Importance of Using Observations of Mixing Depths in order

Importance of Using Observations of Mixing Depths in order to Avoid LargePrediction Errors by a Transport and Dispersion Model

J. M. WHITE AND J. F. BOWERS

Dugway Proving Ground, Dugway, Utah

S. R. HANNA

Hanna Consultants, Inc., Kennebunkport, Maine

J. K. LUNDQUIST

Lawrence Livermore National Laboratory, Livermore, California

(Manuscript received 10 March 2008, in final form 9 June 2008)

ABSTRACT

The mixing depth of the boundary layer is an input to most atmospheric transport and dispersion (ATD)

models, which obtain mixing depths in one of four ways: 1) observations by radiosondes, sodars, or other

devices; 2) simulations by regional or mesoscale meteorological models; 3) parameterizations based on

boundary layer similarity theory; or 4) climatological averages. This paper describes a situation during a

field experiment when exceptionally low mixing depths persisted in the morning and led to relatively high

observed tracer concentrations. The low mixing depths were caused by synoptic effects associated with a

nearby stationary front and the outflow from a mesoscale thunderstorm complex located 20–50 km away.

For the same time period, the ATD model-parameterized mixing depth was a factor of 5–10 higher, leading

to predicted concentrations that were less than the observations by a factor of 5–10. The synoptic situation

is described and local radiosonde and radar observations of mixing depth are presented, including com-

parisons with other more typical days. Time series of local observations of near-surface sensible heat fluxes

are also plotted to demonstrate the suppression of turbulence by negative sensible heat fluxes during the

period in question.

1. Background and objectives

Nearly all atmospheric transport and dispersion

(ATD) models make use of inputs of the mixing depth,

also known as the mixing height or the planetary

boundary layer height (Arya 1999). The mixing depth

defines the top of the layer near the surface where tur-

bulent mixing is occurring. During the daytime, the

mixed layer typically has an adiabatic or superadiabatic

temperature lapse rate and the mixing depth is often

marked by a capping inversion. During sunny convec-

tive conditions, the turbulence in the mixed layer is

mostly generated by the sensible heat flux. When the

wind is strong, the mixed layer near the surface is nearly

adiabatic at all times of the day and the turbulence is

mostly mechanically generated. There may be a cap-

ping inversion at the top of the windy boundary layer

during clear conditions. During the night, the mixed

layer may be stable near the ground if conditions are

mostly clear. There is usually a shallow mixed layer

very near the surface in stable conditions due to gen-

eration of turbulence by wind shear, although the

mixed layer may be only a few meters deep.

The mixing depth can be observed by a variety of

methods. The most widely used method employs radio-

sonde soundings, which provide vertical profiles of tem-

perature and relative humidity (RH). The mixing depth

can often be identified on these vertical profiles by the

capping inversion and also by a sharp drop in RH.

However, these criteria do not always work because the

temperature and RH profiles sometimes can be am-

biguous. Also, there can be elevated ‘‘residual’’ mixing

Corresponding author address: John M. White, TEDT-DPW-

ME MS#6, 4531 B Street, Dugway, UT 84022-5006.

E-mail: [email protected]

22 J O U R N A L O F A T M O S P H E R I C A N D O C E A N I C T E C H N O L O G Y VOLUME 26

DOI: 10.1175/2008JTECHA1134.1

� 2009 American Meteorological SocietyUnauthenticated | Downloaded 04/01/22 01:06 PM UTC

depths that are holdovers from the previous day or may

have formed some distance upwind and were advected

over the region of interest. Other methods of observing

the mixing depth include remote sensing devices such

as radars (Angevine et al. 1994; Bianco and Wilczak

2002) and lidars (Cohn and Angevine 2000). In this case

the mixing height is indicated by a discontinuity in a

remotely observed variable.

