by Marcia Wyatt
Implications for the “stadium wave” and Northern Hemisphere climate variability.
The observed Northern Hemisphere temperature trend over the last 100-plus years increases non-uniformly, with multiple-decade intervals of strong warming alternating with multiple-decade intervals of stalled warming or slight cooling. Similar behavior emerges in proxy data, dating back several centuries (Black et al. 1999; Gray et al. 2004). A question of attribution emerges. What is the source of this non-uniformity? Does the climate system’s intrinsic (internally generated) variability script this pattern or are external forcings (natural and anthropogenic) of the climate system in charge? One may ask why it is necessary to know, or what one gains by knowing. Isolating an intrinsic signal from a forced one is not a matter of sorting out anthropogenic from natural, the value of this distinction more readily apparent. But debate does exist regarding the observed temperature trend – intrinsic versus forced. And debate exists regarding how to disentangle the two components.
Intrinsic variability is not devoid of external forcing. Internal variability emerges with a constant force applied. In addition, an inconstant external forcing can influence the intrinsic character of an intrinsic system. An applied time-varying force, with a frequency close to that of the intrinsic system, can potentially nudge the oscillatory time scale of that system if interaction between the forcing and the system interact sufficiently. In contrast, a forced system oscillates or varies only in direct response to the applied force.
Mann et al. 2014 address this attribution issue. Their approach is two-fold: i) to evaluate the current instrumental surface average temperature trend in context of modeled temperature histories; and ii) to evaluate methodology used in studies whose findings are consonant with the view that intrinsic variability plays a non-trivial role in multidecadal climate behavior. The hypothesis underpinning the Mann et al. work is that the low-frequency component of variability in Northern Hemisphere surface average temperatures (NHT) is dominantly a product of a radiatively forced signal.
In the Mann et al. study, an estimate of the forced component is computed via the use of a simple energy-balance model. Subtracting this component from observed NHT yields their estimated intrinsic component. They combine this estimated internal variability with model-simulated data from the fifth version of the Coupled Intercomparison Model Project (CMIP5) database to generate a collection of ‘alternate’ temperature histories. They use the alternate temperature histories to evaluate the current observed NHT. With their estimated intrinsic component, they evaluate methodology employed in studies whose findings support a non-trivial role for intrinsic variability in the low-frequency climate signal.
Mann et al. submit that: i) the recently observed NHT falls within their computed ensemble of temperature histories; ii) the intrinsic component is minimal and regionally confined; iii) the method of linear detrending overestimates the amplitude of internally generated climate variability; and iv) an apparent hemispheric signal-propagation – the “stadium wave” – is no more than a statistical artifact of that method. This memo examines the Mann et al. conclusions and presents counter-arguments that lend perspective to the debate.
II. Framing the debate: how to interpret low-frequency climate variability:
Low-frequency behavior is evident in surface temperatures across the Northern Hemisphere, with particular focus on sea-surface temperatures (SSTs) in the North Atlantic. Instrumental and proxy data of the North Atlantic SSTs reflect a multi-decadally repeating pattern, with no fixed or narrowly defined frequency over the centuries’ length proxy record (Vincze and Janosi 2011); although during the 20th century instrumental record, its quasi-period centered on ~64 years. This North Atlantic variability has been termed the Atlantic Multidecadal Oscillation (AMO: Kerr 2000), whose timescale of variability is thought to be influenced by the Atlantic sector’s Meridional Overturning Circulation (AMOC) (Knight et al. 2005). Similar timescales of variability have been identified in different climate patterns across the Northern Hemisphere (Enfield et al. 2001; Goldenberg et al. 2001; Sutton et al. 2003; Sutton and Hodson 2003, 2005, 2007; Knight et al. 2006), leading to speculation that the AMO’s reach is hemispheric, perhaps global.
These observations have spawned speculation that a North Atlantic-born signature (AMO) is imprinted on the hemispheric (possibly global (Lee et al. 2011; Feng He 2013)) climate record. If one assumes a relationship to the AMOC, and if one assumes the AMOC to be internally generated, then one might infer the hemispheric (global) temperature signature to contain an intrinsic signal. Herein lies the debate – is the observed low-frequency climate behavior of the AMO forced or intrinsic. And herein lies the crux of the Mann et al. argument. While they do not deny the existence of the AMO, they find its spatial reach minimal and its amplitude low, giving it little influence over hemispheric (global) climate. Mann et al. argue that estimations of amplitude and teleconnected influence of AMO that assign a non-trivial role to intrinsic variability are functions of a flawed statistical methodology, in particular, the method of linear detrending, and not of a physical reality.
III. Identifying the AMO:
Many methods have been used to identify the multidecadal nature of the AMO – principal component analysis (PCA) (Parker et al. 2007), linear detrending (e.g. Enfield et al. 2001; Knight et al. 2005, 2006, 2009), and differencing (e.g. Mann and Emanuel 2006; Trenberth and Shea 2006; Kravtsov and Spannagle 2008; Knight 2009). If the goal in applying these methods is to isolate the intrinsic component from the forced, each carries weaknesses (Knight 2009). In the case of linear detrending, if the forced signal is time-varying, then a portion of it will be retained in the detrended product, thereby modifying the residual. Depending on the time-varying structure of the forced signal, the residual’s variability may be enhanced or dampened. In the case of differencing, there are various versions. In one version, a global signal is subtracted from an Atlantic signal (e.g. Trenberth and Shea 2006). In this case, if an Atlantic fingerprint exists within the global signal, the risk of overfitting leads to underestimation of the residual, as a portion of the Atlantic fingerprint is subtracted from itself. And in differencing versions where modeled terms are used in conjunction with the differencing method (e.g. Mann and Emanuel 2006; Kravtsov and Spannagle 2008; Knight 2009), whereby a modeled forced signal is generated and subtracted from the observed hemispheric signal, results of the end-product depend upon the modeled forced signal. Forcing profiles, climate sensitivity used to generate them, and successful removal of the model’s own internal variability from the simulated data (where applicable) are all subject to assumption and uncertainty. All influence the residual that is termed intrinsic.
IV. Mann et al 2014 “AMO” – differenced vs. linearly detrended:
One goal of Mann et al. is to isolate the intrinsic component of the AMO. Assuming the NHT is a combination of a forced signal and an intrinsic one, they apply their differencing method: From the observed Northern Hemisphere temperatures, they subtract a model-estimated signal, which is forced by natural and anthropogenic contributions. The residual of this operation is their intrinsic component. Smoothing the residual with a 50-year low-pass filter generates the low-frequency expression of this intrinsic component. They term this expression the “AMO”, in reference to the AMOC-driven portion of climate variability.
They compare this “AMO” to one obtained by linearly detrending the Northern Hemisphere mean temperature data (not the North Atlantic SSTs), followed by a 50-year filter. This procedure is not typical of most studies that use a linearly detrended AMO. In these studies, AMO, itself, typically is detrended. The AMO data set provided by NOAA, and commonly used in studies, is a linearly detrended Kaplan SST data set for the North Atlantic SSTs. Mann et al. compare the two constructed “AMO” terms and find differences, with the linearly detrended version having greater amplitude and different phasing than the differenced counterpart, in particular in recent years – the ‘hiatus’ years. They find the differenced “AMO” has been decreasing since the late 1990s, a time during which the detrended AMO was continuing to increase.
V. Mann et al. and the stadium wave:
Mann et al. further pursue their argument by focusing on a relatively recently introduced hypothesis (Wyatt et al. 2012 (first online in 2011)) involving a climate signal that propagates across the Northern Hemisphere through a synchronized network of geophysical indices, geographically and sequentially communicated by a chain-like signal transmission through the coupling of ocean, ice, and atmospheric patterns. This propagation is called the “stadium wave”, the underlying mechanisms of which are detailed in Wyatt and Curry 2014 (online 2013). Mann et al. claim the propagation identified as the stadium-wave signal is no more than a statistical artifact – a product of flawed methodology – i.e. linear detrending.
