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Circulation weather types and their influence on temperature and precipitation in Estonia


Abstract and Figures

An existing objective classiÞ cation scheme of the atmospheric circulation, where daily circulation is determined through the strength, direction and vorticity of the geostrophic ß ow has been applied over the Baltic Sea region for the time period of 1968-1997. The results at sea level and the higher isobaric levels of 500 hPa, 700 hPa and 850 hPa are presented here. The analysis revealed that the most common circula- tion types are anticyclonic and cyclonic. The mean-square-error skill scores are used to investigate classiÞ cationʼs suitability for describing the variability of the local (Pärnu) daily weather elements. The skill scores of the objective classiÞ cation are essentially higher than those for the German Weather Serviceʼs "Grosswetterlagen" scheme, but the scores are still low due to the high variability of daily temperature and precipitation within the weather types. Temperature is best described by the classiÞ cations at higher levels of pressure (500 hPa and 700 hPa), but precipitation is best described by those at the lower levels (sea level and 850 hPa). Developing one good classiÞ cation for both variables is non-trivial.
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Helsinki 2 October 2002 © 2002
Circulation weather types and their inß uence
on temperature and precipitation in Estonia
Piia Post, Valdur Truija and Janno Tuulik
Department of Environmental Physics, University of Tartu, Ülikooli 18, 51014
Tartu, Estonia
Post, P., Truija, V. & Tuulik, J. 2002: Circulation weather types and their inß u-
ence on temperature and precipitation in Estonia. — Boreal Env. Res. 7: 281–
289. ISSN 1239-6095
An existing objective classiÞ cation scheme of the atmospheric circulation, where
daily circulation is determined through the strength, direction and vorticity of the
geostrophic ß ow has been applied over the Baltic Sea region for the time period of
1968–1997. The results at sea level and the higher isobaric levels of 500 hPa, 700 hPa
and 850 hPa are presented here. The analysis revealed that the most common circula-
tion types are anticyclonic and cyclonic. The mean-square-error skill scores are used to
investigate classiÞ cationʼs suitability for describing the variability of the local (Pärnu)
daily weather elements. The skill scores of the objective classiÞ cation are essentially
higher than those for the German Weather Serviceʼs “Grosswetterlagen” scheme, but
the scores are still low due to the high variability of daily temperature and precipitation
within the weather types. Temperature is best described by the classiÞ cations at higher
levels of pressure (500 hPa and 700 hPa), but precipitation is best described by those at
the lower levels (sea level and 850 hPa). Developing one good classiÞ cation for both
variables is non-trivial.
The large-scale atmospheric circulation is an
important surface climate factor. It determines
the dispositions of baric systems and the domi-
nating airß ows. Therefore, several attempts have
been made to relate the large-scale atmospheric
circulation to local weather conditions. Inside
general circulation models this is achieved by
proceeding from physical laws and deriving
parameterisations for unresolved processes.
Traditionally there are two basic methods for
describing large-scale atmospheric circulation:
the use of circulation indices (NAO index etc) or
weather patterns, the latter is based on similarly
situated baric systems on synoptic maps. Nowa-
days, these simpliÞ ed circulation classiÞ cations
are developed mostly for two purposes: investi-
gation of the temporal variability of atmospheric
circulation with the further aim of forecasting
trends in it, or downscaling of weather elements
from climate models output.
Several atmospheric circulation classiÞ cations
have been developed for the area of Europe.
Two manual ones, applying a daily resolution,
have very long time series: the German Weather
Serviceʼs Grosswetterlagen (Gerstengarbe et al.
1993), and Lambʼs classiÞ cation for the British
282 Post et al. BOREAL ENV. RES. Vol. 7
Isles (Lamb 1972). The other group of clas-
siÞ cations, called “automatic” or “objective”
classiÞ cations, have increased in popularity with
the development of computer technology (Yarnal
Grosswetterlagen (GWL) is a planetary scale
classiÞ cation that is especially applicable for
Central Europe (Bissoli and Dittmann 2001).
Post and Tuulik (1999), and Keevallik et al.
(1999) investigated the suitability of the GWL
to describe the weather elements variability in
Estonia. Their results show that the dispersion of
meteorological elements within the weather types
is very large, and several weather patterns could
be interpreted for Estonia independently from
the interpretations for Central Europe (Post and
Tuulik 1999). The horizontal scale of the classi-
Þ cation is much larger than the scale of cyclones
and anticyclones, (which actually determine the
circulation at higher midlatitudes), and since the
process of classifying begins in the middle of the
area, it does not work for peripheries (the Baltic
Sea area already belongs to periphery).
Therefore, our goal was to introduce a syn-
optic scale, automatic classiÞ cation for the Baltic
Sea region atmospheric circulation, and to prove
that the connections with meteorological param-
eters are stronger compared to GWL.
The chosen scheme for atmospheric circula-
tion was developed by Jenkinson and Collison
(1977) (JC) and was initially used for the Brit-
ish Isles region. It was designed as an automatic
version of Lambʼs classiÞ cation. The circulation
pattern for a given day is described using the
locations of the centers of high and low pressure
that determine the direction of the geostrophic
airß ow. It uses coarsely gridded pressure data
and is therefore easily applicable in any area
with available data. Besides the British Isles this
method has already been exploited in several
other European regions: the Netherlands (Buis-
hand and Brandsma 1997), Sweden (Linderson
2001) and Portugal (Trigo 2000).
