Global and Regional Factors of Inter-Annual and Inter

advertisement
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, Ukraine
[email protected]
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 quasiperiodic (inter-decadal and inter-annual) fluctuations.
Time-series representation:
 (t )  0  at   C (t )   I (t )  
T 30
Linear
(secular)
trend
Climatic
(interdecadal)
variations
T 30
Inter-annual
and decadal
fluctuations
''



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 lowfrequency spectral peaks of variability.
AMO index (1856-2008)
Source: http://www.cdc.noaa.gov/Timeseries/AMO/
Series: Mean annual values, smoothed by 5-year moving average
Spectral analysis: Lomb periodogram (significant peak 66 years)
0,5
60
0,4
50
0,3
0,2
0,1
AMO
Power
40
30
0
-0,1
20
-0,2
10
-0,3
-0,4
0,01 0,02 0,03 0,04 0,05 0,06 0,07 0,08 0,09 0,1
Frequency
1860 1870 1880 1890 1900 1910 1920 1930 1940 1950 1960 1970 1980 19902000 2010
Year
NAO index (1824 – 2008)
Source: http://www.cru.uea.ac.uk/~timo/datapages/naoi.htm
Series: winter (Dec-Mar), smoothed by 5-year average, detrended
Spectral analysis: Lomb periodogram (significant peaks on 76, 38, 22 yrs)
20
19
18
17
16
15
14
13
12
11
10
9
8
7
6
5
4
3
2
1
1
NAO win (G-I), 5-yr averaged
Power
2
0
-1
0,01 0,02 0,03 0,04 0,05 0,06 0,07 0,08 0,09 0,1
1830 1840 1850 1860 1870 1880 1890 1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010
Frequency
Year
NAO index paleo-reconstruction (1500 – 2001)
Series: winter (Dec-Feb), smoothed by 5-year average, detrended
Spectral analysis: Lomb periodogram
(significant peaks on 173, 95, 67, 34, 22 yrs)
ftp://ftp.cru.uea.ac.uk/data
30
20
Power
Reference:
Luterbacher, J., Xoplaki, E.,
Dietrich, D., Jones, P.D., Davies,
T.D., Portis, D., GonzalezRouco, 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.
10
0,01 0,02 0,03 0,04 0,05 0,06 0,07 0,08 0,09
Frequency
0,1




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 lowfrequency 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:
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
2
2
Yalta
1
Температура, °С
Температура, °C
1
Odessa
0
0
-1
-1
1890 1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010
Год
1890 1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010
Год
Long-period variations in the
Black Sea:
1
0,9
0,8
0,7
0,6
0,5
0,4
0,3
0,2
0,1
0
-0,1
-0,2
-0,3
-0,4
-0,5
-0,6
-0,7
-0,8
-0,9
Sevastopol
Скорость ветра, м/с
Скорость ветра, м/с
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
1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010
Год
0,9
0,8
0,7
0,6
0,5
0,4
0,3
0,2
0,1
0
-0,1
-0,2
-0,3
-0,4
-0,5
-0,6
-0,7
Odessa
1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010
Год
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
200
River inf.
200
100
Объем, км3
Объем, км3
100
Precip.
0
-100
0
-100
1930 1940 1950 1960 1970 1980 1990 2000 2010
Год
1930 1940 1950 1960 1970 1980 1990 2000 2010
Год



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 hydrometeorological conditions.
Thus, climate changes reflect significant differences
of physical-geographical conditions of the northwestern Black Sea and the southern coast of the
Crimea peninsula.
Conclusion (1) :