To address the potential role of linear detrending in generating false propagation, Mann et al. take their model-simulated forced signal and add to it a random white noise time series. They repeat this operation, generating a collection of surrogate climate indices. Five of these surrogates constitute their “climate network”. The assumption underlying this procedure is that all climate indices in nature are a combination of a common externally forced signal plus interannual climate variability represented by white noise. They call these constructs “AMO teleconnections”, even though there is no AMO, only a forced signal plus noise. They then linearly detrend all surrogate indices, followed with a 50-year filter. Results are plotted. The paper shows some interesting propagation scenarios that actually do resemble the Wyatt et al. plots in that there are phase shifts between filtered surrogate indices, creating an appearance of propagation. The supplementary section hosts additional plots; although their phase-shift sequences are less suggestive of the stadium wave. The basic premises of Mann et al. are: one, there exists an attribution problem, with assessment of intrinsic contribution to NHT largely a function of methodology; and two, that propagation patterns can emerge as statistical artifacts if the methodology applied is flawed (i.e. if linear detrending is used), and that uncertainty exists in lag times between index members.
VI. The stadium-wave:
To clarify a point that might get lost in the Mann et al. argument, the stadium-wave hypothesis does not address the attribution issue. The propagating dynamic is envisioned to be intrinsic with the current boundary conditions of Earth systems in play. AMO sets the tempo. Whether the AMO variability is intrinsic, forced, or a combination is irrelevant to this hypothesis. The stadium-wave describes the communication of a climate signal across the Northern Hemisphere, paced by the AMO. In the stadium-wave studies, all indices were linearly detrended – not in order to isolate an intrinsic component, but rather to highlight multidecadal variability. Removing the secular-scale (century-length) trend is one step toward effecting this goal.
As far as selection of statistical methods applied, in any study, these choices are guided by assumptions associated with the hypothesis being tested. The Mann et al. work is rooted in the assumption of a single forced component, whose various temporal expressions differ due to adulteration by noise. In contrast, the hypothesis underpinning the stadium-wave is that on long time scales, climate variability organizes into network behavior executed through coupled dynamics among ocean, ice, and atmospheric circulation patterns. Thus, different methods of analysis are required for these different views.
To examine collective behavior of the hypothesized stadium wave, the authors employed a multivariate approach – Multiple Channel Singular Spectrum Analysis (M-SSA: Moron et al. 1999; Ghil et al. 2002) – that identifies co-variability among network members. With this method, only the time scales at which all network members vary are identified. Single-variable methods cannot identify such timescales of shared variability among indices. For the stadium wave, only a time scale of between 55 and 70 years emerged as being shared by all network members. Numerous index networks were analyzed (Wyatt (dissertation: 2012) and Wyatt and Curry (2014)). All produced similar results, all with physical basis suggested.
Support for Stadium-Wave propagation:
Model-simulated data: After Wyatt et al. (2012) documented propagation characteristics of the ‘original’ stadium-wave network, Wyatt and Peters (2012) sought to find similar behavior in model-generated data. They used model-generated data from the third version of the Coupled Intercomparison Model Project (CMIP3) to investigate whether the models produce stadium-wave-like behavior. From the modeled raw variables (e.g. SSTs, sea-level-pressures, etc), climate indices that were used in the original stadium-wave study (Wyatt et al. 2012) were reconstructed. These simulated indices were then treated exactly like the ‘real’ indices used in Wyatt et al. 2012. In other words, it was assumed these indices would function as a network on multidecadal time scales.
Twenty-one of 22 models were represented (one model output was corrupted (http://pielkeclimatesci.wordpress.com/2011/06/28/comments-by-marcia-wyatt-on-cmip-data/)). Sixty-six runs were processed – the majority with prescribed “business as usual” CO2 increase; a few runs were pre-industrial control runs. None of the 66 runs produced a stadium wave. Of the models that produced a low-frequency signal, that signal was stationary and in-phase, with no propagation – reminiscent of an externally radiatively forced signal. In contrast, the leading secular-scale stadium-wave signal in observations is captured by two leading M-SSA modes, each reflecting an approximate 60-year quasi-periodicity. The stadium-wave signal is identified in a vast and diverse collection of geophysical instrumental and proxy indices – not just for the 20th century, but prior to itWyatt (dissertation: 2012), when anthropogenic forcing was not a factor; thus further suggesting that propagation is unlikely to be an artifact of linear detrending.
A question surfaces: If linear detrending generated a false propagatory signal in instrumental and proxy data, as Mann et al. suggest, then why did the same methodology applied to indices reconstructed from computer model-generated data – 20th century data and pre-industrial model-generated data – not produce the same false propagation?
Mechanism: Propagation illuminated by statistical means is meaningless without dynamical foundation. The propagation patterns derived in Mann et al’s work have no physical basis. This stands in stark contrast to the stadium-wave phasing. In Wyatt and Curry (2014), a detailed set of mechanisms is offered, each step (ocean, ice, and atmospheric coupling) in the sequence discussed and supported by previous research. Furthermore, proxy data representing the various climate indices peak and trough at the same phasing as their instrumentally measured counterparts. Proxies used in Wyatt and Curry have been long observed to be correlated with certain ocean and large-scale wind patterns. That the phasing of these proxies fall at ‘expected’ times when evaluated separately from their climate-index counterparts, speaks to the mechanisms at play.
Spatio-temporal statistical analysis: Additional statistical evaluation (Kravtsov et al (submitted)) further weakens the Mann et al. argument that the stadium wave was a statistical artifact. To test this, Kravtsov et al. adopted and generalized the Mann et al. procedure to estimate the uncertainty of phase lags in their inherently multivariate-signal-detection approach, and found that the observed lag times between indices were larger than the lags expected from the random sampling at the 5% significance level. This is opposite from what Mann et al. concluded. And finally, Kravtsov et al. identified spatial structures of the observed stadium-wave signal that could not be duplicated with the forced signal generated by the state-of-the-art GFDL model.
VII. Summary and Discussion:
The Stadium Wave:
Failure of modeled data to produce a stadium wave (Wyatt and Peters 2012); mechanisms describing stadium-wave propagation through coupled ocean, ice, and atmospheric indices (Wyatt and Curry 2014); and rejection of Mann et al’s null hypothesis (Kravtsov et al. submitted) combine to provide strong support for the stadium-wave propagation sequence in generating the multidecadal component of the Northern Hemisphere’s observed climate variability. Thus, Mann et al.’s arguments against the stadium wave seem weak.
Mann et al’s understanding of the stadium wave appears incomplete. Evolution of the idea may have obfuscated our message. Thus to clarify: The stadium-wave hypothesis describes a hypothesized intrinsic dynamic of hemispheric signal communication under boundary conditions extant throughout the 20th century (and perhaps for at least a century prior). It is paced by the AMO, regardless of the forced or intrinsic nature of AMO’s variability. Thus, regardless of a forced signal’s magnitude or temporal structure, the stadium wave derives its marching orders from the AMO. If radiative forcing weakens or slows the AMOC, and thus the AMO, then the stadium wave should reflect this. If sea ice in the Eurasian Arctic disappears completely, the stadium wave may cease to operate (see Wyatt and Curry 2014). These are points for further investigation.
Linearly detrending indices in the stadium-wave climate network removes the secular-scale trend. It is used not to isolate the intrinsic component of the AMO, but rather to highlight variability on time scales shorter than century-scale. M-SSA was then applied to the network of indices to detect co-variability among index members. In the stadium-wave analyses of instrumental and proxy data, shared variability among network indices occurred on multidecadal timescales only. Individually, climate indices exhibited additional timescales of variability – annual to interdecadal – but none of these timescales was shared by all network members. Thus, over long timescales, it is hypothesized that ocean, ice, and atmospheric systems across the Northern Hemisphere organize into synchronized (matched rhythms) network behavior. In the architecture of the hypothesized stadium-wave network, a climate signal is sequentially propagated across the Northern Hemisphere, its potential influence on the Southern Hemisphere not yet determined.
Methods and Isolating the Intrinsic Component of the AMO:
And beyond focus on the stadium wave, general arguments put forth by Mann et al. regarding methodology used to isolate forced and unforced components of climate variability serve only to highlight the debate over disentanglement of components, while promoting the tacit assumption that all studies using linear detrending use it to isolate the intrinsic component of NHT. In the case of the stadium-wave, this assumption is false.
