Variabilidad espacio-temporal de los efectos de la NAO en Europa: impactos a distintas escalas...
21
Variabilidad espacio-temporal de los efectos de la NAO en Europa: impactos a distintas escalas temporales, variabilidad interdecadal y escenarios futuros Instituto Pirenaico de Ecología, Instituto Pirenaico de Ecología, CSIC, CSIC, Campus de Aula Dei, P.O. Box 202, Zaragoza 50080, Spain; Campus de Aula Dei, P.O. Box 202, Zaragoza 50080, Spain; e-mail: [email protected] e-mail: [email protected] Vicente-Serrano SM, López-Moreno JI Vicente-Serrano SM, López-Moreno JI
-
Upload
odalys-dudman -
Category
Documents
-
view
218 -
download
0
Transcript of Variabilidad espacio-temporal de los efectos de la NAO en Europa: impactos a distintas escalas...
Variabilidad espacio-temporal de los efectos de la NAO en Europa:
impactos adistintas escalas temporales,
variabilidad interdecadal y escenarios futuros
Instituto Pirenaico de Ecología, Instituto Pirenaico de Ecología, CSIC,CSIC,Campus de Aula Dei, P.O. Box 202, Zaragoza 50080, Spain; Campus de Aula Dei, P.O. Box 202, Zaragoza 50080, Spain; e-mail: [email protected]: [email protected]
Vicente-Serrano SM, López-Moreno JIVicente-Serrano SM, López-Moreno JI
0 5 10 15 20 25 30 35 40 45 50 55 60
Var
ian
ce e
xpla
ined
(%
)
0
1
23
4
5
6
7
8
910
11
1213
14
15
1617
Acc
um
ula
ted
var
ian
ce (
%)
10
20
30
40
50
60
70
80
90
100
Homogeneous regions according to the precipitation variabilityHomogeneous regions according to the precipitation variability
We used a monthly gridded precipitation database at a latitude/longitude resolution of 10’ for the entire European continent, as compiled by the Climate Research Unit of the
University of East Anglia (http://www.cru.uea.ac.uk/~timm/grid/TYN_SC_1_0.html
[Mitchell and Jones, 2005]).
1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000
SP
I
-3
-2
-1
0
1
2
3SPI1
1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000
SP
I
-3
-2
-1
0
1
2
3SPI3
1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000
SP
I
-3
-2
-1
0
1
2
3SPI6
1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000
SP
I
-3
-2
-1
0
1
2
3SPI12
1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000
SP
I
-3
-2
-1
0
1
2
3SPI1
1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000
SP
I
-3
-2
-1
0
1
2
3SPI3
1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000S
PI
-3
-2
-1
0
1
2
3SPI6
1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000
SP
I
-3
-2
-1
0
1
2
3SPI12
A) B)
Drought index calculation in each 10’ pixel at different time scales (1-12 months)Drought index calculation in each 10’ pixel at different time scales (1-12 months)
A) Region 5: British IslandsB) Region 6: Iberian Peninsula
SPI1
J F M A M J J A S O N D
SP
I
-1.0
-0.5
0.0
0.5
1.0 SPI1
J F M A M J J A S O N D
SP
I
-1.0
-0.5
0.0
0.5
1.0
A) B)
SPI3
J F M A M J J A S O N D
SP
I
-1.0
-0.5
0.0
0.5
1.0 SPI3
J F M A M J J A S O N D
SP
I
-1.0
-0.5
0.0
0.5
1.0
SPI6
J F M A M J J A S O N D