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 multiannual fluctuations of the observed hydrometeorological values for the Black Sea.
Regional differences of climatic variability are
manifested for different regions of Ukrainian
seashore
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
Location of observation points used for the
time series construction
Hydrometeorological
variables:
Odessa
Khorly
Wind velocity (W or WV)
Primorskoye
Air temperature (TA)
Evpatoria
Water temperature (TW)
Feodosia
Sevastopol
Yalta
Cape Khersones
Precipitations (P or Pr)
Sea level (SL)
Salinity (S)
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)
Wind velocity: yearly mean values, 1945-2009
PC
Eigenvalue % Variance
1
3.78253
64.454
2
0.984687
16.779
3
0.44019
7.5007
4
0.342968
5.8441
5
0.192841
3.286
6
0.125398
2.1368
Jolliffe cut-off 0.27047
0.4484
0.4276
0.3347
0.3303
0.399
0.4856
Eigenvalue
2
1
2
3
4
5
6
Evpatoria
Feodosia
4
3
Yalta
W_Fds
2
Cape Khersones
PC score
W_Ylt
W_Khs
W_Stp
Sevastopol
2
1
1987
1983
1985
0.5643
1988
1
11978
980
11977
981
1975
1970
1979
1982
1
0
1945
-1
1948
1947
-2
1989
0.1194
0
-0.005996
-0.4217
Component 2
0.3157
1990
1984
1997
1994 1986
1992
0
W_Fds
W_Ylt
W_Khs
W_Stp
W_Evp
-0.6244
W_Ods
Loading
3
Co mpo nent
W_Evp
1
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
-0.1
-0.2
-0.3
-0.4
-0.5
-0.6
-0.7
-0.8
-0.9
W_Ods
Loading
Odessa
4
19741967
1976
20001995
19991998
1991 2001
1996 2004
2003
2002
-1
-3
1971
1973 1946
1968
10
11969
950
1964
1972
1949
1
961
1963
1965
1952
1966
1957
1993
1951
2006
2005
2007
2008
2009
1953
-2
-1
0
Co mpo nent 1
1
2
1959
3
PC-1
PC-2
1954
-3
30
40
Year number (1945-2009)
1956
1958
19551960
1962
20
4
50
60
Wind velocity: 5-year mean values, 1925-2009
PC
Eigenvalue % Variance
1
3,76792
69,916
2
0,898886
16,679
3
0,302493
5,613
4
0,265352
4,9238
5
0,116313
2,1583
6
0,0382312
0,7094
Jolliffe cut-off 0.62874
1
0,3525
0,4957
0,4449
0,3469 0,3422
2
3
4
5
6
Co mpo nent
0
Evpatoria
2
Feodosia
Sevastopol
1
W_Fds
Cape Khersones
0
PC score
W_Ylt
W_Khs
W_Stp
2
1
2007
1957
1962
1952
1
0,5853
-2
-0,3584
1942
1992
1972
PC-1
1947
-0,5773
PC-2
1977
1982
1987
W_Fds
W_Ylt
W_Khs
W_Stp
W_Evp
W_Ods
-1
1927
-3
-2
-1
0
Co mpo nent 1
1
2
3
2007
2002
1997
1992
1987
1982
1977
1972
1967
1962
1997
1957
1932
1937
1952
1967
0
1947
2002
1927
-0,005026
Component 2
0,01047
1942
-3
0,4422
0
-1
1937
W_Evp
W_Ods
Yalta
Loading
2
1
1932
Loading
0,4411
3
Eigenvalue
Odessa
4
Air temperature: yearly mean values, 1945-2009
5
PC
Eigenvalue % Variance
1
4,54574
92,404
2
0,210356
4,276
3
0,091396
1,8579
4
0,0402877
0,81896
5
0,0316175
0,64271
Jolliffe cut-off 0.68872
4
Eigenvalue
Odessa
3
2
1
2
Evpatoria
3
Co mpo nent
Feodosia
Sevastopol
5
4
3
0,452
0,4494
0,4487
0,4542
2
PC score
0,4315
1
0
-1
-2
-3
TA_Fds
TA_Ylt
TA_Stp
-4
TA_Evp
1
0,9
0,8
0,7
0,6
0,5
0,4
0,3
0,2
0,1
0
-0,1
-0,2
-0,3
-0,4
-0,5
-0,6
-0,7
-0,8
-0,9
TA_Ods
Loading
Yalta
10
20
30
40
Year number (1945-2009)
50
60
4
5
Air temperature: 5-year mean values, 1925-2009
Eigenvalue % Variance
4,12873
91,872
0,209957
4,672
0,110598
2,461
0,0300555
0,66879
0,0146398
0,32577
Jolliffe cut-off 0.62916
5
4
Eigenvalue
PC
1
2
3
4
5
Odessa
Evpatoria
3
2
1
Feodosia
Sevastopol
2
3
Yalta
1
Co mpo nent
5
0,4549 0,4361
4
