Egypt. J. Remote Sensing & Space Sci., V. 9, pp. 15-30 (2006)
SIMULATION OF ATMOSPHERIC TEMPERATURE INVERSIONS OVER
GREATER CAIRO USING THE MMS MESO-SCALE ATMOSPHERIC
MODEL
.~
H. A. KandiJl, M.A. Kader 3, A. A. Moaty3, B. Elhadidi2, A. 0. Sherif3
1-Department of Mechanical Engineering, AlexandriaUniversity ,Alexandria,
Egpyt.
2-Department of Aerospace Engineering, Cairo University, Giza, Egypt
3-National Authority for Remote Sensing and Space Sciences (NARSS),
Cairo, Egypt
Abstract: Air pollution episodes have been recorded in Cairo, during the fall
season, since 1999, as a result of specific meteorological conditions
combined with large quantity of pollutants created by several ground-based
sources.
The main reason for the smog-like episodes (black clouds) is adverse
weather conditions with low and variable winds, high humidity and strong
temperature inversions in the few-hundred meters above the ground. The two
important types of temperature inversion affecting the air pollution are
surface or ground (radiation) inversion and subsidence (elevated) inversion .
. The surface temperature inversion is associated with a rapid decrease in the
ground surface temperature with the simultaneous existence of warm air in
the lower troposphere. The inversion develops at dusk and continues until
the surface warms again the following day. Pollutants emitted during the
night are caught under this "inversion lid." Subsidence inversion forms when
warm air masses move over colder air masses. The inversion develops with a
stagnating high-pressure system (generally associated with fair weather).
Under these conditions, the pressure gradient becomes progressively weaker
so that winds become light. These light winds greatly reduce the horizontal
transport and dispersion of pollutants. At the same time, the subsidence
inversion acts as a barrier to the vertical dispersion of the pollutants.
In this study, the Penn State/NCAR meso -scale model (MM5) is used to
simulate the temperature inversion phenomenon over Greater Cairo region
during the fall season of 2004. Accurate computations of the heat transfer at
the surface are needed to capture this phenomenon. This can only be
achieved by high-resolution simulations in both horizontal and vertical
directions. Hence, for accurate simulation of the temperature inversion over
Greater Cairo, four nested domains of resolutions of 27 km, 9 km, 3 km and
1 km, respectively, were used in the horizontal planes. Furthermore, 42
levels were used in the vertical direction to capture the correct surface heat
flux and to observe the small changes in the vertical temperature gradient.
The results of the numerical model showed that it is possible to capture both
types of temperature inversion during the night and early morning hours.
This can be observed from the results of the vertical temperature profile and
temperature gradient, which indicate that an inversion system was present
over Cairo at a layer extending between 300 m and 800 m above the ground.
15
Kandil et al.
INTRODUCTION
Atmospheric Temperature Inversion (TI) is a very important phenomenon that
affects air quality and pollution level over cities. The rate of temperature change
with height is called the lapse rate. The standard atmospheric lapse rate is
-6.5 °C/km(Colette et al., 2003) for wet adiabatic air which means that the
temperature decreases with height. In the case of positive lapse rate, the
atmospheric air temperature increases with height and this is called temperature
inversion. Temperature inversion prevents the air from naturally being ventilated
vertically which keeps any aerosol and pollution always below the temperature
inversion layer which increases the concentration of pollutants in the air.
Temperature inversions are categorized into three types which are radiation
(surface or ground) inversion, subsidence (elevated) inversion and frontal (aloft)
inversion.Ground temperature inversion (GTI) develops at low levels. It occurs
due to the nocturnal ground radiation during night time where ground losses heat
to the black sky by radiation as shown in Figure (1). Any pollutants emitted during
night are caught under this inversion lid. This type of inversion is responsible also
for the morning fogs.
Noon
Midnight
6 p.m.
6 a.m.
N oon
t
-
Temperatm e
~
Figure 1: Typical ambient lapse rates during a sunny day and clear night, during.
(After Colette et al., 2003).