Most of the methods for estimating mixing depth will

have difficulties during stable nights when the mixing

depth may be less than 10 or 20 m and the radiosonde

or remote sounder cannot measure that close to the

ground. In this case, an instrumented tower is useful,

with temperature sensors at multiple heights through

30–40 m.

An alternate source of mixing depth estimates is a

regional or mesoscale meteorological model. Mesoscale

meteorological models such as the fifth-generation

Pennsylvania State University–National Center for At-

mospheric Research Mesoscale Model (MM5) (Liu et

al. 2006) produce outputs of mixing depth that can be

based on the height where the model-simulated turbu-

lent kinetic energy (TKE) first drops below some frac-

tion of its value at the surface or below some arbitrary

lower limit based on experience. Alternatively, the mix-

ing depth can be based on the height where the bulk

Richardson number for the model outputs surpasses a

critical value (as discussed in Angevine and Mitchell

2001).

Many modern dispersion models contain methods to

parameterize the mixing depth in the absence of nearby

direct observations of the mixing height or without the

aid of mesoscale meteorological models. For example,

the American Meteorological Society (AMS)/Environ-

mental Protection Agency (EPA) Regulatory Model

(AERMOD) Meteorological Processor (AERMET)

model (EPA 2004) is a meteorological preprocessor that

parameterizes mixing depth. For convective conditions,

these methods rely on the morning (1200 UTC) radiosonde

profile and an estimate of the sensible heat flux. For neu-

tral and stable conditions, the methods rely on an em-

pirical function that includes the friction velocity u* and

the Monin–Obukhov length L (e.g., Sykes et al. 2007).

The current study focuses on a specific model—the

Hazard Prediction and Assessment Capability (HPAC)

(DTRA 2004), which is a comprehensive modeling sys-

tem that includes the Second-Order Closure Integrated

Puff (SCIPUFF) ATD model (Sykes et al. 2007). The

HPAC application in this paper uses observations from

the Joint Urban 2003 field experiment (JU2003) (Allwine

et al. 2004; Clawson et al. 2005), which was conducted in

the Oklahoma City (OKC) area in July 2003. JU2003

provides an extensive dataset for transport and disper-

sion model evaluation. JU2003 included 10 intensive

observation periods (IOPs) during which the tracer

sulfur hexafluoride (SF6) was released for 30-min pe-

riods. An IOP was conducted on a day that was deemed

favorable by the field managers of the study. This paper

addresses IOPs 3, 4, 5, and 6, which took place during

the daytime on 7, 9, 13, and 16 July 2003, respectively

(these are sometimes referred to in the JU2003 reports

as Julian days 188, 190, 194, and 197). Each of these

IOPs included three 30-min continuous tracer releases,

separated by 2 h. The SF6 from these releases was

sampled by bag samplers at outer arc distances of 1, 2,

and 4 km from the release location. Numerous other

samplers operated at distances less than 1 km. In addi-

tion to the numerous tracer samplers used in JU2003,

extensive meteorological measurements were taken

from diverse observational platforms that were set up

across a broad area, ranging from the downtown area to

rural areas located 10 to 20 km upwind and downwind of

the city.

It was originally thought that meteorological condi-

tions were ‘‘similar’’ during the four daytime IOPs.

However, independent evaluations of the HPAC/

SCIPUFF ATD model by Warner et al. (2008) and

Hanna et al. (2007a) report large underpredictions in

concentration by HPAC/SCIPUFF during IOP 5 (13

July 2003), when tracer releases took place at 0800,

1000, and 1200 LST (1400, 1600, and 1800 UTC). These

large underpredictions did not occur during the other

daytime IOPs (3, 4, and 6). The observed concentra-

tions during IOP 5, which were a factor of 10 or more

larger than the concentrations observed during the

other daytime IOPs, were more typical of concentra-

tions observed during the nighttime IOPs (7, 8, 9, and

10). The current paper describes the results of an in-

vestigation of the reasons for the large underpredic-

tions during IOP 5. It appears that the large observed

concentrations were caused by a relatively low mixing

depth, as observed by on-site remote sounders and as

explained by looking at synoptic and radar maps. The

HPAC/SCIPUFF model, on the other hand, was using

parameterized mixing depths that were much larger

and more typical of climatological values. Even when

using the MM5 outputs of mixing depth, there were still

large underpredictions by HPAC/SCIPUFF, although

not as large as when the parameterized values were

used.