There is value to Mann et al’s method of differencing. It is one way to attempt to isolate an intrinsic component, if that is the goal. Others have used differencing with alternate terms being subtracted (Trenberth and Shea 2006; Mann and Emanuel 2006; Kravtsov and Spannagle 2008; Knight 2009), some with results divergent from Mann et al’s, in fact, some with results that are not too dissimilar from those derived from linear detrending (Kravtsov and Spannagle 2008; Knight 2009).
This memo addresses arguments set forth in Mann et al. 2014 regarding the statistical method of linearly detrending indices, and this method’s purported role in generating a statistical artifact resembling that characterizing the hypothesized ‘stadium wave’. The methodology of Mann et al. is described, their arguments outlined and addressed, and the debate put into perspective.
Mann et al. challenge the method of linear detrending in its ability to separate intrinsic variability that is often associated with the AMO from forced variability associated with radiative signals. No method – linear detrending or the differencing method – is free of uncertainties and weaknesses as applied to the goal of isolating the intrinsic component. Linear detrending removes a secular-scale signal. This highlights multidecadal variability, with no guarantee of separating components of a climate signal. Most who use this approach recognize this, including the authors of the stadium wave studies.
Information in this present memo weakens the case of Mann et al. as it pertains to the stadium wave. Indeed, through Mann et al’s approach, they were able to plot indices that appeared to propagate, suggesting the propagating nature of the ‘real’ stadium wave was of similar specious derivation. A collection of arguments outlined in section VI counter this assertion. Further analysis reaffirms the assertion that the hypothesis of the propagatory nature of the stadium wave is highly unlikely to be due to random sampling.
Mann et al. interpret the stadium wave as a challenge to their forced signal. This conclusion seems unfounded. While the stadium-wave’s propagation dynamic is likely to be intrinsic, AMO is the pace-setter. The stadium wave says nothing about the components of the AMO. It may be forced, intrinsic, or a combination; such is irrelevant to the stadium-wave propagation. The stadium wave represents a dynamic involving ocean-ice-atmospheric coupling sequentially transmitted across the Northern Hemisphere on multiple-decade time scales. A cool signal in the Atlantic leads to a warming hemispheric signal half-a-cycle later, feeding back upon the Atlantic throughout the cycle, continuously planting seeds of reversal (Wyatt et al. 2012; Wyatt and Curry 2014). Boundary conditions of ocean, ice, and atmosphere of the 20th century supported the stadium-wave propagation in its 20th century manifestation. If boundary conditions change, so might the stadium wave. Thus, this hypothesis invites more exploration than simply limiting focus to intrinsic vs. forced contributions. Earth systems appear to redistribute heat laterally and vertically, regardless of source.
Acknowledgements: Feedback from and input by Sergey Kravtsov and Judith Curry enhanced the accuracy and readability of this memo. It is difficult to write a piece that challenges another’s work, as I am fully aware that each study is the product of tremendous effort, time, and thought. Criticism can fuel unproductive motivations. A current of inadvertent bias underlies researcher opinion; thus potentially hindering equal explication of diverging view points. I pose no exception to this observation. The goal I hope to have achieved with this work is to frame the debate between two contrasting points-of-view with scientific perspective so that the reader can see the basis for each.
JC note: For context, see these two previous posts:
This is an invited guest post. As with all guest posts, please keep your comments relevant and civil.
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A brief summary comparison might be in order.
Mann wants to disappear the MWP (and thereby natural, non-CO2 related warming), selects an inappropriate network (bristle cone pines), invents an inappropriate statistical method (see McIntyre), and created his masterpiece the hockey stick. Unfortunately for him Viking ruins in Greenland still exist proving he is wrong; archeology trumps tree rings.
Mann 2014 wants to disappear the stadium wave, because it shows an oscillation not in the CMIP5 archive (with the implication that the GCMs were tuned to a warming period only partly related to CO2, so run hot, hence the pause), invents a new model based definition of AMO, uses a debatable detrending technique, and voila asserts the stadium wave is a statisical artifact. Unfortunately for him the numerous physical indicia for the stadium wave still exist; physical evidence again trumps his model.
Taking this Mannian habit one step further, Mann 2014 wants to disappear the most inconvenient pause, so invents his own temperature index and gets it published in the famous climate research journal National Geographic, along with the claim that it is only a slowdown, not a pause, and within expected CMIP5 internal variability. Unfortunately for him, the pause is showing up in both fiddled terrestrial and unfiddled satellite temperature records. Even more unfortunately for him, Santer published in 2011 that a 15 year hiatus would falsify the GCM models to 95% certainty. RSS is approaching 18 years ‘hiatus’.
(McIntyre had a post on Mann’s magic temperature record for those interested.)
Mann is quite a piece of work. Dr. Wyatt, your post is very scientificaly precise, but IMO way to polite in exposing yet again scientific errors by someone with the temerity to tweet that Dr. Curry is unscientific. It has thrice been Mann, not the two of you, who conjured statistical artifacts.
Rud Istvan good post. two probably minor comments
1. Mann has used “regression on principal components”, but he did not invent it. McIntyre and McKittrick, as well as McShane and Wyner and others have shown that different implementations of the basic method get different answers. That the results depend highly on select time series has been pointed out by McIntyre over and over; that Mann has been inconsistent in his writings on that point has also been pointed out.
Dr. Wyatt, your post is very scientificaly precise, but IMO way to polite in
I prefer Dr Wyatt’s thorough, straightforward polite approach. I think in the long term it persuades more people to take a good look.
Some people are skeptical about the role of CO2 in causing warming. Mann by contrast is skeptical about everything that seemingly discredits the idea that CO2 matters a lot..
if gravity/magnetism is found to be the underlying driver that causes change, and causes balance within the climate system, it will be fun to be able to say that….
“matter” IS what matters.
….Maybe that’s why we called it thus??
Matthew R Marler, while Michael Mann didn’t invent “regression on principal components,” I don’t know of any case where someone calculated principal components over a segment instead of the entire period. It may be appropriate to say he invented decentered principal component analysis in that he may have been the first person foolish enough to use that horribly messed up approach.
Brandon Shollenberger: I don’t know of any case where someone calculated principal components over a segment instead of the entire period.
I agree that was a serious liability in his approach, and much commented upon!. I still do not think it appropriate to claim that Mann invented the approach. Maybe “invent” is more flexible than I am thinking.
Matthew R Marler, I think it just depends on what we feel can be “invented.” Principal component analysis (PCA) was certainly not invented by Michael Mann. I just don’t see how what Michael Mann did could be considered PCA. He called it PCA, and it has some relation to PCA, but I think it deserves a classification of its own.
But that’s all semantics. I really just wanted an excuse to say Mann’s methodology was stupid!
I believe Santer concluded 17 years pause was necessary, not 15. It wouldn’t surprise me though if he revises that soon.
Most of climate science consists of conclusions that derive directly from dogmatic, unproven initial assumptions, the biggest of which is that CO2 is a climate control knob.
James G, I went back and checked. You are correct. It was NOAA in their State of the Climate 2008 report that said 15 years. Thanks for the small correction.
Minor suggestion, “temperature” /= “climate”. They seem to be used interchangeably.
“…but IMO way to polite in exposing yet again scientific errors by someone with the temerity to tweet that Dr. Curry is unscientific.”
Not “unscientific” as I recall, by which I suppose one could mean simply mistaken, but “anti-science.” Of course the very notion is beyond ludicrous, that a scientist of Dr. Curry’s attainments is somehow actively and intentionally and with malice aforethought working to pervert the practice of science, Mann beclowns himself, over and over again.
That said, I like the politeness. It reflects well on those who stray from the supposed consensus. The climate mullahs like Mann only look the worse by comparison.
Sorry, Above is in reference to Rud’s generally excellent comment.
Pokerguy, you recalled correctly, and I did not. That Is why I seldom play serious poker.
But thanks for the general complement. Few and far between. You might be interested in my next ebook, which contains about a dozen longer versions of previous guest posts here. 52 essays in all. Only energy and climate.
It seems to me that even calling yourself a “scientist” is anti-science, because science is about evidence and testing hypothesis and not people.
So, surely as soon as someone calls themselves a “scientist” and by that suggests that gives them credibility, they are in some sense placing themselves as an authority above that of the evidence and so demeaning the authority from the evidence. As as science is the authority of the evidence suggesting an individual is the authority is anti-science.