Subsidence temperature inversion (STI) produced by adiabatic warming of a layer
of subsiding air and it is enhanced by vertical mixing in the air layer below the
inversion. The STI develops with a stagnating high-pressure system (generally
associated with fair weather). Under these conditions, the pressure gradient
becomes progressively weaker so that winds become light. The light winds greatly
reduce the horizontal transport and dispersion of pollutants. At the same time, the
subsidence inversion aloft continuously descends acting as a barrier to the vertical
dispersion of the pollutants. These conditions can persist over large areas for
several days, and the resulting accumulation of pollutants can cause serious health
hazards. Figure (2) shows the mechanism of this temperature inversion.
A frontal (aloft) inversion usually occurs at high altitudes and results when a warm
air mass overruns a cold air mass below. This type of inversion is not important
from a pollution control point of view.
Many studies were carried out in order to simulate and predict the weather
conditions of cities. These studies considered the effect of human activities within
cities on the weather and air quality of the city. Some of these studies focu sed on
the modeling of the temperature inversion and its impact on air pollution.
The early attempts to understand the temperature inversion formation and breakup
mechanisms were carried out using field observations followed by empirical
correlations and simple thermodynamic models. Among the pioneering studies of
16
Simulation of Atomospheric Temperature ...
Figure 2: Formation of subsidence temperatune inversion
(After Colette et al., 2003).
this type are those presented by Whitman (1982), who studied the breakup of
temperature inversion using real time observations of vertical temperature profile
at the western slope of the Rocky Mountains in Western Colorado. The
observations showed three patterns of temperature inversion breakup. The breakup
patterns were classified according to the convective boundary layer height and the
top layer height of the inversion. The first is characterized by the upward growth
from the ground of the convective boundary layer (CBL) which describes the
inversion behavior over flat terrain. The second pattern is caused by the descent of
the top of the inversion into the valley which is accompanied by a warming of the
valley atmosphere. While the third pattern represents a continuum of intermediate
situations in which both the growth of the CBL and the descent of the inversion
top are present. Based on the observations of the temperature inversion breakup,
the wind speeds within the inversion layer were weak (less than 2 meters per
second). Above the top of the inversion layer, the wind speeds were moderated
(greater than 6 meters per second) .
Based on the wind and temperature observations, a hypothesis has been developed
by Whiteman (1982-a) to explain the temperature structure evolution. Since
energy is required to change the temperature structure, and the changes begin at
sunrise. It is reasonable to hypothesize that solar radiation is the driving force. A
fraction of the solar radiation, received on the valley floor and sidewalls, is
converted to the sensible heat flux that provides energy to the valley atmosphere.
Sensible heat flux from a surface causes a convective boundary layer to develop
over the surface. Mass and heat are entrained into the convective boundary layer
from the stable core above. Mass entrained into the valley floor and sidewall
convective boundary layer, however, is carried from the valley in the up- slope
flows that develop in the convective boundary layers over the sidewalls. This
removal of mass from the base and sides of the stable core causes the elevated
inversion to sink deeper into the valley and to warm adiabatically due to
subsidence, and decreases the rate of growth of the convective boundary layer.
Following this hypothesis, the rate of warming depends directly on the rate of
energy input into the valley atmosphere. This energy may be used to deepen the
convective boundary layer or to move mass up the sidewalls, allowing the stable
core to sink ..
A simulation for the nocturnal ground temperature inversion in deep mountains
valley breakup was presented by Whiteman (1982-b ). This simulation was based
on a hypothesis for inversion breakup which was presented by Whiteman (1982-a).
A thermodynamic model was developed in order to evaluate an energy balance
between the valley atmosphere, ground and solar radiation. The model results were
17
-----------------------------------------------------------------------------Kandil et al.
compared to observations for the inversion breakup. These observations were
collected from different valleys and studied by Whiteman (1982-a). The model
was able to predict the vertical temperature structure during the inversion breakup.
