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ENVIRONMENTAL RESEARCH 4 TECHNOLOGY INC
DISCLAIMER
Publication of this report does not signify that the contents
necessarily reflect the views and policies of the U.S. Environmental
Protection Agency, nor does mention of trade names or commercial
products constitute endorsement or recommendation for use.
111
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TABLE OF CONTENTS
ENVIRONMENTAL RESEARCH & TECHNOLOGY INC
LIST OF ILLUSTRATIONS
LIST OF TABLES
1. INTRODUCTION
1.1 Background
1.2 Integrated Mesoscale Modeling System
1.3 Organization of the Report
2. MODEL DESCRIPTION
2.1 Wind Field Algorithm
2.2 Mixing Depth Algorithm
2.2.1 Rationale
2.2.2 MESOPAC Mixing Depth Determination
2.3 The Stability Algorithm
3. USER'S MANUAL
3.1 Model Input
3.1.1 Description
3.1.2 Parameter Input
3.1.3 Radiosonde Input
3.2 Missing Data
3.3 Model Output
3.4 MESOPAC Test Case
REFERENCES
APPENDIX A INPUT PARAMETERS
APPENDIX B INPUT RADIOSONDE DATA
APPENDIX C LINE PRINTER OUTPUT
ABSTRACT
Page
vii
vii
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1-2
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2-1
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2-8
2-10
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3-1
3-1
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ENVIRONMENTAL RESEARCH & TECHNOLOGY INC
LIST OF ILLUSTRATIONS
Figure Page
1-1 Integrated Modeling System 1-3
2-1 Linear Interpolation of a Time-Dependent
Quantity 2-2
2-2 Scan Radius Determination 2-5
2-3 Interpolation of Station Winds (u,v) to Grid
Points 2-6
2-4 Estimation of the Maximum Daytime Convective
Mixing Depth 2-9
2-5 Mechanically Produced Mixing Depths 2-11
2-6 Convectively Produced Mixing Depths 2-12
2-7 Final Mixing Depth Field 2-13
2-8 The PGT Stability Field 2-16
3-1 Sample Plots of Wind Vector (Top), Mixing
Depth (Lower Left), and Stability (Lower
Right) Fields 3-7
LIST OF TABLES
Table Page
2-1 Time Interpolation of Station Wind
Vectors 2-3
2-2 Key to PGT Stability Classes as Generated by
MESOPAC 2-15
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ENVIRONMENTAL RESEARCH S TECHNOLOGY INC
1. INTRODUCTION
1.1 Background
In response to a growing national commitment to the use of
indigenous coal reserves to meet energy generation demands, several
regions of the country will see greatly expanded use of coal and oil
shale resources for steam electric power plants and other coal-based
energy resource development. But, as mandated by federal National
Ambient Air Quality Standards, and by the PSD major source review pro-
cedures, additional coal-based energy resource development (ERD) will
only be pei-mitted where consistent with the maintenance of human health,
welfare, and environmental quality. Accordingly, the siting and
generation capacity of such ERT facilities will be constrained by their
potential impacts on regional ambient air quality.
Various plans have been proposed for regional development of
multiple major new facilities and suitable air quality simulation tools
are needed to assess the impacts of different energy development
scenarios on regional-scale air quality. To meet this need in the
public interest, the National Oceanic and Atmospheric Administration
(NOAA) has sponsored a study by Environmental Research § Technology,
Inc. (ERT) to develop, compare, evaluate, and exercise a number of
alternative approaches to regional-scale ambient air quality modeling.
A major objective of this study is to provide a suite of air quality
simulation models that are both technically sound and computationally
practical for assessing regional-scale impacts of energy development
scenarios.
As described in the companion report, Volume 1 (Bass et al. 1979)
three long-range transport-diffusion models - MESOPUFF, MESOPLUME,
MESOGRID - have been developed, implemented and compared for the simu-
lation of multiple point-source plume dispersion on the mesoscale [e.g.,
dispersion at ranges of 100 to 1,000 kilometers (km)]. These models are
optimized for regional-scale impacts; they have been designed to treat a
broad range of meteorological situations (both worst-case and average
dispersion conditions) over periods of several days to several weeks;
they are easy to use for a variety of decision-making and regulatory
applications; and are also intended as flexible testbeds for further
research, development and simulation tasks.
The MESOPUFF, MESOPLUME and MESOGRID models - like many regional-
scale air quality transport-diffusion models - are driven by spatially-
gridded time sequences of meteorological fields. MESOPAC - a flexible,
fully-independent mesoscale meteorological preprocessor program - is
designed to provide the input meteorological data to these and similar
regional-scale air quality simulation models. Radiosonde data routinely
available from National Weather Service (NWS) radiosonde ("upper air")
and surface stations are used to produce spatially-interpolated, time-
sequenced mesoscale meteorological data fields, including (a) horizontal
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(u,v) wind components; (b) mixing depth; and (c) Pasquill-Gifford-Turner
(PGT) stability class. MESOPAC is highly user-oriented, with optimal
features that make it an attractive tool for a range of practical
problems.
This report, the sixth in a series entitled "Development of
Mesoscale Air Qulity Simulation Models", describes MESOPAC in technical
detail; illustrates its application and provides a User's Guide to the
program. However, to obtain a fuller understanding of MESOPAC's use
in driving regional-scale air quality transport-diffusion models, the
user may wish to refer to the following related reports:
the companion report (Volume 1) describing the multiday
meteorological episodes and extensive series of comparison
and model sensitivity analyses performed with the MESOPUFF,
MESOPLUME and MESOGRID models (Bass et al. 1979);
the companion User's Guides (Volumes 2-4) to the MESOPLUME,
MESOPUFF and MESOGRID models, respectively (Benkley and Bass
1979a; Benkley and Bass 1979b; Morris et al. 1979); and
the companion User's Guide (Volume 5) to the special post-
processing and analysis system MESOFILE (Scire et al. 1979).
