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Mechanisms of the North Atlantic multidecadal internal variability in the CNRM-CM5 model

Low-pass filtered AMOC Leading EOF (80%). Profondeur (m). 2Sv between Iso-contours. Eq. S. N. N. N. N. Sv. Mechanisms of the North Atlantic multidecadal internal variability in the CNRM-CM5 model Y. Ruprich-Robert ( ruprich@cerfacs.fr ) and C. Cassou ( cassou@cerfacs.fr ).

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Mechanisms of the North Atlantic multidecadal internal variability in the CNRM-CM5 model

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  1. Low-pass filtered AMOC Leading EOF (80%) Profondeur (m) 2Sv between Iso-contours Eq S N N N N Sv Mechanisms of the North Atlantic multidecadal internal variability in the CNRM-CM5 model Y. Ruprich-Robert (ruprich@cerfacs.fr) and C. Cassou (cassou@cerfacs.fr) Introduction:At multidecadal timescale, the North Atlantic basin is characterized by sea surface temperature (SST) variability (Schlesinger and Ramankutty, 1994) that could be reconstructed with tree-ring back to 1600 (Gray et al. 2004). This observed variability is defined by the alternation of warming and cooling phases of the entire basin. It is linked to hurricane low frequency activity (Goldenberg et al., 2001) and precipitation anomalies over the surrounding continents, in particular over the Sahel and the Nordeste (Folland et al., 2001). Many studies based on climate coupled models conclude that this variability is partially due to internal climate system processes (e.g. Knight 2009) and is often referred to as the Atlantic Multidecadal Variability (AMV, Kerr 2000). The mechanisms at the origin of the AMV are still unclear (model dependence, scarcity of the observation…). In the present study, the AMV is investigated using the CNRM-CM5 model. 4) SPG and WBC intensification 3) Salt advection to Labrador Sea and deep convection 5) Northward ITCZ shift and NAO- excitation AMOC leads ( : « lag X » is a mean between lag <X-2;-X+2> ) ~ contours : surface salinity 0.1 psu.std-1 ~Lag -18 SPG intensity Florida-Bahamas Mass Transport North Brazil Current ~Lag -28 ~Lag -18 Lag -8 ! mm.d-1 Summer precipitation regressed on AMOC lag -28 lag -18 Cross-correlation between AMOC and SPG Intensity (black), Florida-Bahamas mass transport (blue) and North Brazil current (red) Surface salinity regressed on AMOC ~Lag -13 ~Lag -8 evaporation >0.02 mm/j lag -28 Mix layer depth > 50m lag -18 SPG : SubPolar Gyre WBC : Western Boundary Current 2) Heat oceanic advection to GIN Sea and sea ice melting Mechanisms of the CNRM-CM5 AMOC variability Model:CNRM-CM5 includes the ARPEGE-Climat (v5.2) atmospheric model (1.4°x1.4°, 31 vertical levels), the NEMO (v3.2) ocean model (ORCA1°, 42 vertical levels), the ISBA land surface scheme and the GELATO (v5) sea ice model coupled through the OASIS (v3) system (see Voldoire et al.,2012). The AMV mechanisms are investigated using the preindustrial control run of CNRM-CM5 produced within the 5th Coupled Model Intercomparison Project (CMIP5) framework. This is a 1000-yr long simulation where all external forcings (solar, volcanoes and anthropogenic Green House Gases and aerosols) are kept constant to their observed values of 1850. Pa.std-1 Sea level pressure regressed on AMOC (lag -8) – (lag -13) Bold black line represents statistical significant values at the 95% (lag -8) contours : < T >0-200m 0.1°C.std-1 Barotropic streamfunction climatology : 5 Sv between iso-contours 6 2 6) Damping of the anomalies in GIN Sea by the NAO- Pa.std-1 ~Lag -35 ~Lag -28 1 EAP/SCAND Lag -13 Lag -8 3 lag -35 lag -28 <T>0-200m regressed on AMOC Sea Ice regressed on AMOC at lag -28 only anomalies < -1% shown North Atlantic Sea Surface Temperature Variability and its link with the thermohaline circulation in CNRM-CM5 7 GIN Sea : Greenland - Iceland - Norwegian Sea K.std-1 <T>0-200m regressed on AMOC 1) EAP and SCAND lead AMOC by 35 years ~ 4 ~Lag -13 ~Lag -8 NAO (38%) EAP (15%) b) b) a) 7) Fresher water advection from the