Non-Stationarity in the circulation-climate relationship Stability of NAO-Influence on the Regional...
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Transcript of Non-Stationarity in the circulation-climate relationship Stability of NAO-Influence on the Regional...
Non-Stationarity in the circulation-climate relationship
Stability of NAO-Influence on the Regional Climate of the Baltic Sea Area
Possible Effects on NAO-Reconstructions?
(1) GKSS Research Center Geesthacht – Institute for Coastal Research – System Analysis and Modeling(2) Göteborg University – Earth Sciences Center – Ocean Climate Group
(1) Frederik Schenk, Sebastian Wagner, Eduardo Zorita(1) Frederik Schenk, Sebastian Wagner, Eduardo Zorita
(2) Daniel Hansson(2) Daniel Hansson
PAGE 2
Outline
1 Non-Stationarity in Observations1 Non-Stationarity in Observations
- spatiotemporal changes of NAO-control on regional climate
2 Non-Stationarity in Climate Model Simulations2 Non-Stationarity in Climate Model Simulations
- temporal evolution of the NAO-t2m-relationship over 990 years
3 Idealized pseudo-proxy reconstruction of NAO from local-scale3 Idealized pseudo-proxy reconstruction of NAO from local-scale
4 Summary4 Summary
PAGE 3
Assumption of Stationarity in Climate Reconstructions
Most statistical reconstructions assume stationarity between climate circulation and regional climate impact (proxy location)
i.e. linear relationship between NAO and near-surface climate
n
kkkBaltic ttpctT
1
)()()(
Local climate = F(large-scale + x)
Regional climate orlocal proxy
Proportionalconstant
Large scalei.g. PC
Residuum notcaptured by
linear equation
physical assumption:
PAGE 4
First leading EOFs of 1000-1990
PCA calculates covariability matrix of SLP field anomalies
1 Non-Stationarity in observations
The NAO – temperature relationshipThe NAO – temperature relationship
PAGE 6
Definition of circulation indices and T-Baltic from Echo-G and Luterbacher-SLP-reconstruction
http://www.baltex-research.eu/BACC/media/
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Detection of Non-Stationarity
Non-StationarityNon-Stationarity
=: changes in strength of a relationship between two climate variables
- expressed as Running Correlation coefficients over time (Pearson)
- window size of 31 years = RC30
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Data
Surface Temperature (t2m)Surface Temperature (t2m)
Long historical station temperatures
T-Baltic (t2m) of different AOGCM simulations from ECHO-G
MIB (MIB (MMax. sea-ax. sea-IIce extent of the ce extent of the BBaltic Sea)altic Sea)
MIB (obs.) (Seinä & Palosuo 1996)
MIB (mod.) – box-model PROBE-Baltic (Hansson & Omstedt 2007)
Circulation indicesCirculation indices
NAO of Azores minus Iceland (Jones et al. 1997)
NAO from 500 year SLP-reconstruction (Luterbacher et al. 2002)
NAO from SLP of different simulations from ECHO-G
with different forcings and initial conditions
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Time evolution of NAO-temperature relation
PAGE 10
64%
9%
Time evolution of NAO-temperature relation
PAGE 11
NAO and sea-ice (MIB)
Hansson, D. & A. Omstedt (2007): Modelling the Baltic Sea ocean climate on centennial time scale: temperature and sea ice.
Climate Dynamics 30, 763-778
2 Non-Stationarity in Climate Model Simulations
990 year model study from AOGCM Echo-G990 year model study from AOGCM Echo-G
PAGE 13
Climate Model Simulations
Climate simulation as a surrogate climate:
- Model = simplified representation of „real“ processes
Idealized pseudo-reconstruction-approach:
- comparison of NAO and CEZI
- use of area weighted t2m of the Baltic catchment area for
reconstructing the NAO by simple linear regression (without
adding white noise)
- comparison with „real“ model NAO
- estimation of non-stationarity for reconstructions within the model
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Atmosphere: ECHAM4
T30 (3.75° x 3.75°) 19 vertical layers
Ocean: HOPE-G
Horizontal Resolution 2,81° x 2,81°20 vertical layersincreased tropical resolution
Model description of Echo-G
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Settings of Echo-G simulations
Control-run of 1000 model years with fixed present conditions
External forced simulations I: solar + volcanic + greenhouse Gases
ERIK1: 990-1990 A.D. starting with warm ocean as initial condition
ERIK2: 990-1990 A.D. starting with cold ocean as initial condition
External forced simulations II: + orbital forcing
Oetzi1: 7000 B.P. – 1998 A.D. with orbital forcing only
Oetzi2: 7000 B.P. – 1998 A.D. with orbital, solar and greenhouse gases (no volcanic)
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NAO vs. Baltic Sea climateexternal forced (solar, volcanic, GHG)
PAGE 17
NAO vs. Baltic Sea climateControl-Run
3 Idealized pseudo-proxy reconstruction of NAO from local scale
PAGE 19
Idealized pseudo-reconstruction
)()()(^
ttTtNAO Baltic
estimation of NAO from pseudo-proxy
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Idealized pseudo-reconstruction
PAGE 21
Idealized pseudo-reconstruction
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4 Summary
Magnitude of non-stationarity for NAO-impact is high for Baltic Sea areaMagnitude of non-stationarity for NAO-impact is high for Baltic Sea area
- NAO vs. station-temperature 1824-2008 (DJF): RC30 = {10 - 65%}
- NAO vs. sea-ice (MIB) since 1500: RC30 = {0 – 64%}
- NAO vs. t2m (AOGCM) (DJF) since 1000: RC30 = {0 – 64%}
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4 Summary
Comparison of external forced simulations with control-run (990 years):
- same magnitude of non-stationarity over time with all/no forcings
- no relationship between forcing and non-stationarity
non-stationarity is mainly result of internal climate variabilitynon-stationarity is mainly result of internal climate variability
possible external influence on longer time scales (orbital changes)?
