European Conference on Applied Climatology

13-17 September 2010, Zurich, Switzerland

The Influence of Dominant Global

Climate Phenomena

ENSO, NAO, and AO on Climate in Serbia

Gordana Jovanović, Republic Hydrometeorological Service of Serbia,

Belgrade, Kneza Višeslava 66 gordana.jovanovic@hidmet.gov.rs

Irini Reljin, University of Belgrade, School of Electrical Engineering,

irini@etf.rs

Branimir Reljin, University of Belgrade, School of Electrical Engineering,

reljinb@etf.rs

The Influence of ENSO on Climate in SerbiaTime series of mean monthly SST for Niňo 3,4 & Serbia 1951-98

1951 1961 1971 1981 1991 year22

24

26

28

30Sea-surface temperatures of Niňo3,4 region from 1951 to 1998 yr.

0C

Average temperature 25.8 0C

Warmer than normal – El Niňo

Cooler than normal – La Niňa

1951 1961 1971 1981 1991 year-10

0

10

20

30Temperatures in Serbia from 1951 to 1998

0C Average temperature 10.6

0C

Time series of averaged monthly

temperatures in Serbia from 7 representative

main meteorological stations.

The analyses by the use of FFTFrequency spectra for Niňo 3,4 and Serbia

0 50 100 150 200 250 3000

0.2

0.4

0.6

0.8Amplitude FFT spectrum of temperatures in region Nino3,4

0 50 100 150 200 250 3000

2

4

6Amplitude FFT spectrum of temperatures in the Serbia region

Frequency bin = 1/48 yr-1

Frequency bin = 1/48 yr-1

The first harmonic (1 year)

The second harmonic (1/2 year)

The first harmonic (1 year)

The second harmonic (1/2 year)

(a)

(b)

Niňo 3,4 has

particularly

enhanced

cycles larger than

one year - left part

of diagram.

Teleconnection -

simultaneous,

recurrent

variation of

climate elements

on large

distances.

Cross-correlation analyses

12 8 5 3 2 1.5 year0

0.05

0.1

0.15

0.2

0.25Temperature spectra of regions Nino3,4 and Serbia

Serbia

6 4

Nino 3,4

500 550 600 650-1.0

-0.5

0.0

0.5

1.0

573 576time (months)

(1) (2)

Cross-correlation of

SSTs of Niňo 3,4 and

MTs in Serbia Certain correlation (0.157)

among the average monthly

temperatures in Serbia and in

Niňo 3,4 region, with three

months delay, has been found.

Visual coincidence

between these spectra

indicates teleconnection

of the temperature series.

Fractal and multifractal analyses of series

in regions Niňo 3,4 and Europe

Fractal processes are repeated in non-periodic cycles, not predictable, withoccurrence of catastrophe – sudden and severe changes. Niňo 3,4 and Belgrade diagrams of R/Sstatistic suggest to fractal nature.

Multifractal spectra f( ) The narrowest Niňo 3,4 diagram indicates dominant monofractal nature while Belgrade produces the broadest f( ) spectrum indicating multifractal nature of the process.

10 1001

10

Niňo3,4

H=0.71494

Belgrade

H=0.63978

R/S statistic for

temperature anomalies

aggregated time series

R/S

1 2

-1

0

1 f( )

TacnaNino34

Bourget

Belgrade

Brest

Similarity of diagrams in the middle region

might indicate teleconnection.

NAO – Main mode of natural climate variability

on Northern Hemisphere during winter

The EOF surface pressure chart indicates NAO domination in NH.

Great meridional oscillation of air masses.

Serbia is in the area of high EOF values meaning significant NAO influence.

During December –March NAO explains the most of temperature and precipitation variance.

NAO index is normalised surface pressure difference between Azores andIsland.