The classi cation of weather
We applied the JC classiÞ cation for the Baltic
Sea area, centered at 60°N, 22.5°E. The scheme
was used independently for the data at sea level
and at 850 hPa, 700 hPa and 500 hPa isobar
levels. The daily air pressure and geopotentional
height data used in this study originated from
NCEP/NCAR reanalysis (Kalnay et al. 1996).
The data values from 16 points (shown in
Fig. 1) were used to calculate the following
geostrophic airß ow indices: the zonal or west-
erly ß ow, and the meridional or southerly ß ow.
Combining of these two gives the resultant ß ow
(F) and the direction of the ß ow. The westerly
shear vorticity and the southerly shear vorticity
were calculated analogically, the sum of these
gives the total vorticity (Z). The latter describes
Fig. 1. Locations of clas-
siÞ cations. Numbers mark
the 16 points, applying
Jenkinson and Collison
(1977) scheme for the
Baltic Sea area; stars
mark the original location.
BOREAL ENV. RES. Vol. 7 Weather types’ infl uence on weather in Estonia 283
the rotation of the atmosphere, positive values
correspond to cyclonic circulation and negative
to anticyclonic. The equations for these indices
can be found in Jenkinson and Collison (1977).
We have adjusted the constants that account for
relative differences between the grid point spac-
ing in the east–west and north–south direction to
account for the more northerly location of our
classiÞ cation compared to the original applica-
tion. The geostrophic resultant ß ow F units are
expressed as hPa per 10° latitude at 60°N (each
unit is equivalent to 0.56 m s–1). The (geos-
trophic) vorticity Z units are expressed as hPa
per 10° latitude at 60°N, per 10° latitude. 100
units are equivalent to 0.40 times the Coriolis
parameter at 60°N.
The weather types are deÞ ned by comparing
the numeric values of F and |Z|:
— if , the airß ow is straight and the atmo-
spheric circulation is classiÞ ed into eight
directional weather types according to the
direction of the airß ow (N, NO, O, SO, S,
SW, W, NW).
— If , the airß ow is strongly cyclonic
(Z > 0) or anticyclonic (Z < 0), and the atmo-
spheric circulation is classiÞ ed into synoptic
C (cyclonic) or A (anticyclonic) type, respec-
— If , the airß ow is partly cyclonic or
anticyclonic, and the atmospheric circulation
is classiÞ ed into 16 hybrid types according
to the direction of atmospheric rotation and
the direction of the airß ow (CN, CNO, CO,
If the airß ow is weak, an unclassiÞ ed
weather type (U) occurs: and
, where sZ, sWF and sSF
are the standard deviations of total vorticity,
westerly and southerly ß ow, respectively.
In the original scheme one numeric thresh-
old was set to distinguish the unclassiÞ ed type
from the others. We adapted the scheme also
for higher levels, where the strenght of the ß ow
is greater than at the sea level. Therefore, the
threshold values were related to the standard
deviation of airß ow indices.
The Baltic Sea region atmospheric
circulation description using weather
The Baltic Sea and its adjacent coasts form
a region where the inß uences of the climatic
zones of Northwestern, Central and Northeast-
ern Europe meet and mingle (Mietus 1998).
The climate of this region is controlled, perhaps
more than that in other parts of Europe, by the
main great pressure systems that govern the air
ß ow over the continent: the Islandic low, and the
Azores high. Additionally, in winter, the branch
of the Asian maximum that extends to the South-
ern Europe and the polar high pressure region
are important. In winter both the Islandic low
and the Azores maximum strengthen, and this
results in westerly and southwesterly ß ow over
the Baltic and a relatively mild climate over the
region. But when the Islandic minimum is weak-
ened and shifted westwards towards the Ameri-
can coast, the inß uence of Arctic is prevailing. In
this case northerly and northeasterly winds blow
and this causes cold and severe conditions. The
mean ß ow is especially intensive in January. In
February and March the intensity of the mean
ß ow over the Baltic region decreases, becoming
at its weakest in April. Also in May the pressure
gradient is very weak.
In summer, the atmospheric pressure distribu-
tion is different. As the northern hemisphere heats
more than the southern one, subequatorial zones
of low pressure shift to north and with this the
subtropic zone of high pressure shifts to north.
High pressure regions form over the oceans, the
ocean low pressure centers weaken and the Azores
maximum strengthens. Over the Asian continent
pressure is much lower in comparison to winter.
In June and July, the mean ß ow could be speciÞ ed
as northwesterly to westerly. In August, the mean
pressure gradient starts to increase again.
All these features of the Baltic Sea region
atmospheric circulation are present in our data
and can be seen in the compounded results pre-
284 Post et al. BOREAL ENV. RES. Vol. 7
sented in Table 1 and Fig. 2. In Fig. 2 the Þ elds
of normalized sea level air pressure for all SLP
classiÞ ed types are presented. To reduce the
inß uence of very high and low pressures, the
Þ elds were normalized: for the highest pres-
sure of the region it was assigned a value of 1,
and for the lowest region a value of –1, there-
fore the units are relative. The highest and the
lowest pressure areas are marked with a “+” and
“–” respectively and the isolines are drawn after
every 0.15. The pressure patterns are easily inter-
preted. In case of synoptic types, the anticyclone
(A) or cyclone (C) sits in the middle of the area.
In case of directional types, the pair consisting of
cyclone and anticyclone determines the airß ow.
At the time of hybrid types the air pressure dis-
tribution is similar to the respective directional
one, only the centre of the region is more inß u-
enced by the anticyclone or cyclone.