SP
I
-1.0
-0.5
0.0
0.5
1.0 SPI6
J F M A M J J A S O N D
SP
I
-1.0
-0.5
0.0
0.5
1.0
SPI12
J F M A M J J A S O N D
SP
I
-1.0
-0.5
0.0
0.5
1.0 SPI12
J F M A M J J A S O N D
SP
I
-1.0
-0.5
0.0
0.5
1.0
1 2 3 4 5 6 7 8 9 10 11 12
1
2
3
4
5
6
7
8
9
10
11
12
12
11
10
9
8
7
6
5
4
3
2
1
121110987654321
1 2 3 4 5 6 7 8 9 10 11 12
1
2
3
4
5
6
7
8
9
10
11
12
12
11
10
9
8
7
6
5
4
3
2
1
121110987654321
1 2 3 4 5 6 7 8 9 10 11 12
1
2
3
4
5
6
7
8
9
10
11
12
12
11
10
9
8
7
6
5
4
3
2
1
121110987654321 1 2 3 4 5 6 7 8 9 10 11 12
1
2
3
4
5
6
7
8
9
10
11
12
12
11
10
9
8
7
6
5
4
3
2
1
121110987654321
1 2 3 4 5 6 7 8 9 10 11 12
1
2
3
4
5
6
7
8
9
10
11
12
12
11
10
9
8
7
6
5
4
3
2
1
121110987654321
1 2 3 4 5 6 7 8 9 10 11 12
1
2
3
4
5
6
7
8
9
10
11
12
12
11
10
9
8
7
6
5
4
3
2
1
121110987654321 1 2 3 4 5 6 7 8 9 10 11 12
1
2
3
4
5
6
7
8
9
10
11
12
12
11
10
9
8
7
6
5
4
3
2
1
121110987654321
1 2 3 4 5 6 7 8 9 10 11 12
1
2
3
4
5
6
7
8
9
10
11
12
12
11
10
9
8
7
6
5
4
3
2
1
121110987654321
1 2 3 4 5 6 7 8 9 10 11 12
1
2
3
4
5
6
7
8
9
10
11
12
1 2 3
654
10 11 12
987
13 14 15
1716
SPI (time scale)
Mo
nth
(1 =
Dec
em
ber
)
A)
<-0.8-0.8 to -0.6-0.6 to -0.4-0.4 to -0.2-0.2 to 00 to 0.20.2 to 0.40.4 to 0.60.6 to 0.8> 0.8
16 17
151413
7 8 9
121110
4 5 6
321
12
11
10
9
8
7
6
5
4
3
2
1
121110987654321
1 2 3 4 5 6 7 8 9 10 11 12
1
2
3
4
5
6
7
8
9
10
11
12
12
11
10
9
8
7
6
5
4
3
2
1
121110987654321
1 2 3 4 5 6 7 8 9 10 11 12
1
2
3
4
5
6
7
8
9
10
11
12
12
11
10
9
8
7
6
5
4
3
2
1
1211109876543211 2 3 4 5 6 7 8 9 10 11 12
1
2
3
4
5
6
7
8
9
10
11
12
12
11
10
9
8
7
6
5
4
3
2
1
121110987654321
1 2 3 4 5 6 7 8 9 10 11 12
1
2
3
4
5
6
7
8
9
10
11
12
12
11
10
9
8
7
6
5
4
3
2
1
121110987654321
1 2 3 4 5 6 7 8 9 10 11 12
1
2
3
4
5
6
7
8
9
10
11
12
12
11
10
9
8
7
6
5
4
3
2
1
1211109876543211 2 3 4 5 6 7 8 9 10 11 12
1
2
3
4
5
6
7
8
9
10
11
12
12
11
10
9
8
7
6
5
4
3
2
1
121110987654321
1 2 3 4 5 6 7 8 9 10 11 12
1
2
3
4
5
6
7
8
9
10
11
12
12
11
10
9
8
7
6
5
4
3
2
1
121110987654321
1 2 3 4 5 6 7 8 9 10 11 12
1
2
3
4
5
6
7
8
9
10
11
12
12
11
10
9
8
7
6
5
4
3
2
1
121110987654321
SPI (time scale)M
on
th(1
= D
ece
mb
er)
B)
1 2 3 4 5 6 7 8 9 10 11 12
1
2
3
4
5
6
7
8
9
10
11
12
12
11
10
9
8
7
6
5
4
3
2
1
121110987654321
1 2 3 4 5 6 7 8 9 10 11 12
1
2
3
4
5
6
7
8
9
10
11
12
12
11
10
9
8
7
6
5
4
3
2
1
121110987654321
1 2 3 4 5 6 7 8 9 10 11 12
1
2
3
4
5
6
7
8
9
10
11
12
12
11
10
9
8
7
6
5
4
3
2
1
121110987654321 1 2 3 4 5 6 7 8 9 10 11 12
1
2
3
4
5
6
7
8
9
10
11
12
12
11
10
9
8
7
6
5
4
3
2
1
121110987654321
1 2 3 4 5 6 7 8 9 10 11 12
1
2
3
4
5
6
7
8
9
10
11
12
12
11
10
9
8
7
6
5
4
3
2
1
121110987654321
1 2 3 4 5 6 7 8 9 10 11 12
1
2
3
4
5
6
7
8
9
10
11
12
12
11
10
9
8
7
6
5
4
3
2
1
121110987654321 1 2 3 4 5 6 7 8 9 10 11 12
1
2
3
4
5
6
7
8
9
10
11
12
12
11
10
9
8
7
6
5
4
3
2
1
121110987654321
1 2 3 4 5 6 7 8 9 10 11 12
1
2
3
4
5
6
7
8
9
10
11
12
12
11
10
9
8
7
6
5
4
3
2
1
121110987654321
1 2 3 4 5 6 7 8 9 10 11 12
1
2
3
4
5
6
7
8
9
10
11
12
1 2 3
654
10 11 12
