Quantifying the influence of recent circulation changes on European climatic trends Monika Cahynová (1,2), Radan Huth (1) cahynova@ufa. cas.cz (1) Institute of Atmospheric Physics, Academy of Sciences of the Czech Republic (2) Faculty of Science, Charles University, Prague COST733 Final Event, Vienna, 22-24 November 2010
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Quantifying the influence of recent circulation changes on ... the influence of recent circulation changes on European climatic trends Monika Cahynová (1,2), Radan Huth (1) cahynova@ufa.
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Quantifying the influenceof recent circulation changes on European climatic trends
Monika Cahynová (1,2), Radan Huth (1)cahynova@ufa. cas.cz
(1) Institute of Atmospheric Physics, Academy of Sciences of the Czech Republic(2) Faculty of Science, Charles University, Prague
COST733 Final Event, Vienna, 22-24 November 2010
Outlinewe want to assess the magnitude of climatic trends over Europe in1961-2000 that can be linked to changing frequency of circulation types (as opposed to changing climatic properties of circulation types)data
29 stations from the ECA&D project, daily Tmax, Tmin, precipitation8 objective catalogues from cat.1.2 (CKMEANS, GWT, Litynski, LUND, P27, PETISCO, SANDRA, TPCA), each in 3 variants with 9, 18, 27 CTsall COST733 domains except for D03 – lack of stations
methodsseasonal trends in the frequency of circulation typesseasonal climatic trends from station dataproportion of climatic trends linked to circulation changes - 2 methods of attribution usedcomparison of all results using classifications in D00 and small domains representing each of the stations, Alpine stations in D06+D07
Stations
Results – trends in the frequency of CTs
0
20
40
60
80
100
%
D00 D01 D02 D03 D04 D05 D06 D07 D08 D09 D10 D11
+ MAM + JJA + SON + DJF
CTs are unevenly represented
Percentage of days occupied by CTs withtrends in the seasonal frequencysignificant at the 95% level in 1961-2000
Changes in winter relative frequency ofCTs in GWTC10 in Central Europe(D07)
Upward (downward) stripes denote typeswith positive (negative) linear trendsignificant at the 95% level
Results – trends in the frequency of CTsMagnitude of significant trends in the frequency of CTs in GWTC10 (days perseason in 1961-2000)
W SW NW C A N NE E SE SD00 -5D01 -8D02 6 -3D03 -5D04D05D06D07D08D09 -8 5 3D10D11D00D01 -4D02D03D04D05D06 2D07 -2D08D09 -7D10 -2D11
sprin
gsu
mm
er
W SW NW C A N NE E SE SD00 9D01D02D03 3 4D04D05D06D07 3D08 3D09D10D11D00 16 -8 -3D01 6D02 7D03D04 13 13 -7 -7D05D06 9 3 -8D07 20 -6 -7D08 16 -3 -10 -8D09D10 5 -4 2 -6D11 14 -7
autu
mn
win
ter
Results – seasonal climatic mean and interannual variability
TX
-15-10-505
101520253035
Dal
atan
giVe
stm
anna
eyja
rG
lom
fjord
Osl
oSt
orno
way
Wad
ding
ton
Hel
sink
iO
este
rsun
dBa
mbe
rgH
anno
ver
Hoh
enpe
isse
nber
gKe
mpt
enKr
edar
ica
Pots
dam
Sonn
blic
kW
ien
Cal
aras
iKy
ivLu
gans
kBi
arrit
zVa
lenc
iaBr
indi
siLa
rissa
Sara
jevo
Fini
keC
hani
a
[°C]MAMJJASONDJF
TN
-15-10-505
101520253035
Dal
atan
giVe
stm
anna
eyja
rG
lom
fjord
Osl
oSt
orno
way
Wad
ding
ton
Hel
sink
iO
este
rsun
dBa
mbe
rgH
anno
ver
Hoh
enpe
isse
nber
gKe
mpt
enKr
edar
ica
Pots
dam
Sonn
blic
kW
ien
Cal
aras
iKy
ivLu
gans
kBi
arrit
zVa
lenc
iaBr
indi
siLa
rissa
Sara
jevo
Fini
keC
hani
a
[°C]
MAMJJASONDJF
RR
0
100
200
300
400
500
600
700
Dal
atan
giVe
stm
anna
eyja
rBu
lken
Lien
_i_S
elbu
Stor
now
ayW
addi
ngto
nH
elsi
nki
Oes
ters
und
Bam
berg
Han
nove
rH
ohen
peis
senb
erg
Kem
pten
Kred
aric
aPo
tsda
mSo
nnbl
ick
Wie
nC
alar
asi
Kyiv
Luga
nsk
San_
Seba
stia
nVa
lenc
iaBr
indi
siLa
rissa
Sara
jevo
Cha
nia
[mm
]
MAMJJASONDJF
(a) long-term seasonal mean
TX
00.5
11.5
22.5
33.5
4
Dal
atan
giVe
stm
anna
eyja
rG
lom
fjord
Osl
oSt
orno
way
Wad
ding
ton
Hel
sink
iO
este
rsun
dBa
mbe
rgH
anno
ver
Hoh
enpe
isse
nber
gKe
mpt
enKr
edar
ica
Pots
dam
Sonn
blic
kW
ien
Cal
aras
iKy
ivLu
gans
kBi
arrit
zVa
lenc
iaBr