Seasonal pressure distributions are also pre-
sented. During the cold half of the year stronger
pressure gradients were observed, but mostly
the pressure pattern of different weather types
appeared similar in all seasons. There were some
exceptions. The N type in winter: because of the
well pronounced low, the air ß ow to the Baltic
proper was from the Atlantic, in summer vice
versa from the Arctic. The O type in winter: the
strong Siberian high caused the airß ow from
southeast. In summer during this type the main
ß ow is from northeast, from the Arctic.
The dominating weather types for all seasons
were anticyclonic (A) and cyclonic (C). This con-
tradicts the well-known fact that the annual mean
number of cyclones (132) passing over Estonia
(and the whole Baltic region) is much larger than
the number of anticyclones (65) (Prilipko 1982).
The contradiction could be explained by the fact
that the cyclones move faster and have smaller
dimensions. Linderson (2001), who introduced
Table 1. Occurrences of weather types (%) for the 500 hPa isobar level (500GPH) and the sea level (SLP) clas-
siÞ cation for the Baltic Sea region (1968–1997) and for Southern Scandinavia (1881–1995) for comparison from
Linderson (2001) = LL.
Weather type 500GPH Year SLP Dec Jan Feb SLP Jun Jul Aug SLP Year LL Year
A 17.5 18.7 19.0 19.3 17.0
C 15.1 11.7 18.7 14.6 10.7
N 4.4 3.0 6.5 4.5 3.3
NO 1.1 1.7 3.6 2.7 1.9
O 0.6 2.1 2.0 2.3 2.5
SO 0.9 3.3 1.4 2.4 3.8
S 3.6 7.1 3.4 5.5 4.4
SW 9.5 9.6 7.7 8.7 7.7
W 11.3 10.0 5.4 7.9 11.3
NW 9.5 6.9 4.4 5.6 7.7
AN 1.4 0.9 2.2 1.6 1.1
ANO 0.4 0.7 1.6 1.3 0.8
AO 0.3 0.6 1.3 1.1 1.1
ASO 0.3 1.1 1.0 1.3 1.4
AS 1.3 2.4 1.3 1.9 1.4
ASW 2.7 3.4 1.9 2.7 2.2
AW 3.8 3.4 1.8 2.8 3.3
ANW 3.6 2.6 1.6 1.9 2.5
CN 1.3 1.0 2.3 1.5 1.1
CNO 0.4 1.0 1.3 1.0 0.5
CO 0.3 0.7 0.6 0.8 0.8
CSO 0.3 0.7 0.5 0.6 0.8
CS 1.3 0.9 1.3 1.4 1.1
CSW 2.8 1.8 3.0 2.4 2.2
CW 3.3 2.5 2.9 2.5 2.5
CNW 2.9 1.8 1.5 1.4 1.9
U 0.4 0.3 1.8 0.7 4.9
BOREAL ENV. RES. Vol. 7 Weather types’ infl uence on weather in Estonia 285
the JC classiÞ cation for the area, with the centre
at 55°N, 15°E, also supports the dominance of
anticyclonic weather. Her results are presented
in the last column of Table 1. Summer was the
season of the largest contribution of the cyclonic
vorticity (if to take the C type and cyclonic
hybrids together then 32.2% of days).
The Baltic region lies in a zone of highly
variable westerlies. The main ß ow directions
came out from the occurence distribution of the
weather types in different seasons (Table 1): in
winter the W, SW and S types were the prevail-
ing directional types, and out of four seasons the
directional types had the largest contribution
(48.3%) (because of the large pressure gradient).
The low values of pressure gradients in spring
and summer were observed also from the lower
load of directional types in these seasons: 38.8%
and 34.5% respectively. The classiÞ cation agrees
with the fact that at the 500 hPa level the west-
erly ß ow is stronger than at sea level, and the
easterly weather types vanish.
Fig. 2. Normalized annual
mean sea level pres-
sures (in relative units)
of SLP weather types for
the period 1968–1997. In
parenthesis are shown
the relative occurrences
of weather types. N, NO,
O, SO, S, SW, W, NW =
directional types for differ-
ent directions; AN, ANO,
etc = anticyclonic hybrid
types; CN, CNO, etc. =
cyclonic hybrid types; A=
anticyclonic; C = cyclonic
and U = unclassiÞ ed type.
286 Post et al. BOREAL ENV. RES. Vol. 7
Classi cation de ciencies
The JC scheme is a simple synoptic scale atmos-
pheric circulation classiÞ cation. We have taken
the scheme as it is without making any substan-
tial modiÞ cations, but there are some approxima-
tions and deÞ ciencies what should be considered
when interpreting the results.
The scheme uses geostrophic approxima-
tion that is physically justiÞ ed only for the free
atmosphere. The geostrophic wind speed overes-
timates the real wind speed in cyclonic motion
and underestimates it in anticyclonic motion.
For large-scale motions in midlatitudes the dis-
crepancy is about 10%–20%, and inside intense
cyclones even larger discrepancies can occure.
In the JC classiÞ cation scheme for calculating
the ß ow F, the means of pressures in two or three
points are used. In case of a high curvature of
isobars, this averaging causes a pressure gradient
and consequently an underestimation of the ß ow
strength. This averaging ampliÞ es the difference
Fig. 3. Mean squared
error skill scores (%) for
the predicted daily values
of (a) temperature, (b)
precipitation sums and (c)
precipitation occurrence
at Pärnu in the period
1968–1997. The abbrevia-
tions are the same as in
Table 2.
