climate
Article
Statistical-Synoptic Analysis of the Atmosphere
Thickness Pattern of Iran’s Pervasive Frosts
Iman Rousta 1 , Mehdi Doostkamian 2 , Esmaeil Haghighi 3, * and Bahare Mirzakhani 4
1
2
3
4
*
Climatology, Department of Geography, Yazd University, Yazd 8915818411, Iran; irousta@yazd.ac.ir
Climatology, Department of Geography, Zanjan University, Zanjan 3879145371, Iran; s.mehdi67@gmail.com
Climatology, Department of Geography, Tabriz University, Tabriz 5166616471, Iran
Geomorphology, Department of Humanities, Mohaghegh Ardabili University, Ardabil 5519911367, Iran;
bahare.mirzakhani@gmail.com
Correspondence: es_haghighi@ut.ac.ir; Tel.: +98-91-7190-2098
Academic Editor: Yang Zhang
Received: 18 July 2016; Accepted: 22 August 2016; Published: 26 August 2016
Abstract: The present study aimed at analyzing the synoptic pattern of atmospheric thickness of
winter pervasive frosts in Iran. To this end, the data related to the daily minimum temperature
of a 50-year period (1961–2010) were gathered from 451 synoptic and climatology stations.
Then, the instances in which the temperature was below 0 ◦ C for at least two consecutive days
and this phenomenon covered at least 50% of the entirety of Iran were selected. Subsequently,
the atmosphere thickness pattern was extracted for these days, with the representative day being
identified and analyzed through cluster analysis. The results showed that the Siberian high
pressure plays a significant role in the occurrence of pervasive frosts in Iran. In some other cases,
the northeast–southwest direction of this pattern leads to its combination with the East Europe high
pressure, causing widespread frosts in Iran. Furthermore, the interaction between counter clockwise
currents in this system and the clockwise currents in the Azores high pressure tongue directs cold
weather from northern parts of Europe toward Iran. The formation of blocking systems leads to
the stagnation of cold weather over Iran, a phenomenon that results in significant reduction of
temperature and severe frosts in these areas. In addition, the omega pattern (the fifth pattern) and
Deep Eastern European trough and polar low pressure pattern (the fourth pattern) were the most
dominant and severe frost patterns in Iran respectively.
Keywords: frost; synoptic pattern; atmosphere thickness; Iran
1. Introduction
Changes in the frequency and intensity of climatic events are an indicator of climate change.
Due to their severity and sudden occurrence, extreme frosts have a profound effect on ecosystems and
human societies. They are the result of certain atmospheric conditions and atmospheric circulation [1].
Climatic zoning is often performed based on climatic variables. By so doing, the role of all climatic
variables is taken into account in determining borders between various areas [2]. In studies related
to anomalies of climate variables in each area, the behavior of these variables is investigated in the
light of their long-term average. The values that are smaller or bigger than the long-term average, are,
respectively, regarded as negative and positive anomalies [3]. Numerous studies of synoptic analysis
of East Asian cold waves have indicated that the dominant pattern in these areas is the Siberian
high pressure [4,5]. Many researchers have intended to identify anomaly patterns [6–8]. Some others
have investigated spatial-temporal anomalies of climate variables [9–11]. Lau et al. (2006: 402–411)
have studied circulation patterns that lead to negative temperature anomalies, with the results
demonstrating a significant relationship between sea surface temperature anomalies along the Atlantic
Climate 2016, 4, 41; doi:10.3390/cli4030041
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Climate 2016, 4, 41
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and South Pacific, on the one hand, and the occurrence of extreme temperatures, on the other [12].
Furthermore, Prieto et al. [13,14], who studied extreme winter temperatures, and Guirguis et al. [15],
who investigated the occurrence of wintry heat and cold waves, showed that North Atlantic Oscillation
(NAO) influences the occurrence of cold waves. Pezza & Ambrizzi [16] have also conducted some
studies in the realm of synoptic-dynamic meteorology. In a study in Iran, Shahbaiye Kotanaie [17]
used cluster analysis on the matrix of sea level pressure data of cold days to come up with the
synoptic analysis of wintry cold waves, with the results yielding five influential atmospheric patterns.
The researcher also showed that the formation of cold waves is simultaneous with positive anomalies
of sea level pressure and negative anomalies of the height of 55 hPa across the country. Moreover,
the researcher concluded that the patterns of atmospheric middle level have a considerable effect
on the formation and continuation of cold waves. Thus, the strongest, most widespread, and most
consistent cold wintry waves are formed when blocking systems are located on Eastern Europe and
their eastern troughs are positioned over Iran. Akbari& Masoodian [18] studied the role of macro-scale
pressure anomalies in Iran’s temperatures. Mohammadi [3], on the other hand, concentrated on
identifying spatial and temporal anomalies of different climate variables of Iran. Analysis of sea level
pressure anomalies on days of extreme cold indicated that the most extreme and pervasive frosts
of Iran are simultaneous with four patterns of sea level pressure anomalies [19]. Some researchers
have demonstrated that severe frosts and extreme temperatures are influenced by thermal advection
patterns [20–22]. Some of these studies have adopted synoptic-statistical analysis [23] using the index
of normalized temperature deviation [21]. Others have adopted cluster analysis [24,25] using the Ward
method [1].
Pervasive frosts occur as a result of pouring cold air from higher latitudes. In such a situation,
since air mass density goes up, thickness of the atmosphere declines. Thus, in the current study,
attempts were made to investigate Iran’s frosts by concentrating on the effect of atmosphere thickness
(which is itself influenced by the increase/decrease of air mass density). Due to frosts, Iran incurs
heavy financial losses each year in agriculture and animal husbandry. Frosts impose limitations on
agriculture. They also play an important role constructing roads, dams, and bridges, hence affecting
industry and transportation. On the other hand, the occurrence of frosts in mountainous areas leads
to numerous problems such as traffic blocking and car crashes. Consequently, frosts are regarded as
an important climate risk and receive a lot of attention from climatologists.
2. Materials and Methods
The present study aimed at synoptic analysis atmosphere thickness patterns of Iran’s pervasive
frosts. To this end, two databases were used:
1.
Environmental data: This group of data was obtained through interpolation of values of daily
minimum temperatures registered in stations from 1961 to 2010. The data over these 50 years,
which were collected from 450 synoptic and climatology stations of Iran’s Meteorological
Organization (IRIMO), were sorted and interpolated (Figure 1). The data of this database have
a spatial resolution of 15 km × 15 km, which have been produced in the form of Lambert
Conformal Conic Projection, and arranged in the form of a 7187 × 18262 matrix with an S makeup
(time in rows and place in columns). After collecting the data, the next step was identifying
frosts in each of the cells. In the majority of climate studies, an important part of the research is
defining the studied variable because it will influence other research steps. Many researchers
have considered temperatures below 0 ◦ C as the cut-off criterion for identifying frosts [26,27].
In the current study, a condition should meet the following three criteria to be considered as
an example of frost in Iran:
•
•
•
The temperature in the particular day should be less than 0 ◦ C.
This low temperature should last for at least two consecutive days.
The temperature should have a minimum coverage of 50% (with the assumption of
spatial continuity).
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Based on the first criterion, only very low temperatures were taken into account for each of
Based
on the
first criterion,
very low
were taken
into
for eachFurthermore,
of the
the 7187 cells,
hence
observing
the only
relativity
of temperatures
frost for different
areas
ofaccount
the country.
7187
cells,
hence
observing
the
relativity
of
frost
for
different
areas
of
the
country.
Furthermore,
the second criterion (i.e., continuity of low temperature for at least two consecutive days)the
makes it
second criterion (i.e., continuity of low temperature for at least two consecutive days) makes it
possible to distinguish systematic frosts from local ones that are caused by environmental factors
possible to distinguish systematic frosts from local ones that are caused by environmental factors
(e.g., height)
or clear
which
leads
totoradiation
cooling.
