2000-2010: 2611 journal papers with ENSO or El Nino in the title

Influence of El Nino Southern Oscillation (ENSO) on tomato spotted wilt incidence and peanut yield

Advantages and limits of integrating forecasts of El Nino Southern Oscillation (ENSO) on nutrient management for tomato

ENSO-associated response of field urine osmolality in the insectivorous arsupial Thylamys elegans

Agricultural productivity, the electoral cycle and ENSO effects in Papua New Guinea

Why are South Asians susceptible to central obesity? The El Nino hypothesis

Potential effects of El Nino-South Oscillation (ENSO) on growth of the American crocodile, Crocodylus acutus (Crocodylia: Crocodilydae) in captivity

ENSO lengthens the days of our lives

ENSO Theory: What is new since 2000 and what is achievable by 2020?

1. Progress in the past 10 years• 13 items!

2. What problems remain? (5 items)3. Questions for the next 10 years (8 items)4. Priorities (1 item)

David Battisti and Mark Cane

w/ input from Alexey Fedorov, Eric Guilyardi, Ben Kirtman Dan Vimont and Andrew Wittenberg

1. Progress in the past 10 years

More observational data to force and evaluate high-end component models, and to confirm the essential dynamics and thermodynamics of the ENSO mode, as described in the ZC intermediate model (w/ complete ocean SST equation)

QuikSCAT winds, satellite-derived OSCAR currents, more TAO data, atmospheric reanalyses (NCEP/DOE-2 and ERA40), gridded ocean reanalyses (GODAS, SODA, EN3, ECMWF, GFDL), etc

Theory of the anatomy of an ENSO cycle: ENSO is an eignenmode of the coupled atmosphere ocean system

– The mode features all of Wyrtki’s ideas, plus important ocean adjustment dynamics to swing form warm to cold phase

– There is enough dissipation or nonlinearity to render a warm event/cold event anatomy, rather than a quasi-periodic cycle

– Non-Gausian behavior can be explained by finite ocean thermodynamics and/or nonlinear wind stress response to ocean SST anomalies

Refs: Zebiak and Cane1985, Jin and Neelin 1993, Thompson and Battisti 2000

The ENSO eigenmodethe leading eigen (Floquet) mode of the coupled atmosphere/ocean

system

“Onset phase” “Mature phase”

About 1/4 period later

SS

TT

herm

oclin

e

Period 3.5 to 5 years

Decaying mode

Spatial structure similar to that

observed

Features Wyrtki’s observation of equatorial heat

content and Bjerknes’ feedback

Ref: Thompson (1998), Thompson and Battisti (2000)

The ENSO Eigenmode

Warm events tend to peak at the end of the calendar

year and is irregular

The mode has continuous spectrum with most energy

in interannual band

Additional features of the ENSO eigenmode– The mode evolves in a manner consistent with observed ENSO

cycle (e.g., in evolution and structure of SST and upper ocean heat content, Bjerknes feedback, coordinated to calendar year, …)

– It is irregular (flavors of ENSO)– When stochastically forced, it features a spring barrier and SST and

thermocline EOFs similar to that observed

Ref: Thompson (1998), Thompson and Battisti (2000,01); Roberts and Battisti (2010)

Editorial Comments on toy models of ENSO

– Toy models of ENSO, including the Delayed Oscillator (DO; Suarez and Shopf 1988, Battisti and Hirst 1989) and Recharge Oscillator (RO; Jin et al 1997), are simplifications of the physics of the ENSO eigenmode, in nature and in intermediate models.

– The DO and RO toy models highlight the same physics in different shorthand (aside: not surprisingly the DO and RO can be derived from each other).

– These toy models have served their purpose/done their damage

– The toy models developed thus far are not useful for evaluating GCMS because this neglect things we KNOW are important, such as the seasonality in forcing, in the richness of the upper ocean heat budget, the seasonality in the mean state, and in the coupling dynamics.

