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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, 2010 1: Atmosphere and Ocean Research Institute (AORI), The Univ. of Tokyo 2: Research Institute for Global Change (RIGC), JAMSTEC, Japan
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Motivation (or triggering) Obs.(ProjD_v6.7&ERA40) MIROC3. T42 Collins et al. (2010, Nature Geo.)
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Improvements in an update (MIROC5) Obs.(ProjD_v6.7&ERA40) MIROC3. T42MIROC3. T213MIROC5. T85 impact of resolution impact of new model physics
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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. 2008 Entrainment (incl. cumulus triggering) - Wu et al. 2007, Neale et al. 2008 Low clouds - Toniazzo et al. 2008, Lloyd et al. 2009
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Perturbing cumulus convections Efficiency of the entrainment controlled by large suppress deep clouds exp Length L5000.585 L5250.52585 L5500.5585 L5750.57585 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]
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ENSO in MIROC5 L500 L525 L550 L575 Reality? artificial? CP El Niño? Obs. GCM
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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
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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
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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
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Mechanism of convective control Dry cold tongue -> reduced effective Bjerknes feedback Wet cold tongue -> enhanced effective Bjerknes feedback
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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
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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
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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
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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)
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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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200320072008200920102013 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
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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
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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
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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
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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
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ENSO in MIROC5 A-O coupling strength Guilyardiet al. (2009) MIROC3med MIROC5
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Mean state differences SST Narrow warm pool, but the single ITCZ is well reproduced over the e. Pacific Obs. precipitation model
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Mean state differences Model clim. Q cum L575-L500 More congestus?
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Feedback coefficients Both differences in and do not explain the different ENSO amplitude!
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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
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Mean state differences RH in the eastern Pacific Wet Dry Contour: annual mean clim. Shade: diff from the ensemble mean
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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
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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
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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
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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
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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
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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
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Mean state (SST)
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Mean state (precipitation) seasonal cycles over the eastern Pacific Watanabe et al. (2010) CMAPModel EMDiff L575-L500
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Mean state and ENSO seasonal cycles of clim SST & ENSO amplitude Nino3 SST mean seasonal cycle Nino3 SST std dev
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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
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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
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ENSO in MIROC5 SST mode or thermocline mode? Guilyardiet al. (2006)
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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
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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
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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)
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