The results showed that breakup time increases by increasing the width of the
valley . This results in larger breakup time for plain areas compared to valley at the
same atmospheric conditions. The formation of stable stratification after sunset in
Sofia, Bulgaria, was studied by Kolev et, al. (2000). The dynamics of atmospheric
parameters (e.g. , the wind velocity and temperature profiles, height of various
layers, etc.) associated with the interaction processes of mountain valley
circulation and urban heat island was followed. The observations were carried out
using lidars (aerosol and Raman), kytoon (tethered balloon) and pilot balloons
over the city of Sofia and covered heights from 70 to 900 m. The presence of
neighboring mountains and the urban heat island effect lead to the formation of
three temperature inversions (ground, elevated and capping) and specific vertical
profiles of the wind velocity. The formation mechanism was considered of
two-layer aerosol structure in the atmosphere over the urban area and its dynamics
observed by the lidar after sunset.
Modern computers with enhanced processors and huge memory and storage
capabilities enabled researchers to attempt to solve the governing equations of
fluid dynamics with reasonable accuracy. The trials in the area of atmospheric
modeling are still limited because of the domain size that requires huge amount of
computational memory to handle the full-size domain. In the following studies,
idealized domains with simple configurations and small sizes were modeled. For
instance, Colette et al. (2003) presented a numerical simulation of inversion layer
breakup in idealized steep valley using the Advanced Regional Predication System
(ARPS) model. The valley width and depth and topography shade effects were
investigated. In addition, typical up slope and down slope wind circulation were
reproduced. Influence of atmospheric stability in the valley was analyzed and
characterized. They concluded that the valley width and depth influence the
lifetime of the temperature inversion layer and the topographic shading effect is
eliminated by increasing the width of the valley.
Recently, Hanjalik and Kenjeres (2005) presented a computational simulation of
diurnal air movement and pollutant dispersion over complex terrain with heat and
emission islands. The method, based on numerical solution of momentum, energy
and concentration equations in time and space using an algebraic turbulence
closure for subscale (unresolved) motion, can account for terrain topography and
dynamics of meteorological conditions. The study presented a realistic scenario
over a medium-sized town situated in a mountain valley during windless winter
days when the lower atmosphere is capped by an inversion layer preventing any
escape of pollutants. The results include the predictions of local values of air
velocity, temperature and pollutant concentration. They suggested that the
approach can be used for regulating emission during critical weather periods, as
well as. for long-term planning of urban and industrial development, for optimum
location of industrial zones and for design of city transportation and traffic
systems.
Atmospheric modeling systems such as the meso-scale model MMS enabled the
prediction of weather conditions of cities, countries and continents with fair
accuracy. Such models suffer from losing the accuracy at high resolution. Some
trials were presented where corrective measures were applied to obtain reasonable
results at high resolutions. For example, Hauge and Hole (2002) used MMS to
simulate the surface temperature inversion in complex terrain of Hedmark County,
18
Simulation of Atomospheric Temperature ...
Oslo, Norway. The MMS modeling system was modified to take into account the
slope irradiance in the calculations of the short wave radiation model which is a
part of the MMS model. They compared the MMS simulation results with
soundings observations for the vertical temperature profile and wind speeds at
certain point located at Hedmark County. They reported that the MMS model is
capable of capturing the ground temperature inversion . . In addition, The MMS
model results were improved by implementing the slope irradiance where the
RMSE in temperature was reduced by 13% and it was reduced by 35% in wind
field . They noted also that inversion breakup modeled by MMS was too fast
compared with the measured data, Hole and Hauge (2003). In a recent study by Rantamki et al (2004), the results of MMS model were
evaluated against the observational data during an air pollution episode that
occurred in the Helsinki Metropolitan Area on27-29 December, 1995. The MMS
model was used with triple-nesting configuration that had resolutions of 9 km, 3
km and 1 km. The model runs have been performed with 17 sigma levels; the
highest model level is located at 100 hPa. They concluded that the MMS model
was able to predict the observed ground temperature inversions up to 50 m from
the ground; however, the predicted surface temperature was too high, compared
with the measured data.