Observational evidence for the dynamical adjustment of the upper ocean consistent with the ENSO eigenmode

Refs: Meinen and McPhaden 2000, Wittenberg 2002, van Oldenborgh et al. 2005, Philip & van Oldenborgh 2006, Bosc and Delcroix 2008, Brown and Fedorov 2008, Fedorov 2010

Observational verification of richness of ocean surface heat budget during ENSO that is in qualitative agreement with budget in the ENSO eigenmode from simpler coupled models (e.g., ZC model) and high-end climate models

– The dominant term in the upper ocean heat budget depends on where you are in the ENSO mode (in space and time)

Ref: Wang and McPhaden 2000

The major source of the energy/forcing for ENSO variability is now known

– The stochastically forced Meridional Mode accounts for most of the seasonal westerly activity in the central Pacific that is not (simply) related to ENSO

– The stochastically off-equatorial forcing of the Meridional Mode explains about half to 2/3 of variance in ENSO

– Variability in the boreal wintertime jet in the Pacific is particularly good at forcing the MM, and accounts for about half of the variance in ENSO

Refs: Vimont et al 2003, Chiang and Vimont 2004, Chang et al 2007, Zhang et al 2009

The Meridional Mode and ENSO (observed)

Refs: Vimont et al 2003, Chiang and Vimont 2004, Chang et al 2007, Zhang et al 2009

Indices of MM wind (FMAM)

and ENSO (CTI) NDJ

Amp. of MM wind

Wind leads SST

Chang et al 2007

Meridional Mode

The Seasonal Footprinting Mechanism (observed)

Ref: Vimont et al 2003

~1 Y

ear L

ater

Winter Heat Flux & Summer SST (contoured)

Composite around |CTI| > 1sigma

Integrated winter wind anomaly drives spring SST anomalies that persist into summer, when it drives the atmosphere (w/ positive a/o feedbacks) to generate zonal wind anomalies in the central equatorial Pacific that give rise to ENSO.

Why ENSO is coordinated with the seasonal cycle

– Coordination of the ENSO eigenmode by the annual cycle (Thompson and Battisti 2001, Kallummal and Kirtman 2008)

– Seasonality in the stochastic energy source of ENSO: the winter storm track variability in the midlatitude Pacific and atmospheric feedbacks (Vimont et al 2003)

– A minor contribution by nonlinear interaction of the ENSO mode and the annual cycle

Importance of the atmospheric boundary layer (convergence) response to setting precipitation anomalies, and consequently the zonal wind stress that the ocean cares about

Refs: Chiang et al 2001; see also Kim et al. 2008, Neale et al 2008

Appreciation of importance of non-normal growth

Refs: Thompson and Battisti 2001, Tang at al 2006, Kallummal and Kirtman 2008

Stemming from the pioneering work of Blumenthal (1991), there is an increasing appreciation for non-normal growth and the fundamental impact of the seasonal cycle for modulating non-normal growth and in controlling predictability of ENSO

More high-end climate models have realistic ENSOs (but most still do not)

Refs: AchutaRao and Sperber 2006, Guilyardi 2006, Wittenberg et al. 2006, Guilyardi et al. 2009 and others

Posit that the limited progress is due to faster machines and more experimentation (tuning), and less so to the systematic evaluation of model biases and the identification of offending physics and the subsequent attention to the offending paramerizations.

Further evidence that errors in the mean state of the high end models affects the ENSO mode characteristics in a way expected from ENSO theory

Refs: Fedorov and Philander 2001, Guilyardi et al 2004, van Oldenborgh et al 2005, Guilyardi 2006, Belmadani et al 2010

Structural errors in the ENSO simulated by high end climate models are consistent with the anatomy of the ENSO eigenmode

Refs: Capotondi et al 2006, Capotondi 2009, Belmadani et al 2010 and many more

For example, relationship between too strong/weak zonal currents and period of the ENSO mode.

More evidence that the linear stochastic physics can explain multidecadal shifts in ENSO statistics without exotic physics or any apparent change in the mean state

Refs: Knutson et al. 1997, Thompson and Battisti 2001, AchutaRao and Sperber 2002, Yukimoto and Kitamura 2003, Yeh et al. 2004, Yeh and Kirtman 2004, An et al. 2005, Vimont 2005, Meehl et al. 2006, Lin 2007b, Wittenberg 2009, and others

Intermediate models with prescribed mean states, and in very long runs of high-end climate models show no relationship between mean state changes and changes in ENSO variance.

Intercomparison of ENSOs simulated by high-end models; development of ENSO metrics

Mainly to tell when and where the models go wrong and to identify systematic biases, and the relationship between mean state biases and ENSO biases across models.

