Presentation is loading. Please wait.

Presentation is loading. Please wait.

ENSO sensitivity to change in stratification in CMIP3 Boris Dewitte Sulian Thual, Sang-Wook Yeh, Soon-Il An, Ali Belmadani CLIVAR Workshop, Paris, France,

Published byStephen Holland Modified over 9 years ago

Similar presentations

Presentation on theme: "ENSO sensitivity to change in stratification in CMIP3 Boris Dewitte Sulian Thual, Sang-Wook Yeh, Soon-Il An, Ali Belmadani CLIVAR Workshop, Paris, France,"— Presentation transcript:

1 ENSO sensitivity to change in stratification in CMIP3 Boris Dewitte Sulian Thual, Sang-Wook Yeh, Soon-Il An, Ali Belmadani CLIVAR Workshop, Paris, France, 17-19 November 2010 New strategies for evaluating ENSO processes in climate models

2 Yeh et al. (2009) Dinezio et al. (2009) Impact of climate change on the mean stratification in ensemble models ΔT (2xCO2 – PI)

3 Conclusions/Perspectives The characteristics of the thermocline (depth, sharpness, intensity) needs to be taken into account for determining the stability of ENSO SODA tells us that an increased stratification leads to more energetic and low-frequency ENSO (Climate change paradox..) Need to understand the impact of stratification changes on ENSO non-linearities.

4 Motivation Cf. Battisti and Hirst (1989)  ~6 months η~10-20 years  2 ~? k~? Understand the physical mechanism associated to the ‘rectification’ of ENSO variability/stability by the change in mean state? ?

5 Change in thermocline depth at decadal timescales On thermocline depth: small amplitude (Wang and An, 2001) Levitus data

6 T(1960-2001) D20 (1980-1997) D20 (1960-1975) (Moon et al., 2004; Dewitte et al., 2009) T(1980-1997)-T(1960-1975) Change in mean temperature associated to the 1976/77 climate shift

7 T(1980-1997)-T(1960-1975) The ‘Moon pattern’ indicates that change in mean state cannot be account for just one baroclinic mode..! (modes 1 to 3)

8 Sensitivity of ENSO to stratification Ocean dynamics perspective Shallow-water equations Stratification defined by (c, H) Multimode context Stratification defined by (c n, P n )

9 (Dewitte and Reverdin, 2000) Interannual variability of vertical displacements in a OGCM simulation (1985-1994) A ‘finer’ representation of the thermocline allows for taking into account the ‘loss’ of energy associated to vertical propagation: Implication for ENSO energetics and feedbacks

10 Nonlinear Dynamical Heating Zonal Advective Feedback Thermocline Feedback Sensitivity of ENSO to stratification Thermodynamics perspective

11 1 : BCCR-BCM2.0 2 : CCCMA-CGCM3.1 3 : CCCMA-CGCM3.1 (t63) 4 : CNRM-CM3 5 : CSIRO-MK3.0 6 : CSIRO-MK3.5 7 : GFDL-CM2.0 8 : GFDL-CM2.1 9a : GISS-AOM (run1) 9b : GISS-AOM (run2) 11 : GISS-MODEL-E-R 12 : IAP-FGOALS1.0-g 13 : INGV-ECHAM4 14 : INM-CM3.0 15 : IPSL-CM4 16 : MIROC3.2-HIRES 17 : MIROC3.2-MEDRES 18 : MIUB-ECHO-g 19 : MPI-ECHAM5 20 : MRI-CGCM2.3.2A 21 : NCAR-CCSM3.0 22 : UKMO-HadCM3 23 : UKMO-HadGem1 Belmadani et al. (2010) Mean circulation (, ) in CMIP3