indi
siLa
rissa
Sara
jevo
Fini
keC
hani
a
[°C]MAMJJASONDJF
TN
00.5
11.5
22.5
33.5
4
Dal
atan
giVe
stm
anna
eyja
rG
lom
fjord
Osl
oSt
orno
way
Wad
ding
ton
Hel
sink
iO
este
rsun
dBa
mbe
rgH
anno
ver
Hoh
enpe
isse
nber
gKe
mpt
enKr
edar
ica
Pots
dam
Sonn
blic
kW
ien
Cal
aras
iKy
ivLu
gans
kBi
arrit
zVa
lenc
iaBr
indi
siLa
rissa
Sara
jevo
Fini
keC
hani
a
[°C]
MAMJJASONDJF
RR
0
50
100
150
200
250
300
Dal
atan
giVe
stm
anna
eyja
rBu
lken
Lien
_i_S
elbu
Stor
now
ayW
addi
ngto
nH
elsi
nki
Oes
ters
und
Bam
berg
Han
nove
rH
ohen
peis
senb
erg
Kem
pten
Kred
aric
aPo
tsda
mSo
nnbl
ick
Wie
nC
alar
asi
Kyiv
Luga
nsk
San_
Seba
stia
nVa
lenc
iaBr
indi
siLa
rissa
Sara
jevo
Cha
nia
[mm
]
(b) standard deviation of seasonal means
Results – seasonal climatic trends
trend significant at the 95% level
TX
-2
-1
0
1
2
3
4
Dal
atan
giVe
stm
anna
eyja
rG
lom
fjord
Osl
oSt
orno
way
Wad
ding
ton
Hel
sink
iO
este
rsun
dBa
mbe
rgH
anno
ver
Hoh
enpe
isse
nber
gKe
mpt
enKr
edar
ica
Pots
dam
Sonn
blic
kW
ien
Cal
aras
iKy
ivLu
gans
kBi
arrit
zVa
lenc
iaBr
indi
siLa
rissa
Sara
jevo
Fini
keC
hani
a
[°C
/40
yrs] MAM
JJASONDJFMAM
TN
-2
-1
0
1
2
3
4
Dal
atan
giVe
stm
anna
eyja
rG
lom
fjord
Osl
oSt
orno
way
Wad
ding
ton
Hel
sink
iO
este
rsun
dBa
mbe
rgH
anno
ver
Hoh
enpe
isse
nber
gKe
mpt
enKr
edar
ica
Pots
dam
Sonn
blic
kW
ien
Cal
aras
iKy
ivLu
gans
kBi
arrit
zVa
lenc
iaBr
indi
siLa
rissa
Sara
jevo
Fini
keC
hani
a
[°C
/40
yrs]
MAMJJASONDJF
RR
-200-100
0100
200300
400500
Dal
atan
giVe
stm
anna
eyja
rBu
lken
Lien
_i_S
elbu
Stor
now
ayW
addi
ngto
nH
elsi
nki
Oes
ters
und
Bam
berg
Han
nove
rH
ohen
peis
senb
erg
Kem
pten
Kred
aric
aPo
tsda
mSo
nnbl
ick
Wie
nC
alar
asi
Kyiv
Luga
nsk
San_
Seba
stia
nVa
lenc
iaBr
indi
siLa
rissa
Sara
jevo
Cha
nia
[mm
/sea
son/
40
yrs]
MAMJJASONDJFMAM
(a) trend per 40 years (1961-2000) magnitude of linear trend per 40 years (1961-2000)
massive winter warming at most stations
autumn cooling in Central and Eastern Europe – decreasing daily temperature range
few stations report significant trends in precipitation
2. Decomposition of climatic change that took place between the 1st and the2nd half of the period into frequency-related and within-type change.See e.g. Beck, Jacobeit, Jones (2007).
1. Ratio of “hypothetical” (circulation-induced) and observed long-term seasonal trends. The “hypothetical” trend is calculated from a daily series, constructed by assigning the long-term monthly mean of the given variable under the specific circulation type to each day. See e.g. Huth (2001).
We have studied seasonal linear trends in the frequency of CTs in 24classifications in cat. 1.2 and their relations with trends of Tmax, Tmin, andprecipitation in European regions in the period 1961-2000.
Significant trends in the frequency of CTs occur mostly in winter in domains00 and 04 through 11, and also in summer in the Mediterranean.
Climatic trends can be only partly explained by the changing frequency ofCTs, the link being the strongest in winter. In the other seasons, within-type climatic trends are responsible for a major part of the observed trends.
Classifications in the small domains are usually more tightly connected withclimatic trends than those in D00, except for the northernmost stations.
There are large differences between results obtained with individualclassifications – therefore all studies using just a limited number of themshould be taken with a grain of salt.
References
Cahynová M., Huth R. (2009): Are recent climatic trends in Europecaused by circulation changes? (poster)EGU General Assembly
Cahynová M., Huth R. (2010): Relations of atmospheric circulationand recent climatic variability and trends in Europe – a comparativeapproach based on the COST733 classifications database (poster)10th EMS/8th ECAC
Cahynová M. (2010): The influence of long-term changes ofatmospheric circulation on observed trends of surface climaticelements in the Czech Republic and EuropePhD thesis to be defended on December 14, 2010