2. Observations and ATD model predictions ofconcentrations during daytime IOPs

Figure 1 shows the observed arc maximum tracer

concentrations C, normalized by source emission rate

JANUARY 2009 W H I T E E T A L . 23

Unauthenticated | Downloaded 04/01/22 01:06 PM UTC

Q, at downwind distances of 1, 2, and 4 km for the

tracer releases during daytime IOPs 3, 4, 5, and 6 (in-

dicated on the histogram by different shaded bars). The

concentration averaging time is 30 min. For each re-

lease time in the figure, there are three groupings of

vertical bars, indicating the normalized concentrations

at the three arc distances. The start times for the 30-min

SF6 releases during IOPs 3 and 4 were 1600, 1800, and

2000 UTC (1000, 1200, and 1400 LST), while the start

times for the SF6 releases during IOPs 5 and 6 were

1400, 1600, and 1800 UTC (0800, 1000, and 1200 LST).

Note that, because of the different IOP start times, Fig.

1 shows arc maximum concentrations for only two IOPs

for the 1400 and 2000 UTC release times.

It is seen in Fig. 1 that the maximum concentrations

measured during the first two SF6 releases of IOP 5

(1400 and 1600 UTC, or 0800 and 1000 LST) were al-

most an order of magnitude higher than those mea-

sured at the same times of day during the first two

releases of IOP 6 and the first release of IOPs 3 and 4.

The maximum concentration measured during the third

release of IOP 5 (1800 UTC or 1200 LST) was compa-

rable to the levels measured during the other IOPs for

the same time period. Later it will be shown that the

observed mixing depth during IOP 5 was much less

than the other IOPs for the releases at 0800 and 1000

LST, but had increased to close to the values for the

other IOPs by 1200 LST.

The HPAC/SCIPUFF ATD model (version 4.04),

with standard options, was used to calculate the 30-min

average arc maximum normalized concentrations, C/Q,

for comparison with the observed concentrations dur-

ing the daytime IOPs. The same HPAC urban disper-

sion model option and meteorological inputs, including

point wind measurements from a special field experi-

ment site about 1 km upwind of the tracer release, were

used in the HPAC predictions for all daytime IOPs. It

should be noted that the model’s parameterized mixing

depths were used in the ATD model runs reported

here.

Figure 2 compares the predicted and observed arc

maximum normalized concentrations for each of the

three tracer releases for IOPs 3, 4, 5, and 6. For the arc

maximum concentrations, the predicted and observed

values at each sampling arc do not necessarily occur at

the same sampling location on the arc. In Fig. 2, the

solid diagonal line represents perfect agreement and

the dashed lines represent factor of 2 differences be-

tween predicted and observed normalized concentra-

tions. The general tendency in the figure is for HPAC

to underpredict the observed normalized concentra-

tions, with most of the values for IOPs 3, 4, and 6 near

the line indicating a factor of 2 underprediction. How-

ever, the HPAC predictions for the first two releases of

IOP 5 are about an order of magnitude lower than the

observations. The correspondence between predicted

and observed concentrations for the third release of

IOP 5 is comparable to that obtained for the other

IOPs.

An investigation was mounted to determine the rea-

FIG. 1. Comparison of arc maximum 30-min average concentrations over the three outer

sampling arcs. Note that LST 5 UTC 2 6 h.



sons for the high observed concentrations and severe

model underpredictions for IOP 5. Possible reasons

could be low wind speeds, low turbulence intensities, or

low mixing depths. Low wind speeds were unlikely to

be the cause, since a previous study by Hanna et al.

