Global and Regional Factors of Inter-Annual and Inter-Decadal

Variability of Hydro-meteorological conditions on the Black Sea

Ukrainian Shores

Yuriy ILYIN

Marine Branch of Ukrainian Hydro-meteorological Institute (MB UHI)

Soviet street, 61, 99011, Sevastopol, Ukrainemb_uhmi@stel.sebastopol.u

Main issues

Part 1: Scales of variability: interannual, decadal and

climatic; AMO and NAO as indices of external climatic

influence on the Black Sea.Part 2: Latent (no measured directly) exogenic and

endogenic factors on inter-annual and decadal scales;

Is there direct correlation between AMO (or NAO) and complex regional hydrometeo indices of the Black Sea (Ukrainian shores)?

Introduction

MB-UHI is dealing a long time with studies of hydrometeorological conditions (regime) of the Azov and Black seas (last works are: Ilyin and Repetin, 2006; Ilyin, 2008-2010; Lipchenko et al., 2006; Ilyin et al., 2009, etc…). See also poster by Ilyin and Repetin

Long-term changes of marine meteorological and hydrological parameters (such as air and water temperatures, wind velocity, atmospheric precipitations, sea level, water salinity) can be described as the sum of linear trends and quasi-periodic (inter-decadal and inter-annual) fluctuations.

Time-series representation:''

30 300 )()()(

ttattT T

IC

Linear (secular)

trend

Climatic (inter-

decadal) variations

Inter-annual and

decadal fluctuation

s

Modern estimates of trends and climatic variability in time-series of main meteorological and hydrological parameters mean annual values were discussed in previous works (Ilyin, 2009-2011, Ilyin & Repetin, 2006, 2011).

They were obtained on the base of FSU and Ukrainian marine stations network observations which are performed since the end of 19th century till this time.

Some results are on poster by Ilyin and Repetin

How natural climatic periodicities are manifested in observational data? Secular linear trends in the first approximation can be considered as

evidence of unidirectional human impact on global and regional climate systems. However there are long-term fluctuations of climatic parameters with different periods on their background.

Unfortunately even long enough secular series of instrumental hydrometeorological observations on the Black Sea coast do not allow to obtain the statistically significant estimates of low-frequency periodicities using the standard methods of spectral analysis.

At the same time it is known that the regional climate in the Black Sea is under the influence of global processes that can be adequately described by the indices of Atlantic Multidecadal Oscillation (AMO) and North Atlantic Oscillation (NAO).

Characteristics of the ocean influence and the values of these indices for regional climate studies are in the monograph (Polonsky, 2008).

Climate change indices such as North Atlantic Oscillation (NAO) and Atlantic Multi-decadal Oscillation (AMO) were subjected to spectral analysis in order to obtain their significant low-frequency spectral peaks of variability.

AMO index (1856-2008)

0,01 0,02 0,03 0,04 0,05 0,06 0,07 0,08 0,09 0,1

Frequency

10

20

30

40

50

60

Pow

er

Source: http://www.cdc.noaa.gov/Timeseries/AMO/ Series: Mean annual values, smoothed by 5-year moving averageSpectral analysis: Lomb periodogram (significant peak 66 years)

18601870188018901900 19101920193019401950196019701980199020002010

Year

-0,4

-0,3

-0,2

-0,1

0

0,1

0,2

0,3

0,4

0,5

AM

O

NAO index (1824 – 2008)

0,01 0,02 0,03 0,04 0,05 0,06 0,07 0,08 0,09 0,1

Frequency

123456789

1011121314151617181920

Pow

er

Source: http://www.cru.uea.ac.uk/~timo/datapages/naoi.htm Series: winter (Dec-Mar), smoothed by 5-year average, detrendedSpectral analysis: Lomb periodogram (significant peaks on 76, 38, 22 yrs)

1830 1840 1850 1860 1870 1880 1890 1900 1910 1920 1930 1940 1950 1960 1970 1980 19902000 2010

Year

-1

0

1

2

NA

O w

in (

G-I

), 5

-yr

aver

aged

NAO index paleo-reconstruction (1500 – 2001)