987
13 14 15
1716
SPI (time scale)
Mo
nth
(1 =
Dec
em
ber
)
A)
<-0.8-0.8 to -0.6-0.6 to -0.4-0.4 to -0.2-0.2 to 00 to 0.20.2 to 0.40.4 to 0.60.6 to 0.8> 0.8
16 17
151413
7 8 9
121110
4 5 6
321
12
11
10
9
8
7
6
5
4
3
2
1
121110987654321
1 2 3 4 5 6 7 8 9 10 11 12
1
2
3
4
5
6
7
8
9
10
11
12
12
11
10
9
8
7
6
5
4
3
2
1
121110987654321
1 2 3 4 5 6 7 8 9 10 11 12
1
2
3
4
5
6
7
8
9
10
11
12
12
11
10
9
8
7
6
5
4
3
2
1
1211109876543211 2 3 4 5 6 7 8 9 10 11 12
1
2
3
4
5
6
7
8
9
10
11
12
12
11
10
9
8
7
6
5
4
3
2
1
121110987654321
1 2 3 4 5 6 7 8 9 10 11 12
1
2
3
4
5
6
7
8
9
10
11
12
12
11
10
9
8
7
6
5
4
3
2
1
121110987654321
1 2 3 4 5 6 7 8 9 10 11 12
1
2
3
4
5
6
7
8
9
10
11
12
12
11
10
9
8
7
6
5
4
3
2
1
1211109876543211 2 3 4 5 6 7 8 9 10 11 12
1
2
3
4
5
6
7
8
9
10
11
12
12
11
10
9
8
7
6
5
4
3
2
1
121110987654321
1 2 3 4 5 6 7 8 9 10 11 12
1
2
3
4
5
6
7
8
9
10
11
12
12
11
10
9
8
7
6
5
4
3
2
1
121110987654321
1 2 3 4 5 6 7 8 9 10 11 12
1
2
3
4
5
6
7
8
9
10
11
12
12
11
10
9
8
7
6
5
4
3
2
1
121110987654321
SPI (time scale)M
on
th(1
= D
ece
mb
er)
B)
-3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 3.0
12.0
11.0
10.0
9.0
8.0
7.0
6.0
5.0
4.0
3.0
2.0
1.0
0.0
12.0
11.0
10.0
9.0
8.0
7.0
6.0
5.0
4.0
3.0
2.0
1.0
0.0
Winter NAO Index
Ab
so
lute
fre
qu
en
cy
SPI ANOMALIES IN THE BRITISH ISLANDSA) Positive phasesB) Negative phases
Positive phases
Negative phases
SPI anomalies according to the positive and negative phases of the NAOSPI anomalies according to the positive and negative phases of the NAO
SPI ANOMALIES IN THE DIFFERENT REGIONSA) Positive phasesB) Negative phases
12-months SPI anomalies in August12-months SPI anomalies in August
SPI (time scale)
Mo
nth
(1 =
Dec
emb
er)
A)
SPI (time scale)
Mo
nth
(1 =
Dec
emb
er)
B)
16 17
151413
7 8 9
121110
4 5 6
321
12
11
10
9
8
7
6
5
4
3
2
1
121110987654321
1 2 3 4 5 6 7 8 9 10 11 12
1
2
3
4
5
6
7
8
9
10
11
12
12
11
10
9
8
7
6
5
4
3
2
1
121110987654321
1 2 3 4 5 6 7 8 9 10 11 12
1
2
3
4
5
6
7
8
9
10
11
12
12
11
10
9
8
7
6
5
4
3
2
1
1211109876543211 2 3 4 5 6 7 8 9 10 11 12
1
2
3
4
5
6
7
8
9
10
11
12
12
11
10
9
8
7
6
5
4
3
2
1
121110987654321
1 2 3 4 5 6 7 8 9 10 11 12
1
2
3
4
5
6
7
8
9
10
11
12
12
11
10
9
8
7
6
5
4
3
2
1
121110987654321
1 2 3 4 5 6 7 8 9 10 11 12
1
2
3
4
5
6
7
8
9
10
11
12
12
11
10
9
8
7
6
5
4
3
2
1
1211109876543211 2 3 4 5 6 7 8 9 10 11 12
1
2
3
4
5
6
7
8
9
10
11
12
12
11
10
9
8
7
6
5
4
3
2
1
121110987654321
1 2 3 4 5 6 7 8 9 10 11 12
1
2
3
4
5
6
7
8
9
10
11
12
12
11
10
9
8
7
6
5
4
3
2
1
121110987654321
1 2 3 4 5 6 7 8 9 10 11 12
1
2
3
4
5
6
7
8
9
10
11
12
12
11
10
9
8
7
6
5
4
3
2
1
121110987654321 1 2 3 4 5 6 7 8 9 10 11 12
1
2
3
4
5
6
7
8
9
10
11
12
12
11
10
9
8
7
6
5
4
3
2
1
121110987654321
1 2 3 4 5 6 7 8 9 10 11 12
1
2
3
4
5
6
7
8
9
10
11
12
12
11
10
9
8
7
6
5
4
3
2
1
121110987654321
1 2 3 4 5 6 7 8 9 10 11 12
1
2
3
4
5
6
7
8
9
10
11
12
12
11
10
9
8
7
6
5
4
3
2
1
121110987654321 1 2 3 4 5 6 7 8 9 10 11 12
1
2
3
4
5
6
7
8
9
10
11
12
12