(2007b) found that the IOP average wind speed differ-

ence between daytime IOPs was relatively small. Our

primary hypothesis was that the higher observed nor-

malized concentrations were related to relatively low

mixing depths, which were less than mixing depths pa-

rameterized by HPAC/SCIPUFF when run in the de-

fault mode.

3. Observations of mixing depth

Vertical profiles of temperature and humidity from

the Argonne National Laboratory (ANL) and Pacific

Northwest National Laboratory (PNNL) radiosonde

soundings during JU2003 were studied to determine the

observed mixing depths during IOPs 3, 4, 5, and 6. Ad-

ditionally, the observed mixing depths estimated from

the boundary layer turbulence measurements by Dug-

way Proving Ground’s Frequency Modulated/Con-

tinuous Wave (FM/CW) radar (Gallagher et al. 2004)

were studied. The ANL radiosonde site was approxi-

mately 4.3 km north of the tracer release site, the

PNNL radiosonde site was approximately 2.2 km south-

west of the release site, and the FM/CW radar was

approximately 1.5 km north of the release site. The

tracer release sites were within the Central Business

District (CBD) or on its upwind edge. The radiosonde

releases and the radar were generally located in the

suburbs, as opposed to the CBD. The radiosonde

launch times occurred at or near the start of each of the

tracer releases.

The FM/CW radar provides continuous readings of

the boundary layer turbulence structure. Mixing depths

are estimated using the knowledge that the radar return

in a convective boundary layer is large in the superadia-

batic layer near the surface, small in the well-mixed

portion of the boundary layer above the surface layer,

and large again in the elevated inversion layer at the

top of the mixed layer (Gallagher et al. 2004). The ra-

dar can also provide details on the complexity of the

FIG. 2. Comparison of arc maximum observed and HPAC-predicted normalized 30-min

average concentrations for IOPs 3, 4, 5, and 6.



near-instantaneous structure of the daytime boundary

layer.

As an illustration of the use of the radiosonde pro-

files to estimate mixing depth, Fig. 3 contains the ver-

tical profiles of temperature and RH observed by the

PNNL radiosonde during IOP 5. The height of the cap-

ping temperature inversion and the height where RH

sharply decreases clearly indicate the mixing height for

FIG. 3. Vertical profiles of temperature and humidity from the PNNL radiosonde datasets

for the continuous release trials of IOP 5.



the 1400 and 1600 UTC profiles (about 100 and 210 m,

respectively). The profiles are less sharp at 1800 UTC,

but still suggest a mixing depth at about 400–450 m.

Tables 1 and 2 list the mixing depths observed by the

two on-site radiosondes and the FM/CW radar during

IOPs 5 and 6, respectively. The FM/CW mixing depths

were estimated at the start times of the tracer releases

using the procedures described by Gallagher et al.

(2004). As shown by the fourth column in each table,

the average observed mixing depth ranged from ap-

proximately 100 to 490 m for IOP 5 and from approxi-

mately 430 to 1200 m for IOP 6. Thus, the observed

mean mixing depths for IOP 5 were 3–4 times smaller

than the mean mixing depths for IOP 6.

Figure 4 contains continuous time series of the esti-

mated FM/CW radar mixing depths for the four day-

time IOPs. The estimation method, based on the paper

by Gallagher et al. (2004), is described three paragraphs

above. The black, green, red, and blue lines represent

IOPs 3, 4, 5, and 6, respectively. The red horizontal

lines at the top of the figure identify the tracer gas

release periods. It is obvious in the figure that the mix-

ing depths for IOP 5 are considerably lower than the

depths for the other daytime IOPs.