1.2 Integrated Mesoscale Modeling System
MESOPAC has been incorporated as an independent model element
within an efficient, easy to use integrated mesoscale modeling system.
This integrated system depicted in Figure 1-1, comprises components
for meteorological preprocessing, mesoscale transport-diffusion, and
post-processing. Standardizing model input/output functions in this
system permits easy combination of results from two or more model runs,
or direct and cost-effective comparison of simulations performed with
two or more different models for identical input meteorology (see, for
example, Bass et al. 1979). As shown, MESOPAC drives identically any
of the three mesoscale transport-diffusion models. In turn, each of
these models identically communicates its results to the MESOFILE
postprocessing system - responsible for file management, display, and
statistical analysis of all model output fields.
1.3 Organization of the Report
Section 2 of this report contains a detailed technical description
of MESOPAC; specific user instructions and a test case for MESOPAC is
presented in Section 3.
A Fortran microfiche listing of the MESOPAC model is appended.
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MESOSCALE
METEOROLOGY
MESOPAC
MESOSCALE
TRANSPORT-
DIFFUSION
MODELS
MESOPLUME
MESOPUFF
MESOGRID
ANALYSIS
MESOFILE
Figure 1-1 Integrated MESOSCALE Modeling System
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2. MODEL DESCRIPTION
This section presents the essential algorithms of MESOPAC wind
field, mixing depth, and stability determination. Section 2.1 discusses
how the wind field is produced by an inverse-squared weighing technique
and a divergence-minimization algorithm. At each point, the mixing
depth field is computed as the maximum value of convective and mechani-
cal mixing depth production methods, as detailed in Section 2.2.
Section 2.3 describes how the consideration of wind speed and strength
of convection is used to compute a Pasquill-Gifford-Turner (PGT)
stability at each grid point.
2.1 Wind Field Algorithm
At each time step, the MESOPAC model produces a gridded field of
rectangular (u,v) wind components from National Weather Service (NWS)
radiosonde wind data. This gridded field can be produced at whatever
pressure level or height above sea level the user feels is most appli-
cable to his specific dispersion problem. If terrain heights vary
appreciably over the grid, the user may even wish to choose individual
station measurement heights so that a terrain-following windfield is
simulated. It is suggested that if mandatory pressure levels are only
considered, fields constructed from the 850-millibar (mb) surface,
without any speed or direction scaling, may be more relevant to the
dispersion of a contaminant uniformly mixed through the boundary layer
than surface or 700-mb winds. If the terrain is high, however, the
700-mb surface must be chosen in lieu of the 850-mb surface. The wind
components at each radiosonde station at radiosonde observation times
are interpolated to intermediate hours. Figure 2-1 illustrates the
time-dependent behavior of a hypothetical quantity, F, given values of
FQ at 12Z and FI at OOZ. In this example, the time-dependent weighing
between radiosonde times is linear, although MESOPAC optionally allows
for square-like; sinusoidal (0.5*[1 + cos 0], - TT <_ 0 <_ 0) ; or user-
specified weighting factors as well. In Table 2-1, station wind data at
radiosonde stations A and B at 12Z and OOZ are linearly interpolated to
the intermediate hour, 18Z. (Note that the choice of units for velocity
is arbitrary in this example.)
Once u,v station wind components are produced at the desired time
step, MESOPAC computes gridded u,v fields using a wind field analysis
technique that is essentially the same (except for a modification to the
boundary conditions) as the analysis technique of Clark and Eskridge
(1977). Only a brief description of the Clark and Eskridge algorithm is
given here; for a more detailed treatment, the reader is referred to the
original paper.
At each grid point, an initial windfield is generated at each time
step by inverse-square radius weighting (separately in both wind com-
ponents) , for all stations within one scan radius of the grid point.
The scan radius is computed internally as the largest distance between
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F(21Z)
F(18Z)
F(15Z)
12Z
15Z
18Z
OOZ
Time of Day
Figure 2-1 Linear Interpolation of a Time-Dependent Quantity
01
o
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TABLE 2-1
TIME INTERPOLATION OF STATION WIND VECTORS
Station
A
B
Measured
12Z
u
10
2
V
0
-3
Measured
OOZ
u
4
4
V
6
-7
Interpolated
18Z
u
7
3
V
3
-5
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ENVIRONMENTAL RESEARCH & TECHNOLOGY INC
any grid point and the radiosonde station nearest that grid point, plus
an additional 0.5DX, where DX is the grid spacing. The user may specify
a larger scan radius, thereby forcing the model to compute a smoother
but possibly less realistic initial wind field. Choosing a scan radius
much smaller than the model-computed scan radius would result in there
not being at least one radiosonde station within one scan radius of
every grid point.
A simplified example of the scan radius determination (for only two
radiosonde stations) is illustrated in Figure 2-2. Here, Station A lies
at x = 1.5, y = 1.5 on the 4x4 grid. (Note that the lower left hand
corner point has coordinates x = 0.0, y = 0.0.) Station B lies at
x = 3.0, y = 0.0. The scan radius r (the distance from Station A to
each grid point at each of the four corners of the grid, + 0.5 DX), is
then
r = l/x2 + y2 + 0.5 DX = 2.62 DX (2-1)
Only the grid points in the shaded area fall within one scan radius of
both radiosonde stations. For the text example, the initial windfield
is illustrated in Figure 2-3. Note that since Station B falls directly
on a grid point, the weighting technique is overridden, and the actual
wind components of Station B are used at that grid point.
The initial wind field may have significant divergence. Because
some numerical mesoscale diffusion models (e.g., MESOGRID) require
essentially divergence-free windfields, a program option can be exer-
cised to minimize the divergence of the wind field to within a certain
tolerance. [The tolerance is defined as the maximum allowable diver-
gence at any grid point. This tolerance can be specified by the user;
otherwise, a tolerance of 10 5 (s 1), a typical value for mesoscale-
scale divergence, is used.]
