The Arctic Oscillation. Phenomenon and Possible...
Transcript of The Arctic Oscillation. Phenomenon and Possible...
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The Arctic Oscillation.Phenomenon and Possible Mechanisms
Vladimir Kryjov
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Background: Polar Vortex and Polar Night Jet
Definition
Impacts
Downward propagation
Possible mechanisms
Summary
Outline
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Background:Polar Vortex and Polar Night Jet
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Heating Of Ozone by UVR(sunlit part)
(shadow)
PolarNightJet
PoleEquator
OZONE
westerlies
Circum-Polar
Vortex
WARM COLD
Boreal winter
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More Ozoneand/orMore Heating Of Ozone by UVR(sunlit part)
(shadow)
strongerPNJ
PoleEquator
OZONE
westerlies
strongerCPV
WARMER
COLDER
Boreal winter
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Less Ozoneand/orLess Heating Of Ozone by UVR(sunlit part)
(shadow)
weakerPNJ
PoleEquator
OZONE
westerlies
WeakerCPV or even
LESS WARM
LESS COLD
Planetary Waves
Sudden Stratospheric
WarmingDistruction
of CPV
Boreal winter
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Definition of the AO
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“… As the reference variable we use the leading principal component of the wintertime (November-April) monthly mean SLPanomaly field over the domain poleward of 20°N, which accountsfor 22% of the variance …”
Thompson, D. W. J, and J. M. Wallace, 1998: The Arctic Oscillation signature in the wintertime geopotential
height and temperature fields. Geophys. Res. Lett., 25, 1297–1300.
Predecessors: Lorenz (1951)Kutzbach (1970)
Wallace and Gutzler (1981) Trenberth and Paolino (1981)
DefinitionDefinition
1998:
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The loading pattern of the AO: the leading EOF of year-round monthly mean 1000 mb height anomaly during 1979-2000. Data: the NCEP/NCAR 1000 (700) mb height anomalies on 2.5°x2.5° mesh. The covariance matrix. Weighted by the square root of the cosine of latitude. Monthly AO (AAO) indices are constructed by projecting the monthly mean 1000 (700) mb height anomalies onto the leading EOF mode. Time series are normalized by the standard deviation of the monthly index (1979-2000 base period). (CPC web-site)
2000:
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1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015
-4.00
-3.00
-2.00
-1.00
0.00
1.00
2.00
3.00
Time series of the wintertime (DJF) AO index(year mark as of January)
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Variance of the NCEP CPC’s monthly indicesprior to normalization.
www.cpc.ncep.noaa.gov/products/precip/CWlink/ao_aao.htm
It should be taken into account when averaging over several months!
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The AO and the NAO
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The DJF AOAs The EOF-1 of Z1000
over the Northern Hemisphere
The DJF NAOAs EOF-1 of SLP
in North Atlantic sector
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1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015-4.0
-3.0
-2.0
-1.0
0.0
1.0
2.0
3.0
DJF NAODJF AO
corr = 0.78
Time series of the wintertime AO and NAO
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(From Ambaum and Hoskins, 2002)
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Impacts
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Correlation map between DJF temperature and the AO
Linear impact on concurrentwintertime temperature
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Consistency between the temperature anomaly patternin DJF 2009/10 and the negative AO impact
Linear impact on concurrent wintertime temperature
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See alsoKryjov (2002),Rigor et al. (2002)
JF SLP regressed on Northern Europe annualmean temperature. Correlation between the circulation index of the map (SLP projected on the correlation map) and the AO is 0.94From V. Kryjov (2004)
April-December Temperature regressed on the January-March AO index
Impact on annual mean temperature
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(top) Correlation between March–June temperature and JF AO index and (bottom) Partial correlation between the same variables,
with snow extent influence being removed
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Reconstructions and Projections
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(Waple et al., CD, 2002)
1650 – 1850temperature change pattern
is close to temperatureresponse to the AO
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Upper: Annual SAT EOF1
Middle: Regression of the JF SLP fields on annual SAT PC1;
Bottom: Normalised Mann-Whitney statistic S for annual SAT PC1 (red), JF AO (forest green), the JF CI based on the annual SAT PC1 (navy green);
Units of the regression mapsare hPa per 1 std.dev. of the PC1 (a) and PC2 (b)
From Kryjov (2004)
Longer range influences
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From Hiroshi Tanaka’s Bergen (2010) presentation
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1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015
-4.00
-3.00
-2.00
-1.00
0.00
1.00
2.00
3.00
Time series of the wintertime (DJF) AO index(year mark as of January)
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PREDICTABILITYDownward propagation
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From M.P.Baldwin and T.J.Dunkerton (2001)
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The daily geopotential height (GPH) anomalies at 17 pressure levels are shown for the previous 120 days as indicated, and they are normalized by standard deviation using 1979-2000 base period. The
anomalies are calculated by subtracting 1979-2000 daily climatology, and then averaged over the polar cap poleward of 65°N. The blue (red) colors represent a strong (weak) polar vortex. The black
solid lines show the zero anomalies (From the NOAA NCEP CPC web site).
