Presentation on theme: "North Pacific and North Atlantic multidecadal variability: Origin, Predictability, and Implications for Model Development Thanks to: J. Ba, N. Keenlyside,"— Presentation transcript:
North Pacific and North Atlantic multidecadal variability: Origin, Predictability, and Implications for Model Development Thanks to: J. Ba, N. Keenlyside, W. Park, H. Pohlmann Mojib Latif, Leibniz Institute of Marine Sciences at Kiel University
Deviations of 1999-2008 SAT from long-term warming trend 1950-2008 PDO and AMO can be easily identified
Hurrell et al. 2010 PDO and AMO index at a glance There is a lot of interannual variability (signal-to-noise) PDO and AMO seem not be linked to each other PDO seems to have a slightly smaller period than AMO
Scientific questions 1.Can we explain the multidecadal variability by a simple stochastic model? 2.Is North Pacific (PDV) and North Atlantic multidecadal variability (AMV) linked? 3.What provides the memory in the two basins? 4.What are the implications for decadal predictability? 5.How did the Walker Circulation change during the 20 th century (external and internal factors)?
Hierarchy of stochastic models Atmosphere drives ocean (which just responds) Local model (heat or freshwater forcing) Spatial coherence in atmosphere, with and without oceanic advection Spatial coherence in atmosphere, dynamical ocean models (wind- driven or THC)
Test of the stochastic mechanism 1. ECHAM5-OZ: ECHAM5 (T31) coupled to a multi-level mixed layer ocean (depth 500m), 1000 years (Dommenget and Latif 2008) 2. KCM: ECHAM5 (T31) coupled to an OGCM (NEMO), 4000 years (Park et al. 2009)
SSTA pattern of leading mode and spectra in ECHAM5-OZ Atmospheric teleconnections spread the extratropical signal to the Tropics. Once SST anomalies have developed there, the signal is spread globally (referred to as a Hyper Mode). Dommenget and Latif 2008 aa
Observed EOF-1 (32%), exp. trend removed, P > 10 years ECHAM5-OZ EOF-1 (29%), P > 40 years Leading multidecadal mode of SST Dommenget and Latif 2008 The spatial structure of observed Pacific multidecadal SST variability is consistent with the Hyper Mode picture
Is PDV related to AMV in KCM? Leading mode (40%) has loadings only in the Pacific Park and Latif 2010, subm.
Regression patterns, PDV Does show elements of a Hyper Mode
Is PDV related to AMV in KCM? POP2 (20%) has loadings only in NA. North Pacific and North Atlantic multidecadal SST variability are basically unrelated in KCM. NA SST is not (!) stationary. Park and Latif 2010, subm.
Regression patterns, AMV Hyper Mode picture does not apply
ST Jin Ba, IFM-GEOMAR 3-d T/S EOF1 leads AMOC by a decade
Stochastically forced AMOC variability Most observational evidence points towards the ocean-only oscillator (see also Griffies and Tziperman 1995)
The North Atlantic Oscillation (NAO) NAO-related SAT pattern (°C), +1σ The NAO can affect Labrador Sea convection
The NAOI spectrum is almost white, but there is multidecadal variability AMOC may have responded to the multidecadal NAO changes (Eden and Jung 2003) weak AMOC?strong AMOC?
The NAO: a key for decadal AMOC variability in recent decades? Time lag is of the order of a decade Latif et al. 2006
Overturning anomalies from forced OGCM Forced ocean model (ORCA 0.5°) Alvarez et al. 2008 AMOC changes follow multidecadal NAO changes Cold phase of multidecadal modeWarm phase of multidecadal mode
What do the ocean analyses show? Pohlmann et al. 2010 AMOC at 45°N and 1000m depth from the assimilation experiments of 10 decadal prediction systems (three year running mean are shown) There seems to be some consistency in the multidecadal AMOC changes raw valuesnormalized values
Implications for decadal predictability Pacific Decadal Variability is largely consistent with a simple stochastic model (hyper mode). Decadal predictability potential may be only modest. Atlantic Multidecadal Variability is more consistent with a stochastically driven oceanic eigenmode. This implies a considerably larger decadal predictability potential.
20 th Century Walker Circulation Inter-basin zonal temperature gradient (160°W-80°W, 80°E-160°E; 5°S- 5°N) and inverted SLP gradient (as defined by Vecchi et al. 2006) Forced experiments with ECHAM5 with observed SST 1.Sensitivity to SST forcing (HadISST vs. ERSST) 2.Sensitivity to the radiative forcing (with and without) 3.Sensitivity to horizontal model resolution (T31 and T106) 4.Comparison with 20 th century integrations with coupled models 5.Analysis of the link between SST gradient and SLP gradient in control runs with coupled models 6.Analysis of internal variability of centennial trends in global warming simulations with one coupled model KCM
Trends in 20 th century SST obtained from HadISST and ERSST and SLP response All SST forced ECHAM5 runs yield a strengthening of the Walker Circulation during the 20 th century Meng et al. 2010
20 th Century Walker Circulation change strong circulation weak circulation Trends in inter-basin SST and SLP gradient There is a consistent linear relationship between the inter-basin SST and SLP gradient in all climate models Meng et al. 2010 ECHAM5 Obs.
Walker Circulation response in global warming (1%/year increase) runs strong circulation weak circulation differences between the last 30 and the first 30 years of the 100 year integrations There is no robust response of the Walker Circulation, not even in a single model (KCM) 20 th century obs.
1.Can we explain the variability by a simple stochastic model? A large component in NP. 2.Is North Pacific and North Atlantic multidecadal variability linked? Not much. 3.What provides the memory in the two basins? Gyre (NP) and AMOC (NA). 4.What are the implications for decadal predictability? More potential in NA rel. to NP. 5.What are the relative roles of external and internal factors? Internal variability may mask global warming effects even on centennial timescales (e.g. Walker Circulation strength). Summary