EGU2020-11931, updated on 04 Jun 2020
https://doi.org/10.5194/egusphere-egu2020-11931
EGU General Assembly 2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

ENSO sensitivity to radiative forcing

Evgeniya Predybaylo1, Georgiy Stenchikov2, Andrew Wittenberg3, and Sergey Osipov1
Evgeniya Predybaylo et al.
  • 1Max Planck Institute for Chemistry, Mainz, 55128, Germany
  • 2King Abdullah University of Science and Technology, Earth Science and Engineering, Thuwal Jeddah, Saudi Arabia (evgeniya.predybaylo@kaust.edu.sa)
  • 3NOAA Geophysical Fluid Dynamics Laboratory, Princeton, NJ 08540, USA

To improve El Niño / Southern Oscillation (ENSO) predictions and projections in a changing climate, it is essential to better understand ENSO’s sensitivities to external radiative forcings. Strong volcanic eruptions can help to clarify ENSO’s sensitivities, mechanisms, and feedbacks. Strong explosive volcanic eruptions inject millions of tons of sulfur dioxide into the stratosphere, where they are converted into sulfate aerosols. For equatorial volcanoes, these aerosols can spread globally, scattering and absorbing incoming sunlight, and inducing a global-mean surface cooling. Despite this global-mean cooling effect, paleo data confirm remarkable warming of the eastern equatorial Pacific in the two years after a tropical eruption, with a shift towards an El Niño-like state. To illuminate this response and explain why it tends to occur during particular seasons and ENSO phases, we present a unified framework that includes the roles of the seasonal cycle, stochastic wind forcing, eruption magnitude, and various tropical Pacific climate feedbacks. Analyzing over 20,000 years of large-ensemble simulations from the GFDL-CM2.1 climate model forced by volcanic eruptions, we find that the ENSO response comprises both stochastic and deterministic components, which vary depending on the perturbation season and the ocean preconditioning. For boreal winter eruptions, stochastic dispersion largely obscures the deterministic response, being the largest for the strong El Niño preconditioning. Deterministic El Niño-like responses to summer eruptions are well seen on neutral ENSO and weak to moderate El Niño preconditioning and grow with the eruption magnitude. The relative balance of these components determines the predictability and strength of the ENSO response. The results clarify why previous studies obtained seemingly conflicting results.

How to cite: Predybaylo, E., Stenchikov, G., Wittenberg, A., and Osipov, S.: ENSO sensitivity to radiative forcing, EGU General Assembly 2020, Online, 4–8 May 2020, https://doi.org/10.5194/egusphere-egu2020-11931, 2020

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Presentation version 1 – uploaded on 05 May 2020
  • CC1: Comment on EGU2020-11931, Paul Pukite, 06 May 2020

    An annual forcing is observed in the ENSO cross-spectrum with a mirror symmetry about the 0.5/yr point. It's referred to as double-sideband suppressed-carrier modulation

    (sorry about the size of the graph but there is a 500px limit)

    • AC1: Reply to CC1, Georgiy Stenchikov, 07 May 2020

      Dear Paul,

       

      Thanks for your question. I am not sure I understand it correctly. Volcanic forcing is sporadic and the system is nonlinear. So you should see multiple subharmonics generated.

      • CC3: Reply to AC1, Paul Pukite, 08 May 2020

        Annual impulses aligned at a certain time of year, such as at the spring barrier, will create symmetric satellite bands that repeat at 1/yr intervals in the spectrum.  Each repeat would reveal progressively higher harmonics. This chart below is the mirror symmetry where the 1.5 .. 2 /yr spectrum is reverses and folded into the 1 .. 1.5 /yr interval. 

  • CC2: Comment on EGU2020-11931, John Bruun, 07 May 2020

    Dear Evgeniya

    Thanks for sharing such an interesting analysis approach. The logic and ability to distinguish deterministc and stochastic forced El Nino responses with this type of set up I think is very useful. Yes I agree with your argument:  you should be able to probe the inner nature of the ENSO response process with this. 

    A couple of points:

    a) Could you further explain to me the specfic way the butterfly perturbation works - I couldnt quite understand this from the slides, is this a form of ensemble generator, does this nioise have memory? It sounds like its using deterministic chaos concepts (the butterfluy effect) but it is in fact a form of dynamic system bootstrap approach.

    b) With the Tambura type events, for June perturbations:

          i) the year 1 SST (Nino3.4, so the El Nino phase of ENSO, slide 5 figure b) is reduced by ~ 1/2 degreeC. This is still quite a noticeable  effect. Is this consistent with the historic record of the time?

    ii) the year the 2 SST (figure d) implies an enhanced , higher than usual El Nino, temperature ranging from 1/2 degree to 3 degrees. Does this imply that El Nino's could also persist for longer following such an erruption? If so then this is certainly giving us an insight into the inner workings of ENSO as this may have altered the ENSO eigenmodes atleast in a transient way. Then from this it may be possible to identify the transient decay time back to the usual system state.  

    What an excellent way to approach this.

    We are looking at the nature of the ENSO engenmodes and their internal wave mechanics. You can see more of this at Bruun, Evangelou, Sheen and Collins  (EGU2020-11690).

    I'd be happy to continue the conversation - I'm at j.bruun@exeter.ac.uk.

    Best John

    • AC2: Reply to CC2, Georgiy Stenchikov, 07 May 2020

      Dear John,

      Thanks for your questions. Jenny will talk to you more. Here are short responses in the meantime.

      Small perturbations - just like in Lyapunov stability theory, the solution is stable if small perturbations do not destroy it. The form of perturbation is not important. In our case, we apply small radiative forcing. If this small forcing causes finite (not small) perturbations we can say that the state is poorly predictable, or unstable, or produces a stochastic response.

      Tambora here used as an example of three times larger than for Pinatubo forcing.  We know that Tambora erupted in the El Nino year, but there is little known about the magnitude of the ENSO response in 1816. So it is difficult to compare this with observations.

      Yes, equatorial volcanic forcing tends to prolong the El Nino-like response. Our goal was to identify what physical mechanism is responsible for this effect. Of course, this is intrinsically connected to the ENSO machinery. Go ahead and explore this as a dynamic system.

  • CC4: Comment on EGU2020-11931, Takeshi Izumo, 14 May 2020

    Hi Eugeniya, congrats again for the impressive modelling effort!

    I thought more about your reply concerning my first question I had during the chat at the ENSO session.

    My question was: "have you tried to use relative SST (i.e. SST minus its tropical mean) rather than SST, so as to better highlight the El Nino dynamical response in the context of the volcanically-induced global cooling? (cf. our previous study, Khodri et al. 2018) Does the use of relative SST lead to the same conclusions?"

    And your answer was: "Yes, we tried to use relative SST in the analysis, but we found that it strongly overestimates the response."

    Thinking about it again, I am not sure that using relative SST leads to an overstimation of the dynamical El Nino response, as e.g. Nino3.4 relative SST should be a better index of El Nino dynamics than absolute SST, as relative SST should better match with atmospheric deep convection (e.g. precipitation in Nino4 or Nino3.4 region, whatever), and thus with equatorial zonal windstress (e.g. in Nino4), and thereby with sea surface height (in e.g. Nino3.4 region, e.g. Maher et al. 2017, GRL). So actually it might be that using absolute SST underestimates the ENSO dynamical response. Have you tried to check this, by comparing Nino3.4 relative SST or absolute SST response with the precipitation, zonal windstress and/or SSH indices?

    I am looking forward to your answer.

    Anyway, thank you again for your great work!

    Takeshi