It is noted from the literature review that the temperature inversion phenomenon
was not fully understood and the numerical solutions of idealized valleys models
did not answer all questions because of the scaling problems and the lack of
required resources to simulate the full-size problem. Finally, the MMS model was
used, in limited number of studies, to model the GTI while the . STI was not
considered in any study. In the present study, the MMS is modified and optimized
to simulate the temperature inversions over Cairo which affects the pollution
episodes (black clouds) that have been observed during the fall seasons since
1999.
Temperature inversion and the black cloud over Cairo
According · to Environmental Information and Monitoring Program (EIMP) of
Egypt, the main reason for the smog-like episode experienced by a large part of
the Cairo population in October 1999 is adverse weather conditions with low and
variable winds, high humidity and strong temperature inversions in the fewhundred meters above the ground. The emissions of pollutants released from a
number of different ground sources in the Cairo area were added to a slow
transport of particles emitted from open air waste burning in the Delta.
Furthermore, Sivertsen (1999) presented that a high pressure area is situated north
of Egypt with its centre in the Eastern Mediterranean, giving rise to a slow
movement of humid air from the north-east across the Delta into the Cairo area.
Subsidence of air in the high pressure caused the formation of a temperature
inversion in the lower atmosphere, which created a "lid" on the Cairo air mass.
Under this lid the wind speeds are decreasing during the afternoon of 23 October
1999 to near calm conditions. At the end the local surface winds were turning to
slowly move air pollutants back into Cairo from the south in the evening . . The
unusual high humidity together with high concentrations of suspended dust and
other pollutants created what in Europe is called a "winter type smog episode" .
The main sources of pollutants were traffic, open-air waste burning and a large
number of small enterprises releasing air pollutants near the surface. Moreover,
Cairo is affected by the unorganized burning of agricultural wastes in the north
during the season of rice harvesting and also from industrial emission from
steeland cement factories in the south. Low wind speed conditions combined with
stable atmospheric conditions created the problem. High concentrations of S0 2
and PMl 0 were recorded by all monitoring stations in Cairo, Hussein et al. (2003) .
19
Kandil et al.
In this study, the MM5 model, by Chen and Dudhia (2001), is used to simulate the
weather conditions and capture the temperature inversion over Greater Cairo.
MMS modeling system is coupled with NOAH (N: National Centers for
Environmental Prediction (NCEP), 0: Oregon State University (Dept of
Atmospheric Sciences), A: Air Force (both AFWA and AFRL- formerly AFGL,
PL), H: Hydrologic Research Lab- NWS) land surface model, (Mitchel, 1996), to
simulate the ground effects on temperature inversion. For accurate temperature
inversion modeling, a horizontal grid spacing of 1 km is used and four nests
centered at Cairo are constructed.
Figure (3) shows the four nested domains used in simulating TI. The first domain
has 167x99 grid points with 27-km grid spacing. The second domain has 175x175
grid points with 9-km grid spacing. The third domain has 124x1 1'2 grid points
with a grid spacing of 3 km while the most fine grid has 100x136 grid points and 1
km grid spacing. All four nested domains have 42 vertical grid levels starting at
3.6 m above ground level with 7 levels below 100m.
MMS is initialized using initial conditions from the FNL data base with accuracy
of 1° x 1° ( 111 km) at 26 standard pressure levels under 100 hPa. The vegetation
fraction dataset is updated using satellite observations from VHRR sensors on the
Figure 3: Nested domains used in simulating temperature inversion over Greater
Cairo
20
Simulation of Atomospheric Temperature ...
NOAA observation system. The normalized difference vegetation index (NDVI)
data is available from NOAA receiving station located at the National Authority
for Remote Sensing and Space Sciences (NARSS), Egypt. The data is processed
and validated at NARSS according to the methods described by Gutaman and
lgnatov (1997), Gitelson et. al, (1998) and Wunderle et. al, (2003). Using satellite
derived data enhanced the boundary conditions of the modeling system, which
should result in accurate prediction of the weather conditions as reported by many
investigators, Nicole et. al, and Oesch et. al, (2004). The sea surface temperature
data is obtained from FNL data sets. The physics options of the model used were:
shallow convection scheme, MRF boundary layer scheme and cloud radiation
scheme.