11
10
9
8
7
6
5
4
3
2
1
121110987654321
1 2 3 4 5 6 7 8 9 10 11 12
1
2
3
4
5
6
7
8
9
10
11
12
12
11
10
9
8
7
6
5
4
3
2
1
121110987654321
1 2 3 4 5 6 7 8 9 10 11 12
1
2
3
4
5
6
7
8
9
10
11
12
12
11
10
9
8
7
6
5
4
3
2
1
121110987654321 1 2 3 4 5 6 7 8 9 10 11 12
1
2
3
4
5
6
7
8
9
10
11
12
12
11
10
9
8
7
6
5
4
3
2
1
121110987654321
1 2 3 4 5 6 7 8 9 10 11 12
1
2
3
4
5
6
7
8
9
10
11
12
12
11
10
9
8
7
6
5
4
3
2
1
121110987654321
1 2 3 4 5 6 7 8 9 10 11 12
1
2
3
4
5
6
7
8
9
10
11
12
1 2 3
654
10 11 12
987
13 14 15
1716
<-0.8-0.8 to -0.6-0.6 to -0.4-0.4 to -0.2-0.2 to 00 to 0.20.2 to 0.40.4 to 0.60.6 to 0.8> 0.8
SPI (time scale)
Mo
nth
(1 =
Dec
emb
er)
A)
SPI (time scale)
Mo
nth
(1 =
Dec
emb
er)
B)
16 17
151413
7 8 9
121110
4 5 6
321
12
11
10
9
8
7
6
5
4
3
2
1
121110987654321
1 2 3 4 5 6 7 8 9 10 11 12
1
2
3
4
5
6
7
8
9
10
11
12
12
11
10
9
8
7
6
5
4
3
2
1
121110987654321
1 2 3 4 5 6 7 8 9 10 11 12
1
2
3
4
5
6
7
8
9
10
11
12
12
11
10
9
8
7
6
5
4
3
2
1
1211109876543211 2 3 4 5 6 7 8 9 10 11 12
1
2
3
4
5
6
7
8
9
10
11
12
12
11
10
9
8
7
6
5
4
3
2
1
121110987654321
1 2 3 4 5 6 7 8 9 10 11 12
1
2
3
4
5
6
7
8
9
10
11
12
12
11
10
9
8
7
6
5
4
3
2
1
121110987654321
1 2 3 4 5 6 7 8 9 10 11 12
1
2
3
4
5
6
7
8
9
10
11
12
12
11
10
9
8
7
6
5
4
3
2
1
1211109876543211 2 3 4 5 6 7 8 9 10 11 12
1
2
3
4
5
6
7
8
9
10
11
12
12
11
10
9
8
7
6
5
4
3
2
1
121110987654321
1 2 3 4 5 6 7 8 9 10 11 12
1
2
3
4
5
6
7
8
9
10
11
12
12
11
10
9
8
7
6
5
4
3
2
1
121110987654321
1 2 3 4 5 6 7 8 9 10 11 12
1
2
3
4
5
6
7
8
9
10
11
12
12
11
10
9
8
7
6
5
4
3
2
1
121110987654321 1 2 3 4 5 6 7 8 9 10 11 12
1
2
3
4
5
6
7
8
9
10
11
12
12
11
10
9
8
7
6
5
4
3
2
1
121110987654321
1 2 3 4 5 6 7 8 9 10 11 12
1
2
3
4
5
6
7
8
9
10
11
12
12
11
10
9
8
7
6
5
4
3
2
1
121110987654321
1 2 3 4 5 6 7 8 9 10 11 12
1
2
3
4
5
6
7
8
9
10
11
12
12
11
10
9
8
7
6
5
4
3
2
1
121110987654321 1 2 3 4 5 6 7 8 9 10 11 12
1
2
3
4
5
6
7
8
9
10
11
12
12
11
10
9
8
7
6
5
4
3
2
1
121110987654321
1 2 3 4 5 6 7 8 9 10 11 12
1
2
3
4
5
6
7
8
9
10
11
12
12
11
10
9
8
7
6
5
4
3
2
1
121110987654321
1 2 3 4 5 6 7 8 9 10 11 12
1
2
3
4
5
6
7
8
9
10
11
12
12
11
10
9
8
7
6
5
4
3
2
1
121110987654321 1 2 3 4 5 6 7 8 9 10 11 12
1
2
3
4
5
6
7
8
9
10
11
12
12
11
10
9
8
7
6
5
4
3
2
1
121110987654321
1 2 3 4 5 6 7 8 9 10 11 12
1
2
3
4
5
6
7
8
9
10
11
12
12
11
10
9
8
7
6
5
4
3
2
1
121110987654321
1 2 3 4 5 6 7 8 9 10 11 12
1
2
3
4
5
6
7
8
9
10
11
12
1 2 3
654
10 11 12
987
13 14 15
1716
<-0.8-0.8 to -0.6-0.6 to -0.4-0.4 to -0.2-0.2 to 00 to 0.20.2 to 0.40.4 to 0.60.6 to 0.8> 0.8
Non-stationary relationships. Noticeable differences between the 1900-1950 and 1950-2000 periodsNon-stationary relationships. Noticeable differences between the 1900-1950 and 1950-2000 periods
Difference [(1951-2000)-(1901-1950)] in the average values of SPI at time scales from 1 to 12 months between December (1) and November (12) during the positive (A) and negative (B) extreme phases of the NAO in the 17 homogeneous regions.