Downward Propagation of AO+
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The daily geopotential height (GPH) anomalies at 17 pressure levels are shown for the previous 120 days as indicated, and they are normalized by standard deviation using 1979-2000 base period. The
anomalies are calculated by subtracting 1979-2000 daily climatology, and then averaged over the polar cap poleward of 65°N. The blue (red) colors represent a strong (weak) polar vortex. The black
solid lines show the zero anomalies (From the NOAA NCEP CPC web site).
Nov:+0.46 Dec: -3.42 Jan: -2.78 Feb: -4.21
Downward Propagation of AO-
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Strong heating Of Ozone by UVR(sunlit part)
(shadow)
Tropopause
Strong PNJ
Weak Generation of Planetary Wave
Angular Momentum
PoleEquator
OZONE
ozonedepletion
Description may be found in Shindell et al. (1999, 2001, 2003)
For positive AO are favourable:
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OZONE
Description may be found in Shindell et al. (1999, 2001, 2003)
Wave breaking,Stratosphere warming
Destruction of PNJ
Weak heating of Ozone by UVR(sunlit part)
(shadow)
Weak PNJ
Tropopause
Equator Pole
Enhanced Generation of Planetary Waves
For negative AO are favourable:
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PREDICTABILITYSome model predictions
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Correlations between the observed wintertime (DJF) AO index- and wintertime (DJF) SLP predictions by GPC-Moscow (a),
- and observed wintertime (DJF) SLP (b).
1979 – 2003 (25 yrs.)
a.
b.
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1975 1980 1985 1990 1995 2000 2005 2010 2015
-4.00
-3.00
-2.00
-1.00
0.00
1.00
2.00
3.00
Time series of observed (black) and predicted DJF AO index.SL-AV model. Blue – version of 2004, red – version of 2011.
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Distinct negative phase of the AO
GPC predictions of DJF’12-13 mean SLP (from WMO LC LRF-MME)
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Nowadays, it is believed that the AO is a result from the interaction between
the zonal mean zonal flow and planetary wavesin the Stratosphere.
Possible mechanisms
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The ENSO and the AO
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(from Fletcher & Kushner, 2010)
Indian+Pacific
Indian OceanWeakening
of bothWave 1
and wave 1AO+
Pacific OceanEnhancement
Of wave 1AO-
Wave generation. Influence from the tropics
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From Fletcher and Kushner (2011)The role of linear interference in the Annular Mode response to Tropical SST forcing
Tropical Indo-Pacific (TIP)
Tropical Pacific Ocean (TРO)+AO-
Tropical Indian Ocean (TIO)+AO+
NAO Geopotential HeighResponse
to the five strongest El-Nino(1950-2001)
Wave generation. Influence from the tropics
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From Fletcher and Kushner (2011)The role of linear interference in the Annular Mode response to Tropical SST forcing
Tropical Indo-Pacific (TIP)
Tropical Pacific Ocean (TPO)+AO-
Tropical Indian Ocean (TIO)+AO+
NAOSST anomaly, DJF 2009-10
Geopotential HeighResponse
to the five strongest El-Nino(1950-2001)
Wave generation. Influence from the tropics
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Difference between the Sep.–Jan. cold and warm ENSO composites of DJF zonal mean zonal wind during (left) solar maxima, (middle) solar minima, and (right) the difference between them. Contour interval is 1 m/s, negative values are dashed, the 0 value is omitted. The area where the difference is significant at the 2.5% level is shaded (From Kryjov and Park, 2007).
Stratosphere
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1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010-4.0
-3.0
-2.0
-1.0
0.0
1.0
2.0
3.0DJF AO
El-Nino (red)La-Nina (blue)
year as of January
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Summary
The AO is the dominant mode of atmospheric variability of boreal winter
The wintertime AO strongly impacts the whole climate system on a wide range of time scales from days to decades
Effect of the wintertime AO impact is noticeable throughout the whole year
The AO is believed to be a result from the zonal mean flow – planetary wave interaction
Improvement of the wintertime AO prediction is believed to come from the better simulation of the wave generation and stratospheric processes
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Thank You