The divergence at each grid point is minimized by adjusting wind
components at adjacent grid points. Successive outward iterations
gradually force the divergent wind field components beyond the boun-
daries of the grid. A number of iterations are required to minimize
wind field divergence over the entire grid, because minimizing the
divergence at any point in the grid causes the adjustment of wind
components and creation of divfrgence at adjacent points back towards
the center of the grid.
The Clark and Eskridge algorithm uses a zero-gradient boundary
condition. MESOPAC conserves mass over the entire grid at each itera-
tion by adjusting u-components on the east and west boundaries and
v-components on the north and south boundaries so that the net mass flux
across the boundaries of the grid is zero.
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Figure 2-2 Scan Radius Determination
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7,3
7,3
7,3
7,3
7,3
7,3
7,3
6.6, 2.3
*A
6.6,2.3 6.2,1.4
S.5,-0.1
4.1 ,-2.7
7,3
5.5 ,-0.1 4.1 ,-2.7
3,-5
o
00
Figure 2-3 Interpolation of Station Winds (u,v) to Grid Points
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An additional program feature available during the relaxation
process enables the user to select a variable maximum amount (0% to
100%) by which gridded wind components in the immediate vicinity of
radiosonde stations are permitted to vary (see Clark and Eskridge 1977) .
A 0% allowance is equivalent to holding the wind components fixed at the
grid point nearest a radiosonde station; at the other extreme, a 100%
allowance means that no special emphasis is placed on these grid points
nearest station locations.
2.2 Mixing Depth Algorithm
2.2.1 Rationale
If desired, MESOPAC computes gridded fields of mixing depth at each
model time step. The mixing depth algorithm is derived from simplifying
and generalizing, for regional scales, the site-specific algorithm of
Benkley and Schulman (1979). For each mixing depth grid, the mixing
depth at each point is computed as the larger of two independent values:
a mechanical value and a convective value, respectively. Atmospheric
boundary layers are nearly always turbulent, and the growth or main-
tenance of this turbulent mixed layer stems from the mechanical (wind
shear) production of turbulence and the convective (buoyant) production
of turbulence. Mechanical production and convective production often
occur simultaneously, but, in many instances, a first approximation may
indicate one mechanism to be appreciably stronger than the other. For
example, when the earth's surface cools at night, only mechanical tur-
bulence can form or maintain a turbulent mixed layer (convection is
probably nonexistent). Therefore, the mixing depth can be computed
through mechanical considerations alone. Conversely, strong daytime
heating frequently results in convective production of turbulence that
greatly exceeds mechanical production. The resultant deep mixed layer
can therefore be described in terms of convective production alone. On
cloudy or windy days, however, mechanical production and convective
production may be of the same order. It is therefore necessary during
daytime hours to choose the mixing depth as the maximum of the mechan-
ical and convective values, because it is not always evident whether one
of the production methods will be dominant.
The mechanically produced mixing depth, Hm, computed at OOZ and 12Z
each day, is related through a scaling argument to the friction (shear)
velocity u^. and the Coriolis parameter f.
Hm = cujf (2-2)
This parameterization of the mechanically produced mixing depth is
consistent with the work of many researchers, including Clarke (1970)
and Deardorff (1972). Yu (1978) concluded that such a parameterization
is as good as or better than stability-dependent or time-dependent
parameterization. Values indicated for the constant, c, range from
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about 0.05 (Delage 1974) to 0.3 (Deardorff 1972). Based on theoretical
and empirical considerations, Plate (1971) derived c = 0.185. The data
of Benkley and Schulman (1979) indicated a value of about 0.15. Assum-
ing that c = 0.15 and that u* is approximately 3.5% of the free-stream
velocity, u^ (Blackadar 1962), the mixing depth equation can be expressed
o
as:
H = 53 x 10"4 u /f (2-3)
m g
The convectively produced mixing depth Hc is assumed to be zero at
12Z daily, approximately at the time of sunrise, and the time of minimum
surface temperature for longitudes typical of the contiguous United
States. Consequently, the convective production of turbulence and the
resultant growth of the daytime convective mixed layer has not yet
started. From 12Z to OOZ, assuming that the surface temperature
increases, convective production of turbulence increases the mixing
depth. A maximum mixing depth is reached at approximately the time of
maximum surface temperature. On an adiabatic chart, H is obtained as
the height of the intersection of an adiabat drawn upwards from the OOZ
surface temperature TQQ, with the morning temperature sounding, as
illustrated in Figure 2-4. The area between the adiabat and the morning
sounding is proportional to the convective production of turbulence,
integrated over the daytime hours. In rare cases, an adiabat drawn from
TOO may not intersect the morning sounding below the highest mandatory
level the model includes (500 mb). Hc is then assigned as the height of
the 500-mb surface above ground.
Because OOZ generally follows the time of maximum surface tempera-
ture in the continental United States, this method may somewhat under-
estimate the maximum afternoon mixing depth, especially in eastern and
central time zones. So, if available, the user may substitute the
afternoon maximum surface temperature for the OOZ radiosonde station
temperature.
2.2.2 MESOPAC Mixing Depth Determination
At each time step in the model, a field of mechanically derived
mixing depths is produced. If the divergence-free wind field option has
not been exercised, then the mechanical mixing depth at each grid point
is computed from the wind velocity derived from the u and v wind compo-
nents that were directly interpolated to that grid ;oint. If the wind
fields are divergence-free, then the mechanical depths are based on the
speeds derived from wind components at respective grid points after the
divergence of the entire field has been minimized. Thus, the mechanical
mixing depth field is consistent with the velocity-dependent production
of mechanical turbulence at each grid point, as specified by the wind
field model.