Black lines indicate significant differences ( < 0.05) between the average SPI during the positive and negative years between the first and the second half of the twentieth century.
Non-stationary relationships. Noticeable differences between the 1900-1950 and 1950-2000 periodsNon-stationary relationships. Noticeable differences between the 1900-1950 and 1950-2000 periods
MarchFebruaryJanuaryDecember
0
1-1 -2 -3
2
-4
3
-5
0
-2
-1
0
1
-3 2
1
-1
3
-2
4
5
-3
6
-4
7
-5
8
-6
9
1
2
0
-1
21
0
3
-4-3
-1
4
-5
52
-4
0
-3
21
-5
321
45
0
6
-1-2
5
2
3
1
00
1
0
2
-1
-2 -3
-4
-53
-6
4
- 7
5
1
2
2
1
0
1
0-1
2
-2
3
4 -3
56
-4
12
2
0 0
-3
-4 -1
01
2
-2
-1
1
1
2
0
0
-2
-20
1
-1
-2
2
3
4
-3
0December January February March
A)
B)
Differences in the average anomalies of SLP during the positive (A) and negative (B) extreme phases of the NAO between the 1951-2000 and 1901-1950 periods.
During positive phases changes reinforced flows from the NW, and these flows affected most of Europe. This During positive phases changes reinforced flows from the NW, and these flows affected most of Europe. This reinforcement was most pronounced in March.reinforcement was most pronounced in March.
The results indicate the attenuation of the pressure fields that are typically associated with negative phases of the The results indicate the attenuation of the pressure fields that are typically associated with negative phases of the NAO during winter. NAO during winter.
The decrease in SPI values recorded over large areas of western and central Europe is possibly related to the The decrease in SPI values recorded over large areas of western and central Europe is possibly related to the generally positive SLP differences recorded in this region during negative phases.generally positive SLP differences recorded in this region during negative phases.
CONCLUSIONS:CONCLUSIONS:
The response of droughtsThe response of droughts to positive and negative phases of the NAO to positive and negative phases of the NAO vary spatiallyvary spatially and also depend on the month and also depend on the month and decade and time scale of the SPI. In general, during positive phases, negative SPI averages are recorded in and decade and time scale of the SPI. In general, during positive phases, negative SPI averages are recorded in Southern Europe and positive averages in Northern Europe (Scandinavia and the British Islands), whereas the Southern Europe and positive averages in Northern Europe (Scandinavia and the British Islands), whereas the opposite trends occur during negative phases. opposite trends occur during negative phases.
It is necessary to highlight the outstanding It is necessary to highlight the outstanding influence of positive and negative phasesinfluence of positive and negative phases of the wintertime NAO on of the wintertime NAO on drought conditions drought conditions during the succeeding monthsduring the succeeding months. In the areas of the Iberian Peninsula, South Italy, and the . In the areas of the Iberian Peninsula, South Italy, and the Balkans, strong negative SPI averages, indicative of Balkans, strong negative SPI averages, indicative of severe drought conditions, are recorded in summer and severe drought conditions, are recorded in summer and autumn during positive phasesautumn during positive phases when medium and long time scales of SPI (6–12 months) are considered. The when medium and long time scales of SPI (6–12 months) are considered. The same trends are recognized for Sweden, Finland, Lithuania, Latvia, and West Norway as a response to the same trends are recognized for Sweden, Finland, Lithuania, Latvia, and West Norway as a response to the negative phases of the NAO. The fact that this behavior is found in several regions is indicative of the negative phases of the NAO. The fact that this behavior is found in several regions is indicative of the important important impact of positive and negative phases of the wintertime NAO on usable water sources throughout the impact of positive and negative phases of the wintertime NAO on usable water sources throughout the yearyear. .
Another important result observed for multiple regions is the fact that the magnitude of anomalies in average SPI values Another important result observed for multiple regions is the fact that the magnitude of anomalies in average SPI values differs between positive and negative phases of the NAO. This indicates the differs between positive and negative phases of the NAO. This indicates the asymmetric response of droughts asymmetric response of droughts to the NAO. to the NAO.
The effectsThe effects of positive and negative phases of the NAO on droughts within the European continent at different time of positive and negative phases of the NAO on droughts within the European continent at different time scales were scales were not stablenot stable during the 20th century. In general, during the 20th century. In general, the influencethe influence of positive phases of the NAO on of positive phases of the NAO on droughts droughts is strengthenedis strengthened in the second half of the 20th century compared to the influence in the period 1901– in the second half of the 20th century compared to the influence in the period 1901–1950. In contrast, the negative phases of the wintertime NAO show a weaker influence on the SPI during the 1950. In contrast, the negative phases of the wintertime NAO show a weaker influence on the SPI during the second half of the 20th century. second half of the 20th century. This behavior is related to changes in the SLP patternsThis behavior is related to changes in the SLP patterns associated with associated with positive and negative phases of the NAO during the first and second halves of the 20th century. positive and negative phases of the NAO during the first and second halves of the 20th century.
Right: spatial distribution of correlations between winter precipitation and the NAO index obtained from observations between 1902 and 2000.
