This is a straightforward validation of the ENSO model presented at last December’s AGU.
What I did was use the modern instrumental record of ENSO — the NINO34 data set — as a training interval, and then tested across the historical coral proxy record — the UEP data set.
The correlation coefficient in the out-of-band region of 1650 to 1880 is excellent, considering that only two RHS lunar periods (draconic and anomalistic month) are used for forcing. As a matter of fact, trying to get any kind of agreement with the UEP using an arbitrary set of sine waves is problematic as the time-series appears nearly chaotic and thus requires may Fourier components to fit. With the ENSO model in place, the alignment with the data is automatic. It predicts the strong El Nino in 1877-1878 and then nearly everything before that.
This is an expanded view of the proxy agreement. Now the ENSO proxy is in red with squares showing the yearly readings. It would be nice to get sub-year resolution but that will never happen with yearly-growth-ring data.
9 thoughts on “ENSO Proxy Validation”
This is a better comparison to proxy data, where I retain the same color assignment as in the figure above.
Do you have any hope/insight into whether this can be incorporated into the current generation of GCMs — or is their structure such that this is unlikely?
I would think the ability would be a major step forward
That would be an excellent idea. I am trying to find examples of GCMs that will output ocean tidal sea level height. This would be perfect as a first step because one can calibrate the output against the measurements precisely. The next step is to apply that section of GCM code to the thermocline height instead of the sea level height.
Unfortunately there isn’t any community GCM code that I am aware of that has any hooks for lunar forcing, or for external Newtonian forcing for that matter. Ideally, there should be a callback function somewhere for the external gravitational forcing that would be called for every time step.
But I can’t imagine that any coder would have added that callback in the source as it wouldn’t have been a requirement. For that matter, I have yet to see any reference to any lunar parameterization in any code.
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Missed this reference. Behavior of ENSO from Paleo records can be “reproduced once orbital forcing is taken into account”. Australian+USA team of 11
Geophysical Research Abstracts
Vol. 17, EGU2015-8497, 2015
EGU General Assembly 2015
© Author(s) 2015. CC Attribution 3.0 License.
The sensitivity of ENSO to external forcings: insights from the past
Steven Phipps (1,2), Helen McGregor (3,4), Matthew Fischer (5), Michael Gagan (3), Laurent Devriendt (4),
Andrew Wittenberg (6), Colin Woodroffe (4), Jian-Xin Zhao (7), Jessica Gaudry (4), David Fink (5), and Allan
(1) Climate Change Research Centre, University of New South Wales, Sydney, Australia (email@example.com), (2) ARC
Centre of Excellence for Climate System Science, University of New South Wales, Sydney, Australia, (3) Research School of
Earth Sciences, The Australian National University, Australia, (4) School of Earth and Environmental Sciences, University of
Wollongong, Australia, (5) Institute for Environmental Research, Australian Nuclear Science and Technology Organisation,
Australia, (6) Climate Change, Variability, and Prediction Group, NOAA/Geophysical Fluid Dynamics Laboratory, USA, (7)
School of Earth Sciences, University of Queensland, Australia
El Niño-Southern Oscillation (ENSO) is the dominant mode of interannual variability within the climate system.
However, our knowledge of past changes in ENSO variance remains uncertain, as does our understanding of
ENSO’s response to external forcings. Here, we explore both questions by combining geochemical data from
central Pacific corals with a suite of forced and unforced simulations conducted using the CSIRO Mk3L and GFDL
CM2.1 climate system models. On millennial timescales, the coral data reveal a statistically-significant increase
in ENSO variance over the past 6,000 years. This trend is not consistent with the unforced model simulations, but
can be reproduced once orbital forcing is taken into account. Analysis of the simulations reveals that increasing
ENSO variance arises from a weakening of the Asian summer monsoon circulation and an associated weakening
of the Pacific Walker Circulation. On decadal timescales, natural forcings do not appear to influence the strength of
ENSO; however, there is evidence that anthropogenic influences caused a strengthening of ENSO variability during
the industrial period. Combining these results, a picture emerges: (i) on multi-decadal timescales and longer, ENSO
can exhibit a systematic response to external forcing, but (ii) on shorter timescales, variability arises from within
the ENSO system itself.
Click to access egu2015_enso.pdf