tropics a) Lag -8 Lag +8 5 SCAND (10%) ~Lag -35 NAO EAP SCAND d) c) 150 350 550 750 950 correlation psu.std-1 The CNRM-CM5 AMV is a basin scale sea surface temperature variability, comparable to the observed AMV AMOC lags <salinity>0-500m regressed on AMOC Fig. a : CNRM-CM5 Low-pass filtered (1/25 yr-1 cut-off frequency) standardized AMV Index (colours), and AMOC index : principal component of the low-pass filtered AMOC leading EOF (black curve) Fig. b : Sea Surface Temperature regressed on the AMV Index (only statistical significant values at the 95% level are shown, significativity from Davison et al, 1997) ~Lag -8 ~Lag 8 yr yr yr yr yr Fig. a-c : Sea Level Pressure EOF over the North Atlantic – Europe region (colours), and associated wind (arrows). Fig. d : cross-correlations between the PCs and AMOC, statistical significant correlation at the 95% level are dotted AMOC : Atlantic Meridionnal Overturning Circulation NAO : North Atlantic Oscillation EAP : East Atlantic Pattern SCAND : Scandinavian mode CNRM-CM5 produces an internal variability mode in the North-Atlantic region comparable to the AMV documented in many model studies. The modelled AMV is a damped mode mainly linked to the AMOC variability. The mechanisms for this variability are the following: EAP or/and Scandinavian atmospheric circulation modes (1)force a northward oceanic heat transport between the eastern branch of the SPG and the GIN Sea (2). After advection along the Norwegian current, this heat transport anomaly precludes sea ice formation along the eastern Greenland coast (2), leading to positive surface salinity anomalies due to enhanced local evaporation (3). The latter is advected to the Labrador Sea by the Eastern Greenland Current where it drives deeper convection (3). By geostrophy, the SPG intensifies and current anomalies gradually propagate backward up to the Equator (4). The Atlantic ITCZ northward shift favours negative NAO (5). These all together product an increase of northward heat transport into the North Atlantic ocean, leading in fine to AMV maximum. This cycle takes about 30-40yr to build and is damped about 20yr later by negative salinity anomalies advected into the SPG by the mean circulation from western tropical Atlantic (6). a) b) c) correlation AMOC leads Fig. a : Standardized AMV Index wavelet. Fig. b : AMOC climatology (contours) and low-pass filtered (>25 yr) leading EOF (colours). Fig. c : AMV Index auto-correlation (black), and AMV/AMOC Index cross-correlation (blue). Statistical significant correlation at the 95% level are bold References : Davison, A.C., and D. V. Hinkley, 1997: Bootstrap Methods and their Application, Camb. Univ. Press. Folland, C. K., A. W. Colman, D. P. Rowell, and M. K. Davey, 2001: Predictability of northeast Brazil rainfall and real-time forecast skill,1987–98, J. Clim., 14, 1937–1958. Goldenberg, S. B., C. W. Landsea, A. M. Mestas-Nuñez, and W. M. Gray, 2001: The recent increase in Atlantic hurricane activity: Causes and implications, Science, 293, 474– 479. Gray, S. T., L. J. Graumlich, J. L. Betancourt, and G. T. Pederson, 2004: A tree-ring based reconstruction of the Atlantic Multidecadal Oscillation since 1567 A.D., Geophys. Res. Lett., 31, L12205, doi:10.1029/2004GL019932. Kerr, R. A.,2000: A North Atlantic climate pacemaker for the centuries, Science, 288, 1984–1985. Knight, J. R., 2009: The Atlantic Multidecadal Oscillation Inferred from the Forced Climate Response in Coupled General Circulation Models, J. Clim., 22, 1610-1625 Schlesinger, M. E., and N. Ramankutty, 1994: Have Solar-Irradiance Variations Influenced Climate? In The Solar Engine and its Influence on the Terrestrial Atmosphere and Climate, E. Nemes-Ribes (ed.), Springer-Verlag, Heidelberg, pp. 493-506. Voldoire, A. and coauthors, 2012 : The CNRM-CM5.1 global model: description and basic evaluation, Clim. Dyn., DOI 10.1007/s00382-011-1259-y In CNRM-CM5 the AMV is a multidecadal damped mode, primarily linked to the AMOC variability

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