Left: leading principal component of winter SLPs. T-mode PCA
We used a monthly gridded precipitation database at a latitude/longitude resolution of 10’ for the entire European continent, as compiled by the Climate Research Unit of the University of East Anglia (http://www.cru.uea.ac.uk/~timm/grid/TYN_SC_1_0.html [Mitchell and Jones, 2005]).
The pressure data set was provided by NCEP-NCAR (http://dss.ucar.edu/datasets/ds010.1/), with a spatial latitude/ longitude resolution of 5º. The 5º latitude/longitude grids begin in 1899, and cover the North Atlantic region (20ºN–80ºN,
90ºW–40ºE). The few data gaps in the data set were filled by interpolation (splines with tension) using the data of neighboring grid points.
20th century pattern of the NAO and NAO/precipitation relationship20th century pattern of the NAO and NAO/precipitation relationship
Timisoara
1900 1920 1940 1960 1980 2000
Mo
vin
g w
ind
ow
co
rre
lati
on
-0.8
-0.6
-0.4
-0.2
0.0Wien
1900 1920 1940 1960 1980 2000-0.6
-0.4
-0.2
0.0
0.2
Madrid
1900 1920 1940 1960 1980 2000
Mo
vin
g w
ind
ow
co
rre
lati
on
-0.9
-0.8
-0.7
-0.6
-0.5
-0.4
-0.3
-0.2Paris
1900 1920 1940 1960 1980 2000-0.6
-0.4
-0.2
0.0
0.2
Uppsala
1900 1920 1940 1960 1980 2000
Mo
vin
g w
ind
ow
co
rre
lati
on
-0.2
0.0
0.2
0.4
0.6Bodo
1900 1920 1940 1960 1980 2000-0.2
0.0
0.2
0.4
0.6
0.8
Lisbon
1900 1920 1940 1960 1980 2000-0.9
-0.8
-0.7
-0.6
-0.5
-0.4
-0.3
-0.2
Dublin
1900 1920 1940 1960 1980 2000-0.6
-0.4
-0.2
0.0
0.2
0.4
Observatory series
Grid series
Example of 31-year moving-window correlations between the winter NAO and precipitation for points throughout the European continent. Red lines represent the temporal evolution of NAO-precipitation correlations for selected points in the gridded
database (grey in the map). Blue lines represent moving-window correlations for instrumental observatories with complete records for the period 1902-2000 (black in the map). Horizontal dotted lines represent the significance threshold at 95%.
Observatory data were obtained from the Global Historical Climatology Network (http://www.ncdc.noaa.gov/oa/climate/ghcn-monthly/).
Evolution of moving correlations inform about the markedly unstable response with time of European Evolution of moving correlations inform about the markedly unstable response with time of European precipitation to NAO index.precipitation to NAO index.
1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000
No
rth
Atl
anti
c O
scil
lati
on
-3
-2
-1
0
1
2
3
4
GIBRALTAR
AZORESPRINC. COMPONENT
Right: temporal evolution of three different NAO indices. GIBRALTAR shows the NAO index calculated as the difference between the monthly standardized surface pressures at Gibraltar (south-west Iberian
Peninsula) and Reykjavik (south-west Iceland). AZORES was obtained from the Ponta Delgada station (the Azores), and the third NAO index corresponds to the principal component (PRINC. COMPONENT) time series of the leading PC of SLP anomalies over the
Atlantic sector (20º–80ºN, 90ºW–40ºE).
A–C) Maps of the correlation between the precipitation series and the GIBRALTAR, AZORES,
and PRINC. COMPONENT NAO indices, respectively. Units are Pearson coefficients of correlation (r). The correlations were calculated for 31-year periods, of which the central years are indicated in each plot.
Dotted lines enclose areas with significant correlations (p < 0.05).
Non-stationarity does not depend on the method used to obtain the NAO index. The evolution of NAO indices is Non-stationarity does not depend on the method used to obtain the NAO index. The evolution of NAO indices is rather similar whether they are obtained from pattern-based methods or station/grid point-based rather similar whether they are obtained from pattern-based methods or station/grid point-based approaches.approaches.
Right: spatial distribution of correlations between winter precipitation and the NAO index during the 20th century. The year indicated on each map represents the midpoint of each 31-year period. Units are Pearson coefficients of correlation (r). Dotted lines enclose areas with significant correlations (p < 0.05).
Left: leading principal components of winter SLPs obtained from T-mode PCA. The leading principal components were obtained using moving-window periods of 31 years, centered on the year indicated in each plot. The percentage of variance explained by the leading mode in each period is also shown. Since t he sign of the PC pattern is arbitrary and to make easier the comparison, a common sign of the NAO was selecting for plotted (negative in the North and positive in the South).