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Skill score (%)
Skill score (%)
SLP 850GPH 700GPH 500GPH
Skill score (%)
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
BOREAL ENV. RES. Vol. 7 Weather types’ infl uence on weather in Estonia 287
Table 2. Annually averaged mean squared error skill scores (%) for the predicted daily values of weather elements
at Pärnu (1968–1997) and in parenthesis at De Bilt (1949–1993) (Buishand and Brandsma 1997). SLP-classiÞ ca-
tion for the sea level, 850GPH for the 850 hPa level, 700GPH for the 700 hPa level, 500GPH for the 500 hPa level
and GWL = German Weather Serviceʼs Grosswetterlagen.
T 21.0 (28.7) 25.7 29.2 29.5 22.8 (39.6)
Psums 23.9 (19.3) 23.7 20.0 16.5 10.8 (16.1)
Pocc 28.8 (24.8) 30.9 30.1 26.8 14.5 (25.8)
of the geostrophic wind from the gradient wind
in case of anticyclones, and decreases the differ-
ence in case of cyclonic motion.
The weather types were deÞ ned using numer-
ical thresholds for circulation indicies. The only
ground for concrete numerical values of thresh-
olds is that the resulting mean pressure Þ elds
show different circulation patterns. But, the pro-
cedure of comparing Z to F (or dividing Z to F)
kicks out many combined cases of high cyclonic
vorticity, high wind speeds and powerful weather
events from cases of cyclonic weather type. And
from the mean pressure Þ elds (Fig. 2) it is clearly
seen that the classes NO, O, S and SW show a
clear cyclonic cuvature. This also explains in
part the anticyclonic prevailing: some cases of
cyclonity are included into directional types.
The in uence of weather types on
the daily temperature and
One of our purposes was to investigate the inß u-
ence of atmospheric circulation on the mete-
orological regime of the Baltic region. Under
research were data from several meteorological
stations in Estonia, but the results coincided to
such extent that only results from Pärnu mete-
orological station (58.37°N, 24.50°E) are pre-
sented here. The location of Pärnu on the eastern
coast of the Baltic Sea is shown in Fig. 1. Daily
deviations from the long-term monthly mean
temperature, daily precipitation sums and the
proportion of rainy days (precipitation occur-
rence) for the distinct weather types over the
period of 1968–1997 were calculated.
To evaluate the capability of the classiÞ cation
to describe the variability of the local (Pärnu)
temperature and precipitation, the dispersion
analysis was used. We calculated the mean-
squared-error skill scores as done by Buishand
and Brandsma (1997) for the predicted daily
values that show to how large extent the variabil-
ity of the temperature and precipitation is deter-
mined by the changing of weather types. The
skill score gives the proportion of the explained
variance and is the square of the multiple cor-
relation coefÞ cient. The magnitude of the skill
score is determined by the squared deviations of
the individual values from monthly averages.
The skill scores reveal which pressure levels
were the most suitable for explaining the tem-
poral variability of surface weather elements
(Fig. 3). The skill scores had a strong annual
cycle for temperature. In summer the skill scores
were the largest for the 500 hPa classiÞ cation
and in winter for the sea level pressure classiÞ ca-
tion. This shows that in summer the daily tem-
perature of the local area was more connected
with movements in the free atmosphere, but in
winter the processes in the boundary layer were
more important. From here it follows that the
classiÞ cation describes temperature variations
better if several levels in the atmosphere are
taken into account. Precipitation processes were
more related to surface conditions: the largest
skill scores were for the sea level and 850 hPa
classiÞ cations.
For the objective classiÞ cation at sea level,
the precipitation skill scores were higher in
Pärnu than in De Bilt (in the Netherlands), but
skill scores for temperatures showed the oppo-
site (Table 2). We also included the results of
Grosswetterlagen to obtain comparison with
the previous works (Keevallik et al. 1999, Post
and Tuulik 1999). For GWL the skill scores in
Pärnu were lower than in De Bilt for all weather
288 Post et al. BOREAL ENV. RES. Vol. 7
elements. That proves that the Grosswetterlagen
classiÞ cation is less suitable for Estonia than for
the Netherlands. Concerning temperature, the
Baltic Sea area is a problem also for the objec-
tive scheme (skill scores are lower than for the
Netherlands). It could be related to the fact that
for this spatial scale of classiÞ cation, the Atlantic
Ocean as a homogeneous boundary surface is
too far from the Baltic area, but close enough to
the Netherlands. As our results for the precipita-
tion were better than those for Netherlands, the
determining scale maybe more local in this case
and the vicinity of Atlantic may not play a role.
Nevertheless, the skill scores for the objective
weather types at Pärnu were higher than for
Grosswetterlagen. It should therefore be possible
to develop a classiÞ cation that better describes
the variability of weather elements. The investi-
gation shows that classiÞ cations cannot describe
the variability of temperature and precipitation
equally well. The solution would be to Þ nd rela-
tions between the circulation parameters (direc-
tion and strenght of the dominant airß ow, and
vorticity) and any weather element separately, as
it has been done in many downscaling studies,
and based on the results, to establish respective
classiÞ cations. This would eliminate also the
subjectivity of thresholds.
Discussion and conclusion
From the present work, it follows that for
investigating the temporal variability of the
atmospheric circulation in the Baltic Sea region
the Jenkinson and Collison (1977) scheme is
certainly good enough. It distinguishes certain
different weather patterns; it is physically easily
interpretable and uses only sea level pressures
(that have the longest available time series). Its
simple applicability to the Baltic Sea area pres-
sure Þ elds on different levels has also given
better relations with weather elements than
GWL. Temperature is best described by the clas-
siÞ cations at higher levels of pressure (500 hPa
and 700 hPa) and precipitation at the lower ones
(sea level and 850 hPa). But the skill scores stay
still low, which means that the scheme should be
improved for downscaling purposes.