(e.g., height)
or weather,
clear weather,
which
leads
radiation cooling.
Figure 1. Distribution pattern of the studied stations.
Figure 1. Distribution pattern of the studied stations.
2
2.
Weather data: This part of the data, which was used for calculating atmosphere thickness,
Weather
data: This
of the data,
which
waswere
usedobtained
for calculating
atmosphere
thickness,
consisted
of hPapart
geopotential
height
data and
from National
Centers for
Environmental
Prediction/National
Atmospheric
Researchfrom
(NCEP/NCAR).
consisted
of hPa geopotential
heightCenter
datafor
and
were obtained
National These
Centers for
data havePrediction/National
a spatial resolution of Center
2.5 × 2.5for
degree
of arc. Considering
the research topic, These
the
Environmental
Atmospheric
Research (NCEP/NCAR).
data
researchers intended to include all of the systems that are effective in the formation and
have a spatial resolution of 2.5 × 2.5 degree of arc. Considering the research topic, the researchers
continuation of frost waves in Iran. Therefore, the study covered the atmospheric system ranging
intended
to include all of the systems that are effective in the formation and continuation of frost
from −10 degrees west longitude to 100 degrees east longitude and 10 to 70 degrees north
waves latitude.
in Iran. Another
Therefore,
theofstudy
covered
the
systemis ranging
10 degrees
group
maps that
is used
inatmospheric
synoptic climatology
thickness from
maps.−
They
west longitude
to 100 degrees
east longitude
andranges
10 to from
70 degrees
north
Another
group of
indicate atmosphere
thickness,
which usually
500 to 100
hPa.latitude.
This is the
thickness
that
is
considered
for
the
entire
atmosphere.
In
other
words,
studying
the
thickness
between
maps that is used in synoptic climatology is thickness maps. They indicate atmosphere thickness,
these tworanges
layers (500
and
1000
hPa) hPa.
is representative
the statusthat
of allislayers.
The following
which usually
from
500
to 100
This is theofthickness
considered
for the entire
equation, which is known as hypsometric equation, is used to calculate atmosphere thickness:
atmosphere. In other words, studying the thickness between these two layers (500 and 1000 hPa)
(1)
= following
− equation, which is known as hypsometric
is representative of the status of all layers. The
equation,
usedused
to calculate
atmosphere
thickness:
Thisisstudy
the environment
to circulation
approach to identify and analyze the patterns
that are effective in the formation and continuation of frosts in Iran.
After identifying atmosphere
thickness, =
cluster
was 100
utilized to come up with the
Thickenss
HGTanalysis
(1)
500 − HGT
thickness pattern of Iran’s frosts. In the next step, cluster analysis was conducted to categorize the
thickness pattern data and identify the representative days. Cluster analysis is a data analysis
This
study used
the environment
circulation
to identify
and analyze
the patterns
that
procedure
through
which data aretoclassified
intoapproach
groups according
to predefined
features.
This
are effective
in
the
formation
and
continuation
of
frosts
in
Iran.
procedure is used to reduce complexity by categorizing similar data in a single group. Thus, the
minimum
and maximum
variance
can be, respectively,
observed
within to
andcome
between
groupthe
data.
After
identifying
atmosphere
thickness,
cluster analysis
was in
utilized
up with
thickness
pattern of Iran’s frosts. In the next step, cluster analysis was conducted to categorize the thickness
pattern data and identify the representative days. Cluster analysis is a data analysis procedure
through which data are classified into groups according to predefined features. This procedure is
used to reduce complexity by categorizing similar data in a single group. Thus, the minimum and
maximum variance can be, respectively, observed in within and between group data. There are
different methods for calculating the distance between two points. One of the most popular methods
is the Euclidean distance.
Climate 2016, 4, 41
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There are different methods for calculating the distance between two points. One of the most popular
The Lund correlation method was used to identify the representative days for each of the
methods is the Euclidean distance.
atmosphere thickness clusters. That is, the day with the highest degree of similarity to other days
The Lund correlation method was used to identify the representative days for each of the
of each
cluster was
usedclusters.
as the representative
cluster.
Correlation
coefficient
shows
atmosphere
thickness
That is, the day day
with of
thethat
highest
degree
of similarity
to other days
of the
degree
of
similarity
between
the
patterns
in
two
different
maps.
Indices
of
more
than
0.5
are
indicative
each cluster was used as the representative day of that cluster. Correlation coefficient shows the
of a strong
Therefore,
in the current
study, the
dayIndices
that had
highest
correlation
degree correlation
of similarity[7].
between
the patterns
in two different
maps.
of the
more
than 0.5
are
coefficient
withofother
days
of a cluster
selected
as the
representative
day.that had the highest
indicative
a strong
correlation
[7]. was
Therefore,
in the
current
study, the day
correlation coefficient with other days of a cluster was selected as the representative day.
3. Results and Discussion
3. Results and Discussion
Figure 2 illustrates the dendrogram obtained as a result of conducting cluster analysis on the
Figure
2 illustrates
the dendrogram
obtained
a result
of conducting
cluster analysis
on the
atmosphere
thickness
of Iran’s
frost events.
In thisasfigure,
atmosphere
thickness
maps were
drawn
atmosphere thickness of Iran’s frost events. In this figure, atmosphere thickness maps were drawn
for the representative days of different groups (two to five groups). Then, the maps of representative
for the representative days of different groups (two to five groups). Then, the maps of representative
days of different groups were compared and, through trial and error, the appropriate place for cutting
days of different groups were compared and, through trial and error, the appropriate place for cutting
the map
and selecting suitable groups for extracting patterns were determined. Based on the analysis
the map and selecting suitable groups for extracting patterns were determined. Based on the analysis
outcomes,
fivefive
groups
were
identified.
the number
numberofofdetected
detected
frost
events
and the
outcomes,
groups
were
identified.In
Intotal,
total, the
frost
events
waswas
1622,1622,
and the
date date
and and
features
of the
representative
groupare
aredisplayed
displayed
Table
features
of the
representativedays
daysof
of each
each group
in in
Table
1. 1.
Figure
2. The
dendrogram
obtained
conductinggroup
group
analysis
atmosphere
thickness.
Figure
2. The
dendrogram
obtainedthrough
through conducting
analysis
on on
atmosphere
thickness.
Table
Featuresofofthe
the representative
representative days
the
five
groups.
Table
1. 1.
Features
daysforfor
the
five
groups.
The
The Date of
TheCoverage
Coverage
The
of
of the
the Representative
Frequency
Frequency
Representative Representative
Day (%)
The WholeWhole The Date of
thethe
Pattern Pattern
Frost Event (%)
Representative Day
Siberian
high-pressure
Siberian highand European
pressure and
high-pressure
Frost
Event (%)
20.9
1 January 2007
20.9
European high-
Deep trough
pressure
pattern of Eastern
11.09
EuropeDeep
and trough pattern
of Eastern
Europe
Sudanese
low
andpattern
Sudanese low
Dual-core
of Siberian
10.04
high-pressure
Day
1 January 2007
13 November 1972
11.09
13 November
1972
Day (%)
75.93
75.93
57.84
57.84
339
339
180
180
Average
Average
Temperature
AverageAverage
Temperature
of the
Temperature
of the
Temperature
Representative Day
of the Group
Representative of the Group
Day
−1.73
−5.05
−1.73
−5.05
−1.07
−1.07
−4.20
−4.20
4 January 1986
63.36
163
−1.45
−0.93
Deep Eastern
European trough
and polar low
pressure pattern
25.77
22 February 1961
79.95
418
−2.06
0.51
Omega pattern
32.18
22 December 1960
59.81
522
−2.30
−3.30
pressure
Deep Eastern
European trough
and polar low
pressure pattern
Climate
2016,
4, 41
Omega
pattern
25.77
22 February
1961
79.95
418
−2.06
0.51
32.18
22 December
1960
59.81
522
−2.30
−3.305 of 19
High-Pressure
3.1. The First Pattern: Siberian High-Pressure and European High-Pressure
Figure 33illustrates
illustratesthethe
atmosphere
thickness
pattern
forfirst
thegroup.
first group.