Although the general pattern of negative (positive) correlations in the south (north) of Europe between winter Although the general pattern of negative (positive) correlations in the south (north) of Europe between winter precipitation and NAO index appears generally well defined for all subperiods, the spatial pattern and precipitation and NAO index appears generally well defined for all subperiods, the spatial pattern and magnitude of the correlations varied noticeably over time. The spatial patterns of changes in correlations magnitude of the correlations varied noticeably over time. The spatial patterns of changes in correlations are in agreement with the shifts in position of the main sea level pressure (SLP) centers that characterized are in agreement with the shifts in position of the main sea level pressure (SLP) centers that characterized the NAO dipole throughout the twentieth centurythe NAO dipole throughout the twentieth century
Right: spatial distribution of correlations between winter precipitation and the NAO index during the 19th century. The year indicated on each map represents the midpoint of each 31-year period. Units are Pearson coefficients of correlation (r). Dotted lines enclose areas with significant correlations (p < 0.05).
Left: leading principal components of winter SLPs obtained from T-mode PCA. The leading principal components were obtained using moving-window periods of 31 years, centered on the year indicated in each plot. The percentage of variance explained by the leading mode in each period is also shown. Since the sign of the PC pattern is
arbitrary and to make easier the comparison, a common sign of the NAO was selecting for plotted (negative in the North and positive in the South).
Results are based on reconstructions performed by the Climatology and Meteorology Research Group of the University of Bern (Switzerland).
Interdecadal shifts in the locations of NAO pressure centers were not only unique for the twentieth century, andInterdecadal shifts in the locations of NAO pressure centers were not only unique for the twentieth century, andthey also contribute to most of the changes recorded in the NAO-precipitation relationship since at least the late they also contribute to most of the changes recorded in the NAO-precipitation relationship since at least the late
eighteenth century, analyzed by means of climate reconstructionseighteenth century, analyzed by means of climate reconstructions
1. Right: spatial distribution of correlations between winter precipitation and the NAO index obtained from observations between 1902 and 2000. Left: leading principal component of winter SLPs form
observations.
2. Right: spatial distribution of correlations between winter precipitation and the NAO index obtained from CGCM3.1(T63) model,
Canadian Climate Modeling and Analysis Centre, simulations between 1870 and 1999. Left: leading principal component of winter SLPs simulated from the CGCM3.1(T63) model under the 20th century
emissions scenario. The percentage of variance explained by the leading modes is also shown.
Right: spatial distribution of correlations between winter precipitation and the NAO index from the outputs of the CGCM3.1(T63) model under the 20th century emissions
scenario. The year indicated on each map represents the midpoint of each 31-year period. Units are Pearson coefficients of correlation (r). Dotted lines enclose areas with
significant correlations (p < 0.05).
Left: leading principal components of winter SLPs obtained from T-mode PCA. The leading principal components were obtained using moving-window periods of 31 years, centered on the year indicated in each plot. The percentage of variance explained by the leading mode in each period is also shown. Since the sign of the PC pattern is arbitrary
and to make easier the comparison, a common sign of the NAO was selecting for plotted (negative in the North and positive in the South).
Similar results were obtained from climate data under a twentieth century emissions scenario (20C3M) modeled Similar results were obtained from climate data under a twentieth century emissions scenario (20C3M) modeled using the CGCM3.1(T63) model. Although some differences between the NAO spatial pattern obtained using the CGCM3.1(T63) model. Although some differences between the NAO spatial pattern obtained from observations and the model can be observed: mainly the split of the southern center and the from observations and the model can be observed: mainly the split of the southern center and the southern shift of the eastern part of the southern center; the model records the main features, although southern shift of the eastern part of the southern center; the model records the main features, although more simplified than observations.more simplified than observations.
A)
B)
A) Spatial distribution of rotated principal component scores obtained from leading PCs in the SLP moving-window T-mode PCA procedure for 20th century observations. Time series of loadings are also shown for each
component to identify the periods for which the NAO pattern is representative.
B) As for A), but using climate simulations of the CGCM3.1(T63) model for the IPCC 20th century emissions experiment.
The general patterns show The general patterns show that the dominant NAO that the dominant NAO configuration changes configuration changes noticeably over noticeably over decadal timescales. decadal timescales. Each of the four Each of the four patterns appears as patterns appears as the dominant NAO the dominant NAO configuration during configuration during several time slides. several time slides.
In the four patterns the In the four patterns the spatial structure, spatial structure, based on a pressure based on a pressure dipole, is clearly dipole, is clearly evident and is always evident and is always associated with the associated with the NAO pattern. NAO pattern.
Similar spatial structure has Similar spatial structure has been found using been found using observations and observations and simulations.simulations.
CONCLUSIONS:CONCLUSIONS:
The nonstationary relationship of the NAO is linked to interdecadal variability in the positions of the NAO The nonstationary relationship of the NAO is linked to interdecadal variability in the positions of the NAO pressure centers. pressure centers.
The spatial configuration of the NAO changes substantially prior to marked shifts in the magnitude and spatial The spatial configuration of the NAO changes substantially prior to marked shifts in the magnitude and spatial influences of the NAO on precipitation patterns in Europe. It points to the possible existence of different influences of the NAO on precipitation patterns in Europe. It points to the possible existence of different NAO types related to the location and surface extent of main pressure centers, which lead to very NAO types related to the location and surface extent of main pressure centers, which lead to very different climatic impacts over the European continent.different climatic impacts over the European continent.