Is this even written in English? It is unintelligible.
Ah well Scottish Sceptic as we see now from the BBC following the lead of the LA Times, if you ain’t a scientist then you ain’t $#it and thus even if your a Lord and former chancellor (ala Lord Lawson) you are totally unworthy of debating anything to do with climate science on the airwaves of the BBC. That means such persons like Anthony Watts, and so many others in the debate here are even less worthy of asking those the BBC deems to be real scientists about their claims/works let alone challenging them with the hard questions the leftist journalists of the BBC won’t. We unwashed peons are left with only the opinions of the leftists the BBC wants us to hear without the JC’s of the world. .
One can’t say it often enough: the bulk of earth is a hot ball, largely unvisited and largely unknown. The deep hydrosphere is largely unvisited and largely unknown, though oceanic influence appears in every theory on climate.
That’s just the stuff on this side of the atmosphere.
Unlike ancient primitives, modern primitives often don’t even bother to offer assumptions. They just ignore, staunchly.
Does not compute, Scottie.
In a way, I understand and side with Scottish Sceptic. His point, is if a scientist says the earth is flat, and a bum in the street has a placard saying the earth is round, all the credentials in the world, won’t make the scientist correct. The data makes the bum in the street correct. Period.
A retort may be that a credentialed scientist would never say “the world is flat”. But the fact would remain, that many DID.
Credentials do not necessitate knowledge. They only increase the likelihood of being able to regurgitate the current most popular understanding on a given subject.
Perhaps “Student of Science” is a label you like better than “scientist”, when one is describing themselves??
Politeness here is another description of professionalism and dignity, commodities too infrequent in climate science debates. My estimation of the individual automatically goes up when they display such decorum.
I’ve recently written an article in which I describe some properties of 1/f noise. In this I make the case that because 1/f has a predominance of low frequency/long period noise, these totally random changes are too easily confused with Trends & cycles.
As the climate signal is indistinguishable from 1/f noise, it is just a simple fact that any trend or cycle cannot be attribute to any driver unless there is a specific and provable scientific link.
I hadn’t read much on Stadium wave, and 1/f noise, so am playing catch up here.
But it seems to me, that the Stadium Wave would be driven by the “ripples” in the gravity anomalies, as the circle the globe.
The pattern of gravity anomalies, that earth receives, constantly, can be viewed as an egg carton, or like the waves on the surface of a pool that has lot’s of kids playing in it. And it has periodic signals in it from each of our massive/proximity relevant neighbours. The earth is plowing through this “puckered” space, North pole forward, as is the sun. As we circle the sun, we enter and exit these “puckers”. Part of our planet in sync, and part of it diametrically opposed.
This “scissor” movement of gravity fluctuations, would have leading and trailing edges that would likely at least accelerate, or decelerate a stadium wave, if not be the metronome to which it ticks.
I have in other posts, but will refer again to the gravity anomaly maps available at the GRACE missions data portal, using TYPE Gravity Anomaly, and change the smoothing radius to it’s lowest setting – 25km, to see the data at it’s “rawest”.
Scottish, you write: “As the climate signal is indistinguishable from 1/f noise…” but as I mentioned on your blog, surely it isn’t? Look at temperatures over geological time periods and we see step changes as the Earth goes into and out of ice ages.
Very nicely written, Marcia. Clear and classy.
This picture shows gravity pushing and pulling on Greenland.
I believe it is in relation to magnetism, but gravity is an equally viable and accurate answer. Either way, the “wobble” that the equator of the earth has, relative to the poles, is VERY WELL evidenced, by the reversal of the grey/green from 2002 through 2013.
Please understand, that recognizing this “wobble on axis” for what it is, will explain many other things, like fluctuations in ocean currents, fluctuations in the polar vortex. AND realize that the passage of variation in the motion of the two poles, WILL have a counter nodal output, around the equator, as the pressure wave bounces back and forth in it’s 23 year cycle.
Regardless of whether anyone understands why, or agrees as to the cause. It is an undeniable, simple, observation, that has plausibility, significance, and definitely not a human sourced control mechanism.
PLEASE specifically review the shading of Greenland.
Could it be Anthropogenic Global Wobble?
Wobble, Baby, Wobble!
re: above….definitely, an intrinsic forcing, I would say. :-)
Alistair – head on. Right now, “forcing” and “intrinsic” are just buzzwords. We need a more selective definition. Which came first – the chicken or the egg?
Sorry I was applying my own bias to my use of the words. Dangerous. Well caught. I was using forced, as meaning caused (by us), and intrinsic as being there whether we like it or not. Prob not the popular distinction. And well caught.
I would consider both the up-down movement of the entire core of the earth to be a “naturally” occuring, repetitive event.
Like the angle between the magnetic poles, I imagine there is also a variation in the relative compression of the north and South poles, that is forced by variation in the Sun’s magnetic/gravitational field.
ie, a natural intrinsic cycle, with a magnitude built over a period of time, with a natural and forced variation in the magnitude of the cycle.
@ Alistair Riddoch
The proposal that the AMO, PDO, etc are being mechanically driven by regular shifts in the pattern of the gravitational field sounds WAY more believable to me than ‘ACO2 done it–again’, although I am certainly unqualified to attempt the related mathematical analysis.
My son says, “Dad, I’m good at math, I just don’t like it.”
I try to analogize. Imagine gravity as an egg carton in space, going up and down.
And earth is made up of egg cartons stacked on top of one another, in a sphere.
Imagine us spinning, and plowing into the egg carton in space, because we are tilted, part of earth is going to slide into and out of the egg cartons. part of earth is going to “mash” the egg cartons flat, part of earth is going to “mesh with” and “bend” the egg carton, attempting to “pull it along with us”
Not very hard, then to see. Using an actual egg carton held beside an actual globe might help.
Very simple to disentangle the two. Take an approach such as CSALT and add the stadium wave component represented by LOD as the long-term variability factor.
Thank you, Marcia, for a cool, clear and civil explanation. Well, not actually quite as clear to me as I would like it to be. Perhaps I can use an analogy to see if I am understanding you correctly : When the wind blows across the ocean, large ocean rollers form (an oscillation). This oscillation is intrinsic, not forced, because there is no force acting on the ocean surface with the frequency of the rollers (unlike the tides, for example). You have compared the actual ocean surface to a flat surface and identified the rollers. Mann says there is no forcing, therefore the rollers can’t exist, and that your identification of the rollers is an artefact of your method.
One problem is that there is a cloud over the intellect when Mann, et al., is brought into any discussion about climate because Mann’s science stands for catastrophic warming (be it intrinsic or forced), which is a view that has facilitated the politicization of science, which in turn has caused catastrophic public policy.
That ol’ Hockey StickS designed to disappear the MWP and
the LIA is now, I believe, deceased – may it rest in peace.
The MWP and LIA were well established in the Historical Record,
CET Middle England temperature trends and voluminous witness
testimonies, farmers’ almanacs, ships’ logs, church records on
glacier movements, accounts of ice fairs on the Thames and
also Greenland archaeology, as Tony Brown presented in his
‘Long Slow Thaw’ post here at CE. So much better than an
artifact based on suss techniques applied to suss tree ring
proxies as temperature signals.
The historical record cannot be disappeared by the dismissive
word – ‘anecdotal.’ The events described occured and were
cross-referenced and further supported by Craig Loehle’s
2008 multiple proxy study of 2000 years global temperature
reconstruction based on non-tree ring proxies.Can’t just be
chucked down the memory hole.
the memory hole is where we would find Noah’s Ark and two of every species on earth a few thousand years ago. they’s be hanging out with the Native American rain-dancers, the people bringing fruit baskets to volcanoes, asking them to not blow up, and a few gods that have been known/believed responsible for thunderbolts, lightning, clouds, rain etc.
and the one other thing, we may find down the memory hole, is the moment in time we (humanity) decided each was a story. A well written tale. A fictional past time. A boogie man, to use to scare people into submission, and act in the manner of the presiding authorities. Be they priests, “seers”, spirit-talkers, or plain “crazy”.
our ability to remember the downright stupidity, of some of our earlier thoughts and beliefs, is a subject I find laughable.
but when you put your ear to the memory hole, all you hear is the ocean waves.