The results suggest that if we want the clas-
siÞ cation to describe well the variability of
regional weather elements, then several circula-
tion indices on different height levels should be
taken into account. The use of simple physical
models, like geostrophic wind approximation,
gives a direct physical interpretation of the clas-
siÞ cation and a reasonable number of classes.
The approximation of geostrophic wind is physi-
cally justiÞ ed only for the free atmosphere. If we
have only sea level pressure Þ elds, some statisti-
cal classiÞ cation could be used. If the task is to
conserve also the physical meaning, the sea level
winds in combination with empirical relations
from the boundary layer dynamics could be used
to get upper air motions.
Acknowledgements: This work was Þ nancially supported
by the Estonian Science Foundation (grant No 4347). Two
anonymous reviewers gave many useful comments to the
Þ rst version of the paper. All this is gratefully acknowledged.
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... For describing synoptic-scale atmospheric circulation and flow direction, 500 hPa geopotential height (GPH) fields were classified using synoptic weather types by Jenkinson and Collison [57]. For this task, the GPH values from 16 points in and around the study area were used to calculate six different flow indices, quantifying the geostrophic airflow and vorticity (see Post et al. [58] for details). Jenkinson Collison' circulation types (JCT) are defined by comparing the numeric values of the indices. ...
... So, we do have a synoptic-scale airflow over the area centred at Estonia (58.75 • N, 25 • E). The classification is widely used in Europe and elsewhere (e.g., [58][59][60][61][62][63]). The selected method offers the simplicity of interpretation but also flexibility to make sensitivity studies. ...
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Data from the C-band weather radar located in central Estonia in conjunction with the latest reanalysis of the European Centre for Medium-Range Weather Forecasts (ECMWF), ERA5, and Nordic Lightning Information System (NORDLIS) lightning location system data are used to investigate the climatology of convective storms for nine summer periods (2010–2019, 2017 excluded). First, an automated 35-dBZ reflectivity threshold-based storm area detection algorithm is used to derive initial individual convective cells from the base level radar reflectivity. Those detected cells are used as a basis combined with convective available potential energy (CAPE) values from ERA5 reanalysis to find thresholds for a severe convective storm in Estonia. A severe convective storm is defined as an area with radar reflectivity at least 51 dBZ and CAPE at least 80 J/kg. Verification of those severe convective storm areas with lightning data reveals a good correlation on various temporal scales from hourly to yearly distributions. The probability of a severe convective storm day in the study area during the summer period is 45%, and the probability of a thunderstorm day is 54%. Jenkinson Collison’ circulation types are calculated from ERA5 reanalysis to find the probability of a severe convective storm depending on the circulation direction and the representativeness of the investigated period by comparing it against 1979–2019. The prevailing airflow direction is from SW and W, whereas the probability of the convective storm to be severe is in the case of SE and S airflow. Finally, the spatial distribution of the severe convective storms shows that the yearly mean number of severe convective days for the 100 km2 grid cell is mostly between 3 and 8 in the distance up to 150 km from radar. Severe convective storms are most frequent in W and SW parts of continental Estonia.
... It determines the spatial distribution of air temperature and humidity, cloudiness, or precipitation among others. Therefore, it largely influences the weather conditions over a given area (Post et al., 2002). A particularly high variability of weather patterns is observed at the European mid-latitudes -i.e., in the region where polar air masses collide with arctic or tropical air masses (Sepp and Jaagus, 2002). ...
... The relationship between the synoptic scale air flow strength and the resultant vorticity including air temperature as well as precipitation has been analyzed a number of times (Brandsma and Buishand, 1997;Kilsby et al., 1998;Wilby, 1999). The circulation indices under discussion can be calculated based on the values of mean sea-level pressure and have been deemed applicable and useful in the classification of circulation types (Chen, 2000;Linderson, 2001;Post et al., 2002;Trigo and Da Camara, 2000). ...
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This paper concerns the relationships between selected circulation indices and air temperature over Southeast Poland between 1871-2010. The geostrophic wind speed and the resultant vorticity were computed based on daily gridded fields of mean sea-level pressure over an area defined from 5°20' to 40°20'E and from 41°15' to 61°15'N. The highest daily mean geostrophic wind speed over Southeast Poland is observed from December to February. In turn, the maximum (positive) values of the resultant vorticity occur in April and May, while the minimum (negative) values are observed in January. Mean air temperature from November to February has a strong positive correlation with the geostrophic wind speed. Moreover, the occurrence of the highest coefficients regarding the correlation between the geostrophic wind speed and air temperature in winter as well as the NAO index was recorded at the beginning of the 21st century. This suggests that the range of impact of sea-level pressure distribution over the North Atlantic on the winter air temperature over Southeast Poland may have increased over the last decades. One of the causes may be an eastward shift of the position of the center of the Icelandic Low and the Azores High in the period from December to February.
... Several authors as in Refs. [30][31][32][33][34][35][36] applied this method in different regions. In this study, a weather type classification was used to explain sea states patterns in a region located in the North Atlantic Ocean (see Fig. 3) with northwest coordinates of 63 deg N, 60 deg W, and southeast coordinates of 27 deg N, 0 deg E. ...