This (i.e.,
pattern
(i.e.,
Figure
atmosphere
thickness
pattern
for the
This pattern
Siberian
Siberian high-pressure
and European
high-pressure)
covers
20.9% frosts.
of Iran’s
As the
figure
high-pressure
and European
high-pressure)
covers 20.9%
of Iran’s
As frosts.
the figure
indicates,
indicates,
in
this
pattern,
the
atmosphere
thickness
system
of
Siberian
high-pressure
stretches
from
in this pattern, the atmosphere thickness system of Siberian high-pressure stretches from northeast
to
northeast to
Iran.
Thus,ofthe
tonguehigh-pressure,
of Siberian high-pressure,
which hasofa
southwest
insouthwest
most areasinofmost
Iran.areas
Thus,ofthe
tongue
Siberian
which has a thickness
thickness
of 5250almost
meters,
almost
to the
of leads
Iran. This
tongue
leads
to the
of cold
5250
m, spreads
tospreads
the center
of Iran.
Thiscenter
tongue
to the
pouring
of cold
airpouring
from northern
air
from
northern
latitudes.
As
the
thickness
Siberian
high-pressure
tongue
increases,
the
thickness
latitudes. As the thickness Siberian high-pressure tongue increases, the thickness pattern of European
pattern of European
with
contourinfluences
of 5300 meters,
mainly influences
southern
half
low-pressure,
with alow-pressure,
contour of 5300
m,a mainly
the southern
half of thethe
country.
Many
of the country.
Many
researchers
believe
that
Lake
Baikal is area
the most
important
area
for Siberian cold
researchers
believe
that
Lake Baikal
is the
most
important
for Siberian
cold
high-pressure
[28].
high-pressure
[28]. However,
thickness
plays
a significant
role in As
atmospheric
However,
atmosphere
thickness atmosphere
plays a significant
role in
atmospheric
phenomena.
shown by
phenomena.
As shown
by Alijani,
thickness
maps
can be aprecipitation
good guide type,
for estimating
precipitation
Alijani,
thickness
maps can
be a good
guide for
estimating
the front location,
and
type,
the
front
location,
and
many
other
phenomena
[27].
many other phenomena [27].
anomalies
and thickness
(in meters)
for the representative
days of the first
Figure 3.3.Atmosphere
Atmosphere
anomalies
and thickness
(in meters)
for the representative
dayspattern.
of the
first pattern.
In cold weather, air is contracted and atmosphere thickness reduces, whereas, in hot weather,
atmosphere
thicknessair
increases.
Therefore,
it is observed
that negative
of hot
atmosphere
In cold weather,
is contracted
and atmosphere
thickness
reduces,anomalies
whereas, in
weather,
thickness
have
stretched
all
over
Iran.
The
tongue
of
these
anomalies
reaches
−300
meters
in some
atmosphere thickness increases. Therefore, it is observed that negative anomalies of atmosphere
areas
of
Russia.
The
thickness
of
this
tongue
declines
in
lower
latitudes
and
reaches
−100
meters
in
thickness have stretched all over Iran. The tongue of these anomalies reaches −300 m in some areas of
central areas
of Iran. The
largest
intensity
of negative
(between
−200
andm−150
meters)
can
Russia.
The thickness
of this
tongue
declines
in loweranomalies
latitudes and
reaches
−100
in central
areas
be
observed
in
the
northern
part
of
Iran.
In
addition
to
the
area
from
which
the
Siberian
high-pressure
of Iran. The largest intensity of negative anomalies (between −200 and −150 m) can be observed in
enters
Iran’s part
atmosphere,
local
and regional
factors,
accumulation
topographiesenters
and higher
the
northern
of Iran. In
addition
to the area
from like
which
the Siberianof
high-pressure
Iran’s
latitudes, provide
a suitable
condition
for intensifying
anomalies.
only
in a small
area
atmosphere,
local and
regional
factors, like
accumulationnegative
of topographies
andThus,
higher
latitudes,
provide
of
southeast
of
Iran
have
the
atmosphere
thickness
anomalies
reached
50
meters
on
this
day.
a suitable condition for intensifying negative anomalies. Thus, only in a small area of southeast of
Northwestern
areas, whichthickness
are located
in the western
of on
thisthis
pattern,
are largely influenced
by it.
Iran
have the atmosphere
anomalies
reachedpart
50 m
day. Northwestern
areas, which
On this
day,in
the
average
temperature
the northwestern
reached −12
°COn
(Figure
4B). the
At the
same
are
located
the
western
part of thisofpattern,
are largelyarea
influenced
by it.
this day,
average
temperature of the northwestern area reached −12 ◦ C (Figure 4B). At the same time, atmosphere
thickness has reduced from the east to the west causing a discontinuity. This is the areas where the
abovementioned air mass collides with cold weather coming from higher latitudes (northern Russia)
and significantly decreases temperature in this area. Based on the pattern of atmosphere thickness
lines, masses of cold air have entered Iran from northeast and have moved toward southwest. These
masses come from northern parts of the country and Siberia and have caused cold weather in most
Climate 2016, 4, 41
6 of 19
parts of Iran, hence the reduction of thickness in northern latitudes. Figure 4 displays some statistical
features for the first group and its representative day. Figure 4A,B, shows the spatial distribution of
mean and coefficients of variation for the first group and its representative day. As the figure illustrates,
in the first group, the highest coefficient of spatial variation for Iran’s frosts belong to a strip along the
Zagros mountain ranges. In the central part of Iran, the coefficient of variation is more than 1500%,
which indicates high variability of frosts in this area. On the other hand, the lowest registered average
temperature is −8 ◦ C, which was registered for the central Zagros and northwest of Iran. In the first
group, the majority area of the country (around 41%) has an average temperature ranging from −7.69
to −2.17 ◦ C (Table 2). For the representative day, however, almost 50% of the country’s area has
experienced a temperature between −11.11 and −2.31 ◦ C, which is the lowest recorded temperature.
Thus, in the representative day, the country has experienced very low temperatures to the extent that
about 6% of Iran’s area (which is mainly located in northern part of the country) has experienced
temperatures lower than −20 ◦ C (Table 2). Figure 4C shows the spatial distribution of frosts’ anomalies
and center of masses for the first group. The compact nature of the center of masses shows that frosts
follow a regular pattern, while the dispersion of this center indicates that frosts follow an irregular
pattern. The center of masses for the first group shows that Iran’s frost distribution which is influenced
by the thickness patterns of Siberian high-pressure and European High-pressure follows an irregular
distribution. In the first group, 47.2% of the country’s area has negative anomalies (Table 2). However,
on the representative day, more than 55% of Iran’s area has negative anomalies (Table 2). In this first
group, the severest anomalies of Iran’s frosts happen in the form of a strip along the Zagros mountain
ranges and north and northwest topographies. Figure 4D illustrates the distribution of frosts in the
first group. Accordingly, in the first group, the largest area of the country has had a frequency of more
than 300 days. In contrast, the southern half of the country does not have any frost. Spatial distribution
of frosts in the first group indicates that, in almost all parts of the country, frost has experienced
a downward trend (Figure 4E).
Table 2. Percentage of the covered area of different classes of average temperature, anomalies and
frequency of frosts for the first group.