4. Turbulence observations during the daytimeIOPs

Data from a meteorological tower on the northern

edge of Oklahoma City were inspected to determine

whether anomalous mixing conditions occurred during

IOP 5. Mean and fluctuating velocity and virtual tem-

perature measurements were available from the

Lawrence Livermore National Laboratory (LLNL)

crane pseudotower, which was located approximately

750 m NNW of the downtown area (Lundquist et al.

2004). This pseudotower consisted of a cable ladder

under tension, anchored by a construction crane. Eight

R. M. Young Model 81000 ultrasonic anemometers

were mounted along this pseudotower, from approxi-

mately 8 to 84 m above the surface. The LLNL crane

pseudotower microscale dataset provides high-resolu-

tion wind speed observations necessary for the calcula-

tion of variances, TKE, and the local dissipation of

TKE. The crane data have been tilt corrected, using the

correction algorithm suggested by Wilczak et al. (2001),

lending credibility to the calculation of vertical fluxes in

particular. More details on the construction of this

pseudotower are presented in Gouveia et al. (2007).

The measurements of sensible heat flux from the

LLNL crane pseudotower shown in Fig. 5 reveal a clear

distinction between the delayed development of the

convective boundary layer during IOP 5 and the more

typical growth observed during IOPs 3, 4, and 6. Note

that days 188, 190, 194, and 197 in the x-axis labels in

Fig. 5 correspond to IOPs 3, 4, 5, and 6, respectively.

The heat flux time series in IOPs 3, 4, and 6 show

typical daytime behavior, following an approximate

sine wave, starting to increase at 0700 or 0800 LST and

reaching a maximum at about 1300 or 1400 LST. The

time series for IOP 5 (lower left) remain negative or

near zero, with plus and minus variations, until after

1100 LST. Note that tracer releases occurred at 0800,

1000, and 1200 LST. The negative heat fluxes observed

during IOP 5 are associated with the influences of a

distant thunderstorm complex, and suppress mixing ac-

tivity and boundary layer growth in the JU2003 do-

main.

5. Synoptic maps and radar maps during IOP 5

The synoptic situation was studied for IOP 5 (13 July

2003) to find an explanation for the anomalously low

mixing depths. NWS observations at the nearby Wiley

Post Airfield indicated mostly cloudy to cloudy condi-

tions over the area from 0700 to 1400 UTC (0100–0800

LST) 13 July 2003, but no precipitation. However, some

of the surface observations from the Norman, Oklaho-

ma, weather station, located to the south of OKC, re-

ported lightning to the distant NW direction during this

time period. The surface weather map analysis for 0000

UTC 13 July 2003 (or 1800 LST on the previous day)

TABLE 1. Mixing depths observed for IOP 5 by ANL and PNNL

radiosonde soundings and FM/CW radar turbulence profiles.

Note that LST 5 UTC 2 6 h.

Time

(UTC)

ANL

radiosonde

(m)

PNNL

radiosonde

(m)

FM/CW

radar

(m)

Average

(m)

1400 100 100 100 100

1600 180 210 170 190

1800 530 430 510 490

TABLE 2. Mixing depths observed for IOP 6 by ANL and PNNL

radiosonde soundings and FM/CW radar turbulence profiles. Note

that LST 5 UTC 2 6 h.

Time

(UTC)

ANL

radiosonde

(m)

PNNL

radiosonde

(m)

FM/CW

radar

(m)

Average

(m)

1400 No data 450 420 430

1600 870 740 650 750

1800 1210 1290 1100 1200



showed a propagating wave moving along a stationary

front, with the frontal boundary over OKC and areas of

rain showers in central Oklahoma. The surface map for

1200 UTC (0600 LST) 13 July, which is given in Fig. 6,

shows that the wave moved into northwest Arkansas

and the area of rain over central Oklahoma increased.

The radar map analysis at 1045 UTC (0445 LST) 13

July 2003 showed a general area of rain generated by

convective activity from southwest to north of OKC.