A statistical analysis of significant wave height (Hs) in eight locations offshore Portugal continental coast is performed. Specifically, locations at different water depths at Aguçadoura, Leixões, Nazaré, Peniche, Sines and Faro were chosen. The spectral and parametric information from these points used in this analysis was obtained from 21-year hindcast simulations using the spectral wave model SWAN. The modelling of the climatic variability of directional spectra provides reliable information of the most relevant parameters at these locations, i.e., how the spectral parameters and their probability of occurrence change in the regions studied. The occurrences of spectral classes are estimated, and for each class, the variability of the spectral parameters is described by means of joint distributions. The classification of the different sea states provides important information about the wave conditions present in the target areas. A relation between the sea states and the Lamb weather types (WTs), a methodology for classifying atmospheric circulation patterns, is presented in this study. The results of this study provide a description of the wave climate, through the interaction between the sea states and weather patterns, relating different circulation patterns to different sea states. This study provides useful information on the wave conditions that can be used in the design of ocean engineering structures, in the assessment of the operability and safety of shipping and renewable energy devices.
... This method has been applied to many regions and with many different objectives, especially in Europe where there are examples from the Iberian Peninsula [31][32][33][34], Sweden [35,36], Scandinavia [37], Estonia [38], and the southwestern region of Russia [39]. It has also been employed in other regions such as Chile [40]. ...
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Coastal spaces exploited for tourism tend to be developed rapidly and with a desire to maximise profit, leading to diverse environmental problems, including flooding. As the origin of flood events is usually associated with intense precipitation episodes, this study considers the general rainfall characteristics of tourist resorts in two islands of the Canary Archipelago (Spain). Days of intense rainfall were determined using the 99th percentile (99p) of 8 daily precipitation data series. In addition, the weather types that generated these episodes were identified, the best‐fitting distribution functions were determined to allow calculation of probable maximum daily precipitation for different return periods, and the territorial and economic consequences of flood events were analysed. The results show highly irregular rainfall, with 99p values ranging 50–80 mm. The weather types associated with 49 days of flooding events were predominantly cyclonic and hybrid cyclonic. The Log Pearson III distribution function best fitted the data series, with a strong likelihood in a 100‐year return period of rainfall exceeding 100 mm in a 24 h period. However, values below 30 mm have already resulted in significant flood damage, while intense rainfall events in the period 1998–2016 saw over 11.5 million euros paid out in damages for insured goods. Such floodinduced damages were found to be caused more by inadequate urban planning than by rainfall intensity.
... Lamb's daily types for the British Isles (since 1861) and the corresponding JC types (since 1880) can be found at http:// Uses and applications of JC in European regions, especially the north of the continent, can be found in Buishand and Brandsma (1997), Trigo and DaCamara (2000), Linderson (2001), Post et al. (2002), Fowler and Kilsby (2002), Buchanan et al. (2002), Antonsson et al. (2008), Demuzere et al. (2008), Post and Kärner (2008), etc. In other regions of the planet, the JC method has as yet been little used, although one of the first pilot applications was in a scope outside of the mid-latitudes, specifically in Egypt (Dessouky and Jenkinson, 1977). ...
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We determined the weather type, according to the Jenkinson and Collison procedure, of the 22 646 days in the 1948-2009 period for the western Mediterranean basin. The analysis is based upon the surface pressure values of the NCEP/NCAR reanalysis, for a grid of nine points with extreme vertices at 45º N, 5º W and 35º N, 15º E, which provides a broad synoptic catalogue for this region. We analyzed the trends of the types and their different groupings during the same period. The most frequent type is U (undetermined), with an annual average of approximately 100 days (99.4, 27.2%), followed by type A (anticyclone), with 75.5 days/ year (20.7%), and C (depression), with 67.8 days/year (18.6%). The high frequency of type U is due to the habitual pressure of baric fields with a low gradient over Mediterranean waters in the warm half of the year. According to their directions, the types from the west are the most frequent and those from the south, the least. The monthly regime of the most frequent types and groupings is quite regular; type C groups, as well as advective and cyclonic curvature groups, present summertime minima and maxima in the cold half of the year, whereas the opposite occurs with types U and A. The main statistically significant annual trends in the 1948-2009 period involve a decrease in type A (–4.19 days/decade, that is, –29.0%) and an increase in type U, the cyclonic types and those presenting an easterly component. On comparing the 31-yr sub-pe- riods 1948-1978 and 1979-2009, the tendencies of A and U were confirmed, and increases can generally be seen in the types presenting an easterly component and a decrease in those with a westerly component. The variation in type A ranged from 2490 days in the first sub-period to 2192 in the second one (p = 0.000), mainly concentrated in summer and autumn. This evident reduction of type A coincides, paradoxically, with an increase in the sea surface pressure variable (+0.31 hPa/decade) throughout the 62 years of analysis. The negative trend found in type A differs from the results of some studies. The different analysis periods, the different scales or areas of study and the variety of methods used to determine the weather types can account for the fact that these results are discordant. Moreover, warming over the last few decades in the waters of the western Mediterranean basin, as well as the clearly cyclogenetic character of the gulfs of Lion and Genoa, might account for the decrease in type A and the increase in the cyclonic curvature types.
... In recent years, there have been several studies which have applied the methodology of Jenkinson & Collison (J&C) to various study areas, including the Iberian Peninsula (Grimalt et al. 2013;Martín-Vide 2002;Spellman 2000;Trigo and DaCamara 2000); however, it is not the only synoptic classification that has been applied in this region, as demonstrated by the completion of the COST 733 action for the European continent (Philipp et al. 2014) and various regions of the world outside of the inter-tropical and polar areas, as is the case for Scandinavia, Central Europe, Russia, the United States and Chile (Esteban et al. 2006;Linderson 2001;Pepin et al. 2011;Post et al. 2002;Sarricolea et al. 2014Sarricolea et al. , 2017Soriano et al. 2006;Spellman 2016;Tang et al. 2009). ...