As an example of the computation of the mechanical mixing depth
field, the wind components at 18Z from Figure 2-3 are used. At each
grid point, the mechanically produced mixing depth is Hm = 53 ue, where
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ENVIRONMENTAL RESEARCH & TECHNOLOGY INC
0>
I
Morning
Temperature
Sounding
Mixed
Layer
12
'00
Potential Temperature
K>
8
o
OJ
Figure 2-4 Estimation of the Maximum Daytime Convective Mixing Depth
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u = /u^ + vz. If u = 7 and v = 3, then H = 404 m. The entire gridded
field is reproduced in Figure 2-5. Note that the mixing depths at four
points on the grid are lower than those of the two station mixing depth
values. This is because the weighting of individual wind velocity
components to grid points from two or more stations does not necessarily
yield the grid point wind speeds that would be derived by direct weight-
ing of station wind speeds.
For the hours 01Z to 12Z inclusive, convection is negligible, and
the mechanical method alone adequately describes the mixing depth at all
grid points. At other hours, 13Z to OOZ inclusive, the mixing depth at
each grid point is taken as the maximum of the mechanical and convective
values. The mechanical field is computed as before. The convective
depth field is produced at each time step by first time-weighting the
convective mixing depth at each station to the desired time and then
interpolating these weighted depths at each station to all grid points.
The time-weighted mixing depth at each station is computed by the
weighting technique described in Figure 2-1. In this example, the
mixing depth HC = F0 = 0 at 12Z. As daytime heating progresses, the
mixing depth increases linearly with time, reaching a maximum value of
Hc = 7i at OOZ.* If the maximum convective mixing depths at Stations A
and B are 750 and 1,000 meters, respectively, then the linearly inter-
polated mixing depths at 18Z are 375 and 500 meters. After the station
convective mixing depths are derived, they are interpolated to grid
points using the same inverse-square radius technique used to produce
the fields of initial wind components. Given that H(station A) = 375
meters and Hfstation B) = 500 meters at 18Z, Figure 2-6 represents the
convectively producing mixing depth field on the 4x4 grid at 18Z. The
composite field is generated by finding the maximum mixing depth value
at each grid point. For the example case, the composite field is
represented in Figure 2-7.
As a general rule in the analysis of mixing depths, the composite
field will be a clear representation of the actual spatially varying
mixing depth field as produced by the mechanical and convective forcing
functions. Regions on the grid with strong winds will exhibit deep
mixing depths, even without convection. Without dominant mechanical
influence, the mixing depth will be dependent on the strength of con-
vection and, therefore, on the amount of cloudiness in a region.
2.3 The Stability Algorithm
As an option, MESOPAC computes gridded fields of PGT stabilities
each model time step at each grid point. The normal method for com-
puting PGT stability (Turner 1970) relies on wind speed and solar
insolation data during the day and wind speed and cloud cover data at
night. Wind speed at each grid point is readily available in MESOPAC,
but solar insolation and cloud cover data are not. Certain assumptions
can be made enabling MESOPAC to compute realistic stabilities.
*The user has the option to constrain the convective mixing depth to
grow from HC = F = 0 at 12Z to HC = FX at a user-specified hour
between 12Z and OOZ; H = F will then persist until OOZ.
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404 404 404 404
404 404 370 292
*
404
404 370 337 260
404 292 260
5JC
309
Figure 2-5 Mechanically Produced Mixing Depths
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o
00
375 375 375 375
375 375 386 423
375
375 386 400 464
375 423 464
'f*
500
Figure 2-6 Convectively Produced Mixing Depths
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404 404 404 404
404 404 386 423
404 386 400 464
404 423 464 500
Figure 2-7 Final Mixing Depth Field
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At night, PGT stability is primarily wind-speed dependent. Low
cloud coverage can, at most, alter the stability by one PGT class and
then only for wind speeds less than 5 meters per second (m/s). At
night, MESOPAC assumes partly cloudy conditions so that the computed
stability is an average of the stabilities in Turner for cloudy and
clear conditions.
During the day, the PGT stability is as dependent on incoming solar
radiation (and the convective turbulence it produces) as it is on wind
speed. Because the depth of the convective mixed layer is dependent on
incoming solar radiation in much the same manner as PGT stability is, it
follows that the strength of incoming solar radiation can be estimated
from the depth of the daytime convective layer. As a rough estimate,
MESOPAC assumes weak insolation when the mixing depth by convective con-
siderations is HC < 500 m; moderate insolation when 500 m < Hc < 1,000 m;
and strong insolation when H > 1,000 m.
Considering a day with a maximum afternoon convective depth
Hc > 1,000 m, it follows that the PGT stability goes from Class C to
Class A as the mixed layer deepens from zero at sunrise to greater than
one kilometer by afternoon. The solar elevation angle increases from 0°
at sunrise to a probable elevation angle greater than 60° at midday,
ensuring that sufficient insolation produces a deep convective layer.
With these considerations in mind, Table 2-2 is constructed in a form
consistent with Turner.
Assuming a logarithmic wind profile in the surface layer with the
roughness length 10 centimeters and the Von Karman constant 0.35; and,
as in Section 2.2.1, the friction velocity u^ = 0.035 ug (ug is the free
stream velocity), the free stream velocity is scaled by a factor of 0.46
to produce a value of u (10 meters) at each grid point for use in
determining the PGT stability from Table 2-2.
In the example problem at 18Z, all the convective depths in
Figure 2-6 are below 500 meters except at the point I =4, J = 1, and
therefore imply light insolation. Because wind speeds at 10 meters are
all within 2 to 5 m/s, then the PGT stability is taken as Class C. At the
point I = 4, J = 1, insolation is moderate, and u (10 m) = 0.46 ug =
2.68 m/s, resulting in a PGT stability of Class B. The PGT stability
field is presented in Figure 2-8. Where two stability classes appear in
Table 2-2 for the same wind spee-"1 range, MESOPAC uses the more unstable
class for the lower end of the wind speed range during the day and the
more stable class for the lower end of the range at night.