Series: winter (Dec-Feb), smoothed by 5-year average, detrendedSpectral analysis: Lomb periodogram (significant peaks on 173, 95, 67, 34, 22 yrs)

0,01 0,02 0,03 0,04 0,05 0,06 0,07 0,08 0,09 0,1

Frequency

10

20

30

Pow

er

Reference:Luterbacher, J., Xoplaki, E., Dietrich, D., Jones, P.D., Davies, T.D., Portis, D., Gonzalez-Rouco, J.F., von Storch, H., Gyalistras, D., Casty, C., and Wanner, H., 2002. Extending North Atlantic Oscillation Reconstructions Back to 1500. Atmos. Sci. Lett., 2, 114-124.

ftp://ftp.cru.uea.ac.uk/data

Revealed periods of climatic variability obtained for the NAO series practically coincide with the low-frequency oscillations in solar activity (SA) described by the series of Wolf numbers (Herman and Goldberg, 1981; Landscheidt, 1998).

As is known, except of the most expressed 11-year Schwabe cycles, changes in the SA have 22-year Hale cycles and the secular Gleissberg cycles. Additionally there is a 180-year cycle explained by the period of the Sun rotation relative to the centre of the solar system mass and an associated 35-year cycle.

In a circle of geo- and astrophysics possible mechanisms for the external (space) influences on Earth's climate are discussed (Landscheidt, 1998), but the debate about the prevalence of natural climate variability over anthropogenic factors (greenhouse gases) is far from complete.

Evidently the 70-year cycle of AMO is not related to extraterrestrial factors while NAO reflects both own low-frequency vibrations of the “ocean-atmosphere” and the variation of external influences on global climate.

Given the fact that climatic changes are low-frequency oscillations with periods of no less than 30 years (Polonsky, 2008), it was attempted the Least Squares (LS) approximation of the hydrometeorological series by the superposition of harmonics with periods 95, 67 and 34 years.

Previously linear trends were removed from the original series

Long-period variations in the Black Sea:

1890 1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010Год

-1

0

1

2

Тем

пера

тура

, °C

Yalta

18901900 1910 1920 19301940 1950 19601970 19801990 2000 2010Год

-1

0

1

2

Тем

пера

тура

, °С

Odessa

Climatic changes of the mean annual air temperature in Yalta and Odessa approximated by the sum of harmonic functions with periods of 95, 67 and 34 years, revealed from spectrum of paleo-NAO

190019101920 1930194019501960 1970198019902000 2010

Год

-0,7-0,6-0,5-0,4-0,3-0,2-0,1

00,10,20,30,40,50,60,70,80,9

Ско

рост

ь ве

тра,

м/с

Odessa

190019101920 1930194019501960 1970198019902000 2010Год

-0,9-0,8-0,7-0,6-0,5-0,4-0,3-0,2-0,1

00,10,20,30,40,50,60,70,80,9

1

Ско

рост

ь ве

тра,

м/с

Sevastopol

Long-period variations in the Black Sea:

Climatic changes of the mean annual wind velocity in Sevastopol and Odessa approximated by the sum of harmonic functions with periods of 95, 67 and 34 years, revealed from spectrum of paleo-NAO

1930 1940 1950 1960 1970 1980 1990 2000 2010Год

-100

0

100

200

Объ

ем

, км

3

Precip.

1930 1940 1950 1960 1970 1980 1990 2000 2010Год

-100

0

100

200

Объ

ем

, км

3

River inf.

Long-period variations in the Black Sea:

Climatic changes of the mean annual river discharge and precipitations (km3) approximated by the sum of harmonic functions with periods of 95, 67 and 34 years, revealed from spectrum of paleo-NAO

Above approximations satisfactorily describe the long-period (decadal and secular) changes in observations series, which serve as proof of the natural global climatic oscillations impact on regional climate changes.

However, the nature of the original series and the low-frequency variations is unequal for different areas of the coast which reflect the impact of the various regional factors on local hydro-meteorological conditions.

Thus, climate changes reflect significant differences of physical-geographical conditions of the north-western Black Sea and the southern coast of the Crimea peninsula.