Overall Temperature
of the First Group
Area (%)
Representative Day
Temperatures
Area (%)
−13.21 to −7.69
−2.17 to −7.69
3.34 to −2.17
8.87 to 3.34
14.4 to 8.87
10.8
41.1
30.5
13.1
4.5
−27.28 to −19.91
−19.91 to −11.11
−11.1 to −2.31
−2.31 to 6.51
6.51 to 15.32
5.3
11.8
48.6
28.8
5.5
The Frequency
of Frost Days
Area (%)
Representative Day
Anomaly
Area (%)
0 to 69
69 to 139
139 to 209
209 to 279
279 to up
20.5
5.5
8.8
14.3
50.9
Negative anomalies
Positive anomalies
Anomalies the whole group
Negative anomalies
Positive anomalies
56.4
43.6
Area (in percentage)
47.2
52.8
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Figure
The
firstpattern:
pattern:(A)
(A)Spatial
Spatial distribution
distribution of
ofof
variation
Figure
4. 4.
The
first
of temperature
temperatureaverage
averageand
andcoefficient
coefficient
variation
for
the
whole
group;
(B)
spatial
distribution
of
temperature
average
and
coefficient
of
variation
forfor
for the whole group; (B) spatial distribution of temperature average and coefficient of variation
the
representative
day;
(C)
anomalies
and
center
of
masses
for
the
whole
group;
(D)
anomalies
for
the
the representative day; (C) anomalies and center of masses for the whole group; (D) anomalies for the
representative day; (E) frequency of frosts for the whole group; and (F) spatial distribution of the
representative day; (E) frequency of frosts for the whole group; and (F) spatial distribution of the trend
trend of Iran’s frosts for the whole group.
of Iran’s frosts for the whole group.
3.2. The Second Pattern: Deep trough Pattern of Eastern Europe and Sudanese Low Pressure
3.2. The Second Pattern: Deep Trough Pattern of Eastern Europe and Sudanese Low Pressure
This pattern encompasses 11.03% of Iran’s frosts. Based on the thickness map (Figure 5), a high
This pattern
11.03%
ofmeters,
Iran’s frosts.
Based
on theEurope.
thickness
map (Figure
5), a high
pressure
center, encompasses
with a thickness
of 5250
is located
on central
In addition,
the Siberian
pressure
center, with
a thickness
of of
5250
m,meters,
is located
on central
Europe. InAaddition,
the Siberian
high
high pressure,
which
has a height
4950
is located
over Mongolia.
weak tongue
of Siberian
pressure,
which
has
a
height
of
4950
m,
is
located
over
Mongolia.
A
weak
tongue
of
Siberian
high
high pressure has stretched on Iran. However, in this pattern, Iran’s frosts are mainly influenced by
pressure
has
stretched
onofIran.
However,
this
pattern,low
Iran’s
frosts are mainly influenced by the
the deep
trough
pattern
Eastern
Europein
and
Sudanese
pressure.
deep trough pattern of Eastern Europe and Sudanese low pressure.
Climate 2016, 4, 41
Climate 2016, 4, 41
8 of 19
8 of 19
and
atmosphere
thickness
(in meters)
for the
day of day
the second
Figure 5.
5. Anomalies
Anomalies
and
atmosphere
thickness
(in meters)
forrepresentative
the representative
of the
second
pattern.pattern.
Because of
ofits
itslocation,
location,
Siberian
high
pressure
system
an insignificant
role pattern.
in this
Because
thethe
Siberian
high
pressure
system
playsplays
an insignificant
role in this
pattern. However,
the European
low pressure
is located
polarweather
cold weather
However,
the way the
theway
European
low pressure
system system
is located
directsdirects
polar cold
from
from
northwest
toward
southeast,
hence
the
movement
of
this
cold
weather
toward
Iran. These
northwest toward southeast, hence the movement of this cold weather toward Iran. These factors
have
factors
have
resulted
in
the
movement
of
cold
weather
of
northern
latitudes
toward
Iran.
resulted in the movement of cold weather of northern latitudes toward Iran. Furthermore, the center
of
Furthermore,
the
center
of
these
anomalies
(with
a
thickness
of
−200
meters)
is
located
in
northern
these anomalies (with a thickness of −200 m) is located in northern latitudes of the country, especially
latitudes
of theSea
country,
on part
the Caspian
Sea and
the northeastern
part
Iran.
Many
on
the Caspian
and theespecially
northeastern
of Iran. Many
researchers
believe that
the of
main
origin
of
researchers
believe
that
the
main
origin
of
northeastern
frosts
is
advection.
In
the
meantime,
the
northeastern frosts is advection. In the meantime, the Siberian and European migratory high pressure
Siberian play
and an
European
migratory
high
pressure
systems
an important
role;cold
that weather
is, whenenters
these
systems
important
role; that
is, when
these
systemsplay
dominate
Iran’s area,
systems
dominate
Iran’s
area,
cold
weather
enters
the
country
from
west,
northwest,
and
northeast,
the country from west, northwest, and northeast, causing cold weather in these areas [1,27,29].
causing
cold6 weather
insome
thesespatial
areas [1,27,29].
Figure
illustrates
features for the representative day and the whole second group.
Figure
6
illustrates
some
spatial
featuresof
for
the representative
and the
whole
second
group.
Accordingly, when the deep trough patterns
Eastern
Europe and day
Sudanese
low
pressure
dominate
Accordingly,
when
deepoftrough
patterns
of Eastern
Sudanese
low
pressure
dominate
◦ C and
◦ C during
the
country, in
mostthe
areas
Iran, the
temperature
is Europe
betweenand
−2.31
−11.5
the
the
country,
in
most
areas
of
Iran,
the
temperature
is
between
−2.31
°C
and
−11.5
°C
during
the
representative day. This mainly includes latitudes above 30 degrees (Table 3). On the contrary, for the
representative
day.
This
mainly
includes
latitudes
above
30
degrees
(Table
3).
On
the
contrary,
for
◦
◦
third group, a large area of the country has a temperature between −5.93 C and −0.76 C. In this
the thirdabout
group,57%
a large
area
of the country
has a temperature
between
−5.93
°C andthan
−0.76
°C.
In this
pattern,
of the
country’s
area experience
a temperature
that
is lower
the
average
pattern,
about
57%
of
the
country’s
area
experience
a
temperature
that
is
lower
than
the
average
on the representative day (Figure 6A). At the same time, in southern areas of the country, due on
to
the representative
day (Figure
At theissame
time, in southern
areas of
country,
to lack of
of
lack
of frosts, the coefficient
of6A).
variation
insignificant
(Figure 6A,B).
Inthe
general,
thedue
frequency
frosts,events
the coefficient
of variation
is insignificant
(Figure
6A,B).
In general,
the frequency
of frost
frost
is insignificant
in southern
areas of Iran
because
of the
role of dynamic
high pressure
events
is
insignificant
in
southern
areas
of
Iran
because
of
the
role
of
dynamic
high
pressure
system
system [27,30,31], low latitude, and high radiation. The highest frost frequencies belong to high
areas
[27,30,31],
low
latitude,
and
high
radiation.
The
highest
frost
frequencies
belong
to
high
areas
of
of the country, especially Tehran, Tabriz, Adrebil, Hamedan, Zanjan, and Sharekord. Thus, it canthe
be
country, especially
Tehran, Tabriz,
Hamedan,
Zanjan,
Sharekord.
Thus,Asit acan
be
concluded
that the frequency
of frostsAdrebil,
is influenced
by height
and and
latitude
(Figure 6D).
result,
concluded
that
the
frequency
of
frosts
is
influenced
by
height
and
latitude
(Figure
6D).
As
a
result,
high areas of the country, like Sahand and Damavand, have the highest frequency of frost occurrence.
highareas
areas of
of the
and Damavand,
the highest
frequency
frostmid
occurrence.
The
the country,
country like
thatSahand
are mainly
close to thehave
Zagros
mountain
ranges of
have
to high
The
areas
of
the
country
that
are
mainly
close
to
the
Zagros
mountain
ranges
have
mid
to
frost
frost frequencies (Figure 6D). Hejazizadeh and Naserzadeh, for example, studied frosts inhigh
Lorestan
frequencies
(Figure
6D).