0,4399 0,4539
3
PC score
0
2
1
0
2007
2002
1992
1997
1987
1977
1982
1967
1972
1962
1952
1957
1947
1937
1942
-2
1927
1932
TA_Fds
TA_Ylt
TA_Stp
TA_Evp
-1
TA_Ods
Loading
0,451
4
5
Water temperature: yearly mean values, 1945-2009
5
PC
Eigenvalue % Variance
1
4,5332
92,219
2
0,153216
3,1169
3
0,116208
2,364
4
0,0709133
1,4426
5
0,0421697
0,85785
Jolliffe cut-off 0.6882
4
Eigenvalue
Odessa
3
2
1
Evpatoria
2
3
Co mpo nent
Feodosia
Sevastopol
Yalta
1
5
4
0,4516
0,4497
0,4434
3
0,4456
PC score
2
0
1
0
-1
-2
TW_Fds
TW_Ylt
TW_Stp
TW_Evp
-3
TW_Ods
Loading
0,4458
-4
10
20
30
40
Year number (1945-2009)
50
60
4
5
Water temperature: 5-year mean values, 1925-2009
PC
1
2
3
4
5
Odessa
Eigenvalue % Variance
4,10097
90,918
0,278897
6,1831
0,0726385 1,6104
0,0351542 0,77937
0,0229547 0,5089
Jolliffe cut-off 0.63149
5
4
Feodosia
Sevastopol
1
Yalta
0,4447 0,4468 0,4483
0,4476 0,4487
3
2
1
2
5
3
Co mpo nent
4
0
3
1
0
-1
-2
2007
2002
1992
1997
1987
1977
1982
1967
1972
1962
1952
1957
1947
1937
1942
-3
1927
1932
TW_Fds
TW_Ylt
TW_Stp
TW_Evp
PC score
2
TW_Ods
Loading
Eigenvalue
Evpatoria
4
5
Precipitations: yearly mean values, 1945-2009
PC
Eigenvalue % Variance
1
3.21358
64.279
2
0.7646
15.294
3
0.465429
9.3097
4
0.333887
6.6785
5
0.221895
4.4384
Jolliffe cut-off 0.6986
3
Eigenvalue
Odessa
4
2
1
1
0.4938
0.4702
0.4697
2
0.4473
Loading
0.3384
3
4
5
Co mpo nent
0
Feodosia
Sevastopol
Yalta
Cape Khersones
5
3
3
P_Fds
2
1983
2
1
2002
0
-0.008975-0.01452
0
-1
P_Fds
P_Ylt
P_Khs
P_Stp
-0.8831
P_Ods
Loading
0.3976
0.2484
Component 2
1994
1
PC score
P_Ylt
P_Khs
P_Stp
P_Ods
4
1999
1950
1987
1989
1964
1992
1991
199619852001
1955
19721998
1
951
1
959
1948
1982
1956 1995
1946 1945
1973
1953 200819572009 1990 1960
2003
1
962
2007
1968
1986
1954 1967
1975
1979
1993
1974
1949
2006
1947 1961
1965
1981
2004
2000 19691977
1978
1
976
19631958
1988
1980
1971
1984
1952
1970
1966
2005
-3
-2
-1
0
1
2
Co mpo nent 1
3
4
1
0
-1
1997
-2
-3
10
20
30
40
Year number (1945-2009)
PC-1
PC-2
5
6
50
60
Precipitations: 5-year mean values, 1925-2009
4
PC
Eigenvalue % Variance
1
3,35931
67,239
2
0,682865
13,668
3
0,456327
9,1337
4
0,322828
6,4616
5
0,174731
3,4974
Jolliffe cut-off 0.69945
3
Eigenvalue
Odessa
2
1
1
0,4883 0,4843
Loading
0,3707
2
3
0,4272 0,4551
0
4
5
Co mpo nent
Feodosia
Sevastopol
4
Yalta
Cape Khersones
3
2
2
1
1
1
0
-1
1972
1937
-0,153
PC-1
-1
-0,3345
-0,3815
1997
PC-2
P_Fds
P_Ylt
P_Khs
P_Stp
P_Ods
1992
-3
-2
-1
0
Co mpo nent 1
1
2
3
4
2007
2002
1992
1997
1987
19872002
0
1977
1982
1932
1952
1967
1972
-3
1962
1927
1952
1957
11962
957
1947
2007
1982
1947
0
-2
1977
1937
1942
0,2601
1942
1927
1932
Component 2
0,8072
Loading
PC score
P_Fds
P_Ylt
P_Khs
P_Stp
P_Ods
1967
Sea level: yearly mean values, 1945-2009
Chernomorsk
6
5
4
Eigenvalue
Khorly
PC
Eigenvalue % Variance
1
5.69787
95.154
2
0.161114
2.6906
3
0.0533152
0.89036
4
0.043241
0.72212
5
0.0224371
0.3747
6
0.0100571
0.16795
Jolliffe cut-off 0.69992
3
2
1
2
3
4
Co mpo nent
Evpatoria
Feodosia
Sevastopol
Yalta
5
1
4
3
2
0.4157 0.4099 0.391
1
PC score
0.4102 0.411
0
0
-1
-2
-3
-4
SL_Fds
SL_Ylt
SL_Stp
SL_Evp
SL_Chm
-5
SL_Khl
Loading
0.4111
-6
10
20
30
40
Year number
50
60
5
6
Sea level: 5-year mean values, 1925-2009
Khorly
Chernomorsk
6
5
4
Eigenvalue
PC
Eigenvalue % Variance
1