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Precipitation on the Spanish mainland and in the Balearic archipelago exhibits a high degree of spatial and temporal variability, regardless of the temporal resolution of the data considered. The fractal dimension indicates the property of self-similarity, and in the case of this study, wherein it is applied to the temporal behaviour of rainfall at a fine (10-minute) resolution from a total of 48 observatories, it provides insights into its more or less convective nature. The methodology of Jenkinson & Collison which automatically classifies synoptic situations at the surface, as well as an adaptation of this methodology at 500 hPa, was applied in order to gain insights into the synoptic implications of extreme values of the fractal dimension. The highest fractal dimension values in the study area were observed in places with precipitation that has a more random behaviour over time with generally high totals. Four different regions in which the atmospheric mechanisms giving rise to precipitation at the surface differ from the corresponding above-ground mechanisms have been identified in the study area based on the fractal dimension. In the north of the Iberian Peninsula, high fractal dimension values are linked to a lower frequency of anticyclonic situations, whereas the opposite occurs in the central region. In the Mediterranean, higher fractal dimension values are associated with a higher frequency of the anticyclonic type and a lower frequency of the advective type from the east. In the south, lower fractal dimension values indicate higher frequency with respect to the anticyclonic type from the east and lower frequency with respect to the cyclonic type.
... This classification was applied to each flood event using the average daily surface pressure data according to Lorenzo et al. (2008) or Post et al. (2002) for each of the nine points. When the events lasted more than 1 day, the date with the maximum precipitation was selected. ...
The aim of this work was to identify the circulation weather types associated with flood events that occurred in Catalonia (Northeastern Spain) during the period 1900–2010. To achieve this objective, 261 extraordinary and catastrophic flood and flash flood events that were recorded during this period were characterized and classified based on impact data. A preliminary analysis of maximum precipitation and discharge was conducted in order to have some quantitative hydrometeorological indicators associated with these kinds of events. The objective classification developed by Jenkinson and Collison, which is based on differences in synoptic patterns according to surface pressure, was implemented. Once the weather regimes for each flood event had been established, a statistical and comparative analysis was performed that allowed us to determine which synoptic patterns were more frequently associated with the different flood types, their differences and their similarities. The results howthat most synoptic situations were pure cyclonic structures, in both extraordinary and catastrophic events, although they were more frequent in the latter. Catastrophic floods generally had a synoptic origin enhanced by certain mesoscale factors, while extraordinary floods were usually associated with local flash floods that occurred primarily in summer and early autumn, highlighting the undetermined types that were not reflected at a synoptic scale. As the Mediterranean basin is a region where floods cause serious socio-economic impacts, this work will help improve prevention measures and provide information for policymakers, mainly for land-use planning and early warning systems.
It is very important to identify the possible mechanism of precipitation generation in southeastern China. To determine the weather type (WT) that is likely to generate precipitation, the Jenkinson‐Collison (JC) classification method was applied to wintertime daily mean sea level pressure (MSLP) data across southeastern China. We found that all WTs with easterly components are prone to generate precipitation. These WTs were merged into one type named the ensemble of easterly wind components (the EE type). The persistence and transformation rules of the EE type are studied. Anticyclone type is the easiest one to convert to EE type. The persistence and transformation rules of the EE type provide favorable conditions for the formation of precipitation. Furthermore, we examined the influence of two common teleconnections (Western Pacific (WP) and Eurasian (EU)) in East Asia in winter on the WTs. When WP is in the positive phase and EU is in the negative phase, EE type weather patterns will appear frequently in southeastern China. At this time, it is most conducive to the formation of precipitation. On the one hand, warm and cold air converge in this area. On the other hand, the prevailing east wind can provide sufficient water vapor. The study implies that whether a weather type is easy to produce precipitation can be judged by wind direction. The results will help us better understand the physical mechanism of precipitation generation in this area. This article is protected by copyright. All rights reserved.
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The paper assesses the relationship between atmospheric circulation and seasonal air temperature in the Lublin region from 1951 to 2010. It also specifies the relations between the occurrence of extremely warm and cool seasons, and anomalies of sea level pressure (SLP) in the Atlantic European region. For this purpose, the classification of circulation types over East-Central Europe as well as mean seasonal air temperature values from 5 meteorological stations located in the area of research or in the vicinity were used. The strongest influence of atmospheric circulation on thermal conditions in the Lublin region was noticed in winter season, and the weakest in the spring months. The zonal circulation played an important role for seasonal air temperature both in winter and in summer, whereas meridional air flow in autumn. Compared to air flow direction, the character of atmospheric circulation, expressed by anticyclonic, cyclonic and transitional circulation, had a significantly weak influence on the seasonal air temperature. Moreover, strong relationship between anomalies of sea level pressure in the Atlantic European region and strong positive or negative deviations of seasonal air temperature in the Lublin region were found primarily during winter and summer seasons.
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The objective of the study was the long-term and annual variability of atmospheric circulation indices over the Lublin region in the years 1951–2010. The zonal, meridional and cyclonicity indices were calculated based on the calendar of circulation types over East-Central Poland. Furthermore, the relationships between atmospheric circulation and thermal as well as precipitation conditions in the Lublin region were examined. In winter season, the strongest zonal circulation was noticed in the period from the second half of the 1980s to the end of the 20th century. In the last two decades of the analyzed period, a higher frequency of southern circulation in summer was observed. The characteristic features of atmospheric circulation in the study area include the prevalence of westerly circulation in autumn and winter, and easterly air flow in spring. The zonal circulation had an important role for monthly air temperature both in winter and in summer, whereas meridional air flow in spring and autumn. Compared to the air flow direction, the character of atmospheric circulation, expressed by anticyclonic and cyclonic circulation, had a weak influence on monthly air temperatures. The cyclonicity index most accurately reflects the variability of monthly precipitation totals in the Lublin region.
