ENSO simulation in MIROC: Perspectives toward CMIP5 M. Watanabe 1, M. Chikira 2, Y. Imada 1, M. Kimoto 1 and MIROC modeling team Watanabe et al. (2010, JC in press.) CLIVAR ENSO WS, Nov 17-19, : Atmosphere and Ocean Research Institute (AORI), The Univ. of Tokyo 2: Research Institute for Global Change (RIGC), JAMSTEC, Japan

Motivation (or triggering) Obs.(ProjD_v6.7&ERA40) MIROC3. T42 Collins et al. (2010, Nature Geo.)

Improvements in an update (MIROC5) Obs.(ProjD_v6.7&ERA40) MIROC3. T42MIROC3. T213MIROC5. T85 impact of resolution impact of new model physics

ENSO in CGCMs ENSO diversity in CMIP3 models -> Controlling ENSO in complex system is still challenging ENSO diversity in CGCMs is likely due to the atm. component - Schneider 2002, Guilyardi et al. 2004, 2009 In particular, convection scheme potentially has a great impact CMT - Wittenberg et al. 2003, Kim et al. 2008, Neale et al Entrainment (incl. cumulus triggering) - Wu et al. 2007, Neale et al Low clouds - Toniazzo et al. 2008, Lloyd et al. 2009

Perturbing cumulus convections Efficiency of the entrainment controlled by  large  suppress deep clouds  exp Length L L L L  is the default value in the official T85 CTL Sensitivity experiments w/ T42 MIROC5 Chikira and Sugiyama (2010, JAS) Entrainment rate (  Conventional A-S scheme: prescribed C-S scheme: state dependent Chikira-Sugiyama convection scheme: Mixture of A-S and Gregory schemes A-SC-S Vertical profiles of  in a single column model Cloud type Altitude [eta]

ENSO in MIROC5 L500 L525 L550 L575 Reality? artificial? CP El Niño? Obs. GCM

Comparison of the ENSO structure As ENSO amplifies, maximum in both precipitation and  x anomalies be stronger but shifted to the western Pacific -> reduction in the effective Bjerknes feedback Precipitation Zonal stress Nino3-regression along EQ longitude Lloyd et al. (2009)   Nino3 SST Std Dev L500 L575

Mean state differences SST Deviations from the ensemble mean precip. L500 L525 L550 L575 ENSO amplitude Larger (efficient cumulus entrainment) -> drier & colder mean state in E. Pacific weaker ENSO

ENSO metric in MIROC5 Cold tongue dryness (CTD) index AGCM experiments (5yrs each) exp Remark L500a0.5 L525a0.525 L550a0.55 L575a0.575 L500b0.5 =0.575 over Nino3 L575b0.575 =0.5 over ITCZ SST & ice from CGCM ensemble mean Coupling always works to reduce the precipitation contrast Direct effect of convection Coupled feedbacks

Mechanism of convective control Dry cold tongue -> reduced effective Bjerknes feedback Wet cold tongue -> enhanced effective Bjerknes feedback

Summary & remarks In MIROC5, a parameter for the cumulus entrainment ( ) greatly affects the ENSO amplitude ENSO controlling mechanisms involve: Direct changes in convective systems over the E. Pacific Coupled feedback (incl. ENSO structural change) The mean meridional precipitation contrast over the E. Pacific is a relevant indicator of the ENSO amplitude in MIROC. * the former is not necessarily the cause of the latter!! Generality? Similar experiments with the other GCMs desired Implication for the future change of ENSO

CTDI-ENSO in CMIP3 models Axes of the parametric and structural uncertainties are quite different!! CTL or 20C GDFL CM2.1 (by J-S Kug) MIROC5 CMIP3

CTDI-ENSO in CMIP3 models Sensitivity to increasing CO 2 agrees well with the axis of the parametric uncertainty in MIROC5 → by chance? 2xCO 2 or A1b