Refs: AchutaRao and Sperber 2002, 2006; Cai et al 2003; Capatondi et al 2006;Collins 2000, 2004, 2007, 2009; Wang et al. 2005, Collins et al. 2010,Guilyardi 2006, Guilyardi et al 2004, 2009, Jungclaus et al 2006; Marryfield 2006, van Oldenborgh et al 2005, Toniazzo 2006, Wittenberg etal 2006, DiNezio et al. 2009; Yeh and Kirtman 2007

2. What problems remain?

Most high-end climate models do not have realistic ENSOs (and they still suffer from gross biases in their mean states)

Problem areas: Ocean mixing, treatment of shallow clouds, deep atmospheric convection, atmospheric and oceanic pbl processes, horizontal (and vertical) resolution of the atmospheric models, …

Refs: Guilyardi et al 2004, Van Oldenborgh et al. 2005, Capotondi et al 2006, Wittenberg 2006, Guilyardi et al 2009, Belmadani et al 2010; Brown et al 2010

Many studies suggest a major problem is in the response of the atmosphere GCM to the observed SST anomalies

Refs: Sun et al 2003, Guilyardi et al 2004, Sun et al 2006, Sun et al 2008, Neale et al 2008, Lloyd et al 2009, Wu et al 2009, Guilyardi et al 2009, Zhang et al 2009, and many others

Seasonal prediction skill using dynamical models is arguably no better than that from the empirical models.

Ref: Kirtman and Min 2009

Posit that this is due to problems with model parameterizations/approximations, and not due to initialization problems (e.g., lack of data, better DA).

How will we know if ENSO has changed?

Wittenberg 2009

Stochastic variability w/ no mean state change? Impact of lower frequency (mean state) variability on ENSO?

Nonlinear interaction of ENSO with X?

What would it take to recognize a forced climate change?

3. Questions for the next 10 years

Is the ENSO mode unstable or stable? Four views:

– ENSO as a chaotic non-linear dynamical system (stochastic forcing is relatively unimportant)

– ENSO as a damped stochastically forced system. Details of the noise matter in the sense of of projecting onto the stochastic optimals.

– ENSO as damped stochastically forced system where the noise is state dependent.

– ENSO as a non-linear self-sustained oscillation where noise produces irregularity

Does it matter?

What is the relationship between ENSO and the Indian Monsoon?

The sub-interannual “Modoki” pattern– Is it a true mode? – Is it a consequence of weak positive feedback between

the atmosphere and ocean in the Meridional Mode physics?

– Is it a pattern that is robust over time (e.g., do we see it in the PI climate)?

– Or is it linked to changes in the mean state in the past 30 years associated w/ increasing GH gases?

What would it take to recognize a multi-decadal mean state modulation of ENSO?

What is the relationship, if any, between multidecadal to centennial variability and ENSO in the unforced climate system?

Where is the remaining energy for ENSO coming from?

– What fraction of the low-frequency variability in westerly wind activity in the central-western Pacific is not already accounted for by the midlatitude jets and (Kug et al 2009) the quasi-steady adjustment of the atmosphere to the changing ENSO mode itself?

– What else could add energy to the ENSO mode besides uncoupled zonal wind variance?

About 2/3 of the energy for ENSO is associated with the stochastic forcing by the midlatitude wintertime storm track (through the SFM/MM physics). This also accounts for most of the seasonal zonal wind activity in the central/western Pacific that is not related to ENSO.

Why was the variance in ENSO reduced in the early-mid Holocene?

How will ENSO change in a world with increased greenhouse gases? Clues: we think we know how parts to the mean state will change:

Consensus on mean state with weakened Trades, decreased the east-west SST gradient, increased upper ocean temperature gradient and shallowing and decreased thermocline tilt along the equator (e.g., Vecchi et al 2006; 2008, DiNezio et al 2009, Collins et al 2010, …)

Do you trust these changes from models w/ gross biases in the mean state (e.g., double ITCZ, shallow cloud errors, gross paramerizations of ocean mixing and atmospheric pbl processes)?

Strength of the stochastic forcing?

4. Priorities (1)

A large engineering effort to fix high end climate models

– so they have realistic climatological mean states – and so they have ENSOs that don’t violate robust

observational constraints

One indicator that high-end climate models still can’t do ENSO well

Preindustrial

2x CO2

Standard Deviation of Nino3

Guilyardi et al 2009

How will ENSO change due to increasing GH gases?

Collins et al 2010

Six of 17 models have that have “the best” (good?) ENSOs don’t agree