Hejazizadeh
and
Naserzadeh,
for
example,
studied
frosts
in
Lorestan
Province and concluded that height is the main factor determining the frequency of frost occurrence
Province
and [32].
concluded
that some
heightresearchers
is the mainbelieve
factor determining
the frequency
of frost
in
this region
However,
that the majority
of Iran’s frosts
areoccurrence
caused by
in
this
region
[32].
However,
some
researchers
believe
that
the
majority
of
Iran’s
frosts
are caused by
advection [33].
advection [33].
Climate 2016, 4, 41
9 of 19
Climate 2016, 4, 41
9 of 19
Figure
pattern:(A)
Spatial
distribution
of temperature
averageaverage
and coefficient
of variation
Figure 6.6.The
Thesecond
second
pattern:(A)
Spatial
distribution
of temperature
and coefficient
of
for
the whole
group;
(B) spatial
of temperature
average and average
coefficient
of coefficient
variation for
variation
for the
whole
group; distribution
(B) spatial distribution
of temperature
and
of
the
representative
day; (C) anomalies
of masses
for theofwhole
group;
(D) whole
anomalies
for (D)
the
variation
for the representative
day; and
(C) center
anomalies
and center
masses
for the
group;
representative
(E) frequency ofday;
frosts
the wholeofgroup;
thespatial
trend
anomalies for day;
the representative
(E)for
frequency
frostsand
for (F)
thespatial
wholedistribution
group; andof(F)
of
Iran’s frosts
whole
group.
distribution
of for
thethe
trend
of Iran’s
frosts for the whole group.
Climate 2016, 4, 41
10 of 19
Table 3. Percentage of the covered area of different classes of average temperature, anomalies and
frequency
Climate
2016, 4, of
41 frosts for the second group.
10 of 19
Day
Temperature
Table 3.Overall
Percentage
of the covered area of different Representative
classes of average
temperature, anomalies and
Area (%)
Area (%)
Temperatures
ofof
the
Second
Group
frequency
frosts
for the
second group.
−5.93 to −11.13
Overall Temperature
of the
−0.76 to −5.93
Second Group
4.46 to −0.76
−5.93 to −11.13
9.66 to 4.46
−0.76 to −5.93
14.87 to 9.66
4.46 to −0.76
ThetoFrequency
9.66
4.46
of Frost
Days
14.87
to 9.66
12.3
Area
51.4 (%)
21.1
12.3
11.1
51.4
4.1
21.1
Area11.1
(%)
4.1
The Frequency36oftoFrost
0 Days
36 72
to 0to 36
to 72
72 110
to 36
to 110
110145
to 72
To up
145145
to 110
Area
21.1 (%)
6.1
21.1
86.1
18.58
46.3
18.5
145 To up
46.3
−19.19
to −28.72 Day
Representative
−11.8 to
−19.19
Temperatures
−2.31 to −11.8
−19.19 to −28.72
6.50 to −2.31
−11.8 to −19.19
15.32 to 6.50
−2.31 to −11.8
Representative
6.50 to Day
−2.31
Anomaly
15.32 to 6.50
5.3
11.8 Area (%)
48.6
5.3
28.8
11.8
5.5
48.6
Area (%) 28.8
5.5
Representative
Day Anomaly 57.9 Area (%)
Negative
anomalies
Positive
anomalies
42.1 57.9
Negative
anomalies
AnomaliesPositive
the entire
group
Area (%) 42.1
anomalies
Negative
anomalies
Anomalies
the entire group 60.4 Area (%)
Positive
anomalies
39.6 60.4
Negative
anomalies
Positive anomalies
6.39
3.3. The Third Pattern: Dual-Core Pattern of Siberian High-Pressure
3.3. The Third Pattern: Dual-Core Pattern of Siberian High-Pressure
The outstanding issue in this pattern is that the lines with the same degree of thickness gradually
move from
to Iran.
For
theisline
the thickness
of 5400
m is of
located
in western
parts
The Europe
outstanding
issue
inexample,
this pattern
thatwith
the lines
with the same
degree
thickness
gradually
move from
to Iran.
example,
line the
with
the line
thickness
meters
is northeastern
located in
of Europe
withEurope
a latitude
of 44 For
degrees
north,the
while
same
in Iranofis5400
located
in the
western
of Europe
with a latitude
44 degrees
north,
thepattern,
same line
in Iran is located
in
part
with aparts
latitude
of 38 degrees
north. ofThis
indicates
that,while
in this
conditions
are suitable
part
withweather
a latitude
of 38northern
degrees north.
Thistoindicates
that, in
pattern,
conditions
forthe
thenortheastern
advection of
cold
from
Europe
Iran (Figure
7).this
Cold
weather
centers
areare
suitable
foron
the
advection
cold
fromSea
northern
Europe
to Iran (Figure
7).Iran
Coldhas
weather
that
located
the
eastern of
part
of weather
the Caspian
and the
northwestern
part of
further
centers
that
are
located
on
the
eastern
part
of
the
Caspian
Sea
and
the
northwestern
part
of
Iran has
lowered temperature in these areas, hence they experience a colder weather compared to other
parts.
lowered
temperature
in temperature
these areas, hence
they experience
a colder
weather
compared
to
Forfurther
example,
in these
regions, the
has reached
−26 ◦ C (Figure
8A).
Therefore,
compared
For example,
in these
regions, theintemperature
reached −26
(Figure 8A).
to other
otherparts.
patterns,
the degree
of anomalies
atmospherehas
thickness
has°C
decreased
in Therefore,
this pattern,
compared to other patterns, the degree of anomalies in atmosphere thickness has decreased in this
reaching −100 to −200 m during the representative day. This shows a decline of −50 m compared to
pattern, reaching −100 to −200 meters during the representative day. This shows a decline of −50
the second group. This condition indicates that this group has warmer advections compared to other
meters compared to the second group. This condition indicates that this group has warmer
ones. However, on the same day, a large area in Europe experienced the advection of cold weather,
advections compared to other ones. However, on the same day, a large area in Europe experienced
an argument that is supported by the −200 m thickness anomalies. Based on this map, it can be
the advection of cold weather, an argument that is supported by the −200 meter thickness anomalies.
argued
that when the low pressure system is located in northern parts of Russia, the two high pressure
Based on this map, it can be argued that when the low pressure system is located in northern parts
systems
move
toward
lower
latitudes.
The interaction
between
clockwise
air currents
in the
of Russia,
the
two high
pressure
systems
move toward
lower counter
latitudes.
The interaction
between
low
pressure
system
and
clockwise
air
currents
in
the
tongue
of
Azores
high
pressure
system
draws
counter clockwise air currents in the low pressure system and clockwise air currents in the tongue of
cold
weather
northern
ofcold
Europe
toward
(Figure
7).of Europe toward Iran (Figure 7).
Azores
highfrom
pressure
systemparts
draws
weather
fromIran
northern
parts
Figure7.7. Anomalies
and
atmosphere
thickness
(in meters)
the representative
day of the thirdday
pattern.
Figure
Anomalies
and
atmosphere
thickness
(in for
meters)
for the representative
of the
third pattern.
Climate 2016, 4, 41
Climate 2016, 4, 41
11 of 19
11 of 19
Figure
8. The
third
pattern:
Spatialdistribution
distribution of
and
coefficient
of variation
Figure
8. The
third
pattern:
(A)(A)
Spatial
of temperature
temperatureaverage
average
and
coefficient
of variation
for the whole group; (B) spatial distribution of temperature average and coefficient of variation for
for the whole group; (B) spatial distribution of temperature average and coefficient of variation for
the representative day; (C) anomalies and center of masses for the whole group; (D) anomalies for the
the representative day; (C) anomalies and center of masses for the whole group; (D) anomalies for the
representative day; (E) frequency of frosts for the whole group; and (F) spatial distribution of the
representative day; (E) frequency of frosts for the whole group; and (F) spatial distribution of the trend
trend of Iran’s frosts for the whole group.
of Iran’s frosts for the whole group.