The modified MM5 modeling system coupled with the NOAH LSM with the
boundary conditions upgraded by satellite observations was used by the present
authors in building weather simulation models for Egypt, the Nile Basin, North
Africa and the continent of Africa, Sherif et. al (2005-a, 2005-b, and 2005-c). The
first simulation of the temperature inversion over Egypt was presented by the
present authors in 2005, Sherif et. al, (2005 -d)
In order to study the effect of simulating the ground surface processes on the
prediction of the temperature inversion, two simulations were carried out starting
on 28 September 2004, one with land surface modeling (LSM) and the other
without any land surface modeling (NOLASM). The simulated time was selected
because a temperature inversion was observed at that time at Cairo International
Airport. The model was initialized using FNL datasets at 12:00 UTC. The vertical
temperature gradient was calculated for the two simulations and the results are
shown in Figure (4) for selected time frames. The horizontal axis shows the
temperature gradient (Deg. m-1) while the vertical axis shows the altitude in
meters.
l-'
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&~J _:::::-..:::=-
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Figure 4: Vertical temperature gradient when using NOAH LSM and without
NOAHLSM
21
Kandil et al.
The simulations started with the same initial conditions at 12:00 UTC as shown in
Figure (4 ). After three hours of simulation, a reasonable difference in temperature
gradients was detected as shown at 15:00 UTC. The temperatur~ gradient was
strongly changed for the LSM simulation in the lowest I 00 meters. At that time,
the solar elevation was 8.63 degrees and the solar radiation was low. This lead to
rapid decrease in ground temperature while the air temperature was relatively high
and the temperature gradient was strongly changed with altitude. The NOLSM
simulation did not show a large change in temperature gradient since the surface
heat fluxes were not modeled.
After 3hours from sunset, at 18:00 UTC, subsidence temperature inversions began
to develop at an altitude of 400 meters for the LSM simulation and 700 meters for
the NOLSM simulation. At 22:00 UTC, a ground temperature inversion was
detected for the LSM simulation while the NOLSM simulation did not predict any
ground temperature inversions. Because of the ground temperature was decreased
by nocturnal radiation, the adjacent air temperature was affected. These processes
were simulated in .the LSM simulation and resulted in detecting the ground
temperature inversion. In the case of NOLSM simulation, the ground radiation
w~s not simulated which leads to higher ground temperatures compared to the real
case. These .conditions are not suitable for a temperature inversion.
By 01:00 UTC, 29th of September 2004, the ground temperature inversion was
totally developed at 60 meters above the ground level for the LSM simulation.
This ground temperature inversion was destructed by 04:00 UTC just after the sun
rise (3:46 UTC). Furthermore, the two simulations predicted subsidence
temperature inversions since this type of inversion is not greatly affected by the
surface processes. The effect of the surface processes appears only in the
thickness and the elevation of the subsidence temperature inversion.In brief,
simulating the surface processes, using a land surface model, has direct impact in
predicting the ground temperature inversion. The subsidence temperature
inversion is detected weather the surface processes are modeled or not.
Temperature Gradients of Vertical Cross Sections
In orderto study the temperature inversion phenomenon, the simulation results for
a set of cross sections are plotted at different locations in Cairo. This includes
longitudinal and latitudinal cross sections for Cairo domain. Temperature gradient
contours ..are plotted from 0.0 deg.m-1 to 0.015 deg.m-1 for the considered cross
.sections. The height is clipped at 1500 meters in order to focus on the inversion
layers. The . results are shown in Figures (6) and (7) for the selected sections.
Three latitudinal cross sections are considered to cover most of the terrain features
of the region. The latitudes of the cross sections passing through North Cairo,
Middle Cairo and South Cairo are 30.29, 30.116?- and 29.9, respectively.
At the north of Cairo, the terrain is almost flat and the ground is vegetated while
in the south of Cairo, the terrain is complex and the vegetation coverage is lower
than that of the north of Cairo. At the middle of Cairo, the train is less
complicated than that of the south of Cairo but the urban areas are larger than both
the north and south sections. Figure (5) shows the location of the cross sections
for the Cairo domain.
