gaussian dispersion parameter methods. With the 

uniform vertical mixing method, puffs are completely dispersed through the 

entire extent of the boundary layer after release. These test results gave 

more evidence that modeled plumes required greater vertical mixing during 

the afternoon release periods. In lieu of the suggested revision to the 

Gaussian dispersion scheme noted earlier, the selection of this optional 

dispersion method appears to be an attractive alternative since it produces 

the desired vertical dispersion when neutral conditions are prevalent. 

A limited group of model sensitivity runs was also performed in an effort 

to examine the impact on 24-h peak and plume average S02 and sulfate concentrations from variations in certain key parameters and changes in methods 

in the dry deposition and chemical transformation components of the model. 

The model base case and test case runs were exercised with the same meteorological fields from CAPTEX #l and the same emission rates from a large, 

elevated point source. Results showed that sulfate concentrations were more 

sensitive to the selected variation in a parameter or method. In particular, 

sensitivity run results with differences in the surface so4 resistance or 

±50% differences in background ozone concentration produced negligible vari 

ations in so2 peak and mean concentrations; however, the impact on sulfate 

concentrations was from 15-20%. This finding is particularly relevant to 

regional model applications since the higher concentration levels for sulfate 

were found at much greater downwind distances than was so2 . It follows 

that so4 is influenced to a greater extent by transformation and deposition 

-processes. A more extensive evaluation of these modules is advocated with 

suitable experimental data. 

95 
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simulation models; Vol. 3. User's guide to MESOPUFF. EPA/600/7-80-058, 

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Brown, R., M. Leach, G. Raynor, and p_ Michael, 1985: A summary of the 

weather documentation for the 1983 Cross-Appalachian Tracer 

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96 
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Scire, J. S., F. W. Lurmann, A. Bass, and S. R. Hanna, 1984b: User's 

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98 
APPENDIX A 

MODEL TEST RESULTS FOR DIFFERENT PUFF RELEASE/SAMPLING RATES 

A series of MESOPUFF II model runs for the CAPTEX #l case was performed 

with various puff r~lease and sampling rates. The results presented below 

were generated from peak tracer concentration values at the initial tracer 

measurement arc at 300 km where the highest concentrations were found. 

An average peak concentration value (CAVE) was computed from the results of 

each model test runs and the individual peak concentrations were normalized 

by this average value to determine the amount of difference among the test 

runs. Differences over this set of puff release/sampling rates indicated 

relatively little sensitivity to the peak concentrations at this distance 

under the conditions of this experiment. Similar test runs are advocated 

in other applications to determine sensitivity of modeled concentrations 

to these rates. 

TABLE lA 

DIFFERENCES IN PEAK VALUES AT THE INITIAL ARC 

FOR DIFFERENT PUFF RELEASE/SAMPLING RATES 

RUN RELEASE RATE SAMPLING RATE Cmax/CAVEmax CPU TIME 

(puffs/h) ( #/h) (s) 

1 2 2 0.997 12.7 

2 2 4 0.966 22.1 

3 4 2 1. 020 22.4 

4 4 4 0.984 41.0 

5 8 2 1.023 41.8 

6 12 2 1.024 61.6 

7 12 4 0.986 117 0 6 

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