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TABLE 2-2
KEY TO PGT STABILITY CLASSES AS GENERATED BY MESOPAC
Surface Wind
Speed at 10m
(m s"1)
<2
2-3
3-5
5-6
>6
Day
Mixing Depth
H >_ 1000m
A
A-B
B
C
C
500 < H < 1000
c
A-B
B
B-C
C-D
D
H <; 500
c
B
C
C
D
D
Night
E-F
D-E
D
D
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o
00
3333
3
Figure 2-8 The PGT Stability Field
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3. USER'S MANUAL
The MESOPAC user's manual provides a detailed description of the
preparation of a model run. A test example is proposed for illustrative
purposes; both the model input and output are included for the test
case. In addition, the entire program listing is appended in micro-
fiche. [The Fortran listing may appear somewhat unusual--the actual
Fortran code shown here was machine-translated from a higher-level
language, RATIONAL FORTRAN (RATFOR)].
3.1 Model Input
3.1.1 Description
MESOPAC input is divided into two separate parts. parameter input
and meteorology input. Both files are coded in card image form as one
compo5iTe'~ftTg^and~Tnput via logical unit 5. As detailed in Section
5.1.2, the parameter input contains all the variables necessary to
define any MESOPAC run. Grid size, run length and time step, and
radiosonde station names and locations are some of the key input param-
eters. In addition, various program options are specified through the
choice of other input parameters. The second input data file, radio-
sonde input (Section 3.1.51. contains the wind components, tempera_ture,
and pressure~o"ata at radiosonde stations. The data file, input daily
during the run stream at OOZ and 12Z, must begin at or before the
desired starting time input from the parameter file. Two radiosonde
sets are necessary for a 12-hour run, three sets for a 24-hour run, and,
in general, N + 1 radiosonde sets for a 12*N-hour run. Because the
model recognizes station names, it is not necessary to keep station data
cards in any particular order for any radiosonde set. Also, if one
station's data are missing, that station's card can be omitted at that
time. Detailed input description for the meteorology file is given in
Section 3.1.3. Note that because of the way the mixing depth algorithm
works, pressure and temperature data are only necessary for the morning
(12Z) soundings.
3.1.2 Parameter Input
Card_# Columns Format Name Definition
1 1-76 38A2 HEAD (38) Title for output data tape.
1 77-80 14 METCOD 4-digit integer code for output
tape.
2 1-5 15 IMAX Number of grid intersections in
the x-direction (a maximum of
40 are allowed).
2 6-10 15 JMAX Number of grid intersections in
the y-direction (a maximum of
40 are allowed).
3-1
-------
EN.IBONWENTAL RESEARCH S TECHNOLOGY INC
Card # Columns Format
11-15
16-20
21-25
11-20
15
15
15
3
3
3
3
3
3
4
1-2
3-5
6-7
11-12
13-15
16-17
1-10
12
13
12
12
13
12
F10.0
IHRBEG
IDYBEG
IYRBEG
IHREND
IDYEND
IYREND
DX
F10.6
21-30 F10.6
31-40 F10.6
41-50 110
1-10 L10
Name Definition
NMAX Number of radiosonde stations
(a maximum of 40 are allowed).
ISTEP Time step (hours) between
output maps, (allowable time
steps are 1, 2, 3, 4, 6, and
12 hours).
ICOEF Weighting coefficient for the time
interpolation of station winds to
ISTEP intervals (1-linear, 2-sinusoidal,
3-square-Iike, 4-user-specified).
Beginning hour of program run.
Beginning Julian day of run.
Beginning year of run.
Ending hour of run.
Ending Julian day of run.
Ending year of run.
Grid space (meters). Defaults to
40,000 if field is blank.
EPSI Windfield relaxation (if desired)
terminates when divergence at every
grid intersection is less than
EPSI. EPSI defaults to .00001 (s )
if field is blank.
RADIUS Scan radius (in units of grid
space, DX) for interpolation of
station winds to grid points.
RADIUS is computed internally if
field is left blank.
WFRAC Maximum allowable fraction (0.0 to
1.0) that individual wind components
can vary at grid points near
stations during wind field
relaxation.
KKMAX Windfield relaxation (if desired)
terminates after KKMAX iterations
if EPSI criterion has not already
been met. KKMAX defaults to 50
if field is left blank.
DVFREE If DVFREE = .TRUE., output wind-
fields are "divergence-free". If
DVFREE = .FALSE., output wind
fields are not divergence-free.
3-2
-------
ENVIRONMENTAL RESEARCH 8 TECHNOLOGY INC
Card #
Columns Format
5
6
11-20 L10
21-30 L10
1-10 L10
11-20 L10
Name Definition
HMODEL If HMODEL = .TRUE., the described
mixing depth calculation is
performed.
LSTAB If LSTAB = .TRUE., PGT stability
fields are generated.
LTAPE If LTAPE = .TRUE., generated
fields are output to tape or
disk every ISTEP hours. If
LTAPE = .FALSE., there is no out-
put to tape or disk.
LPRINT If LPRINT = .TRUE., generated
fields are output in gridded form
every ISTEP * IPRFRQ hours. If
LPRINT = .FALSE., there is no
gridded output.
IPRFRQ For LPRINT = .TRUE., printing
frequency is in terms of ISTEP for
gridded fields.
NHRZ Hour (13Z < NHRZ < OOZ) at which
the maximum daytime convective
mixing depths at all stations are
constrained to be reached. If
NHRZ precedes OOZ, the model persists
the maximum depths from NHRZ to
OOZ.