e.g. Groll et al. (2005): Changes in AO-regional-climate relationship during Eemian (125 kyr BP) compared with pre-industrial (1800 A.D.)
- significantly lower AO-t2m signal for NH winter during Eemian
- also stronger NH winter westerlies towards Europe, warmer CET
Groll, N., Widmann, M., Jones, J., Kaspar, F. & S. Lorenz (2005): Simulated relationship between regional temperatures and large-scale circulation: 125 kyr BP (Eemain) and the preindustrial periodJournal of Climate 2005, 18(19), 4032-4045
PAGE 24
References
Cassou, C., L. Terray, J.W. Hurrell and C. Deser (2004): North Atlantic winter climate regimes: spatial asymmetry,
stationarity with time and oceanic forcing, J. Climate, 17, 1055-1068.
Hansson, D. & A. Omstedt (2007): Modelling the Baltic Sea ocean climate on centennial time scale: temperature and sea
ice. Climate Dynamics 30, 763-778
Jacobeit, J., Beck, C. & A. Philipp (1998): Annual to Decadal Variability in Climate in Europe. Würzburger Geographische
Mauskripte, Vol. 43.
Luterbacher, J., Xoplaki, E., Dietrich, D., Rickli, R., Jacobeit, J., Beck, C., Gyalistris, D., Schmutz, C. & H. Wanner (2002):
Reconstruction of sea level pressure fields over Eastern North Atlantic and Europe back to 1500. Clim. Dyn. 18: 545-561.
Osborn, T.J., Briffa, K.R., Tett, S.F.B., Jones, P.D. and R.M. Trigo (1999): Evaluation of the North Atlantic Oscillation as
simulated by a coupled climate model. Climate Dynamics 15, 685-702.
Vicente-Serrano, S. M., and J. I. López-Moreno (2008), Nonstationary influence of the North Atlantic Oscillation on
European precipitation, J. Geophys. Res., 113.
Zorita, E. and F. González-Rouco (2002): Are temperature-sensitive proxies adequate for North Atlantic Oscillation
reconstructions? Geophysical Research Letters, 29 (14), 48-1 - 48-4.
Zorita, E., Gonzalez-Rouco, F. and S. Wagner (2009): Low-frequency response of the Arctic Oscillation to
external forcing in the past millennium. Geophysical Research Letters (submitted).
Thank you for your attention!
Climate is what we expect,
Weather is what we get.
(after Lorenz)
5 Outlook Principal Component Analysis
teleconnection patterns describe the low-frequency extratropical atmosphere generally in terms of space-
stationary and time-fluctuating structures
PAGE 27
Stability of SLP-patterns over time:Running EOF
Moving-EOF-analysis with window size a = 31years
Comparison of reference patterns (EOFs over 1000-1998) with subperiods
Field-correlation detected by |scalarproduct| of reference pattern R of the whole time period with each subperiod-EOF S yields |rR,S| = [0,1]
with
|r| = [0,1] due to orthogonality of EOFs
* Field correlations like RunCor(X,Y) of anomaly field with mean
**
*
)()(
),(,
kSR
SRk
YVarXVar
YXCovSRr k
0 kk yx
PAGE 28
Slides for Discussion
PAGE 30
Time evolution of NAO-temperature relation
PAGE 31
PAGE 32
__Changes of westerly winds in the North Atlantic region_Temporal evolution of the DJF North Atlantic Oscillation Index
Zorita, E., Gonzalez-Rouco, F. and S. Wagner (2009): Low-frequency response of the Arctic Oscillation to external forcing in the past millennium.
Geophysical Research Letters (submitted).