This is consistent with the observation of lightning re-

ported by the Norman weather station. Figure 7 [the

radar map at 1345 UTC (0745 LST)] shows that there is

a moderate area of convection NW of Oklahoma City,

and a larger line of cells centered along the Oklahoma–

Arkansas border. This mesoscale convective complex is

active at the time (0800 LST) of the first tracer release

during IOP 5. The timing of this development corre-

sponds to the location of the propagating wave along

the frontal boundary at 1200 UTC 13 July (Fig. 6).

We suggest that the combination of the outflow from

the nearby convective activity and the propagating

wave along the frontal boundary caused the surface

heat flux to be nearly zero and sometimes negative on

the morning of IOP 5. These factors inhibited the

growth of the mixing depth. The low mixing depths

(100–200 m) during the first two tracer releases are

more representative of nighttime situations.

6. Mixing depths estimated by MM5

As part of JU2003, high-resolution (4-km horizontal

grid spacing) runs were made with MM5 (Liu et al.

2006). The HPAC/SCIPUFF ATD model is able to di-

rectly use mixing depth (and other) outputs from MM5.

The Hanna et al. (2007a) HPAC/SCIPUFF (version

4.04) model evaluation exercise using the JU2003 field

data considered the MM5 mixing depth input option as

well as the observed and the HPAC/SCIPUFF param-

eterized mixing depth inputs. The MM5 mixing depths,

which partially account for the stationary front and the

rain showers, are about halfway in between the param-

eterized and the observed mixing depths and thus

partly correct for the large HPAC/SCIPUFF underpre-

dictions. However, since it is difficult for MM5 to simu-

late the timing and the spatial patterns of the outflow

from the mesoscale convective complexes, the ex-

tremely low mixing depths during IOP 5 were not cap-

tured by MM5.

7. HPAC/SCIPUFF model-parameterized mixingdepths compared with observations, and revisedHPAC/SCIPUFF runs with observed mixingdepths

The mixing depths parameterized by the HPAC/

SCIPUFF (version 4.04) model, when run in its default

mode, have been compared with the observations by

the PNNL radiosonde. The comparisons are shown in

Fig. 8 for each release time of IOPs 3, 4, 5, and 6. The

HPAC/SCIPUFF parameterized mixing depths for IOP

5 are seen to be much larger than the observed mixing

depths. For example, for the first IOP 5 tracer release

(at 0800 LST), the HPAC/SCIPUFF parameterized

FIG. 4. FM/CW radar boundary layer height estimates for the daytime IOPs.



FIG. 5. Observed time variation of heat flux (m K s21) from seven levels (lowest level not plotted) at

the LLNL crane pseudotower for IOPs 3, 4, 5, and 6 (days 188, 190, 194, and 197, respectively) where

fluctuating quantities are calculated from 30-min averages centered at the data point. The heaviest solid

line denotes data from the top level, 83 m. The light dotted line denotes data from the lowest level, 15

m. The remaining solid lines represent data from 22, 28, 43, 56, and 70 m. The horizontal line indicates

zero heat flux. LST 5 UTC 2 6 h. Tracer releases were at 1000, 1200, and 1400 LST during IOPs 3 and

4 and at 0800, 1000, and 1200 during IOPs 5 and 6.

FIG. 6. Surface weather map analysis for 1200 UTC 13 Jul 2003. The star shows the location of OKC.



mixing depth is about 650 m while the observed mixing

depth is about 100 m. In contrast to the mixing depth

discrepancies found for IOP 5, all of the mixing depths

parameterized by HPAC/SCIPUFF for the other day-

time IOPs are within a factor of 2 of the observed val-

ues in Fig. 8.

The HPAC/SCIPUFF model calculations were re-

peated for IOPs 3 through 6 using the same meteoro-

logical data and urban modeling options as in the pre-

vious runs, but with the mixing depths based on the

radiosonde observations. The use of the observed mix-

ing depths increases the simulated IOP 5 concentra-

tions so that they are within the range of the simulated

concentrations for IOPs 3, 4, and 6.

