ENSO simulation in MIROC

Report
CLIVAR ENSO WS, Nov 17-19, 2010
ENSO simulation in MIROC:
Perspectives toward CMIP5
M. Watanabe1, M. Chikira2, Y. Imada1, M. Kimoto1
and
MIROC modeling team
1: Atmosphere and Ocean Research Institute (AORI), The Univ. of Tokyo
2: Research Institute for Global Change (RIGC), JAMSTEC, Japan
Watanabe et al. (2010, JC in press.)
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. T42
impact of resolution
impact of new model physics
MIROC3. T213
MIROC5. T85
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
Perturbing cumulus convections
Entrainment rate ()
Conventional A-S scheme: prescribed
C-S scheme: state dependent
w2
w2
aB
 2a(1 - l ) B  l 2 ,
z

w
Altitude [eta]
Chikira-Sugiyama convection scheme:
Vertical profiles of  in a single column model
Mixture of A-S and Gregory schemes
C-S
A-S
Efficiency of the entrainment controlled by l
(large l -> suppress deep clouds)
Cloud type
Chikira and Sugiyama (2010, JAS)
Sensitivity experiments w/ T42 MIROC5
exp
l
Length
L500
0.5
85
L525
0.525
85
L550
0.55
85
L575
0.575
85
* l0.53 is the default
value in the official T85 CTL
ENSO in MIROC5
L500
GCM
L525
Reality?
Obs.
L550
L575
artificial? CP El Niño?
Comparison of the ENSO structure
Nino3-regression along EQ
a
L575
Precipitation
Nino3 SST Std Dev
L500
m
Zonal stress
longitude
Lloyd et al. (2009)
As ENSO amplifies, maximum in both precipitation and x anomalies be stronger
but shifted to the western Pacific -> reduction in the effective Bjerknes feedback
Mean state differences
Deviations from the ensemble mean
SST
precip.
L500
L550
ENSO amplitude
L525
L575
Larger l (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
l
L500a
0.5
L525a
0.525
L550a
0.55
Coupled feedbacks
L575a
0.575
Direct effect of convection
L500b
0.5
l=0.575 over Nino3
L575b
0.575
l=0.5 over ITCZ
SST & ice from CGCM ensemble mean
Coupling always works to reduce
the precipitation contrast
Mechanism of convective control
Wet cold tongue
-> enhanced effective
Bjerknes feedback
Dry cold tongue
-> reduced effective
Bjerknes feedback
Summary & remarks
 In MIROC5, a parameter for the cumulus entrainment (l) 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
CTL or 20C
MIROC5
GDFL CM2.1
(by J-S Kug)
CMIP3
Axes of the parametric and structural uncertainties
are quite different!!
CTDI-ENSO in CMIP3 models
2xCO2 or A1b
Sensitivity to increasing CO2 agrees well with the axis of
the parametric uncertainty in MIROC5 → by chance?
What’s the issues for CMIP5/AR5?
“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)
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)
What’s the issues for CMPI5/AR5?
Nino 3.4 SST std dev [K]
Result from the Hadley Centre PPE
?
Toniazzo et al. (2008)
Equilibrium climate sensitivity [K]
Does this occur only when the model’s ENSO is controlled by
low clouds? But, it seems consistent with MIROCs, too …
backup
RR2002
2003
EarthSimulator
Simulator2
Earth
“Kakushin”
2007
2008
2009
2010
AR4
AR5
AR5 data submission
MIROC history
MIROC3.2
T42+1deg (med)
T106+1/4x1/6deg (hi)
2013
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)
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
MIROC5
MIROC3med
ENSO was greatly
improved
Guilyardi et al. (2009)
Mechanism of the convective control
What is likely to be happening in MIROC5:
Large l (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
Atmos.
Dynamical core
MIROC3 (for AR4)
MIROC5 (for AR5)
Spectral+semi-Lagrangian
Spectral+semi-Lagrangian
(Lin & Rood 1996)
(Lin & Rood 1996)
V. Coordinate
Sigma
Eta (hybrid sigma-p)
Radiation
2-stream DOM 37ch
2-stream DOM 111ch
(Nakajima et al. 1986)
(Sekiguchi et al. 2008)
Diagnostic (LeTreut & Li
1991) + Simple water/ice
partition
M-Y Level 2.0
Prognostic PDF (Watanabe et al.
2009) + Ice microphysics (Wilson
(Mellor & Yamada 1982)
(Nakanishi & Niino 2004)
Prognostic A-S + critical
RH (Pan & Randall 1998,
Prognostic AS-type, but original
scheme (Chikira & Sugiyama 2010)
Cloud
Turbulence
Convection
& Ballard 1999)
MYNN Level 2.5
Emori et al. 2001)
simplified SPRINTARS
SPRINTARS + prognostic CCN
(Takemura et al. 2002)
(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
Aerosols
Entrainment rate ()
Vertical profiles of  in a single column model
C-S
A-S
eta
New convection
scheme
Mixture of A-S and Gregory scheme
Conventional A-S scheme:
prescribed
C-S scheme:
Cloud type
dependent upon buoyancy and cloud-base mass flux
What’s the consequence?
Chikira and Sugiyama (2010)
Deep cumulus
altitude
Strong w’ -> large 
Shallow cumulus
Weak w’ -> small 
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
MIROC3med
MIROC5
Guilyardiet al. (2009)
Mean state differences
SST
precipitation
Obs.
model
Narrow warm pool, but the single ITCZ is well reproduced
over the e. Pacific
Mean state differences
Model clim.
L575-L500
w
Qcum
More congestus?
Feedback coefficients
Both differences in a and m 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 histgram
Wet (dry) mid-troposphere is less (more)
frequent in Nino3 region for larger l
Composite Pr. wrt RH600
“Rich-get-richer” for larger l ?
Mechanism of convective control
Composite cumulus heating wrt CAPE in AGCM
Large l (efficient entrainment)
works to prevent deep cumulus
convection
Opposite direction of change
in congestus clouds
Question
Small but cooler cold tongue (=larger zonal SST gradient)
for large l: is it consistent with weaker ENSO?
A simple tropical climate model (Jin 1996, Watanabe 2008)
Te  -T (Te - Tr ) -  ( w)
rbL
hw  - rhw 2
Te - Tse
Hm
w  -ad
   0 - m (Tr - Te )
he  hw  bL
1 - tanh ( H  he - z0 ) / h* 