12 1 : BCCR-BCM2.0 2 : CCCMA-CGCM3.1 3 : CCCMA-CGCM3.1 (t63) 4 : CNRM-CM3 5 : CSIRO-MK3.0 6 : CSIRO-MK3.5 7 : GFDL-CM2.0 8 : GFDL-CM2.1 9a : GISS-AOM (run1) 9b : GISS-AOM (run2) 11 : GISS-MODEL-E-R 12 : IAP-FGOALS1.0-g 13 : INGV-ECHAM4 14 : INM-CM3.0 15 : IPSL-CM4 16 : MIROC3.2-HIRES 17 : MIROC3.2-MEDRES 18 : MIUB-ECHO-g 19 : MPI-ECHAM5 20 : MRI-CGCM2.3.2A 21 : NCAR-CCSM3.0 22 : UKMO-HadCM3 23 : UKMO-HadGem1 Thermocline depth bias in CMIP3

13 Nonlinear Dynamical Heating Zonal Advective Feedback Thermocline Feedback Sensitivity of ENSO to stratification Thermodynamics perspective

14 y=y n y=0° Equator ~3°N Kelvin waves (he, ue) y=0°-> Rossby waves (hn) y=y n -> H mix hn=r E  hehe=r W  hn The Jin two- strip model (An and Jin, 2001)

15  =1 ~4 yrs  =0 (basin mode) ~ 9 months α β Solution of the mode [X µ =X 0.e .t.cos(β.t +φ)] as a function of coupling efficiency  The Jin two- strip model (An and Jin, 2001)

16 Stability of ENSO as a function of thermocline depth Period Growth rate Federov and Philander (2001) Increased thermocline depth -- ------>lower frequency stronger ENSO

17 Defining thermocline… Depth (P 1 ) Intensity, Sharpness (P n, n>1) Gent and Luyten (1985)

18 Decadal variability of P n – CNRM-CM3  D20<0  D20>0 180° 90°W  D20>0  D20<0 thermocline CNRM-CM3 N3VAR =0.5, =0.5, =0.2  P n (t) Dewitte et al. (2007)

19 Conceptual Model Ocean dynamics : Kelvin and Rossby wave on 3 baroclinic modes : K n, R n Thermodynamics : Thermocline depth and zonal currents : H, U Atmospherical component : Statistical relationship (SVD) with a coupling coefficient µ. comparable to the Jin two-strip model (Jin 1997b, An & Jin 2001) except for the ocean dynamics. Variables : (Thual et al., 2010)

20 Thermodynamical feedbacks Thermocline feedback Zonal advective feedback SODA dataset (1958-2008) Adimentionalised feedback intensity

21 Stability Analysis Dominant eigenmode=ENSO modeEigenvectors of the ENSO mode (µ=1) Find eigenvalues (a+ ib) of from Each eigenmode (a,b) has the form

22 Sensitivity to Stratification Stratification acts as a coupling parameter, but with physical meaning. P 1 (1-δ), P 2 (1+δ/2), P 3 (1+δ/2) δ

23 Sensitivity of ENSO mode to stratification in the TD model Model parameters: P 1 (1-δ), P 2 (1+δ/2), P 3 (1+δ/2) frequency Growth rate

24 Pre-70s to Post-70s : Strong increase in stratification (δ =120%). => Stronger, lower frequency ENSO The 1976/77 Climate shifts: Data: SODA

25 Post-2000 : Slight decrease in stratification (δ =95%). => ENSO variability displaced toward the west. Processes ? Data: SODA The 2000 shifts:

26 Change in ENSO stability in the GFDL model

27 « Metrics » for the sensitivity to stratification change using the extended Jin’s two-strip model

28 Yeh et al. (2010) Change in feedback processes EOF1 of low-passed filtered T(x,z,y=0) (PI runs) MRI GFDL 2xCO2 - PI

29 Sensitivity of ENSO to a warming climate: GFDL versus MRI Change in feedback processes Yeh et al. (2010)

30 Conclusions/Perspectives The characteristics of the thermocline (depth, sharpness, intensity) needs to be taken into account for determining the stability of ENSO SODA tells us that an increased stratification leads to more energetic and lower-frequency ENSO (Climate change paradox.?.) Need to understand the impact of stratification changes on ENSO non-linearities.