8. Conclusions

This study shows that the high normalized tracer con-

centrations observed during the morning releases of

JU2003 IOP 5 can be attributed to unusually low mix-

ing depths, which are evident in the radiosonde and

FIG. 7. Radar map analysis at 1345 UTC 13 Jul 2003. The blue star shows the location of OKC.

FIG. 8. Comparison of observed boundary layer heights with

HPAC default boundary layer heights for IOPs 3, 4, 5, and 6.



FM/CW radar soundings and, by inference, from the

measurements of sensible heat flux at a meteorological

tower. The low observed mixing depths were likely

caused by the presence of a stationary front combined

with the effects of outflows from nearby thunderstorm

complexes. The standard mixing depth parameteriza-

tion in the HPAC/SCIPUFF ATD model, which is simi-

lar to the parameterizations in other state-of-the-art

ATD models, led to large underpredictions of the ob-

served concentrations during IOP 5. Thus, standard op-

erational use of an ATD model may not account for

atypical weather situations and may lead to large er-

rors. Underpredictions are especially undesirable be-

cause the public may not be adequately protected from

serious air quality impacts. Clearly, it is better to make

use of local meteorological soundings or analyses that

capture those conditions in the place of the model de-

fault parameters.

This detailed investigation of mixing depths has been

possible only because of the intensive research-grade

observations taken during JU2003. The soundings were

made often and produced excellent vertical resolution.

Routine soundings are seldom available at this time and

space resolution. Thus, our recommendation that local

soundings be available to better observe mixing depths

would require large expenditures. Nevertheless, our

study has shown that without realistic mixing depths,

the ATD model may have large errors, including the

potentially harmful underpredictions described here.

Perhaps a compromise would be to install enhanced

vertical sounders in critical locations such as near large

cities or where pollution problems are severe.

Finally, atmospheric dispersion field studies almost

always are conducted under fair-weather conditions,

because of safety concerns and because of the desire for

well-behaved dispersion patterns. But, as illustrated by

the tracer concentration measurements made during

JU2003 IOP 5, critical meteorological regimes resulting

in the highest concentrations can be missed when field

studies are restricted to fair weather. We recommend

that more field experiments be planned and carried out

during non–fair-weather conditions.

Acknowledgments. The research by J. White, J. Bow-

ers, and S. Hanna was sponsored by the Defense Threat

Reduction Agency, with Rick Fry as project manager.

S. Hanna’s research was cosponsored by the National

Science Foundation and by the Department of Home-

land Security. J. Lundquist’s research was supported by

the LLNL Laboratory-Directed Research and Devel-

opment program, and was performed under the aus-

pices of the U.S. Department of Energy by Lawrence

Livermore National Laboratory under Contract DE-

AC52-07NA27344.

REFERENCES

Allwine, K. J., M. Leach, L. Stockham, J. Shinn, R. Hosker, J.

Bowers, and J. Pace, 2004: Overview of Joint Urban 2003—

An atmospheric dispersion study in Oklahoma City. Pre-

prints, Symp. on Planning, Nowcasting, and Forecasting in the

Urban Zone, Seattle, WA, Amer. Meteor. Soc., J7.1 [Avail-

able online at http://ams.confex.com/ams/pdfpapers/74349.

pdf.]

Angevine, W. M., and K. Mitchell, 2001: Evaluation of the NCEP

mesoscale Eta Model convective boundary layer for air qual-

ity applications. Mon. Wea. Rev., 129, 2761–2775.

——, A. B. White, and S. K. Avery, 1994: Boundary-layer depth

and entrainment zone characterization with a boundary-layer

profiler. Bound.-Layer Meteor., 68, 375–385.

Arya, S. P., 1999: Air Pollution Meteorology and Dispersion. Ox-

ford University Press, 310 pp.