The first EOF mode of surface pressure and

precipitation indicates to NAO influenceThere is a resemblance between isolines over wide Atlantic region and in FRY

19 20 21 22 23

42

43

44

45

46

*

*

P A L I ]

S O M B O R

N O V I S A DZ R E N J A N I N

K I K I N D A

B .K A R L O V A C

V R [ A C

L O Z N I C A

V A L J E V O

B E O G R A D

K R A G U J E V A C

S M .P A L A N K A

V .G R A D I S T E

C R N I V R H

N E G O T I N

P L J E V L J A

Z L A T I B O R

S J E N I C A

P O @E G A

K R A L J E V O

K O P A O N I K

K R U [ E V A C

] U P R I J A

N I [

L E S K O V A C

Z A J E ~A R

D I M I T R O V G R A D

T I V A TP O D G O R I C A

V R A N J E

19 20 21 22 23

42

43

44

45

46 PA LI] SOMBOR

NOVI SA D

KIKINDA

VR[ A C SR.MITROVICA

VA LJEVO

BEOGRA D

SM.PA LA NKA NEGOTIN

ZLA TIBOR

SJENICA

KRA LJEVO

] UPRIJA

NI[

DIMITROVGRA D

PODGORICA

PE] PRI[ TINA VRA NJE

ULCINJ

ZRENJA NIN

LOZNICA

PO@EGA

KRU[ EVA C

LESKOVA C

NIK[ I ] HERCEGNOVI

PRIZREN

The first surface pressure EOF mode

explains 92,3 % of the variance in winter

comparing to 87.345 % for the whole year.

The first EOF precipitation mode explains

58,7 % of the variance (at 32 stations for the

period 1950-99).

Obvious NAO influence on pressure and

precipitation field in Serbia and Montenegro

Time series (1960-2000. winter) of

average monthly values of NAO index

and pressure anomalies (at 13 stations)

in reference to 1961-90 normal in

Serbia and Montenegro.

Time series (1951-2000. winter) of

average monthly values of

precipitation anomalies (at 32 stations)

and NAO index (x10) in relation to

1961-90 normal.

-6.0

-4.0

-2.0

0.0

2.0

4.0

6.0

8.0

1961 1971 1981 1991Godine

NAO index

Pressure anomalies

-100.0-80.0-60.0-40.0-20.0

0.020.040.060.080.0

100.0

1951 1961 1971 1981 1991Godine

NAO index * 10Precipitation anomalies

Cross-correlation between time series of NAO

index and temperature and precipitation

Cross-correlation between NAO index

and precipitation in Nikšić. Min value is

-0,53 (DJFM).

0 50 100 150-0.6

-0.5

-0.4

-0.3

-0.2

-0.1

0

0.1Crosscorr NAOI-Niksic-Rain, 1981-2000, Dec-March

0 50 100 150-0.3

-0.2

-0.1

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7Crosscorr NAOInd-BGDTemp, 1979-1998, Dec-March

Cross-correlation between NAO

index and temperature in Belgrade.

Max value is 0,64 (DJFM).

TRENDS

• Precipitation trends were much lower since 1980 in winter when AO and NAO

positive phase were the most active.

• There was an increase of precipitation for both periods during the year in most of

country except on a few stations in the far east.

• High positive precipitation trends were obtained for Vojvodina which are in

agreement with high positive temperature trends for the same period 1961-2006.

Annual trend 1961-2006

Winter trend 1961-2006

Annual trend 1980-2006

Winter trend 1980-2006

BEOGRAD Y = 0.7x + 671 y = -0.7x + 164 y = 1.1x + 670 y = 0.8x + 126

NIS Y = 0.1x + 587 y = -0.5x + 142 y = 3.4x + 527 y = 0.2x + 121

NOVI SAD Y = 2.8x + 544 y = -0.3x + 125 y = 5.2x + 556 y = 0.6x + 106

SJENICA y = 3.6x + 653 y = 1.0x + 124 y = 8.4x + 628 y = 2.8x + 111

ZAJECAR y = -3.1x + 652 y = -0.8x + 147 y = -0.2x + 575 y = -1.0x + 139

*Series have no fractal nature since

Hurst index is about 0.5, that indicate

to random walk processes.