Tse  Tr - (Tr - Tr 0 )
2
Stationary solutions
Question
Radiative heating
Obs. Mean Te
Range of mean Te
in four runs
Larger l ?
Std of J96
Larger l ?
Bjerknes feedback efficiency
Cooler cold tongue & weaker ENSO can coexist if l-1 ∝ bL
Can feedback factors explain the model’s diversity?
ENSO parameters in CMIP3 models
r > 0, may be
consistent with
what a means
r < 0, inconsistent
with what m means
Nino3 SST Std Dev
a (net heat flux damping)
m (Bjerknes feedback)
Lloyd et al. (2009)
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
CMAP
Model EM
Diff L575-L500
Watanabe et al. (2010)
Mean state and ENSO
seasonal cycles of clim SST & ENSO amplitude
Nino3 SST mean seasonal cycle
Nino3 SST std dev
Mean state differences
SST
Contour: annual mean clim.
Shade: diff from the grand ensemble mean
SST is warmer in E. Pacific when ENSO is stronger, but the difference is
quite small (less than 2 %)
Mean state differences
Precipitation
Contour: annual mean clim.
Shade: diff from the grand ensemble mean
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%!)
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
aB
w2
w2
 l 2 ,
 2a(1 - l ) B w
z

The parameter l is found to control the frequency of
deep cumulus clouds (l->large, suppress deep clouds)
hence affect ENSO amplitude
l=0.5
l=0.55
l=0.525
MIROC3.2
Guilyardi et al. (2009)
2001)
Convective control of ENSO
Mean climate is quite similar to each other; nevertheless,
ENSO amplitude is different with factor 2!!
l=0.55
SST
T along Eq.
Pr/SLP/
Regression with Nino 3 index
l=0.5
Implication to 20th century trend
20C runs
MIROC3
MIROC5
Cl trend
(%/100y)
SST trend
(K/100y)
Decrease (-0.28%/100y)
Increase (+0.47%/100y)
Tropical
Cl (30S-30N)
 Likely due to fast response (but change is much slower)
 (CO2 increase; abrupt vs gradual) -> (fast response)?

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