The reliability of the results obtained is supported by evidence from the consistency of analyses conducted with The reliability of the results obtained is supported by evidence from the consistency of analyses conducted with observed data during the twentieth century, reconstructed precipitation and sea level pressure since observed data during the twentieth century, reconstructed precipitation and sea level pressure since 1785, and physically modeled climate by Atmosphere-Ocean Global Climate Models (AOGCMs). 1785, and physically modeled climate by Atmosphere-Ocean Global Climate Models (AOGCMs).
Our findings suggest that climate prediction and climate change scenarios based on the NAO must take Our findings suggest that climate prediction and climate change scenarios based on the NAO must take interdecadal shifts in the position of NAO pressure centers into account.interdecadal shifts in the position of NAO pressure centers into account.
The simulations of sea level pressure (SLP) for the North Atlantic region (20º–80ºN, 90ºW–40ºE) and precipitation The simulations of sea level pressure (SLP) for the North Atlantic region (20º–80ºN, 90ºW–40ºE) and precipitation for Europe from the AOGCM CGCM 3.1 (T63) model (single run) provided by the Canadian Centre for for Europe from the AOGCM CGCM 3.1 (T63) model (single run) provided by the Canadian Centre for Climate Modelling and Analysis does not show changes in the NAO index obtained for the 20th century Climate Modelling and Analysis does not show changes in the NAO index obtained for the 20th century under the 20C emission scenario, and for the 21st century for the B1 and A2 scenarios. under the 20C emission scenario, and for the 21st century for the B1 and A2 scenarios.
1900 1920 1940 1960 1980 2000 2020 2040 2060 2080 2100
NA
O in
dex
-1.5
-1.0
-0.5
0.0
0.5
1.0
1.5
B1
A2
20C
No important changes between the different emission scenarios in the spatial pattern of the NAO dipole and the No important changes between the different emission scenarios in the spatial pattern of the NAO dipole and the NAO-precipitation correlationsNAO-precipitation correlations
Analysis of moving window correlations showed marked differences among the four emission scenarios. In the Analysis of moving window correlations showed marked differences among the four emission scenarios. In the PI and 20C scenarios the spatial pattern of NAO/precipitation correlations changed noticeably among PI and 20C scenarios the spatial pattern of NAO/precipitation correlations changed noticeably among different periods. different periods.
The 31-year slices for the B1 and A2 emission scenarios also show some changes in the NAO/precipitation The 31-year slices for the B1 and A2 emission scenarios also show some changes in the NAO/precipitation correlations but they are more stable than observed for the PI and 20C scenario.correlations but they are more stable than observed for the PI and 20C scenario.
This is related to the few differences in the position and magnitude of the NAO pressure centers among different This is related to the few differences in the position and magnitude of the NAO pressure centers among different periods. periods.
It seems to have some relationship between the percentage of variance explained by the NAO and the It seems to have some relationship between the percentage of variance explained by the NAO and the magnitude and surface extent of correlations. In general, a smaller variance explained by the leading PC magnitude and surface extent of correlations. In general, a smaller variance explained by the leading PC (NAO) transfers to some extent into generally weaker relationship with precipitation and vice versa. (NAO) transfers to some extent into generally weaker relationship with precipitation and vice versa.
Higher variance values indicate a higher variability of the NAO-precipitation correlations throughout the Higher variance values indicate a higher variability of the NAO-precipitation correlations throughout the emission scenario simulation. There were large differences among the four scenarios. Higher variance emission scenario simulation. There were large differences among the four scenarios. Higher variance values were found for the PI and 20C emission scenarios. There was a decrease in variability in the values were found for the PI and 20C emission scenarios. There was a decrease in variability in the NAO/precipitation relationship in line with increased greenhouse gas concentrations.NAO/precipitation relationship in line with increased greenhouse gas concentrations.
CONCLUSIONS:CONCLUSIONS:
The scenarios showed a general decrease in the surface affected with significant positive correlations in The scenarios showed a general decrease in the surface affected with significant positive correlations in northern Europe and an increase in the magnitude of negative correlations in southern Europe, in parallel northern Europe and an increase in the magnitude of negative correlations in southern Europe, in parallel to increased greenhouse gas concentrations. The differences are in agreement with shifts in the location to increased greenhouse gas concentrations. The differences are in agreement with shifts in the location of the NAO pressure centers. of the NAO pressure centers.
Even more important than the changes in the spatial patterns are the changes expected in the temporal stability Even more important than the changes in the spatial patterns are the changes expected in the temporal stability of the NAO/precipitation relationship among the four emission scenarios. The PI and 20C scenarios of the NAO/precipitation relationship among the four emission scenarios. The PI and 20C scenarios showed large differences in the magnitude and spatial extent of the NAO/precipitation correlations among showed large differences in the magnitude and spatial extent of the NAO/precipitation correlations among different periods, as a consequence of shifts in the position of the NAO pressure centers. In addition, the different periods, as a consequence of shifts in the position of the NAO pressure centers. In addition, the NAO pressure centers appear to be more stable under increased greenhouse gas concentrations. NAO pressure centers appear to be more stable under increased greenhouse gas concentrations.