When this system is located over this area, air flow deviate from its direct route and change the
direction
westerniswinds
from
northern
partsair
of flow
Europe
toward
Iran,its
thus
the movement
cold the
When thisofsystem
located
over
this area,
deviate
from
direct
route and of
change
weather
of northern
latitudes
theparts
country.
When this
pattern
dominates
Iran,
the average
direction
of western
winds
from toward
northern
of Europe
toward
Iran,
thus the
movement
of cold
temperature of cold waves has a considerable increase in comparison with the previous two patterns.
weather of northern latitudes toward the country. When this pattern dominates Iran, the average
Nevertheless, the formation of this core, especially in the northern part of Iran, leads to recording
temperature of cold waves has a considerable increase in comparison with the previous two patterns.
temperatures between −10.73 °C and −17.06 °C. However, when this pattern dominates Iran, the
Nevertheless,
the
this
especially
in the
northern part
of Iran,
leads
recording
largest area
of formation
the country of
(45%
oncore,
average)
experience
a temperature
between
1.92 °C
and to
−4.40
°C
◦ C and −17.06 ◦ C. However, when this pattern dominates Iran,
temperatures
between
−
10.73
(Table 4). On the other hand, considering the whole group, the majority of the country’s area (over
the largest area of the country (45% on average) experience a temperature between 1.92 ◦ C and
−4.40 ◦ C (Table 4). On the other hand, considering the whole group, the majority of the country’s area
(over 68%) has a temperature between −8.045 ◦ C and 3.52 ◦ C (Table 4). The average temperature in
Climate 2016, 4, 41
12 of 19
this group (illustrated in Figure 8A) indicates that, in the northeastern part, temperature has reached
−2 ◦ C on average, which is not significantly different from the temperature pattern. Nonetheless,
compared to the first pattern (when the Siberian high pressure system is dominant), temperature has
increased in this area. By the same token, the northwestern part has had a 1 ◦ C increase compared to
the first pattern. However, on the representative day, temperature has increased by 2 ◦ C compared to
the whole group. As a result, in the northeastern part, temperature reaches −2 ◦ C, while, in the whole
group, the average temperature is −4 ◦ C (Figure 8A,B). Anomaly maps further support this argument;
that is, the negative anomaly of the representative day increase in comparison with that of the whole
group in the northern part of the country (Figure 8B,C). On the other hand, the frequency of frost
events in this group is in line with that of the other groups. More precisely, it is like a strip ranging
along the Zagros mountain ranges as well as some parts of northwest and northeast (Figure 8D). It is
thus concluded that, on average, in this group, 64.5% of the country’s area has negative anomaly
(Table 4).
Table 4. Percentage of the covered area of different classes of average temperature, anomalies and
frequency of frosts for the third group.
Overall Temperature
of the Third Group
Area (%)
Representative Day
Temperatures
Area (%)
−8.45 to −13.82
−2.26 to −8.45
3.52 to −2.26
9.30 to 3.52
15.9 to 9.30
11.3
37.1
33.5
13.4
4.7
−10.73 to −17.06
−4.40 to −10.73
1.92 to −4.40
8.2 to 1.92
14.59 to 8.2
5
21.3
45.3
20.7
7.7
The Frequency
of Frost Days
Area (%)
Representative Day
Anomaly
Area (%)
32 to 0
62 to 32
97 to 62
130 to 97
163 to 130
21.4
8.2
9.7
11.2
49.6
Negative anomalies
Positive anomalies
Anomalies the entire group
Negative anomalies
Positive anomalies
69.6
30.1
Area (%)
64.5
35.5
3.4. The Fourth Pattern: Deep Eastern European Trough and Polar Low Pressure Pattern
In this pattern of atmosphere thickness, a relatively deep trough, which has stretched from
north to south, can be observed in high latitudes. This trough is extended to the east of the Caspian
Sea. It represents the fall of cold weather from the latitude 70 degrees north toward the south of
Kazakhstan. On the north of the Caspian Sea, the thick curve is compacted causing temperature
gradient. This compactness is the cause of cold weather transfer from higher latitudes to lower ones
including the studied area. In addition, from Northern Europe, thin tongues with a thickness of
5330 m, which move from northwest toward southeast, move toward Iran, leading to the fall of cold
weather in this area. On this day, height anomalies are negative over this area and are between −60
and −20 m. All these conditions make it possible for cold weather of upper latitudes to create a high
trough over Iran, leading to stagnant air and severe cold weather. As a result, the majority area of the
country, especially the central part, experiences a temperature between −0.42 and −10.9 ◦ C (Figure 9).
Through conducting a synoptic and dynamic study of cold waves in tropical regions of South America,
Pezza and Ambrizzi concluded that external tropical cyclones play a significant role in the formation
of cold waves in these areas. They also found a relationship between cold waves in this region and
changes in the waves of upper atmosphere in eastern parts of the Atlantic Ocean [16]. However, in this
pattern, the interaction between low pressure systems of Europe has created a corridor of cold weather
which connects northern parts of Europe and northern and western parts of Iran. These air currents
move from Northern Europe toward Iran, which therefore result in thickness anomalies of −60 to
−20 m over Iran. Furthermore, a core frigid temperature was formed in latitude 60 degrees north with
Climate 2016, 4, 41
13 of 19
Climate 2016, 4, 41
13 of 19
a negative
anomaly of −180 m. The positive thickness of Icelandic low pressure, which has
a positive
anomaly
of
20
m,
stretched
to
latitude
45
degrees
north.
Nonetheless,
the
poor
blocking
of
Siberian
positive anomaly of 20 meters, stretched to latitude 45 degrees north. Nonetheless, the poor blocking
high pressure
prevents
this tongue
entering
northern
of the
country
(Figure(Figure
9). 9).
of Siberian
high pressure
preventsfrom
this tongue
from
enteringareas
northern
areas
of the country
9. Anomalies and atmosphere thickness (in meters) for the representative day of the fourth
FigureFigure
9. Anomalies
and atmosphere thickness (in meters) for the representative day of the
pattern.
fourth pattern.
In this pattern, 79.95% of the country’s area is covered by this cold wave, which is the highest
percentage
among
representative
days.isFurthermore,
to otherwhich
representative
Incoverage
this pattern,
79.95%
of the
country’s area
covered by compared
this cold wave,
is the highest
days,
the temperature
of representative
the country is significantly
lower during
the dominance
of representative
this pattern. In days,
coverage
percentage
among
days. Furthermore,
compared
to other
this time, the
temperature
of the northeastern
part of
country decreases
to −5 °C, which
the temperature
ofaverage
the country
is significantly
lower during
thethe
dominance
of this pattern.
In this time,
indicates a decline of −3 °C in comparison with the fourth pattern. On the other
hand, in the
◦
the average temperature of the northeastern part of the country decreases to −5 C, which indicates
northwestern part of the country, this temperature reduction is significant. However, on the
a decline of −3 ◦ C in comparison with the fourth pattern. On the other hand, in the northwestern
representative day, the majority of the country’s area (over 49%) experiences a temperature between
part of−0.42
the country,
this
significant.
on the representative
day, the
and −10.9
°C.temperature
This mainlyreduction
includes is
areas
along theHowever,
Zagros mountain
ranges and the
majority
of
the
country’s
area
(over
49%)
experiences
a
temperature
between
−
0.42
and
−
10.9 ◦ C.
northwestern parts of the country. It is then obvious that, in addition to external systems, heights,
This mainly
includes
areas
along to
thethe
Zagros
mountain
anddistribution
the northwestern
of the
country.
especially
ripples,
contribute
cold weather.