What’s the issues for CMIP5/AR5? TODO Theory & GCM (e.g. BJ index -> CMIP3/CMIP5 outputs) Verification of convective processes using TRMM Combined analyses to AMIP+20C Single param. perturbed experiments -> PPE Climate sensitivity and ENSO changes Extensive use of near-term predictions (assimilation/hindcasts) “KNOWN” & UNKNOWN Relatively robust: mean change (weakening of trades / shoaling of thermocline / warming in the e. Pacific) Not robust: ENSO property changes (amplitude/preference etc)

What’s the issues for CMPI5/AR5? Result from the Hadley Centre PPE Toniazzo et al. (2008) ? Equilibrium climate sensitivity [K] Nino 3.4 SST std dev [K] Does this occur only when the model’s ENSO is controlled by low clouds? But, it seems consistent with MIROCs, too …

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AR4AR5 MIROC3.2 T42+1deg (med) T106+1/4x1/6deg (hi) RR2002“Kakushin” AR5 data submission MIROC history Near-term MIROC4.0 (bug fixed version of 3.2) T42+1deg (med) T213+1/4x1/6deg (hi) MIROC-ESM T42L80+1deg MIROC4.1 (prototype new model) MIROC5.0 T85+1deg (med) Near-term Long-term Earth Simulator Earth Simulator 2

Guilyardi et al. (2009) Introduction ENSO diversity in CMIP3 models -> Controlling ENSO in complex system is still challenging MIROC3 (for AR4) -> MIROC5 (for AR5) Most of the atm. physics schemes replaced Std resolution: T85L40 atm. 0.5x1 deg ocean ENSO was greatly improved MIROC5 MIROC3med

Mechanism of the convective control What is likely to be happening in MIROC5: Large  (effective entrainment) → deep cumulus suppressed ( → more congestus in ITCZ → drying the cold tongue due to subsidence) → strong north-south moisture contrast in the eastern Pacific (mean state change) → precip./  x response to El Nino confined to the western-central Pacific → weaker effective Bjerknes feedback → weak ENSO Feedback to the mean state

New version of MIROC MIROC3 (for AR4) MIROC5 (for AR5) Atmos.Dynamical coreSpectral+semi-Lagrangian (Lin & Rood 1996) Spectral+semi-Lagrangian (Lin & Rood 1996) V. CoordinateSigmaEta (hybrid sigma-p) Radiation 2-stream DOM 37ch (Nakajima et al. 1986) 2-stream DOM 111ch (Sekiguchi et al. 2008) CloudDiagnostic (LeTreut & Li 1991) + Simple water/ice partition Prognostic PDF (Watanabe et al. 2009) + Ice microphysics (Wilson & Ballard 1999) Turbulence M-Y Level 2.0 (Mellor & Yamada 1982) MYNN Level 2.5 (Nakanishi & Niino 2004) Convection Prognostic A-S + critical RH (Pan & Randall 1998, Emori et al. 2001) Prognostic AS-type, but original scheme (Chikira & Sugiyama 2010) Aerosols simplified SPRINTARS (Takemura et al. 2002) SPRINTARS + prognostic CCN (Takemura et al. 2009) Land/ River MATSIRO+fixed riv flownew MATSIRO+variable riv flow OceanCOCO3.4COCO4.5 Sea-iceSingle-category EVPMulti-category EVP

New convection scheme Chikira and Sugiyama (2010) Entrainment rate (  Conventional A-S scheme: prescribed C-S scheme: dependent upon buoyancy and cloud-base mass flux Mixture of A-S and Gregory scheme A-SC-S Deep cumulus altitude Strong w’ -> large  Shallow cumulus Weak w’ -> small  Vertical profiles of  in a single column model Cloud type eta What’s the consequence? Both work to increase middle level cumulus that was less in A-S Not necessary to use empirical cumulus triggering function

ENSO in MIROC5 A-O coupling strength Guilyardiet al. (2009) MIROC3med MIROC5

Mean state differences SST Narrow warm pool, but the single ITCZ is well reproduced over the e. Pacific Obs. precipitation model

Mean state differences Model clim.  Q cum L575-L500 More congestus?