31 « Metrics » for the sensitivity to stratification change using the extended Jin’s two-strip model

32 MRIGFDL Low frequency change of temperature (EOF1) in the MRI and GFDL models Change in stratification tends to project on the high-order or « very slow » modes (n>3)  impact Ekman layer physics Change in stratification does project on the gravest modes (n=1,3)  Impact ENSO stability

33 Yeh et al. (2010) Change in feedback processes

34 Yeh et al. (2010) Change in feedback processes

35 Low frequency change of temperature (EOF1) in CMIP3 MIROC3_3_HIRESMIROC3_3_MEDRESMPI_ECHAM5 MRI_CGCM2_3_2ANCAR_CCSM3_0UKMO_HADCM3

36 CCCMA_CGCM3_1_t63CNRM_CM3CSIRO_MK3_5 GFDL_CM2_0INMCM3_0MIUB_ECHO_G CCCMA_CGCM3_1 FGOALSrun1GFDL_CM2_1 INVG_ECHAM4IPSL_CM4GISS_AOMrun1 Low frequency change of temperatu re (EOF1) in CMIP3

Download ppt "ENSO sensitivity to change in stratification in CMIP3 Boris Dewitte Sulian Thual, Sang-Wook Yeh, Soon-Il An, Ali Belmadani CLIVAR Workshop, Paris, France,"

Similar presentations

The effect of climate change and systematic model bias on the monsoon-ENSO system: the TBO and changing ENSO regimes Andrew Turner

The effect of climate change and systematic model bias on the monsoon-ENSO system: the TBO and changing ENSO regimes Andrew Turner
3 Reasons for the biennial tendency: The biennial tendency in HadCM3 2xCO 2 is in contrast with observed basinwide El Niño events which are often of 4-5.

3 Reasons for the biennial tendency: The biennial tendency in HadCM3 2xCO 2 is in contrast with observed basinwide El Niño events which are often of 4-5.
North Pacific and North Atlantic multidecadal variability: Origin, Predictability, and Implications for Model Development Thanks to: J. Ba, N. Keenlyside,

North Pacific and North Atlantic multidecadal variability: Origin, Predictability, and Implications for Model Development Thanks to: J. Ba, N. Keenlyside,
Temporal structure of ENSO in 20 th Century Climate simulations Antonietta Capotondi NOAA/Earth System Research Laboratory Collaborators: Andrew Wittenberg,

Temporal structure of ENSO in 20 th Century Climate simulations Antonietta Capotondi NOAA/Earth System Research Laboratory Collaborators: Andrew Wittenberg,
The flavor of El Nino in a changing climate Sang-Wook Yeh Hanyang University 2010.11 Colleagues: Jong-Seong Kug, Boris Dewitte, MinHo Kwon, Ben Kirtman,

The flavor of El Nino in a changing climate Sang-Wook Yeh Hanyang University Colleagues: Jong-Seong Kug, Boris Dewitte, MinHo Kwon, Ben Kirtman,
El-Nino, climatic variability and North Pacific Surface Temperature Fields Analysis Prof. Victor I.Kuzin Institute of Computational Mathematics & Mathematical.

El-Nino, climatic variability and North Pacific Surface Temperature Fields Analysis Prof. Victor I.Kuzin Institute of Computational Mathematics & Mathematical.
Modeling of Regional Ocean-Atmosphere Feedback in the Eastern Equatorial Pacific; Tropical Instability Waves Hyodae Seo, Art Miller and John Roads Scripps.

Modeling of Regional Ocean-Atmosphere Feedback in the Eastern Equatorial Pacific; Tropical Instability Waves Hyodae Seo, Art Miller and John Roads Scripps.
Annular Modes Leading patterns of variability in extratropics of each hemisphere Strongest in winter but visible year-round in troposphere; present in.