One of the following cards is needed for each of the NMAX (total number)
of radiosonde stations.
Card # Columns Format Name Definition
2-4 A3 NAME(N) Radiosonde station name.
6-10 F5.1 XS(N) x-coordinate of radiosonde
station (N); XS(N) = 0.0
corresponds to I = 1.
7... ll-?5 F5.1 YS(N) y-coordinate of radiosonde station
(N); YS(N) = 0.0 corresponds
to J = 1.
The following card is read only if a specified option is requested.
21-25 15
29-30 12
3-3
-------
ENVIRONMENTAL RESEARCH 8 TECHNOLOGY INC
Card #
last
Columns
varies
in length
Format
Name
12F5.2 COEFF
(4, ISTEP)
3.1.3 Radiosonde Input
Card # Columns Format Name
1-2
12
NCH
1
1
1
2. . .
2. ..
2...
2. . .
2. . .
2. . .
2...
3-5
6-7
11-15
2-4
11-15
16-20
21-25
26-30
31-35
36-40
13
12
15
A3
F5.0
F5.1
F5.1
F5.1
F5.1
F5.1
NDY
NYR
NSTAT
N2
P(N)
T(1,N)
T(2,N)
T(3,N)
T(4,N)
US(N)
41-45
F5.1 VS(N)
Definition
If ICOEF = 4, these time-inter-
polative weights are used to
construct station winds from hours,
t = ISTEP to t = 12, at ISTEP
hour intervals between radio-
sonde times. COEFF (ICOEF, ISTEP)
= 0.0 means that the wind components
at the beginning of the time
period are used. COEFF (ICOEF, ISTEP)
= 1.0 means that the wind components
at the ending radiosonde of the
12-hour period are used.
Definition
Hour (OOZ or 12Z) of radiosonde set
that follows.
Julian day of following set.
Year of following set.
Number of radiosonde stations
reporting at this year, day, hour
(NSTAT < NMAX).
Station name for radiosonde data
on each individual card.
Surface pressure millibars (mb)
at radiosonde station (N) (not
read at OOZ).
Surface temperature (°C)* at radio-
sonde station (N)
850 mb temperature (°C) (not read
at OOZ) .
700 mb temperature (°C) (not read
at OOZ) .
500 mb temperature (°C) (not read
at OOZ) .
Radiosonde station (N)
u-component (m s *) a the most
relevant station-specific pressure
level or height above ground.
v-component (m s *) .
*If available, the user may substitute the afternoon maximum surface
temperature for the OOZ radiosonde station temperature.
3-4
-------
ENVIRONMENTAL RESEARCH & TECHNOLOGY It
3.2 Missing Data
Often in the course of processing meteorology data for input to
MESOPAC, some data will be missing or unavailable. If data are missing,
MESOPAC recognizes this absence and attempts to manage without them. At
a minimum, there must be at least one radiosonde station with usable
data each 12-hour time step. A MESOPAC run will terminate if all data
for every radiosonde station named in the parameter input are missing.
If data for more than half of the radiosonde stations named in the
parameter input are missing at any given radiosonde time, a warning will
be printed by the program.
The missing value indicator '999.0' is entered in all cases of
missing input data, except for missing surface pressure data, for which
'9999.' is entered. (For line printer output '9999.' indicates a
missing mixing depth at a station, and '9' a missing PGT stability.)
The missing value indicator should be entered on the station card for
any value the user cannot obtain. It is assumed at all times that if
the station wind u-component is missing, the v-component is missing as
well.
For a missing station wind vector, MESOPAC will use the wind
vector for the same station from the previous radiosonde set, or next
set, whichever set is closer in time. If two consecutive wind vectors
are missing, MESOPAC cannot determine the wind vector at intermediate
hours. In this case, that station will be dropped from the computation
of both the wind fields and the mechanically produced mixing depth
field. If the radiosonde station surface pressure is less than the
desired pressure level, then winds at that level are, obviously, unavail-
able. The user should therefore enter the missing value indicators on
the input card for the wind components at this station.
If the OOZ surface temperature is missing at a station, MESOPAC
cannot compute the afternoon maximum convective depth at that station.
Therefore, the station will not be used in constructing the convectively-
produced mixing depth field.
If the temperature at any level in a morning (12Z) radiosonde
sounding at a station is missing, MESOPAC will compute the temperature
at that level as a linear average of the temperatures measured at
adjacent levels. If the temperatures at two or more levels are missing,
MESOPAC will not compute a convective depth at that station for that
day.
3.3 Model Output
Fields of horizontal (u,v) wind components, mixing depth, and
stability are output by MESOPAC through two media: line printer and
sequential disk (or tape) file. Line printer output is produced every
ISTEP * IPRFRQ hours (if LPRINT = .TRUE.), starting with the initial
3-5
-------
ENv RO".UEN~AL RESEARCH & TECHNOLOGY INC
hour of the run. Seqiential disk or tape output is produced every ISTEP
hours (if LTAPE = .TRUE.), also starting with the initial hour of the
run. The disk or tape file is output through logical unit 2,in a form
comp 1 etely ready for use by'MESOPLUME, MESOPUFt-', and MHSOGR1D.
High quality Calcomp plots of MESOPAC fields can be produced
directly from the output sequential disk or tape file by use of MESOPLOT
and PLOTVEC, two plotting programs that are part of the MESOFILE post-
processing system (Scire et al. 1979). A sample set of plots of wind
vector, mixing depth, and stability fields are shown in Figure 3-1.
3.4 MESOPAC Test Case
A test case is contained in this manual to help the potential user
to understand the MESOPAC model. Appendix A contains a copy of the
input parameter set, as coded on cards for the test case. Appendix B
contains a copy of the radiosonde set. Appendix C contains the entire
output from the line printer.