Theranges
frequency
of frostsparts
in these
areas
(heights)
further
confirms
the
findings
of
this
study
(Figure
10A).
Moreover,
due
to
its
typographic
It is then obvious that, in addition to external systems, heights, especially ripples, contribute to the
features, The
this frequency
part of thedistribution
country has of
a high
of variation,
a phenomenon
that further
cold weather.
frostscoefficient
in these areas
(heights)
further confirms
the findings
confirms the findings. In contrast, in southern parts of the country, especially the coasts of the Persian
of this study (Figure 10A). Moreover, due to its typographic features, this part of the country has a high
Gulf, fewer cold waves and frosts are experienced because of low latitude and the dynamic influence
coefficient of variation, a phenomenon that further confirms the findings. In contrast, in southern parts
of subtropical high pressure. Thus, in this pattern, the largest area of the country has a frost frequency
of the of
country,
especially
the5).
coasts of the Persian Gulf, fewer cold waves and frosts are experienced
428 to 342
days (Table
because of low latitude and the dynamic influence of subtropical high pressure. Thus, in this pattern,
of the
covered
area
of differentof
classes
of 342
average
temperature,
the largestTable
area 5.
ofPercentage
the country
has
a frost
frequency
428 to
days
(Table 5).anomalies and
frequency of frosts for the fourth group.
Table 5. Overall
Percentage
of the covered
area of different classes
of averageDay
temperature, anomalies and
Temperature
of the
Representative
Area (%)
Area (%)
frequency of frosts
for
the
fourth
group.
Fourth Group
Temperatures
−8.4 to −14.3
13.1
−10.9 to −17.39
4
−0.42
to
−10.9
−2.6
to
−8.4
37
49
Overall Temperature
Representative Day
Area 30.8
(%)
Area29.7
(%)
3.19
to −2.6Group
2.06 to -0.42
of the
Fourth
Temperatures
9.02 to 3.19
−14.87
8.4 to
14.3
to −
9.02
−
2.6
to
−
8.4 Days
The Frequency of Frost
3.19
to
−
2.6
85 to 0
9.02
to 85
3.19
171 to
14.87
9.02
256 toto171
14.1
13.15
37 (%)
Area
30.8
20.6
14.15.3
5 9.7
342Frequency
to 256
The
to 342
of428
Frost
Days
Area 51.3
(%)
13.2
85 to 0
171 to 85
256 to 171
342 to 256
428 to 342
20.6
5.3
9.7
13.2
51.3
8.54 to 2.06
−10.915.04
to −to
17.39
8.54
−
0.42
to
−
10.9 Anomaly
Representative Day
2.06
to −0.42
Negative
anomalies
8.54 to 2.06
Positive
anomalies
15.04 tothe
8.54
Anomalies
entire group
Negative anomalies
Representative
Day
Positive
anomalies
Anomaly
Negative anomalies
Positive anomalies
Anomalies the entire group
Negative anomalies
Positive anomalies
14.3
4 3
49
Area (%)
29.7
67.7
14.3
32.3
3 (%)
Area
65.7
Area 34.3
(%)
67.7
32.3
Area (%)
65.7
34.3
Climate 2016, 4, 41
14 of 19
Climate 2016, 4, 41
14 of 19
Figure
10. The
of
Figure 10.
The fourth
fourth pattern;
pattern; (A)
(A) Spatial
Spatial distribution
distribution of
of temperature
temperature average
average and
and coefficient
coefficient of
variation
for
the
whole
group;
(B)
spatial
distribution
of
temperature
average
and
coefficient
of
variation for the whole group; (B) spatial distribution of temperature average and coefficient of variation
variation
for the representative
day; (C) and
anomalies
and
center
masses
the whole
group; (D)
for the representative
day; (C) anomalies
center of
masses
forofthe
wholefor
group;
(D) anomalies
for
anomalies
for the day;
representative
day;of(E)
frequency
of frosts
for the
group;
and (F) spatial
the representative
(E) frequency
frosts
for the whole
group;
andwhole
(F) spatial
distribution
of the
distribution
of frosts
the trend
of Iran’s
for the whole group.
trend of Iran’s
for the
wholefrosts
group.
Climate
2016, 4,
4, 41
41
Climate 2016,
15
15 of
of 19
19
3.5. The Fifth Pattern: Omega Pattern
3.5. The Fifth Pattern: Omega Pattern
In this pattern of atmosphere thickness, southern Mediterranean Omega blocking is formed.
this
pattern
ofof
atmosphere
thickness,
southern
is formed.
SinceInthe
eastern
part
Omega system
is located
on theMediterranean
east of Europe Omega
and the blocking
west of the
Middle
Since
the
eastern
part
of
Omega
system
is
located
on
the
east
of
Europe
and
the
west
of
the
Middle
East, cold weather falls from higher latitudes toward these regions and the studied area. As a result
East,
cold weather
from higher
latitudes
toward
these
regions and become
the studied
area. Asreaching
a result
of
blocking
system falls
formation,
west winds
over
western
Mediterranean
meridional
of blocking
formation, west
reaching
polar
areas. system
The northwestern
part winds
of Iranover
is inwestern
front ofMediterranean
the path of thisbecome
troughmeridional
and the 5459
meter
polar
areas.
The
northwestern
part
of
Iran
is
in
front
of
the
path
of
this
trough
and
the
5459
m
curve
curve passes over this area. Spatial spread of these currents directs a larger proportion of cold weather
passesupper
over this
area. toward
Spatial spread
of theseincluding
currents directs
a larger
proportion
cold weatherinfrom
from
latitudes
lower regions
the studied
area.
Thus, theoftemperature
this
upper
latitudes
toward
lower
regions
including
the
studied
area.
Thus,
the
temperature
in
this
area
area significantly declines. On this day, the anomaly over the region was positive and between 150
significantly
OnGarcia
this day,
the anomaly
over
the region
was
positive
and between
150 of
to
to
100 meters declines.
(Figure 11).
conducted
synoptic
analysis
for the
north
and northeastern
frosts
100
m (Figure
11). Garcia
conducted
synoptic
for were
the north
and northeastern
frostssystems
of Mexico,
Mexico,
concluding
that the
main reasons
foranalysis
the frosts
the formation
of blocking
on
concluding
that
the
main
reasons
for
the
frosts
were
the
formation
of
blocking
systems
on
the
way
of
the way of western winds and the existence of cyclone centers in the northeastern part of the United
western
winds and the existence of cyclone centers in the northeastern part of the United States [34].
States [34].
Figure 11.
atmosphere
thickness
(in (in
meters)
for for
the the
representative
day day
of the
11. Anomalies
Anomaliesand
and
atmosphere
thickness
meters)
representative
offifth
the
pattern.
fifth pattern.
Blocking
Blocking is
is an
an atmospheric
atmospheric phenomenon
phenomenon that
that considerably
considerably influences
influences the
the climate
climate of
of its
its affected
affected
areas.
In
middle
latitudes,
atmospheric
currents
normally
move
in
the
form
of
waves
from
areas. In middle latitudes, atmospheric currents normally move in the form of waves from west
west to
to
east.
The
wave-like
movement
of
these
currents
can
be
clearly
observed
in
middle
latitudes
of
mid
east. The wave-like movement of these currents can be clearly observed in middle latitudes of mid
and
and upper
upper levels
levels of
of troposphere.
troposphere. Observing
Observing the
the monthly
monthly or
or seasonal
seasonal average
average of
of these
these currents
currents on
on the
the
abovementioned
levels
shows
that
the
wave-like
movement
is
more
regular
and
larger
in
cold
abovementioned levels shows that the wave-like movement is more regular and larger in cold seasons.
seasons.
A day-to-day
study
of the phenomenon
maythis
notregularity.
show thisInregularity.
Ininvestigation,
this type of
A
day-to-day
study of the
phenomenon
may not show
this type of
investigation,
the
obvious
issue
is
the
tongues
that
are
called
trough
or
ridge.