Main period of the last centuries inter-decadal variability is the period of about 70 years. Besides, significant spectral peaks were discovered in the NAO time-series on the scales of secular changes (95, 173 years) and more high-frequency inter-decadal oscillations (34, 22 years). Close periods exist also in the SA index time series (i.e. Wolf numbers).

Superposition of harmonic functions with periods 95, 67 and 34 years describes satisfactory the multi-annual fluctuations of the observed hydro-meteorological values for the Black Sea.

Regional differences of climatic variability are manifested for different regions of Ukrainian seashore

Conclusion (1) :

Factor analysis of data series

To study how related “global” and “regional” factors in time series of different parameters measured in different points of the shore, exploratory factor analysis was performed using the algorithm of principal components (PC) for correlation matrices;

Latent (not measured directly) factors: exogenic (“globality”) – unidirectional changes in all points of measurements and endogenic (“regionality”) – differently directed changes for different regions of the shore

Odessa

Sevastopol

Yalta

Cape Khersones

Feodosia

Khorly

Evpatoria

Primorskoye

Location of observation points used for the time series construction

2 kinds of time series were constructed for the each parameter:

1) Yearly mean values for 1945 – 2009 (1952 -2009 for S): inter-annual scale (2-year and more periods)

2) 5-year mean values for 1925-2009 (1950-2009 for S): decadal scale (10-year and more periods)

Hydrometeorological variables:

Wind velocity (W or WV)

Air temperature (TA)

Water temperature (TW)

Precipitations (P or Pr)

Sea level (SL)

Salinity (S)

Odessa

Sevastopol

Yalta

Cape Khersones

Feodosia

Evpatoria

Wind velocity: yearly mean values, 1945-2009

PC Eigenvalue % Variance 1 3.78253 64.4542 0.984687 16.7793 0.44019 7.50074 0.342968 5.84415 0.192841 3.2866 0.125398 2.1368Jolliffe cut-off 0.27047

PC-1

PC-2

2 3 4 5 6

Component

1

2

3

4

Eig

env

alue

0.42760.3303

0.44840.3347 0.399

0.4856

W_O

ds

W_E

vp

W_S

tp

W_K

hs

W_Y

lt

W_F

ds

-0.9-0.8-0.7-0.6-0.5-0.4-0.3-0.2-0.1

00.10.20.30.40.50.60.70.80.9

1

Load

ing

0.3157

-0.6244

0.1194

0.5643

-0.4217

-0.005996

W_O

ds

W_E

vp

W_S

tp

W_K

hs

W_Y

lt

W_F

ds

0

1

Load

ing

1945

1946

19471948

1949

1950

1951

19521953

1954

1955

1956

1957

1958

19591960

1961

1962

1963

1964

19651966

1967

1968

1969

1970

1971

1972

19731974

1975

1976

19771978

1979

19801981

1982

1983

1984

1985

1986

1987

1988

19891990

1991

1992

1993

1994

1995

1996

1997

199819992000

2001

2002

20032004

20052006 200720082009

-3 -2 -1 0 1 2 3 4

Component 1

-1

0

1

2

Com

pone

nt 2

10 20 30 40 50 60

Year number (1945-2009)

-3

-2

-1

0

1

2

3

4

PC

sco

re

Odessa

Sevastopol

Yalta

Cape Khersones

Feodosia

Evpatoria

2 3 4 5 6

Component

1

2

3

4

Eig

enva

lue

0,44110,3525

0,44490,3469 0,3422

0,4957

W_O

ds

W_E

vp

W_S

tp

W_K

hs

W_Y

lt

W_F

ds

0

1

Load

ing

-0,3584

0,4422

0,01047

-0,5773

0,5853

-0,005026

W_O

ds

W_E

vp

W_S

tp

W_K

hs

W_Y

lt

W_F

ds

0

1

Load

ing

1927

1932

1937

1942

1947

1952

19571962

1967

1972

197719821987

19921997

2002

2007

-3 -2 -1 0 1 2 3

Component 1

-1

0

1

2

Com

pone

nt 2

Wind velocity: 5-year mean values, 1925-2009

PC Eigenvalue % Variance 1 3,76792 69,9162 0,898886 16,6793 0,302493 5,6134 0,265352 4,92385 0,116313 2,15836 0,0382312 0,7094Jolliffe cut-off 0.62874

