ENSO simulation in MIROC: Perspectives toward CMIP5 M. Watanabe 1, M. Chikira 2, Y. Imada 1, M....

ENSO simulation in MIROC: ENSO simulation in MIROC: Perspectives toward CMIP5Perspectives toward CMIP5

M. Watanabe1, M. Chikira2, Y. Imada1, M. Kimoto1

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 Tokyo2: Research Institute for Global Change (RIGC), JAMSTEC, Japan

Motivation (or triggering)Motivation (or triggering)Obs.(ProjD_v6.7&ERA40) MIROC3. T42

Collins et al. (2010, Nature Geo.)

Improvements in an update (MIROC5)Improvements in an update (MIROC5)Obs.(ProjD_v6.7&ERA40) MIROC3. T42 MIROC3. T213 MIROC5. T85

impact of resolution

impact of new model physics

ENSO in CGCMsENSO in CGCMsENSO 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

Perturbing cumulus convectionsPerturbing cumulus convections

Efficiency of the entrainment controlled by large suppress deep clouds

2 ,

aB

w

2 2

2 (1 )w w

a Bz

exp Length

L500 0.5 85

L525 0.525 85

L550 0.55 85

L575 0.575 85 is the default value in the official T85 CTL

Sensitivity experiments w/ T42 MIROC5Sensitivity experiments w/ T42 MIROC5Sensitivity experiments w/ T42 MIROC5Sensitivity experiments w/ T42 MIROC5

Chikira and Sugiyama (2010, JAS)

Entrainment rate (Conventional A-S scheme: prescribedC-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

Alt

itud

e [

eta

]

ENSO in MIROC5ENSO 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)

N

ino3

SS

T S

td D

ev

L500L575

Mean state differencesMean state differences

SSTDeviations from the ensemble mean

precip.

L500

L525

L550

L575

EN

SO

amplitude

Larger (efficient cumulus entrainment) -> drier & colder mean state in E. Pacific <-> weaker ENSO

ENSO metric in MIROC5Cold tongue dryness (CTD) index

AGCM experiments (5yrs each)exp Remark

L500a 0.5

L525a 0.525

L550a 0.55

L575a 0.575

L500b 0.5 =0.575 over Nino3

L575b 0.575 =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 Mechanism of convective control control

Dry cold tongue -> reduced effective Bjerknes feedback

Wet cold tongue -> enhanced effective Bjerknes feedback

Summary & remarksSummary & 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 modelsCTDI-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 modelsCTDI-ENSO in CMIP3 models

Sensitivity to increasing CO2 agrees well with the axis of the parametric uncertainty in MIROC5 → by chance?

2xCO2 or A1b

What’s the issues for CMIP5/AR5?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?What’s the issues for CMPI5/AR5?

Result from the Hadley Centre PPE

Toniazzo et al. (2008)

?

Equilibrium climate sensitivity [K]

Nin

o 3

.4 S

ST s

td d

ev

[K]

Does this occur only when the model’s ENSO is controlled by low clouds? But, it seems consistent with MIROCs, too …

backup

2003 2007 2008 2009 2010 2013

AR4 AR5

MIROC3.2T42+1deg (med)T106+1/4x1/6deg (hi)

RR2002 “Kakushin”

AR5 data submission

MIROC historyMIROC history

Near-term

MIROC4.0(bug fixed version of 3.2)T42+1deg (med)T213+1/4x1/6deg (hi)

MIROC-ESMT42L80+1deg

MIROC4.1(prototype new model)

MIROC5.0T85+1deg (med)

Near-term

Long-term

Earth SimulatorEarth SimulatorEarth SimulatorEarth SimulatorEarth SimulatorEarth Simulator 22Earth SimulatorEarth Simulator 22

Guilyardi et al. (2009)

IntroductionIntroductionENSO 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 controlMechanism 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 New version of MIROCMIROCNew version of New version of MIROCMIROC MIROC3 (for AR4) MIROC5 (for AR5)

Atmos. Dynamical core Spectral+semi-Lagrangian (Lin & Rood 1996)

Spectral+semi-Lagrangian(Lin & Rood 1996)

V. Coordinate Sigma Eta (hybrid sigma-p)

Radiation 2-stream DOM 37ch (Nakajima et al. 1986)

2-stream DOM 111ch (Sekiguchi et al. 2008)

Cloud Diagnostic (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 flow new MATSIRO+variable riv flow

Ocean COCO3.4 COCO4.5

Sea-ice Single-category EVP Multi-category EVP

New convection New convection schemeschemeNew convection New convection schemescheme

Chikira and Sugiyama (2010)

Entrainment rate (Conventional A-S scheme: prescribedC-S scheme: dependent upon buoyancy and cloud-base mass flux

Mixture of A-S and Gregory schemeA-SC-S

Deep cumulus

altit

ude

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-SNot necessary to use empirical cumulus triggering function

ENSO in MIROC5ENSO in MIROC5

A-O coupling strength

Guilyardiet al. (2009)

MIROC3med

MIROC5

Mean state differencesMean state differences

SST

Narrow warm pool, but the single ITCZ is well reproduced over the e. Pacific

Obs.

precipitation

model

Mean state differencesModel clim.

Qcum

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 meanWhite contour: 19,20,21 degC mean isotherms

Mean state differencesRH in the eastern Pacific

Wet

Dry

Contour: annual mean clim.Shade: diff from the ensemble mean

RH-precipitation relationshipRH600 histgram Composite 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 changein congestus clouds

Large (efficient entrainment)works to prevent deep cumulusconvection

QuestionSmall 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)

dw

0 ( )r eT T

*0

0

1 tanh ( ) /( )

2

ese r r r

H h z hT T T T

e wh h bL

( ) ( ) e see T e r

m

T TT T T w

H

2w wrbL

h rh

Stationary solutions

Question

Cooler cold tongue & weaker ENSO can coexist if -1 ∝ bL

Obs. Mean Te

Larger Larger

Rad

iativ

e he

atin

g

Bjerknes feedback efficiency

Std of J96

Range of mean Tein four runs

Can feedback factors explain the Can feedback factors explain the model’s diversity?model’s diversity?

r > 0, may be consistent with what means

Lloyd et al. (2009)

net heat flux damping)

(Bjerknes feedback)

Nin

o3 S

ST

Std

Dev

ENSO parameters in CMIP3 models

r < 0, inconsistent with what means

Convective control of ENSO?Convective control of ENSO?Most of the recent studies point out the role of cumulus parameterization in ENSO simulationsCCSM3 : 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 (SST)

Mean state (precipitation)Mean state (precipitation)

seasonal cycles over the eastern Pacific

Watanabe et al. (2010)

CMAP Model EM Diff L575-L500

Mean state and ENSOMean state and ENSO

seasonal cycles of clim SST & ENSO amplitude

Nino3 SST mean seasonal cycle Nino3 SST std dev

Mean state differencesSST

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 ENSOThe absolute difference is quite small (less than 1mm/dy), but relative differenceis quite large (more than 50%!)

Precipitation Contour: annual mean clim.Shade: diff from the grand ensemble mean

ENSO in MIROC5ENSO in MIROC5

SST mode or thermocline mode?

Guilyardiet al. (2006)

Convective control of ENSONew version of MIROC (MIROC4.5)

State-dependent entrainment in cumulus scheme (Chikira 2009)

2 ,

aB

w

Assumption between the entrainment rate and updraft velocity w (Gregory 2001)

2 2

2 (1 )w w

a Bz

The parameter is found to control the frequency ofdeep 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 20Implication to 20thth century century trendtrendMIROC3 MIROC5

Cl trend(%/100y)

TropicalCl (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)