3-6
-------
* *
ENVIRONMENTAL RESEARCH & TECHNOLOGY INC
Figure 3-1 Sample Plots of Wind Vector (Top), Mixing Depth (Lower Left),
and Stability (Lower Right) Fields
3-7
-------
ENVIRONMENTAL RESEARCH 8, TECHNOLOGY INC
REFERENCES
Bass, A., C. W. Benkley, J. S. Scire, and C. S. Morris. 1979.
Development of Mesoscale Air Quality Simulation Models. Volume 1.
Comparative Sensitivity Studies of Puff, Plume and Grid Models for
Long-Distance Dispersion Modeling. EPA 600/7-79-XXX, Environmental
Protection Agency, Research Triangle Park, NC, 210 pp.
Benkley, C. W. and A. Bass. 1979a. Development of Mesoscale Air
Quality Simulation Models. Volume 2. User's Guide to MESOPLUME
(Mesoscale Plume Segment) Model. EPA 600/7-79-XXX, Environmental
Protection Agency, Research Triangle Park, NC, 141 pp.
Benkley, C. W. and A. Bass. 1979b. Development of Mesoscale Air
Quality Simulation Models. Volume 3. User's Guide to MESOPUFF
(Mesoscale Puff) Model. EPA 600/7-79-XXX, Environmental Protection
Agency, Research Triangle Park, NC, 118 pp.
Benkley, C. W. and L. L. Schulman. 1979. Estimating Hourly Mixing
Depths from Historical Meteorological Data. J. Appl. Meteor.
18:772-780.
Blackadar, A. K. 1962. The Vertical Distribution of Wind and Turbulent
Exchange in a Neutral Atmosphere. J. Geophys Res., 67: 3095-3102.
Clark, T. L. and R. E. Eskridge 1977. Non-Divergent Wind Analysis
Algorithm for the St. Louis RAPS Network. EPA 600/4-77-049.
Environmental Protection Agency, Research Triangle Park, NC, 63 pp.
Clarke, R. H. 1970. Observational Studies in the Atmospheric Boundary
Layer. Quart. J. Roy. Met. Soc., 96:91-114.
Deardorff, J. W. 1972. Rate of Growth of the Atmospheric Surface
Layer. Proc. of the Symposium on Air Pollution, Turbulence and
Diffusion. Albuquerque, MM (December 1971). Ed. H. W. Church and
R. E. Luna, pp. 183-190.
Delage, Y. 1974. A Numerical Study of the Nocturnal Atmospheric
Boundary Layer. Quart. J. Roy. Met. Soc., 100:351-364.
Morris, C. S., C. W. Benkley, uJ A. Bass. 1979. Development of
Mesoscale Air Quality Simulation Models. Volume 4. User's Guide
to MESOGRID (Mesoscale Grid) Model. EPA 600/7-79-XXX, Environ-
mental Protection Agency, Research Triangle Park, NC, 106 pp.
Plate, E. J. 1971. Aerodynamic Characteristics of Atmospheric Boundary
Layers. U.S. Atomic Energy Commission TID-25465, 190 pp.
-------
ENVIRONMENTAL RESEARCH 5 TECHNOLOGY INC
Scire, J. S., J. E. Beebe, C. W. Benkley, and A. Bass. 1979. Develop-
ment of Mesoscale Air Quality Simulation Models. Volume 5. User's
Guide to the MESOFILE Postprocessing Package. EPA 600/7-79-XXX,
Environmental Protection Agency, Research Triangle Park, NC, 67 pp.
Turner, D. B. 1970. Workbook of Atmospheric Dispersion Estimates.
U.S. Department of Health, Education and Welfare, Publ. 999-AP-26,
88 pp.
Yu, T. 1978. Determining the Height of the Nocturnal Boundary Layer.
J'. Appl. Met. 17:28-33.
-------
APPENDIX A
INPUT PARAMETERS
-------
MESGPAC USEK'S MANUAL TEST CASE
13 13
1316778 1
80000. 0
.TRUE.
.FALSE.
INW 5.0
UCC -0.3
ABU 9.6
GJT 7.3
TUS 4.8
DEN 11.4
LND 7.6
SLC 3.9
ELY 0.8
BOI -o.a
«MC -a.i
RAP 13.0
L8F 15.7
DDC 17.4
AMA 15.4
MAF 14.6
EL.P 9.8
SAN -3. 6
18 6 1
216876
.00001 1
.TRUE. .TRUE.