1927

1932

1937

1942

1947

1952

1957

1962

1967

1972

1977

1982

1987

1992

1997

2002

2007

-3

-2

-1

0

1

2

PC

sco

re

PC-1

PC-2

Odessa

Sevastopol

Yalta

Feodosia

Evpatoria

Air temperature: yearly mean values, 1945-2009

PC Eigenvalue % Variance 1 4,54574 92,4042 0,210356 4,2763 0,091396 1,85794 0,0402877 0,818965 0,0316175 0,64271Jolliffe cut-off 0.68872

2 3 4 5

Component

1

2

3

4

5

Eig

enva

lue

0,4315 0,452 0,4494 0,4487 0,4542

TA

_Ods

TA

_Evp

TA

_Stp

TA

_Ylt

TA

_Fds

-0,9-0,8-0,7-0,6-0,5-0,4-0,3-0,2-0,1

00,10,20,30,40,50,60,70,80,9

1

Load

ing

10 20 30 40 50 60

Year number (1945-2009)

-4

-3

-2

-1

0

1

2

3

4

5

PC

sco

re

Odessa

Sevastopol

Yalta

Feodosia

Evpatoria

2 3 4 5

Component

1

2

3

4

5

Eig

enva

lue

PC Eigenvalue % Variance 1 4,12873 91,8722 0,209957 4,6723 0,110598 2,4614 0,0300555 0,668795 0,0146398 0,32577 Jolliffe cut-off 0.62916

Air temperature: 5-year mean values, 1925-2009

0,451 0,4549 0,4361 0,4399 0,4539

TA

_Ods

TA

_Evp

TA

_Stp

TA

_Ylt

TA

_Fds

0

1

Load

ing

1927

1932

1937

1942

1947

1952

1957

1962

1967

1972

1977

1982

1987

1992

1997

2002

2007

-2

-1

0

1

2

3

4

5

PC

sco

re

Odessa

Sevastopol

Yalta

Feodosia

Evpatoria

PC Eigenvalue % Variance 1 4,5332 92,2192 0,153216 3,11693 0,116208 2,3644 0,0709133 1,44265 0,0421697 0,85785Jolliffe cut-off 0.6882

Water temperature: yearly mean values, 1945-2009

2 3 4 5

Component

1

2

3

4

5

Eig

enva

lue

0,4458 0,4516 0,4497 0,4434 0,4456

TW

_Ods

TW

_Evp

TW

_Stp

TW

_Ylt

TW

_Fds

0

1

Load

ing

10 20 30 40 50 60

Year number (1945-2009)

-4

-3

-2

-1

0

1

2

3

4

5

PC

sco

re

Odessa

Sevastopol

Yalta

Feodosia

Evpatoria

PC Eigenvalue % Variance 1 4,10097 90,9182 0,278897 6,18313 0,0726385 1,61044 0,0351542 0,779375 0,0229547 0,5089 Jolliffe cut-off 0.63149

Water temperature: 5-year mean values, 1925-2009

2 3 4 5

Component

1

2

3

4

5

Eig

enva

lue

0,4447 0,4468 0,4483 0,4476 0,4487

TW

_Ods

TW

_Evp

TW

_Stp

TW

_Ylt

TW

_Fds

0

1

Load

ing

1927

1932

1937

1942

1947

1952

1957

1962

1967

1972

1977

1982

1987

1992

1997

2002

2007

-3

-2

-1

0

1

2

3

4

5

PC

sco

re

Odessa

Sevastopol

Yalta

Feodosia

PC Eigenvalue % Variance 1 3.21358 64.2792 0.7646 15.2943 0.465429 9.30974 0.333887 6.67855 0.221895 4.4384Jolliffe cut-off 0.6986