These
tongues
have
the obvious issue is the tongues that are called trough or ridge. These tongues have different sizes
different
sizes andbased
are measured
based on their
wavelength.
In their normal
movement,
and are measured
on their wavelength.
In their
normal movement,
western
currents western
transfer
currents
transfer
troughs
and
ridges
toward
east.
These
systems
move
within
middle
latitudes
and
troughs and ridges toward east. These systems move within middle latitudes and along
the polar
along
the
polar
front.
Sometimes,
the
abovementioned
systems
appear
in
larger
sizes
and
longer
front. Sometimes, the abovementioned systems appear in larger sizes and longer waves, hence moving
waves,
hence moving
more
slowly.
They may
even stop
moving
or move
in theThis
opposite
more slowly.
They may
even
stop moving
or move
in the
opposite
direction.
meansdirection.
that the
This
means
that
the
wave
does
not
move
eastward
and
stays
in
its
own
place
or
moves
westward.
In
wave does not move eastward and stays in its own place or moves westward. In the evolution
process
the
evolution
process
of
blockings,
the
ridge
may
be
associated
with
high
cell
or
closed
cells,
while
of blockings, the ridge may be associated with high cell or closed cells, while the trough may be
the trough may be accompanied by low cells or closed cells. Such a system may stay around a
accompanied by low cells or closed cells. Such a system may stay around a meridian for a long
meridian for a long time (some days or some weeks). It functions as an obstacle disturbing the normal
time (some days or some weeks). It functions as an obstacle disturbing the normal path of western
path of western currents in middle latitudes. Thus, because of this system, western currents cannot
currents in middle latitudes. Thus, because of this system, western currents cannot move through
move through their normal path, hence moving toward northern or southern latitudes. On the other
their normal path, hence moving toward northern or southern latitudes. On the other hand, low and
Climate 2016, 4, 41
Climate 2016, 4, 41
16 of 19
16 of 19
high
of the earth’s
surface
around
themove
blocked
system
on the
currents
of
hand,pressure
low andsystems
high pressure
systems
of themove
earth’s
surface
around
thebased
blocked
system
based
mid-tropospheric
on the currents of levels.
mid-tropospheric levels.
According to Figure 12, cold weather reaches southern latitudes of the country, with its impacts
observed in almost two third area of the country. For example, a large area of east, southeast, center
◦ C. The lowest values of temperature anomaly were
and west of the country has
has aa temperature
temperature of
of −
−77 °C.
The lowest values of temperature
observed in central parts of the Zagros mountain ranges. The areas with lowest temperatures were
also located
sporadically
in in
southern
areas
of
located in
in this
this territory.
territory.Negative
Negativeanomalies
anomalieswere
werealso
alsoobserved
observed
sporadically
southern
areas
◦
the
country.
The
coastal
areas
ofof
the
southern
C
of the
country.
The
coastal
areas
the
southernpart
partofofthe
thecountry
countryexperienced
experiencedaatemperature
temperature of
of 22 °C
(Figure 12A,C and
Table6).6).
& Table
Figure 12.
12.The
Thefifth
fifth
pattern:
Spatial
distribution
of temperature
and coefficient
of
Figure
pattern:
(A)(A)
Spatial
distribution
of temperature
averageaverage
and coefficient
of variation
variation
for the
whole
(B) spatial distribution
of temperature
andof coefficient
of
for
the whole
group;
(B) group;
spatial distribution
of temperature
average andaverage
coefficient
variation for
variation
for the representative
day; and
(C) anomalies
and center
masses
for the
group;
the
representative
day; (C) anomalies
center of masses
for theofwhole
group;
(D)whole
anomalies
for (D)
the
anomalies for day;
the representative
(E)for
frequency
frostsand
for (F)
thespatial
wholedistribution
group; andof(F)
representative
(E) frequency ofday;
frosts
the wholeofgroup;
thespatial
trend
distribution
of
the
trend
of
Iran’s
frosts
for
the
whole
group.
of Iran’s frosts for the whole group.
Climate 2016, 4, 41
17 of 19
Table 6. Percentage of the covered area of different classes of average temperature, anomalies and
frequency of frosts for the fifth group.
Overall Temperature
of the Fifth Group
Area (%)
Representative Day
Temperatures
Area (%)
−8.13 to −13.86
−2.40 to −8.13
3.32 to −2.40
9.05 to 3.32
14.79 to 9.05
13.2
43.5
25.4
13.4
4.5
−8.19 to −3.8
−3.8 to 0.55
0.55to 4.9
9.29 to 4.9
9.29 to 13.68
35
27.5
15.8
13.6
8.2
The Frequency
of Frost Days
Area (%)
Representative Day
Anomaly
Area (%)
106 to 0
212 to 106
319 to 212
425 to 319
532 to 425
19.9
4.9
7.9
13.3
53.9
Negative anomalies
Positive anomalies
Anomalies the entire group
Negative anomalies
Positive anomalies
67.6
32.4
Area (%)
64.5
35.5
4. Conclusions
As an index of heat severity, temperature is one of the essential elements for identifying the
weather features. Since the amount of energy that sun radiates to earth follows an irregular pattern,
temperature experiences a lot of oscillations in comparison with other meteorological elements.
These oscillations (i.e., excessive increases and decreases) can result in the formation of heat and cold
waves. In recent decades, climate change has been studied as a global challenge. Abnormal changes in
temperature affect precipitation and results in droughts or severe floods. These changes are regarded
as a threat to world food security. It is therefore necessary to conduct studies in order to estimate
changes in the main climate variables. By so doing, future plans will be designed in the light of specific
aims and will yield better results. The present study aimed at synoptic analysis of the atmosphere
thickness pattern of Iran’s pervasive frosts. To this end, daily temperature data were obtained from
Iran’s Meteorological Organization. The results indicated that the occurrence of frosts was mainly
influenced by five patterns, namely Siberian high-pressure and European high-pressure, deep trough
pattern of Eastern Europe and Sudanese low pressure, dual-core pattern of Siberian high-pressure,
deep Eastern European trough and polar low pressure pattern, and Omega pattern. The severest frosts
occurred during the dominance of the Omega pattern. However, Siberian high-pressure and European
high-pressure dominated the country for a longer period of time. Studying the Siberian high-pressure
pattern revealed that the spread of this pattern’s canon to central parts of Russia and the location of
ridges of mid atmosphere levels in this area directed this tongue toward Iran. The formation of counter
clockwise currents over the earth’s surface and other atmosphere levels in the region transferred cold
weather from northeastern parts of Russia toward Iran. Considering the factors that contribute to frosts
in various areas of Iran, the result of this study are largely in line with the ones obtained by [19,33,35,36].
In conclusion, the spread of migratory high pressure and Siberian high pressure tongues to Iran and
the location of blocking systems in Eastern Europe as well as atmospheric mid-level troughs over the
country are the main factors that cause frosts in Iran. Nevertheless, the results indicated that frosts
occur alongside contours that have a thickness of 5300 to 540 geopotential meters. In fact, in all five
patterns, pervasive frosts occur alongside these contours that are as thick as the atmosphere (especially
the ones that are 530 geopotential meters thick). Finally, the omega pattern (the fifth pattern) and Deep
Eastern European trough and polar low pressure pattern (the fourth pattern) were the most dominant
and severe frost patterns in Iran, respectively.
Acknowledgments: The daily meteorological data were provided by Iman Rousta of Iran Meteorological
Organization (IRIMO). The authors also gratefully acknowledge the NCEP/NCAR data was provided by the
NOAA-CIRES Climate Diagnostics Center, Boulder, Colorado, USA.
Climate 2016, 4, 41
18 of 19
Author Contributions: Authorship has been limited to those who have made a significant contribution to the
Conception, design, execution, and interpretation of the study.
Conflicts of Interest: The authors declare no conflict of interest.
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