Annular Modes Leading patterns of variability in extratropics of each hemisphere Strongest in winter but visible year-round in troposphere; present in.
The ENSO : El Niño and the Southern Oscillation J.P. Céron (Météo-France) and R. Washington (Oxford University)

The ENSO : El Niño and the Southern Oscillation J.P. Céron (Météo-France) and R. Washington (Oxford University)
Aumont O. et al. 2005: An ecosystem model of the global ocean including Fe, Si, P colimitations, Global Biogeochemical Cycles, Volume 17, DOI 10.1029/2001GB001745.

Aumont O. et al. 2005: An ecosystem model of the global ocean including Fe, Si, P colimitations, Global Biogeochemical Cycles, Volume 17, DOI /2001GB
The 1997/98 ENSO event. Multivariate ENSO Index Index is based on 6 parameters relevant to phase.

The 1997/98 ENSO event. Multivariate ENSO Index Index is based on 6 parameters relevant to phase.
SSH anomalies from satellite. Observed annual mean state Circulation creates equatorial cold tongues eastern Pacific Trades -> Ocean upwelling along Equator.

SSH anomalies from satellite. Observed annual mean state Circulation creates equatorial cold tongues eastern Pacific Trades -> Ocean upwelling along Equator.
This model predicts wetter conditions over the Sahel, and drier conditions along the Guinean coast in the 21 st century. This is opposite to what is expected.

This model predicts wetter conditions over the Sahel, and drier conditions along the Guinean coast in the 21 st century. This is opposite to what is expected.
The 1997/98 ENSO event. Multivariate ENSO Index Index is based on 6 parameters relevant to phase.

The 1997/98 ENSO event. Multivariate ENSO Index Index is based on 6 parameters relevant to phase.
El Nino Southern Oscillation (ENSO) 20 April 06 Byoung-Cheol Kim METEO 6030 Earth Climate System.

El Nino Southern Oscillation (ENSO) 20 April 06 Byoung-Cheol Kim METEO 6030 Earth Climate System.
Modes of Pacific Climate Variability: ENSO and the PDO Michael Alexander Earth System Research Lab michael.alexander/publications/

Modes of Pacific Climate Variability: ENSO and the PDO Michael Alexander Earth System Research Lab michael.alexander/publications/
Mechanisms controlling ENSO: A simple hybrid coupled model study Cheng-Wei Chang 1 * and Jia-Yuh Yu 2 1. Institute of Geography, Chinese Culture University,

Mechanisms controlling ENSO: A simple hybrid coupled model study Cheng-Wei Chang 1 * and Jia-Yuh Yu 2 1. Institute of Geography, Chinese Culture University,
Climate Variability and Change in the U.S. GLOBEC Regions as Simulated by the IPCC Climate Models: Ecosystem Implications PIs: Antonietta Capotondi, University.

Climate Variability and Change in the U.S. GLOBEC Regions as Simulated by the IPCC Climate Models: Ecosystem Implications PIs: Antonietta Capotondi, University.
Didier Swingedouw, Laurent Terray, Christophe Cassou, Aurore Voldoire, David Salas-Mélia, Jérôme Servonnat CERFACS, France ESCARSEL project Natural forcing.

Didier Swingedouw, Laurent Terray, Christophe Cassou, Aurore Voldoire, David Salas-Mélia, Jérôme Servonnat CERFACS, France ESCARSEL project Natural forcing.
Ocean energetics in GCMs: how much energy is transferred from the winds to the thermocline on ENSO timescales? Alexey Fedorov (Yale) Jaci Brown (CSIRO)

Ocean energetics in GCMs: how much energy is transferred from the winds to the thermocline on ENSO timescales? Alexey Fedorov (Yale) Jaci Brown (CSIRO)

Similar presentations

Ads by Google