The Left chose Al Gore over the scientific method.
I agree with you, I stopped reading as soon as I saw “Mann et al”. I will probabily read this after because I saw the comment “Mann … Incomplete”
Mann2014: model output is incorporated into another model whose output is incorporated into yet again another model whose output is commented upon. Model output is not data, or so I have been told in other areas of science except it seems climate science. So, Mann’s models compounding assumptions and errors reveals artifacts of the methodology, just like Mann is accusing the stadium wave hypothesis of. At all costs, Mann feels the need to preserve the trace gas radiative transfer model as the prime mover in climatology.
Fundamental to Mann’s series of model abstractions is a reliance upon a temperature data set that is adjusted because of (at least) flawed methodology in transitioning from LiG thermometers to automated systems. (see previous post Zeke Hausfather). Specious data being touted as settled science.
” Internal variability emerges with a constant force applied. ” This statement is hard for me to understand as I can envision internal variability may be a resultant of multiple and variable influences and not a constant force. A constant “force” may be the sun although we have been learning that there are sun energy outputs of a spectrum of radiation and particles some or all of which maybe playing a role in earth’s climate change.
On the other hand, are you saying that internal variability can be revealed by applying a constant force to the climate parameters?
I am curious.
Of course, curiosity killed Schrodinger’s cat.
“… internal variability can be revealed by applying a constant force to the climate parameters?”
Consider the pitch pipe. A constant flow of air across the end of the pipe creates a wave (variation in pressure) caused by the least perturbation of the flow. E.g. the edge of the pipes lip or the coastline or depth change in an ocean.
Rih008, I apologize for the confusion. What was text in a footnote was merged into the text when Judy posted it – something about the idiosyncrasies of blogs. I agree that it did not read well. Next time, no footnotes! now I know.
First, no, I was not saying applying a constant force to climate parameters can reveal intrinsic variability. I can see how this was puzzling. I am not convinced that any method can reveal the pure component of internal variability. My intention was to explain what an intrinsic component is, as it is not intuitive. Internal variability can emerge with a constant, non-varying force applied. Consider a pendulum clock. Put a battery in it (or set the weights) for its energy source. That energy source is constant, or effectively so. The pendulum, set into motion, will swing back and forth, not in tempo with an external non-uniform forcing. Its tempo of back and forth is governed by its structure – i.e. the length of its pendulum, for example. Now, if there are minor variations in the energy source, the pendulum length would still be the main influence on the swinging frequency. But no variability in the energy source is necessary for this swing tempo to continue. Enter clock number two. It has a slightly different length pendulum. Nail it into a beam that the first clock is on. The two clocks now have the potential to weakly couple (interact), through vibrations, subtle as they are, through the wooden beam. Give the second clock its energy source. Initially, clock number two swings at its own unique intrinsic time scale. But the clocks are beginning to feel each other’s movement. With time, clock two modifies its tempo slightly, while clock number one does the same. In time, the two clocks have matched rhythms. They are synchronized. An additional forcing – i.e. clock two – with a similar, albeit not exact, frequency, entrained the frequency of the other – clock one. If they later lose their connection to one another, i.e. uncouple, each goes back to its own intrinsic frequency.
Another scenario. If the second clock had no energy source, but instead you moved the pendulum manually, the first clock will ‘feel’ the movement of this forced clock through the beam. If the frequency of this manual movement is close, but not exact, to that of clock one, it is conceivable that clock one will adjust to the tempo of clock two. In other words, clock two might entrain clock one. the difference here is that clock one must do all the adjusting for synchronization to occur. Clock two cannot adjust. it is forced (by you).
Lastly, when you stop the manual movement on clock number two, it slows to a stop. Clock one, no longer under the influence of clock two, resumes its original tempo, it’s intrinsic variability.
The oceans are analogous to the pendulum clock (clock one). In the oceans, a variety of surface and subsurface interactions occur. Basin size, configuration, and latitudinal placement, interacting with wind-induced surfac and subsurfac dynamics, influence the intrinsic oscillatory nature of the varying properties (SSTs, salinity, etc). Feed backs modify further, especially as they affect freshwater balances in the ocean, and thereby impact deep convection and related overturning circulation. These things are the clock’s pendulum length, so to speak. An external forcing would be the manually moved clock. The temporal character of that external forcing -natural or anthropogenic – would have implications on the intrinsic variability, but not in an uncomplicated nor easily predicted manner.
Perhaps this is the reason why research in climate journals is all the same garbage? Notice how “gatekeeper” Adam Savage puts the heretic back in line…
wow. correct or not that was a fantastic explanation.
That YouTube video is a massive “own goal” by the deniers.
Elsewhere on this comment thread, I referenced how a.periodic external force can destroy chaos and result in a periodic regime.
That is not good for the denialists insistence that chaos will lead to unconstrained variability.
Thank you for your explanation, that was helpful.
Now I have a shop filled with cookoo clocks, all with different lengths of pendulums, not any set to a particular time, announcing time to their own rhyme and rhythm: cacophony.
I will have to think about this for a while.
Again, thank you.
Trying to make sense of the above metronome video we have:
“We find that in those cases where the synchronous state was followed by a steady increase in the coupling strength between the indices, the synchronous state was destroyed, after which a new climate state emerged.” – Tsonis et al 2007
When they sync the platform has an oscillation. Now the sync must be destroyed, which is done by stopping the platform oscillation. I’ve thought of the transition between regimes as exhibiting a shudder then a collapse. So if the platform collapses by whatever process, a new platform would emerge over time. If we had 4 climate metronomes a platform may emerge between only 2 of them or 3 of them. Smaller platforms, less than one including all 4 metronomes might sync and collapse without a new climate resulting. So we have oscillating platforms coming into and out of existence with syncing on smaller scales.
Rather than 4 climate metronomes there may be 4 trillion of them or more. What are these platforms? Something strong enough to sync distant locations, but not strong enough to sustain a syncing.
Ragnaar, that is nickel & dime pseudo-science philosophizing on your part. It doesn’t work — either come up with some mathematical models or perhaps get a science degree and then return
In general the video is demonstrating conservation of momentum and a system seeking the lowest energy state. This is a case of where a synchronized oscillation is a lower energy state than that of random oscillations.
The sloshing of the ocean waters will cause slight changes in the earth’s axis of rotation to conserve angular momentum. Gross at JPL made that observation here: R. S. Gross, “The excitation of the Chandler wobble,” Geophysical Research Letters, vol. 27, no. 15, pp. 2329–2332, 2000.
The earth acts as an analogy to the freely-translatable platform that the metronomes are sitting on while the ocean’s water acts as a metronome. Something else, possibly lunar tidal forces is what gives the system a kick and acts as the stored energy in a pendulum. see http://ContextEarth.com
Once these are synchronized it is difficult to move out of this low-energy state.
Interesting comment on the lowest energy state. Metronome F (fast) and metronome S (slow) on the same platform each have their roles. F tries to speed up S and S tries to slow F. When they sync they’ve done that. F and S have reached a joint outcome. Apparently F has transferred energy to S.
The network model is described in the paper quoted. It shows NH indices synchronizing and then the synchronization being destroyed as a new climate state emerges.
It is not primarily about ENSO – which is at any rate far from a metronome. The characteristic frequency of ENSO is 2 to 5 years – which changed from 6 to 7 years in the last century.
The metronomes is a simple problem. The energy supplying the metronomes is constant or nearly so and the losses are minimal. It is an open system leading to a equilibrium synchronized maximum entropy state. Synchronized motions reinforce and unsynchronized motions cancel. Although a metaphor of sorts for the stadium wave – it hardly applies to the ideas of synchronized chaos in climate indices at multi-decadal intervals.
In his grasp of the fundamental ideas – Ragnaar is streets ahead of webby.
Ragnaar is a financial accountant and Rob is a civ.
If any of you two geniuses want to engage with people trying to predict El Nino, I recommend that you join up at http://azimuth.mathforge.org.
You can throw your ideas out there and see who will bite. But I am certain that you are too chicken to do that. It is much easier to toss hand grenades under the cover of a denier-friendly blog.