Bianco, L., and J. M. Wilczak, 2002: Convective boundary layer

depth: Improved measurement by Doppler radar wind pro-

filer using fuzzy logic methods. J. Atmos. Oceanic Technol.,

19, 1745–1758.

Clawson, K., and Coauthors, 2005: Joint Urban 2003 (JU2003) SF6

atmospheric tracer field tests. NOAA Tech. Memo. OAR

ARL-254, Air Resources Laboratory, Silver Spring, MD,

162 pp.

Cohn, S. A., and W. M. Angevine, 2000: Boundary layer height

and entrainment zone thickness measured by lidars and wind

profiling radars. J. Appl. Meteor., 39, 1233–1247.

DTRA, 2004: HPAC Version 4.04.04. DTRA, CD-ROM. [Avail-

able from 8725 John J. Kingman Road, MSC 6201, Ft. Bel-

voir, VA 22060-6201.]

EPA, 2004: User’s guide for the AERMOD Meteorological Pre-

processor (AERMET). Environmental Protection Agency

EPA-454/B-03-002, 252 pp. [Available online at http://www.epa.

gov/scram001/metobsdata_procaccprogs.htm.]

Gallagher, F. W., III, J. F. Bowers, E. J. Laufenberg, E. P. Ar-

genta, D. P. Storwold, and S. A. McLaughlin, 2004: Analysis

of the evolution of an urban boundary layer as detected by a

frequency modulated-continuous wave radar. Preprints, Fifth

Conf. on Urban Environment, Vancouver, BC, Canada,

Amer. Meteor. Soc., 15.7. [Available online at http://ams.

confex.com/ams/pdfpapers/79938.pdf.]

Gouveia, F. J., M. J. Leach, J. H. Shinn, and W. E. Ralph, 2007:

Use of a large crane for wind and tracer profiles in an urban

setting. J. Atmos. Oceanic Technol., 24, 1750–1756.

Hanna, S. R., J. C. Chang, J. M. White, and J. F. Bowers, 2007a:

Evaluation of the HPAC dispersion model with the Joint

Urban 2003 (JU2003) tracer observations. Preprints, Seventh

Symp. on the Urban Environment, San Diego, CA, Amer.

Meteor. Soc., 10.1. [Available online at http://ams.confex.

com/ams/pdfpapers/126616.pdf.]

——, J. White, and Y. Zhou, 2007b: Observed winds, turbulence,

and dispersion in built-up downtown areas of Oklahoma City

and Manhattan. Bound.-Layer Meteor., 125, 441–468.

Liu, Y., F. Chen, T. Warner, and J. Basara, 2006: Verification of

a mesoscale data assimilation and forecasting system for the

Oklahoma City area during the Joint Urban 2003 field

project. J. Appl. Meteor. Climatol., 45, 912–929.



Lundquist, J. K., J. H. Shinn, and F. Gouveia, 2004: Observations

of turbulent kinetic energy dissipation rate in the urban en-

vironment. Preprints. Symp. on Planning, Nowcasting, and

Forecasting in the Urban Zone, Seattle, WA, Amer. Meteor.

Soc., J7.6. [Available online at http://ams.confex.com/ams/

pdfpapers/71468.pdf.]

Sykes, R. I., S. Parker, D. Henn, and B. Chowdhury, 2007:

SCIPUFF version 2.3. Tech. Doc., 336 pp. [Available at L-3

Titan Corporation, P.O. Box 2229, Princeton, NJ 08543-2229.]

Warner, S., N. Platt, J. Urban, and J. Heagy, 2008: Comparisons of

transport and dispersion model predictions of the Joint Ur-

ban 2003 field experiment. J. Appl. Meteor. Climatol., 47,1910–1928.

Wilczak, J. M., S. P. Oncley, and S. A. Stage, 2001: Sonic an-

emometer tilt correction algorithms. Bound.-Layer Meteor.,

99, 127–150.



Documents

Importance of Using Observations of Mixing Depths in order