22
Simulation of Atomospheric Temperature ...
Figure 5: Latitudinal cross sections locations for the Greater Cairo
Figure (6) shows the temperature gradient contours for the three latitudinal
sections where the results for each section are shown in a row containing 4 frames.
Each column shows the results of the three sections at a selected time.
The MM5 model was initialized at 12:00 UTC of 30th of September 2004 and a
spin up time of 6 hours is used in all simulations . A subsidence temperature
inversion (STI) was detected in the three cross sections at 17:00 UTC a:s shown in
Figure (6). It covered large area at the north of Cairo while it covered small areas
at the middle and south of Cairo. The strength of the STI at the north of Cairo was
greater than for the middle and the south of Cairo. The STI elevation at the north
of Cairo was below 500 meters. At the middle and south of Cairo, the subsidence
inversion elevation was 750 meters. Ground temperature inversions (GTI) were
also detected at the three cross sections with different strengths. This layer of
inversion has a small thickness for the three cross sections (20 meters). This type
of inversion covered large area at the north of Cairo and smaller areas at the
·
,
middle and south sections.
At the north of Cairo, the STI covered the whole domain while the elevation was
not changed at 20:00 UTC. Its thickness and strength was increased from 150
meters to 250 meters and from 0.07 deg.m-lto 0.10 deg.m-1 respectively.The GTI
thickness, strength and coverage area were increased form 17:00 UTC to 20:00
UTC at the north section. The GTI thickness was increased from 20 meters to 300
meters at 20:00 UTC while the elevation was maintained at 3.6 meters. The GTI
and STI were matched at 300 meters at the north of Cairo. This may lead .to a
stagnant area which increases the concentrations of aerosols and pollutants in this
region at that day. The north of Cairo cross section intersects the River Nile at
30.92° east which leads to destruction of GTI at 30.92° east.
Moreover, the STI covered the whole domain at the middle and south of Cairo at
20:00 UTC. The STI elevation was decreased while the STI strength was
increased for both middle and south of Cairo. The GTI was not detected at this
time at middle and south of Cairo. The results in the third column, 01:00 UJ'C, 1st
October, the STI began in destruction and the strength was decreased at the north
of Cairo while the strength didn't almost change at the middle and the south of
Cairo. The elevation of the STI was increased from about 400 meters at 20:00
UTC to 500 meters at 01:00 UTC at the north of Cairo. While the STI elevation
23
- - - - -- - - - -
Kandil et al.
(w)z
(w)z
(W)Z
twJz
.
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t, j
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'l
:r
l
(W)Z
24
Simulation of Atomospheric Temperature ...
was maintained at about 500 meters at the middle and the south of Cairo. The STI
thickness was increased at the three cross sections with average of 500 meters. The
GTI began in destruction with highest strength in the north of Cairo at 01:00 UTC.
The GTI was constructed at the middle and the south of Cairo with average
thickness of 20 meters and vegetated areas were present. Finally, the.STI and GTI
was completely destructed by 07:00 UTC at the three cross sections. In brief, the
STI has a strong strength, lower elevation and smaller thickness in construction
time compared to destruction time at the flat vegetated areas. The STI has weak
strength and higher elevation in construction time compared to the destruction at
complex urban areas. The GTI has stronger strength, larger thickness in
destruction time compared to construction time for flat vegetated areas.
Three longitudinal cross sections are considered. The longitudes of the cross
sections passing through West Cairo, Middle Cairo and East Cairo are 30.90,
31.25 and 31.383, East respectively.
At the west of Cairo, the terrain is simple and the vegetation coverage expands
from 30.26° to 30.43° north while in the east of Cairo, the terrain is more
complicated compared to the west of Cairo and the vegetation coverage expands
from 30.13° to 30.43° north. At the Middle of Cairo, the terrain is almost flat and
the ground is vegetated across the section except in the region from 29.95° to
30.125° north which represents the urban areas in the Cairo city as shown in
Figure (7).
l
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k
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]'d iddle Cau(>
C 1u\ >
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Figure 7: Longitudinal cross sections locations for the Greater Cairo.