Feedback coefficients Both differences in  and  do not explain the different ENSO amplitude!

Comparison of the ENSO structure Contour: regression of Eq. temperature anomaly on to Nino3 (per 1K) Shade: difference from the grand ensemble mean White contour: 19,20,21 degC mean isotherms

Mean state differences RH in the eastern Pacific Wet Dry Contour: annual mean clim. Shade: diff from the ensemble mean

RH-precipitation relationship RH600 histgramComposite Pr. wrt RH600 Wet (dry) mid-troposphere is less (more) frequent in Nino3 region for larger “Rich-get-richer” for larger 

Mechanism of convective control Composite cumulus heating wrt CAPE in AGCM Opposite direction of change in congestus clouds Large  (efficient entrainment) works to prevent deep cumulus convection

Question Small but cooler cold tongue (=larger zonal SST gradient) for large  is it consistent with weaker ENSO? A simple tropical climate model (Jin 1996, Watanabe 2008) Stationary solutions

Question Cooler cold tongue & weaker ENSO can coexist if -1 ∝ bL Obs. Mean Te Larger  Radiative heating Bjerknes feedback efficiency Std of J96 Range of mean Te in four runs

Can feedback factors explain the model’s diversity? r > 0, may be consistent with what  means Lloyd et al. (2009)   net heat flux damping )  ( Bjerknes feedback ) Nino3 SST Std Dev ENSO parameters in CMIP3 models r < 0, inconsistent with what  means

Convective control of ENSO? Most of the recent studies point out the role of cumulus parameterization in ENSO simulations CCSM3 : Cumulus convection (Neale et al. 2008) GFDL CM2: Cumulus convection (Wittenberg et al. 2006) IPSL: Cumulus convection (Guilyardi et al. 2009) SNU: Cumulus convection (Kim et al. 2008) HadCM3: Low cloud (Toniazzo et al. 2008) What is meaningful with MIROC5? ー ENSO controlled by a single parameter (1D phase space) ー mean state changes are not large (but large for the TRH) Generality ? ー diff model has diff bias, so the mechanisms may not be unique

Mean state (SST)

Mean state (precipitation) seasonal cycles over the eastern Pacific Watanabe et al. (2010) CMAPModel EMDiff L575-L500

Mean state and ENSO seasonal cycles of clim SST & ENSO amplitude Nino3 SST mean seasonal cycle Nino3 SST std dev

Mean state differences SST SST is warmer in E. Pacific when ENSO is stronger, but the difference is quite small (less than 2 %) Contour: annual mean clim. Shade: diff from the grand ensemble mean

Mean state differences Wetter in E. Pacific for larger ENSO The absolute difference is quite small (less than 1mm/dy), but relative difference is quite large (more than 50%!) Precipitation Contour: annual mean clim. Shade: diff from the grand ensemble mean

ENSO in MIROC5 SST mode or thermocline mode? Guilyardiet al. (2006)

Convective control of ENSO New version of MIROC (MIROC4.5) State-dependent entrainment in cumulus scheme (Chikira 2009) Assumption between the entrainment rate  and updraft velocity w (Gregory 2001) The parameter is found to control the frequency of deep cumulus clouds ( ->large, suppress deep clouds) hence affect ENSO amplitude Guilyardi et al. (2009) =0.55 =0.5 =0.525 MIROC3.2

Convective control of ENSO SST T along Eq. Pr/SLP/  Regression with Nino 3 index Mean climate is quite similar to each other; nevertheless, ENSO amplitude is different with factor 2!! =0.55 =0.5

Implication to 20 th century trend MIROC3 MIROC5 Cl trend (%/100y) Tropical Cl (30S-30N) Decrease (-0.28%/100y) Increase (+0.47%/100y) Likely due to fast response (but change is much slower)  (CO2 increase; abrupt vs gradual) ->  (fast response)? 20C runs SST trend (K/100y)