An objective classification scheme of the atmospheric circulation affecting Portugal, between 1946 and 1990, is presented, where daily circulation is characterized through the use of a set of indices associated with the direction and vorticity of the geostrophic flow. The synoptic characteristics and the frequency of ten basic circulation weather types (CWTs) are discussed, as well as the amount of precipitation associated with each type between 1957 and 1986. It is shown that the anticyclonic (A) type, although being the most frequent class in winter (37%), gives a rather small (less then 16%) contribution to the winter precipitation amount, observed on a daily basis. On the other hand, the three wettest CWTs, namely the cyclonic (C), southwesterly (SW) and westerly (W) types, together representing only 32% of all winter days, account for more than 62% of the observed daily precipitation. Results obtained highlight the existence of strong links between the interannual variability of monthly precipitation and interannual variability of CWTs. Multiple regression models, developed for 18 stations, show the ability of modelling monthly winter precipitation through the exclusive use, as predictors, of the wet CWTs (i.e. C, SW and W). The observed decreasing trend of March precipitation is also analysed and shown to be especially associated with the decrease of the three wet weather types. The anomalous low (high) frequency of wet CWTs during the hydrological year is shown to be strongly related with the occurrence of extreme dry (wet) years in Portugal, which had important impacts on Portuguese agriculture. Overall, the results suggest that the precipitation regime over Portugal, including interannual variability, trends and extremes, may be adequately explained in terms of variability of a fairly small number of circulation weather patterns. On the other hand, observed contrasts in the spatial distribution of correlations between frequency of wet CWTs and rainfall amounts suggest that precipitation regimes are of a different nature in northern and southern regions of Portugal; the former possessing an orographic origin and the latter being associated to cyclogenetic activity. Copyright © 2000 Royal Meteorological Society
There have been several attempts to classify the large-scale circulation within the area of Europe. One of the oldest and most popular one is the German Weather Service's Grosswetterlagen, with time-series of daily records beginning in 1881. Grosswetterlagen (atmospheric circulation patterns) are actually classified for Central Europe using Northern Hemispheric weather maps at the sea level and 500 hPa height. Only large-scale features of general circulation are included in the classification scheme. In our work we have investigated the suitability of the Grosswetterlagen classification for an outlying region of Europe. The research area — Estonia — lies in the northeastern part of Europe. Typical weather maps of Grosswetterlagen are used to determine the prevailing air flow over Central Europe and Estonia. 500 hPa wind measured at Tallinn station for the time period 1992–1993 have been used as additional data. Annual cycles of temperature deviation at Pärnu station for different circulation patterns are used for determining air masses during these circulation patterns. The upper air flow in Central Europe and Estonia is similar for zonal and half-meridional circulations, But the air masses during circulation patterns from all 3 circulation groups could be very different for these regions. Examples demonstrate the links of circulation patterns to local temperature fields, but give also the reason for further complex investigation of relationships.
The objective weather type classification of the German weather service and its application possibilities are described. Meteorological criteria for this classification are the advection of air masses, the cyclonality and the humidity of the troposphere, leading to numerical indices from which the weather types are derived. The data basis is the numerical weather analysis and forecast system of the German Weather Service. A time series of the weather type data covering more than 20 years is available now. The classification area is Germany, in principle it can be transferred to other areas as well. There are 40 different weather types, but the numerical indices provide the possibility to enlarge or to reduce the number of types without changing the meteorological criteria. This makes the classification very flexible for individual users. Various applications of this weather type classification are listed. A regularly weather type monitoring via INTERNET has been realized.
Three existing classification schemes of daily circulation patterns are considered: (i) the subjective Grosswetterlagen; (ii) an objective scheme, the Jenkinson classification, which produces weather types similar to the subjective Lamb classification for the British Isles; and (iii) the objective P27 classification scheme developed at the Royal Netherlands Meteorological Institute. The comparison between these schemes is based on the mean-squared-error skill score (percentage of explained variance) and the correlation coefficient between the observed and predicted values. The relationship between these performance measures is examined.
A method for calculating circulation indices and weather types following the Lamb classification is applied to southern Scandinavia. The main objective is to test the ability of the method to describe the atmospheric circulation over the area, and to evaluate the extent to which the pressure patterns determine local precipitation and temperature in Scania, southernmost Sweden. The weather type classification method works well and produces distinct groups. However, the variability within the group is large with regard to the location of the low pressure centres, which may have implications for the precipitation over the area. The anticyclonic weather type dominates, together with the cyclonic and westerly types. This deviates partly from the general picture for Sweden and may be explained by the southerly location of the study area. The cyclonic type is most frequent in spring, although cloudiness and amount of rain are lowest during this season. This could be explained by the occurrence of weaker cyclones or low air humidity during this time of year. Local temperature and precipitation were modelled by stepwise regression for each season, designating weather types as independent variables. Only the winter season-modelled temperature and precipitation show a high and robust correspondence to the observed temperature and precipitation, even though < 60% of the precipitation variance is explained. In the other seasons, the connection between atmospheric circulation and the local temperature and precipitation is low. Other meteorological parameters may need to be taken into account. The time and space resolution of the mean sea level pressure (MSLP) grid may affect the results, as many important features might not be covered by the classification. Local physiography may also influence the local climate in a way that cannot be described by the atmospheric circulation pattern alone, stressing the importance of using more than one observation series.