Precipitations: yearly mean values, 1945-2009

PC-1

PC-2

2 3 4 5

Component

1

2

3

4

Eig

enva

lue

0.33840.4938 0.4702 0.4697 0.4473

P_O

ds

P_S

tp

P_K

hs

P_Y

lt

P_F

ds

0

1

Load

ing

Cape Khersones

-0.8831

0.24840.3976

-0.008975-0.01452

P_O

ds

P_S

tp

P_K

hs

P_Y

lt

P_F

ds

0

1

Load

ing

19451946

1947

1948

1949

1950

1951

1952

19531954

19551956

1957

1958

1959

1960

1961

1962

1963

1964

1965

1966

1967 1968

1969

19701971

1972

1973

19741975

19761977

1978

1979

1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

19911992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

20072008 2009

-3 -2 -1 0 1 2 3 4 5 6

Component 1

-1

0

1

2

3

Com

pone

nt 2

10 20 30 40 50 60

Year number (1945-2009)

-3

-2

-1

0

1

2

3

4

5

PC

sco

re

Odessa

Sevastopol

Yalta

Feodosia

Cape Khersones

PC Eigenvalue % Variance 1 3,35931 67,2392 0,682865 13,6683 0,456327 9,13374 0,322828 6,46165 0,174731 3,4974Jolliffe cut-off 0.69945

Precipitations: 5-year mean values, 1925-2009

2 3 4 5

Component

1

2

3

4

Eig

enva

lue

0,37070,4883 0,4843 0,4272 0,4551

P_O

ds

P_S

tp

P_K

hs

P_Y

lt

P_F

ds

0

1

Load

ing

0,8072

-0,153

-0,3345

0,2601

-0,3815

P_O

ds

P_S

tp

P_K

hs

P_Y

lt

P_F

ds

0

1

Load

ing

19271932

1937

1942

1947

1952

19571962

1967

1972

1977

1982

1987

1992

1997

2002

2007

-3 -2 -1 0 1 2 3 4

Component 1

-1

0

1

2

Com

pone

nt 2

1927

1932

1937

1942

1947

1952

1957

1962

1967

1972

1977

1982

1987

1992

1997

2002

2007

-3

-2

-1

0

1

2

3

4

PC

sco

re

PC-1

PC-2

Sevastopol

Yalta

Feodosia

Khorly

Evpatoria

Chernomorsk

Sea level: yearly mean values, 1945-2009

PC Eigenvalue % Variance 1 5.69787 95.1542 0.161114 2.69063 0.0533152 0.890364 0.043241 0.722125 0.0224371 0.37476 0.0100571 0.16795Jolliffe cut-off 0.69992 2 3 4 5 6

Component

1

2

3

4

5

6

Eig

env

alue

0.4111 0.4102 0.411 0.4157 0.4099 0.391

SL_

Khl

SL_

Chm

SL_

Evp

SL_

Stp

SL_

Ylt

SL_

Fds

0

1

Load

ing

10 20 30 40 50 60

Year number

-6

-5

-4

-3

-2

-1

0

1

2

3

4

5

PC

sco

re

Sevastopol

Yalta

Feodosia

Khorly

Evpatoria

Chernomorsk

Sea level: 5-year mean values, 1925-2009

PC Eigenvalue % Variance 1 5,80404 97,652 0,0741789 1,2483 0,0307556 0,517454 0,0246876 0,415365 0,00772474 0,129966 0,00234684 0,039484Jolliffe cut-off 0.69344

2 3 4 5 6

Component

1

2

3

4

5

6

Eig

enva

lue

0,4109 0,4081 0,4099 0,4114 0,4069 0,4021

SL_

Khl

SL_

Chm

SL_

Evp

SL_

Stp

SL_

Ylt

SL_

Fds

0

1

Load

ing

1927

1932

1937

1942

1947

1952

1957

1962

1967

1972

1977

1982

1987

1992

1997

2002

2007

-4

-3

-2

-1

0

1

2

3

4

PC

sco

re

Odessa

Yalta

Cape Khersones Feodosia

Primorskoye

Salinity: yearly mean values, 1952-2009

PC Eigenvalue % Variance 1 2,09728 44,932 1,0009 21,4423 0,78665 16,8534 0,51704 11,0775 0,265998 5,6984Jolliffe cut-off 0.65351