.TRUE. 1 0
1.8
4.1
1.6
7.3
-a.o
8.4
ia.9
9.9
7.8
13.8
10.4
14.4
10.7
6.1
a. 5
-a.i
-a. 6
-1.4
50
-------
APPENDIX B
INPUT RADIOSONDE DATA
-------
1216778
BOI
RAP
WMC
LNU
SLC
LBF
ELY
GJT
DEN
DDC
UCC
INK
ABU
AMA
SAN
TUS
ELP
MAP
0016878
BOI
RAP
WMC
LNO
SLC
LBF
ELY
GJT
DEN
ODC
UCC
INN
ABU
AMA
SAN
TUS
ELP
MAP
1216878
BOI
HAP
WMC
LND
SLC
LBF
tLY
GJT
DEN
DDC
UCC
INN
ABU
AMA
SAN
TUS
ELP
MAP
18
918. 6.6 10. » 3,5-20.5 7.6 -5.3
904. 13.8 13.4 6.8-11.9 5.5 -1.5
870. 6.6 8.0 -0.9-23.5 1.4 3.9
9999.999.0999.0999.0999.0999.0999.0
870. 13.8 13.8 5.4-12.7 2.6 7.3
910. 18.8 21. d 15.0 -9.1 4.7 -4.0
9999.999.0999.0999.0999.0999.0999.0
9999.999.0999.0999.0999.0999.0999.0
9999.999.0999.0999.0999.0999.0999.0
920. 23.2 26.6 15.6 -6.9 11.6 4.2
9999.999.0999.0999.0999.0999.0999.0
9999.999.0999.0999.0999.0999.0999.0
9999. 999. 0999. 0999. 0999. 0999. 0999.0
890. 21.6 27.4 16.2 -7.7 8.5 4.9
9999.999.0999.0999.0999.0999.0999.0
9999.999.0999.0999.0999.0999.0999.0
9999.999.0999.0999.0999.0999.0999.0
916. 21.0 25.2 14.6 -6.3 -1.5 -0.3
18
20.6 9.1 -1.6
22.2 4.3 5.1
21.6 3.6 -0.3
999.0 999.0999.0
25.6 10.8 0.9
28.8 6.2 3.6
21.6 8.0 5.6
31.6 12.5 7.2
31.6 0.2 -1.0
36.6 10.5 10.5
999.0 999.0999.0
32.8 9.8 5.7
34.4 11.8 -0.0
34.4 5.5 3.8
23.4 18.4 1.6
38.4 3.8 -2.7
36. 0 4.5 -1.2
34.4 2.9 -2.1
18
922. 9.4 12.4 -0.7-17.9 7.5 -2.0
907. 12.8 10.8 -1.5999.0 14.5 -5.3
«74. 4.4 12.6 1.0 16.3 3.8 -2.7
835. 6.8999.0 -1.1 19.7 2.7 -3.8
87fl. 8.8 13.0 0.0 15.1 4.7 -6.7
914. 15.0 15.8 8.8 8.7 7.2 -0.0
816. 1.8999.0 4.4 14.1 1.0 -1.2
856. 17.2 17.4 6.4 12.5 4.7 -4.7
839. 13.2999.0 9.4 10.9 6.3 -4.4
919. 22.8 28.6 15.6 6.5 13.5 4.9
9999.999.0999.0999.0999.0999.0999.0
655. 10.0 16.8 10.8 7.7 6.5 1.7
841. 15.6999.0 10.6 8.1 4.5 -1.2
890. 22.2 26.4 16.0 7.1 8.3 6.9
1000. 16.0 23.2 11.0 9.3 12.3 -0.0
925. 22.6 26.6 13.2 8.1 6.5 -3.0
882. 23.6 28.0 14.8 7.9 6.0 -1.6
916. 21.6 20.8 15.6 7.5 -0.3 -0,4
-------
APPENDIX C
LINE PRINTER OUTPUT
-------
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TECHNICAL REPORT DATA
(Please read Instructions on the reverse before completing)
1 DEPORT NO
EPA-600/7-78-XXX
2
4 TITLE AND SUBTITLE
7 AbTHOFUS)
Carl W. Benkley
Arthur Bass
9 PERFORMING ORGANIZATION NAM
Environmental Research
696 Virginia Road
Concord, MA 01742
12. SPONSORING AGENCY NAME AND
Environmental Sciences
Office of Research and
U.S. Environmental Prot
Research Triangle Park,
E AND ADDRESS
$ Technology, Inc.
ADDRESS
Research Laboratory
Development
ection Agency
NC 27711
3. RECIPIENT'S ACCESSION NO.
5. REPORT DATE
September 1979
6. PERFORMING ORGANIZATION CODE
8. PERFORMING ORGANIZATION REPORT
NO.
10. PROGRAM ELEMENT NO.
11. CONTRACT/GRANT NO.
03-6-022-35254/NOAA Contract
13. TYPE OF REPORT AND PERIOD COVERED
Contract Report
14. SPONSORING AGENCY CODE
EPA-600/7
15. SUPPLEMENTARY NOTES
Performed under contract to the National Oceanic and Atmospheric Administration
16. ABSTRACT
MESOPAC is a mesoscale meteorological preprocessor program; it is designed to
provide meteorological data to regional-scale air quality simulation models. Radio-
sonde data routinely available from National Weather Service (NWS) radiosonde
("upper air") and surface stations are used to produce spatially-interpolated,
time-sequenced mesoscale meteorological data fields. These include: (a) horizon-
tal (u,v) wind components; (b) mixing depth; (c) Pasquill-Gifford-Turner (PGT) sta-
bility class. An interpolation/iterative relaxation scheme is used to consturct
the wind field. The mixing depth and PGT stability fields are created with a new,
physically appealing algorithm.
MESOPAC is a fully-independent program, easily coupled to any reasonably modu-
lar transport-diffusion model. Currently, it is used to drive the MESOPUFF,
MEOSPLUME, and MESOGRID models. MESOPAC is highly user-oriented: .easy to under-
stand; easy to use; easy to modify. It offers a range of features including: user-
specified grid resolution (maximum resolution is 40 x 40 elements); arbitrary grid
orientation and size; user-specified data stations and significant data levels (e.g.
surface, 850 mb, 700 mb); user-controllable minimization of wind field divergence;
time-weighted (centered) interpolation of data fields; arbitrary duration of
meteorological episode; and multiple choices of output time interval (1, 2, 3, 4,
6, or 12 hours).
A full technical description of the MESOPAC model algorithms; user instructions;
a test case to verify program operation; and a full Fortran listing are provided.
17. KEY WORDS AND DOCUMENT ANALYSIS
3. DESCRIPTORS
*Air Pollution
*Algorithms
*Atmospheric Models
*Wind (Meteorology)
13. DISTRIBUTION STATEMENT
RELEASE TO PUBLIC
b. IDENTIFIERS/OPEN ENDED TLRMS
19. SECURITY CLASS (This Report)
UNCLASSIFIED
20. SECURITY CLASS (This page)
UNCIASSTFTFn
*:. COS ATI Picld/C-ouD
13B
12A
04A
04B
21. NO. OF PAGES
76
22. PRICE
EPA Form 2220-1 (9-73)
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