5,80404
97,65
2
0,0741789
1,248
3
0,0307556
0,51745
4
0,0246876
0,41536
5
0,00772474
0,12996
6
0,00234684
0,039484
Jolliffe cut-off 0.69344
3
2
1
Evpatoria
2
3
Feodosia
Sevastopol
Yalta
1
4
3
2
1
PC score
0
0
-1
-2
2007
2002
1992
1997
1987
1977
1982
1967
1972
1962
1952
1957
1947
1937
1942
-4
1927
1932
SL_Fds
SL_Ylt
SL_Stp
SL_Evp
SL_Chm
-3
SL_Khl
Loading
0,4109 0,4081 0,4099 0,4114 0,4069 0,4021
4
Co mpo nent
5
6
Salinity: yearly mean values, 1952-2009
PC
Eigenvalue % Variance
1
2,09728
44,93
2
1,0009
21,442
3
0,78665
16,853
4
0,51704
11,077
5
0,265998
5,6984
Jolliffe cut-off 0.65351
Primorskoye
2
Eigenvalue
Odessa
3
1
1
2
Cape Khersones
Loading
0,5124
0,3081
4
5
Co mpo nent
Feodosia
0,5596
3
0,455
0,3498
3
Yalta
0
2
3
1
Component 2
1
0
0,04358
2007
0
0,09377
1978
1980 1979
1975 1977
1969
1974
1964
1962 1973
1960
1976
1959
19881963
1
958
1989 2003
1967
11947
948 1949 1953
1946
945
1
985
1
950
1
993
2004
1983
20091998
1991
1952
1965 1951
1972
2002
11992
1999
1
957
1996 986
1995
1987
2006
1984
20012000
1955
1994
2005
1956
1968
1966
1961
2008
-1
-1
-3
10
20
PC-1
1997
1954
Fds
_Ylt
Khs
-3
Ods
30
40
Year number (1952-2009)
-0,3982
-0,4121
0
-2
-2
Prm
Loading
0,813
1971
1981
1982
1990
1
PC score
2
S_Fds
S_Ylt
S_Khs
S_Ods
S_Prm
1970
-2
-1
0
Co mpo nent 1
1
2
3
4
PC-2
50
Salinity: 5-year mean values, 1950-2009
Odessa
Eigenvalue % Variance
1,93269
55,8
1,14691
33,113
0,264239
7,629
0,089541
2,5852
0,0302281
0,8727
Jolliffe cut-off 0.48491
Primorskoye
2
Eigenvalue
PC
1
2
3
4
5
1
1
Cape Khersones
Loading
0,6078 0,583
Feodosia
0,2559
2
0,3092 0,3601
4
5
Co mpo nent
Yalta
0
3
2
3
1
1987
2002
0
1997
1962
1982 1992
1942
927
932
937
1967
-2
S_Fds
S_Ylt
S_Khs
S_Ods
-0,6087
-2
-1
0
Co mpo nent 1
1
PC-1
2
3
PC-2
2007
2002
1997
1992
1987
1982
1977
1972
1967
1952
1957
-2
-0,4251
1962
-0,399
-1
1972
1977
-1
0
S_Prm
Loading
0,4043 0,3551
2007
1957
Component 2
1
0
1952
1
PC score
2
S_Fds
S_Ylt
S_Khs
S_Ods
S_Prm
1947
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
Sea level
95
Salinity
45
15
67
14
98
21
56
33
Complex variables of the Ukrainian coast
HM state: from 5 to 2 variables:
1
0,4191 0,4099
Loading
0,469
0,4858
0
SL
Pr
TW
TA
-0,4475
W
PCA (correlation matrix) 5-year
mean values:
WV, TA, TW, Pr, SL
PC
Eigenvalue % Variance
1
3,24748
69,543
2
0,9457
20,252
3
0,37465
8,022
4
0,0854076
1,829
5
0,0165286
0,353
Jolliffe cut-off 0.65377
1
0,5677 0,575
0
-0,2943
SL
Pr
TW
TA
-0,3816
W
PC-2: windy, warm and dry
Loading
PC-1: not windy, warm and watery
0,3389
2
1937
4
2007
1962
2
1942
1927
1947
2002
1932
PC score
1972
1957
1967
1977
1992
1982
-1
1
0
1997
-1
-2
-1
0
1
2
Co mpo nent 1
3
2007
2002
1992
1997
1987
1977
1982
1967
1972
1962
1952
1957
1927
1932
1987
1947
-2
-2
1937
1942
0
3
1952
4
2
r = 0.54 (p=0.03)
1937
2007
1
1952
Significant (but not too
close) correlation was
obtained only between
AMO and PC-2 on
decadal scale
1962
1927
0
1942
2002
1932
1947
1972
1967
PC-2
Component 2
1
1977
1957
1992
1982
-1
1997
-2
1987
-0,2
-0,1
0
AM O
0,1
0,2
0,3
Conclusion (2) :


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.
Thanks for your
attention!
Download
Related flashcards

Plasma physics

32 cards

S-type asteroids

71 cards

Black holes

19 cards

Indian astrophysicists

17 cards

Create Flashcards