PC-1

PC-2

2 3 4 5

Component

1

2

3

Eig

enva

lue

0,3081 0,3498

0,5124 0,55960,455

S_P

rm

S_O

ds

S_K

hs

S_Y

lt

S_F

ds

0

1

Load

ing

0,813

-0,4121

0,04358 0,09377

-0,3982

S_P

rm

S_O

ds

S_K

hs

S_Y

lt

S_F

ds

0

1

Load

ing

194519461947194819491950

19511952

1953

1954

19551956

1957

1958195919601961 1962

1963

1964

1965

1966

1967

1968 1969

1970

1971

1972

1973

19741975

1976

1977

197819791980

1981

1982

1983

1984

1985

19861987

19881989

1990

1991

1992

1993

1994

19951996

1997

1998

1999

20002001

2002

20032004

2005

2006

2007

2008

2009

-3 -2 -1 0 1 2 3 4

Component 1

-2

-1

0

1

2

3

Com

pone

nt 2

10 20 30 40 50

Year number (1952-2009)

-3

-2

-1

0

1

2

3

PC

sco

re

Odessa

Yalta

Cape Khersones Feodosia

Primorskoye

Salinity: 5-year mean values, 1950-2009

PC Eigenvalue % Variance 1 1,93269 55,82 1,14691 33,1133 0,264239 7,6294 0,089541 2,58525 0,0302281 0,8727 Jolliffe cut-off 0.48491

2 3 4 5

Component

1

2

Eig

enva

lue

0,6078 0,583

0,2559 0,3092 0,3601

S_P

rm

S_O

ds

S_K

hs

S_Y

lt

S_F

ds

0

1

Load

ing

0,4043 0,3551

-0,399 -0,4251

-0,6087

S_P

rm

S_O

ds

S_K

hs

S_Y

lt

S_F

ds

0

1

Load

ing

1927193219371942

1947

19521957

1962

1967

19721977

1982

1987

19921997

2002

2007

-2 -1 0 1 2 3

Component 1

-2

-1

0

1

2

3

Com

pone

nt 2

1952

1957

1962

1967

1972

1977

1982

1987

1992

1997

2002

2007

-2

-1

0

1

2

PC

sco

re

PC-1

PC-2

Percentage of “globality” (PC-1) and “regionality” (PC-2)

Variable 1-year averaged 5-year averaged

PC-1 PC-2 PC-1 PC-2

Wind veloc. 65 17 70 17

Air temperat. 92 92

Water temp. 92 91

Precipitations 64 15 67 14

Sea level 95 98

Salinity 45 21 56 33

Complex variables of the Ukrainian coast HM state: from 5 to 2 variables:

-0,4475

0,4191 0,4099 0,469 0,4858

W TA TW Pr SL

0

1

Load

ing

0,3389

0,5677 0,575

-0,3816-0,2943

W TA TW

Pr SL

0

1

Load

ing

PCA (correlation matrix) 5-year mean values: WV, TA, TW, Pr, SLPC Eigenvalue % Variance1 3,24748 69,5432 0,9457 20,2523 0,37465 8,0224 0,0854076 1,8295 0,0165286 0,353 Jolliffe cut-off 0.65377

PC-1: not windy, warm and watery

PC-2: windy, warm and dry

1927

1932

1937

19421947

1952

1957

1962

19671972

1977

1982

1987

1992

1997

2002

2007

-2 -1 0 1 2 3 4

Component 1

-2

-1

0

1

2C

ompo

nent

2

1927

1932

1937

1942

1947

1952

1957

1962

1967

1972

1977

1982

1987

1992

1997

2002

2007

-2

-1

0

1

2

3

4

PC

sco

re1927

1932

1937

19421947

1952

1957

1962

19671972

1977

1982

1987

1992

1997

2002

2007

-0,2 -0,1 0 0,1 0,2 0,3

AMO

-2

-1

0

1

2

PC

-2

r = 0.54 (p=0.03)

Significant (but not too close) correlation was obtained only between AMO and PC-2 on decadal scale

On inter-annual and decadal scales, variations of air and water temperatures as well as sea level are under global influence while changes of wind velocity, precipitations and salinity are subjected also by substantial regional impact (more or less evident result, except for water temperature)

To date, no practically significant linear correlations were obtained between global indices (AMO and NAO) and some measured or latent parameters used for the description of HM conditions within the Ukrainian Black Sea shore on inter-annual and decadal scale of variability.

Conclusion (2) :

Thanks for your attention!