ENSO simulation in MIROC: Perspectives toward CMIP5

1. 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.)

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

3. Improvements in an update (MIROC5) MIROC3. T42 MIROC3. T213 MIROC5. T85 Obs.(ProjD_v6.7&ERA40) impact of resolution impact of new model physics

4. 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

5. Perturbing cumulus convections Chikira-Sugiyama convection scheme: Mixture of A-S and Gregory schemes Vertical profiles of e in a single column model C-S A-S • Entrainment rate (e) • Conventional A-S scheme: prescribed • C-S scheme: state dependent Altitude [eta] Cloud type Efficiency of the entrainment controlled by l (large l -> suppress deep clouds) Chikira and Sugiyama (2010, JAS) Sensitivity experiments w/ T42 MIROC5 * l=0.53 is the default value in the official T85 CTL

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

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

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

9. ENSO metric in MIROC5 Cold tongue dryness (CTD) index AGCM experiments (5yrs each) Coupled feedbacks Direct effect of convection Coupling always works to reduce the precipitation contrast SST & ice from CGCM ensemble mean

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

11. 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

12. 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!!

13. 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?

14. “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 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)

15. What’s the issues for CMPI5/AR5? Result from the Hadley Centre PPE Nino 3.4 SST std dev [K] ? 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 …

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17. RR2002 “Kakushin” 2003 2007 2008 2009 2010 2013 AR4 AR5 AR5 data submission MIROC history Near-term MIROC3.2 T42+1deg (med) T106+1/4x1/6deg (hi) MIROC4.0 (bug fixed version of 3.2) T42+1deg (med) T213+1/4x1/6deg (hi) Long-term MIROC-ESM T42L80+1deg Earth Simulator MIROC4.1 (prototype new model) Near-term Earth Simulator2 MIROC5.0 T85+1deg (med)

18. 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 Guilyardi et al. (2009)

19. 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./tx response to El Nino confined to the western-central Pacific → weaker effective Bjerknes feedback → weak ENSO Feedback to the mean state

20. New version of MIROC MIROC5 (for AR5) MIROC3 (for AR4)

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

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

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

24. Mean state differences Model clim. L575-L500 w Qcum More congestus?

25. Feedback coefficients Both differences in a and m do not explain the different ENSO amplitude!

26. 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

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

28. RH-precipitation relationship RH600 histgram Composite Pr. wrt RH600 Wet (dry) mid-troposphere is less (more) frequent in Nino3 region for larger l “Rich-get-richer” for larger l ?

29. 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

30. 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) Stationary solutions

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

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

33. 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

34. Mean state (SST)

35. Mean state (precipitation) seasonal cycles over the eastern Pacific CMAP Model EM Diff L575-L500 Watanabe et al. (2010)

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

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

38. Mean state differences Contour: annual mean clim. Shade: diff from the grand ensemble mean Precipitation 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%!)

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

40. Convective control of ENSO New version of MIROC (MIROC4.5) State-dependent entrainment in cumulus scheme (Chikira 2009) Assumption between the entrainment rate e and updraft velocity w(Gregory 2001) 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=0.525 l=0.55 MIROC3.2 Guilyardi et al. (2009)

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

42. Implication to 20th century trend 20C runs MIROC5 MIROC3 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) • t(CO2 increase; abrupt vs gradual) -> t(fast response)?