What a weird statement. I am as webby knows a Civil Engineer specializing in hydrology with a Masters in Environmental Science with a broad interest in environmental policy, law, management and economics as well as expertise in biogeochemical cycling.
I have studied ENSO for decades – it is a core hydrologic influence in my neck of the woods.
Webby is an especially clueless electrical engineer who imagines that calumny substitutes for rational discourse and that he convince someone of his psycho Earth sciences.
So you are afraid to engage with other scientists who are trying to predict the occurrence of El Ninos?
For God’s sake – they are playing with a model that is decades old and used for instructing students in the basics. It has no chance at all of structurally incorporating the difficult aspects of ENSO without fundamental theoretical breakthroughs. What causes the observed centennial change in periodicity? What causes multi-decadal shifts in intensity and frequency?
Yet webby complains that I am afraid of playing with children? It is the usual irrelevant nonsense.
It appears that this Aussie dude is afraid to expose his ignorance amongst PhD scientists, physicists, and mathematicians trying to apply network and nonlinear models to characterize the ENSO process.
‘We study the dynamics of the El Nino phenomenon using the mathematical model of delayed-action oscillator (DAO). Topics such as the influence of the annual cycle, global warming, stochastic influences due to weather conditions and even off-equatorial heat-sinks can all be discussed using only modest analytical and numerical resources. Thus the DAO allows for a pedagogical introduction to the science of El Nino and La Nina while at the same time avoiding the need for large-scale computing resources normally associated with much more sophisticated coupled atmosphere-ocean general circulation models. It is an approach which is ideally suited for student projects both at high school and undergraduate level.’
I have seen the site – http://www.azimuthproject.org/azimuth/show/ENSO – let me know when they say something we don’t know already. In the meantime I will stick to science.
The detrended AMO signal gets latched up in its warm phase for several decades, and transitions to its cold phase in a far shorter period. It doesn’t behave much like an resonant oscillating slosh.
The correlation to declines in solar forcing from 1995 and to increased negative NAO/AO, and the rapid transition to the warm AMO phase, is not only evident through inter-annual trends, but it is there at the seasonal-monthly noise level too.
‘Over the last 1010 yr, the LD summer sea salt (LDSSS) record has exhibited two below-average (El Niño–like) epochs, 1000–1260 ad and 1920–2009 ad, and a longer above-average (La Niña–like) epoch from 1260 to 1860 ad. Spectral analysis shows the below-average epochs are associated with enhanced ENSO-like variability around 2–5 yr, while the above-average epoch is associated more with variability around 6–7 yr. The LDSSS record is also significantly correlated with annual rainfall in eastern mainland Australia. While the correlation displays decadal-scale variability similar to changes in the interdecadal Pacific oscillation (IPO), the LDSSS record suggests rainfall in the modern instrumental era (1910–2009 ad) is below the long-term average. In addition, recent rainfall declines in some regions of eastern and southeastern Australia appear to be mirrored by a downward trend in the LDSSS record, suggesting current rainfall regimes are unusual though not unknown over the last millennium.’ http://ecite.utas.edu.au/81621
This links ENSO and the polar modes. One significant point is 20 to 40 year regime shifts combined with much longer term modulation of ENSO frequency and intensity. The quasi regularity of the Pacific climate shifts suggest an external control variable. A subtle change in external forcing that tips the system into a new state every 20 to 40 years. Far from ‘destroying chaos’ – it is the essence of chaos in the climate system as new states emerge from the interactions of component parts in a system pushed by a control variable past a dynamic threshold.
As Ragnaar suggests – the network nodes synchronize on a multi-decadal scale and then synchronization is destroyed as the system shifts into a new state.
What I love about the stadium wave hypothesis is that it’s observation-based.
It isn’t too surprising models that don’t properly forecast temperature, that when used in the described Mannian manner don’t produce any useful conclusions.
Mann is very talented.
When you incorporate stadium wave theory into a Mannian model, instead of a “hockey stick” you get a “sticky wicket.”
This is good:
“…continuously planting seeds of reversal.”
There’s something in the above that’s possibly describing why and/or how phase changes occur.
I have been out for the day and have just got back and seen your article. It’s late over here and I can’t do it justice this evening so will have a look tomorrow.
“The assumption underlying this procedure is that all climate indices in nature are a combination of a common externally forced signal plus interannual climate variability represented by white noise.”
And this is why they can’t model the climate because far from white noise being the norm in natural systems, the reality is that 1/f noise is pretty ubiquitous.
> the reality is that 1/f noise is pretty ubiquitous.
There. Climate. Solved.
Thank God. What’s the next stupid thing all the progressives are going to get on about?
(See, Edward J. Wegman, et al., Ad Hoc Committee Report On The ‘Hockey Stick’ Global Climate Reconstruction)
1/f natural variability is the elephant in the room that climate scientists won’t touch. The uncertainty monster on steroids. “Pretty ubiquitous” is an understatement – 1/f variability is pervasive at longer timescales, for reasons that should be obvious to anyone with an elementary grasp of mathematics.
f-n probably is more appropriate for pink noise in the context of climate change because there is either no CO2 signal in the data at all (e.g., McShane and Wyner 2010 re the data of Mann, et al.) or we’re looking at a multidimensional phenomenon involving multiple signals.
The global climate system is composed of a number of subsystems — atmosphere, biosphere, cryosphere, hydrosphere and lithosphere — each of which has distinct characteristic times, from days and weeks to centuries and millennia. Each subsystem,moreover, has its own internal variability, all other things being constant, over a fairly broad range of time scales. These ranges overlap between one subsystem and another. The interactions between the subsystems thus give rise to climate variability on all time scales.’ http://www.academia.edu/3226175/Mathematical_Theory_of_Climate_Sensitivity
The interaction of subsystems – and consequent variability at all scales – are such obvious properties of climate. In a fundamental sense a ‘stadium wave’ must exist as a consequence of the interaction of sub-systems. Although the stadium wave is an example of network math that is a level removed from the physical reality of the underlying system. In this network view of things – the ocean and atmospheric indices are chaotic oscillating nodes on the underlying system.
The reality is that the dynamically complex system is pushed past a threshold and the system shifts with changes in ice, cloud, dust and biology to a new emergent state. The rhythm of climate shifts over millennia is the 20 to 40 year beat with a greater or lessor scope for climate change at each beat. This leads to a modified concept of climate. Nominally increasing greenhouse gas forcing against a backdrop of disputed and neglected data from satellites showing large and coherent – occurring to the beat of climate shifts – changes in cloud radiative forcing. Nor is the future scope of multi-decadal shifts knowable in advance – but they do typically involve large changes in climate means and variance. This certainly means that future climate – beyond the next decade or so – is intrinsically unpredictable. The history of climate shifts suggests that the current mode could persist for another decade to three.
Mann et al (2014) rely on distinguishing estimated changes in sulphates from imputed changes as a result of an intrinsically varying AMO. The limitations of this approach seem evident. Sulphates are poorly quantified – natural variability is unquantified in any substantive way but is far from confined to the AMO. Neither can 20th century patterns of climate variability be expected to be repeated in the 21st.
While this statement may be technically semantically correct, it loses the reality of the situation. If you did a network map of the elements that actually drive the system behavior, most of them would be very local, with more connections to local elements that are part of different “subsystems — atmosphere, biosphere, cryosphere, hydrosphere and lithosphere”. Thus, calling these general categories “subsystems” is highly misleading.