25
I
L,._~~~
Kandil et al.
The temperature gradient contours of the three longitudinal sections are shown
in Figure (8) where the results of each section are shown in one column with
four frames. As shown in Figure (8), a GTI was detected at the three cross
sections at 17:00 UTC. It covered a limited vegetated area at the west and the
east of Cairo. Its thickness was about 10 meters (the first two vertical grid
levels) at the three cross sections. The average GTI strength was 0.015 deg.m-1.
The STI was not detected at this time.
At 20:00 UTC, the STI was detected and covered the whole cross section at the
west and east of Cairo and it covered about 75% of the middle of Cairo cross
section. The STI average strength at the west and east of Cairo was larger than
the middle of Cairo. The elevation of the STI was 500 meters at the three cross
sections. The STI average thickness was 200 meters at the three cross sections.
The GTI was detected at middle and east of Cairo at 20:00 UTC. At the middle
section, the STI matched the STI at 300 meters while the thickness of the GSI
was 70 meters at the east of the Cairo. The GTI coverage at the middle of Cairo
was largest coverage where vegetation coverage is high. At the first of October,
2004, 01:00 UTC, the STI covered the whole three cross sections. The STI
strength was higher at the west and east of Cairo than the middle of Cairo. The
maximum thickness was obtained at the west of Cairo with average of 500
meters. The average thickness was 300 meters at the middle and east of Cairo
cross sections. The STI elevation was 300 meters at the three cross sections.
l
\V~st Cni.ro
North
l
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~-~ 4 ¥1 ~ \ ~M
r·-·----·~
E
Figure 8: Longitudinal cross section for different locations at Greater Cairo.
26
Simulation of Atomospheric Temperature ...
The GTI was detected in the three cross sections and its maximum strength was
close to the ground surface. The GTI covered the vegetated areas at the south and
north longitudinal cross section at the middle of Cairo while the urban areas were
not covered by GTI. The vegetated areas at the northern east and west of Cairo
were covered by GTI. At 07:00 UTC, the STI began in destruction at the three
cross sections while the GTI was totally destructed. The STI was decreased at the
three cross sections and the elevation was increased from 300 meters to 600
meters.
At 08:00, the STI was totally destructed. The vertical temperature profiles at
Cairo International Airport are presented in Figure (9). Referring to figure 9, at
the start of simulation, the negative laps e rate is sustained until 16:00 UTC. By
18:00 UTC, the formation of an inversion layer begins at 500-m above the ground
level. The thickness and strength of the inversion layer was continuously
changing during the simulation which agrees with the results in Figures (6) and
(8). After sunrise the inversion layer started to break up. By 10:00 UTC (12:00
CLT) this layer totally disappeared.
Vertical T ompvraturv Profile
Vertlcel Temperature Profile
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Profli~
Vertical TumpuraturQ Promo
Vurtlclll Tvmpvrature
Vertlesl Temperature Promo
vatt!CAJ TamporahJtA Protuo
Figure 9 : Vertical temperature profiles at Cairo International Airport
27
Kandil et al.
CONCLUSIONS
-The MM5 model coupled with NOAH land surface model was
configured and optimized to simulate the temperature inversion over the
Greater Cairo region in Egypt. The model was optimized to get accurate
results for the high horizontal resolution of 1 km used in the Cairo
domain. The following conclusions are drawn from the results of
temperature inversion simulation:
- The thickness and strength of the STI increase in complex terrains
while its elevation decreases.
- The construction of the STI begins from higher elevation and descends
to reach its maximum strength and minimum elevation. At the
destruction time, the strength decreases and the elevation increases. The
maximum strength is related to the maximum elevation of the complex
terrain area.
- The GTI covers the vegetated areas with the minimum elevation very
close to the ground. The GTI thickness and strength at vegetated areas
are larger than that in the urban areas.
- The obtained results match the real observations and help in explaining
the physics of the temperature inversion phenomenon. Simulating more
days requires extensive computational resources.
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(Received 22 March 2006)
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