* But, all series are multifractal with

relatively narrow spectras f( ).

* Belgrade spectra is identical with the

First EOF mode of SLP in FRY, as

expected.

* Iceland has the broadest spectra i.e.

most significant MF nature. Azores is

following.

* Both spectras have two roughnesses

that could point to additive processes.

* Azores as well as Iceland have

maximum spectras when 0<1

indicating to more intensive

oscillations and higher average values.

0.995 1 1.0050

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

AzoresGibraltar

Iceland

Belgrade

YU mod 1

Fractal and Multifractal analyses of SLP

time series 1951-98 winter (DJFM)

Azores, Iceland, Gibraltar, Belgrade and

first EOF mode in Serbia and Montenegro

Arctic oscillation (AO) is NAO complement

AO is an alternate view of NAO, described as a seesaw

pattern in which pressure fluctuates between positive and

negative phases at polar and middle latitudes.

Wallace (2004) argued that NAO is a part of AO since AO

involves atmospheric circulation in lower stratosphere during

winter up through 6 to 30 miles above surface.

Arctic oscillation might be of importance for global warming

and of significant impact on climate variability.

AO and NAO represent the same teleconnection mode of

climate variability for NH since there are no meaningful

distinctions between them and their consequences.

Their time series are very similar.

Daily precipitation in Serbia and NAO, AO index

Station name min AO

minNAO

1 Beograd -0.39 -0.12

2 Dimitrovgrad -0.41 -0.13

3 Gradiste -0.39 -0.14

4 Kikinda -0.44 -0.12

5 Kragujevac -0.38 -0.13

6 Kraljevo -0.35 -0.14

7 Nis -0.40 -0.11

8 Novi Sad -0.43 -0.12

9 Sjenica -0.39 -0.13

10 Sombor -0.40 -0.13

11 Smed.Palan -0.39 -0.13

12 Zajecar -0.40 -0.11

A new evidence of NAO and AO

influences on climate in Serbia are

proved by the cross-correlation

between daily NAO and AO index and

daily precipitation at 12 stations for the

winter period 1950-2003.

Three to four times higher correlation

coefficients for AO (–0.44 in Kikinda)

than for NAO are calculated for

Serbian region.

It seems that AO phenomenon has

stronger impact than NAO.

These results should be compared with

similar results from other regions.

CONCLUSIONS

The analyses of time series of SST in Nino 3,4 and Serbia temperatures in frequency domain (FFT) and time domain (cross-correlation) has been done.

The teleconnection among the average monthly temperatures in Serbia and in Niňo 3,4 region, with three months delay, has been proved.

The fractal analyses confirm similarity between shapes of the R/S diagrams while multifractal spectra of temperature series suggest teleconnection. SST in Niňo 3,4 has fractal nature.

By comparing the observed data from the stations in (former) Yugoslavia with the NAO indices, through several linear and non-linear methods of analysis, the significant influence of the NAO to the climate is approved (considering pressure, precipitation and temperature regime).

CONCLUSIONS – contd.

The first SLP EOF mode that explains 92,3 % of the variance in winter also indicates to the NAO influence.

Cross-correlation between time series of NAO index and temperature is 0.63 in Belgrade and -0.54 in Niksic for precipitation during summer.

Precipitation trends were much lower since 1980 in winter when AO and NAO positive phase were the most active, as expected.

SLP time series for Azores, Iceland, Gibraltar, Belgrade and first EOF mode in Serbia and Montenegro have multifractal nature.

The dependence of daily precipitation with AO is higher than with NAO indicies. Three to four times higher correlation coefficients for AO (–0.44 in Kikinda) than for NAO in Serbian region.

It seems that AO phenomenon has stronger teleconnection impact than NAO, but to be more reliable, these results should be compared with similar results from other regions.