‘Most studies of African dust and North Atlantic climate have been limited to the short time period since the satellite era (1980 onward), precluding the examination of their relationship on longer time scales. Here a new dust dataset with the record extending back to the 1950s is used to show a multidecadal covariability of North Atlantic SST and aerosol, Sahel rainfall, and Atlantic hurricanes. When the North Atlantic Ocean was cold from the late 1960s to the early 1990s, the Sahel received less rainfall and the tropical North Atlantic experienced
a high concentration of dust. The opposite was true when the North Atlantic Ocean was warm before the late 1960s and after the early 1990s. This suggests a novel mechanism for North Atlantic SST variability—a positive feedback between North Atlantic SST, African dust, and Sahel rainfall on multidecadal time scales. That is, a warm (cold) North Atlantic Ocean produces a wet (dry) condition in the Sahel and thus leads to low (high) concentration of dust in the tropical North Atlantic, which in turn warms (cools) the North Atlantic Ocean. An implication of this study is that coupled climate models need to be able to simulate this aerosol related feedback in order to correctly simulate climate variability in the North Atlantic. Additionally, it is found that dust in the tropical North Atlantic varies inversely with the number of Atlantic hurricanes on multidecadal time scales because of the multidecadal variability of both direct and indirect influences of dust on vertical wind shear in the hurricane main development region.’ file:///C:/Users/Robert/Documents/Technical/Climate/Wang_etal_2012_JC%20dust%20and%20atlantic%20sst.pdf
In this case a dust feedback to north Atlantic SST originating in the Sahel. But before getting into such detail I think it is fair to define the system as interacting elements of atmosphere, biosphere, etc. As the elements that define the system are subordinate to the total system it seems fair also to define them as sub-systems. I get your point but disagree that it is a substantive issue.
I am interested in a top down mechanistic concept that explains the broad sweep of climate data. I am interested in details as well. What causes SST change in the north Atlantic? Conceptually – there are control variables that periodically push the system past thresholds. Only then can you effectively understand the need to identify control variables – which according to the NAS may be so small as to be undetectable.
Personally – I think top down modulation of polar pressure fields by ozone/UV interactions are a good fit. These spin up sub-polar oceanic gyres in ways that feed into global changes in ocean and atmospheric circulation and consequently biology,ice, dust and cloud.
It seems very unlikely that we can distinguish between ‘forced’ and ‘natural’ variability in pressure fields at the poles let alone anticipate all of the disparate feedbacks.
When people break the total system down into functional categories (such as “atmosphere, biosphere, cryosphere, hydrosphere and lithosphere”), they tend to think they can create a model that will approximate the total despite leaving out one or more of these categories. Calling such categories “subsystems” tends to imply modularity. A picture is worth a thousand words.
When people think of such functional categories as “subsystems”, they will be led to picture something like network “C” in the linked picture, with each of the colored modules representing one of your “subsystems”. But at best the reality is much more probably something like network “D”.
In fact, IMO there are probably functional subsystems that look something like network “C”, but they are made up of more localized elements from all of the categories you named, with the functional modules being more made up of neighbors in a geographic sense.
Indeed, the example you quoted fits perfectly:
These elements (“North Atlantic SST, African dust, and Sahel rainfall”), along with some associated elements, could probably be isolated into a functional “module”. Like a flip-flop in an integrated computer circuit, this module can be switched among various states by external factors, while maintaining its state when undisturbed. Such a module, along with the mechanisms that drive its changes of state, IMO, make a much better “subsystem” than some lumped-together category that includes, e.g., “African” (meaning Sahel) dust with that from the Kalahari, Tibet/Taklamakan, Oklahoma, and the like, while excluding “North Atlantic SST […] and Sahel rainfall”.
The first link is to the first chapter of Werner Callebaut & Diego Rasskin-Gutman (eds.), Modularity. Understanding the Development and Evolution of Natural Complex Systems, Cambridge: MIT Press, 2005.
The picture linked to by the second link is figure 3 from Meunier D, Lambiotte R and Bullmore ET (2010) Modular and hierarchically modular organization of brain networks. Front. Neurosci. 4:200. doi: 10.3389/fnins.2010.00200.
I think AK is right. It makes much more sense that regions (each one including each “subsystem”) interact with each other and that the subsystems interact within the regions. Well, some more than others. Conceptually, the atmosphere seems much more of a contiguous subsystem than the biosphere, for example.
atmosphere has a constant “gravity pressure” interference pattern running through it, the earth, and everything.
the pattern is clear on these maps,
(I recommend smoothing radius =25km)
and it probably at least adjusts the tempos of weather patterns on earth, if not controls outright.
AK has raised some interesting points.
The world is divided into ‘Koppen’ climate classifications on the basis that each has certain characteristics. It would follow that the climate within each koppen classification is LIKELY to all be moving in the same direction and that it MAY (sometimes) be the opposite direction to those in other classifications. In other words some places may be cooling as others warm or some have increased rainfall whilst others experience drought.
We can clearly see in the historic record for the UK that some decades are notably cooler than others and some decades are notably wetter than others.
These presumably are affected by SST’s, jet streams, wind direction etc. How they interact or are affected by-or affect-the stadium wave is a mystery. I would certainly like to see more emphasis placed on regional/local nuances than a somewhat meaningless ‘global’ average which misses these nuances.
I have previously asked Mosh if he could produce a graphic of temperatures based on Koppen climate types but I think it was a lot of work.
try this website. But it is trying to do trends in classification of areas, not trends in temperature or climate BY classified area, which is what I think you were getting at. An interesting exercise…it would be pretty straightforward to do without GIS if there was a list of classification by lat long grid cells somewhere.
indeed Tony you can download gridded versions of the K-G classifications for each of the time periods they discuss on the web site I linked. For instance you could download a text file of the K-G classifications for the average of 1901-1926 (average of an older HadCrut and GISSTemp I think). You could get the gridded HadCrut or GISSTemp data, compute trends by grid cell and organize those trends by K-G classification bins to get average trends for each classification. definitely doable in excel let’s say.
As you – it is semantically correct to refer to the elements as sub-systems. There is a more profound point here than isolating the aspects of these elements that are active in specific circumstances.
The example I gave was a feedback – warmer north Atlantic SST, more Sahel rainfall, less vegetation, more dust, cooling SST. Ocean, atmosphere and biology interacting.
As you say…
On detrending vs. differencing approaches, this post I wrote back in 2011 is still relevant: http://rankexploits.com/musings/2011/the-atlantic-multidecadal-oscillation-and-modern-warming/
Zeke I enjoy reading what you think at Lucia’s and here. Glad to see your reading Dr.Wyatt’s work and the extra information on the AMO is appreciated. You are a good scientist and first temperature paper was excellent.
The PDO has it’s own “rhythm” and presumably a “forced” and “natural” component. I don’t see that differencing it and the AMO makes any sense, physically.
So, once again, you are left with an unknown contribution from ACO2 and other causes for SST variations.
But I think the magnitude of the AMO doesn’t matter much to the stadium wave hypothesis. The physicality is to a large extent captured in the phasing, rather than magnitudes, of the various components of the wave.
Sure it does. A better example would be taking the indian ocean as a forcing control region and then differencing the other basins. Since the IO has the least THC flow and near zero northward outflow it has the least intrinsic variability. I did that a while back. Pretty interesting.
CD – care to share the source of the IO SST data? I could continue to google for another hour, but if you already have it, seems like a waste of time.
knmi climate explorer lets you do area masks. Mine weren’t perfect but close enough for a fair estimate. I used ERSSTv3b.
Dallas, you might be interested in Lee et al 2011
What caused the significant increase in Atlantic Ocean heat content since the mid-20th century?
So, based on Lee et al 2011, it appears the Indian Ocean isn’t a viable candidate to which to difference the AMO either.
jim2, “So, based on Lee et al 2011, it appears the Indian Ocean isn’t a viable candidate to which to difference the AMO either.”
It doesn’t work that way. If you are going to difference you should have several references and the IO would be one.
steven, ” What caused the significant increase in Atlantic Ocean heat content since the mid-20th century?”
When I was doing ocean basin comparisons I scaled the 0-700 meter vertical temperature data to the basin SST. Other than a few short term divergences, 0-700 tracks SST, so what caused the the loss of Atlantic Ocean heat content from the peak in the early 1940s to mid 1970s? I think the Stadium Wave might offer a clue or two.
Dallas, maybe. I can look at the UKMO EN3 OHC series where it shows OHC in the Indian Ocean increasing during that time period. Ed Hawkins has a post called the signal the noise and the time of emergence. It matches up reasonably well with a warming Indian Ocean sending heat south around Africa and then up to the Arctic.
steven, “Dallas, maybe”
There aren’t that many definite signals. There is an indication of long term persistence in the IO from ~1700 using SST regional reconstructions though which should be sorted out and there is the issue of land amplification and precipitation influence on proxies like tree rings and sediments.
Have you ever seen any papers that refer to the effects of wind on cooling the ocean? I appreciate the wind would only affect the surface but it is like continually blowing on the surface of a hot drink to cool it down, eventually it has an effect
Winds vary widely in direction and strength from decade to decade and its direction in particular will, according to season, have a marked impact on ocean surface temperature.
I have never seen any references to this subject.
tonyb, “Have you ever seen any papers that refer to the effects of wind on cooling the ocean?”
Toggwieler with the GFLD has a few on the shifting westerlies but I haven’t seen many dealing with the NH. Manabe estimated latent transfer from the oceans to land at around 18 Wm-2 global equivalent and since most of the land is in the NH that is a better place to look IMO.
wow. good series of comments by Zeke, jim2, Rud, captain dallas and steven. thank you.
Zeke, since that post BEST has noted 30 to 60 north land amplification is a tad more than expected. How would that impact your estimate?
Zeke, thanks for calling attention to your previous post on detrending. Had not seen it before. Differencing results in half and half, more or less. (I am deliberately not trying to be statistically precise as you are, with areas under the curve, error ranges, confidence levels, and all that science stuff in this comment). There is a powerful simple irrefutable point Marcia made in her lead post, that you also make here (and that Mann 2014 tries to disappear).
There is a non-anthropogenic component to the observed warming since (pick your year) about 1975 (back when Holdren was still writing about global cooling, so works nicely politically). That component is nontrivial. The CMIP5 models tuned hind casts on this period without excluding that nontrivial non-anthropogenic warming component (halfish). So they run hot by a factor of twoish. Nic Lewis and now many others finding running hot by TCR and ECS roughly double what observational methods now suggest. (1.3 verus 1.7-1.8, 1.7 or so versus 3 to 3.2 respectively). Halfish because of twoish AGW overheated because ignored the non-anthropogenic halfish in the tuning hind cast period.
This becomes a simple ‘ladies and gentlemen of the jury’ layman’s level (ignoring non-linearities and bunches of other lesser stuff) complete condemnation of the IPCC and it’s Assessment reports. And, a strong argument that the lukewarm position is most likely correct. So the UNFCCC mitigation policy plus ‘Green Climate Fund’ reparation responses are most likely incorrect.
I sense a great deal of potential political traction in this formative sound bite.
Plus another essay for the book on energy and climate whose ‘final’ draft was supposed to have been finished two months ago. More work ahead.
Zeke, that would work if the AMO is actually limited to the North Atlantic. Wang et al 2011 is a 400 year reconstruction of the AMO. It was done in Eastern Asia.
Imprint of the Atlantic Multidecadal Oscillation on Tree-Ring Widths in Northeastern Asia since 1568
“Although AMO is a feature of the North Atlantic Ocean basin, recent studies suggest that it is also related to multidecadal variability of Asian and Indian monsoons –. Through comprehensive observational analyses and ensemble experiments with atmospheric general circulation models (AGCMs), it was found that twarm-phase AMO leads to warmer winters in much of China, resulting in less precipitation in coastal areas of southern China and more precipitation in northern China . Wang et al.  extended these analyses to examine the seasonal dependence of the AMO influence on Asian monsoon. Their results indicated that warm-phase AMO causes increases in air temperature in East Asia and rainfall in Northeast China in all four seasons. In addition, positive phases of AMO induce strong Southeast and East Asian summer monsoons, and a late withdrawal of the Indian summer monsoon . All these studies have together demonstrated a probable influence of Atlantic SST anomalies on Asian climate on multidecadal timescales.”
Besides the papers Wang et al and Marcia mention I am fairly sure I have seen model studies indicating the influence of the AMO may extend as far away as Austrailia and Antarctica but I don’t have references for those handy.
Since I’m commenting I’ll mention that Knudsen et al 2013 is a good paper examining the possible external forcing of the AMO.
Good paper, Steven.
External forcing of the AMO since the LIA
The close relationship between both AMO reconstructions and the combined solar and volcanic forcing after ca. AD 1775 (Figs 2 and 3) lends strong observational support to the climate model simulations by Otterå et al.9 In these model simulations, the AMO lags the external forcing by ~5 years, which is in close agreement with the ~5-year lag observed in the present study for the period after AD 1775. A more detailed explanation for this lagged North Atlantic SST response to solar variability was recently proposed based on idealized experiments showing that a step change in ultraviolet forcing has an immediate impact on the atmosphere, which subsequently takes several years to accumulate in the ocean35. During this time, the atmospheric response continues to increase, suggesting a positive feedback between the ocean and atmosphere. Similarly, several studies indicate that the ‘top-down’ stratosphere–troposphere mechanism represents an important response to solar variability, particularly at high latitudes. However, the magnitude of this effect is uncertain, in part, because past changes in the ultraviolet region of the solar irradiance spectrum are poorly constrained as satellite observations of spectral irradiance cover less than one solar cycle36. The combined solar and volcanic forcing applied in the present study (in W m−2) therefore provides a simplistic representation of the external forcing that, similar to most other studies, underestimates indirect mechanisms between external forcing and climate. Nevertheless, we note that the regression models for both solar and volcanic forcings provide significant fits to both AMO reconstructions after AD ~1775 (Fig. 3b), suggesting that these forcings are highly consistent with AMO variability during this period. This strongly supports a link between the AMO and solar as well as volcanic forcing for the period after AD ~1775 that scales linearly with the reconstructed changes in W m−2.
“Assuming that the multidecadal variability we are examining is limited to the North Atlantic”
Which there is no reason to assume but if it gives the “right” result, run with it.
Thank you for another fine post on the Stadium Wave and the carefully constructed rebuttal to Dr. Mann.
When you have the facts and a strong argument one can take the higher road. You provided everyone with a significant amount to consider. Very professional (which is your norm).
Look forward to your further comments,
This was a very informative post– thanks Marcia!
A few things that really stuck out. First, you said:
“While the stadium-wave’s propagation dynamic is likely to be intrinsic, AMO is the pace-setter. The stadium wave says nothing about the components of the AMO. It may be forced, intrinsic, or a combination; such is irrelevant to the stadium-wave propagation. The stadium wave represents a dynamic involving ocean-ice-atmospheric coupling sequentially transmitted across the Northern Hemisphere on multiple-decade time scales. ”
This really helped to clarify your thinking on the stadium-wave, and the relationship to the “pace-setting” function of by the AMO. Looking at it from an intrinsic versus externally forced perspective misses the whole point. It is not an either or proposition, nor does it seem to matter what components “set the pace” — the AMO reflects those components. If that’s the case then, the next step is certainly to understand the components of the AMO and how they have varied over time to alter the pace of AMO, which in tern have been reflected in the character of the stadium-wave. In particular, it would be interesting to see how three known external forcings, all of varying intensity, duration, and dynamics might have affected the pace of the AMO, and therefore the nature of the stadium-wave. Specifically, it would be interested to use proxy data to see how large volcanic activity, solar activity, and increased GH forcing might have altered the pace of the AMO. Volcanic activity is particularly interesting as there seems to be long-term air-sea-ice interactions from large volcanoes that are not fully account for in any of the climate models, but certainly this is also the case for GH forcing. But the volcanic data is getting especially accurate over the past few years with high-resolution ice-core data from both hemispheres that give us a pretty good idea what size of the forcing was from volcanoes.
The other thing that Marcia said is especially excellent. She said:
“If boundary conditions change, so might the stadium wave. Thus, this hypothesis invites more exploration than simply limiting focus to intrinsic vs. forced contributions. Earth systems appear to redistribute heat laterally and vertically, regardless of source.”
Understanding the vertical and lateral redistribution of energy (either as heat or other forms) is central to fully advancing the science, but understanding this redistribution must include both spatial as well as temporal scales with related delays and feedbacks. To the extent that the stadium-wave is a real phenomenon intrinsic to the Earth System and not (as some have suggested) merely an artifact from the techniques applied in analysis, this phenomenon could provide greater insight into the redistribution of energy in the system on previously unseen temporal and spatial scales. I am intrigued by this possibility but remain skeptical pending further analysis– with the key to this analysis probably being better proxy data during periods of known significant changes in external forcing such as following large volcanoes.
Very sensible comment, gatesy.
The problem though is that models appear to be the only tool for investigating these issues ATM but marcia has already shown in their present state they appear incapable of reproducing these teleconnections
@ R. Gates
“But the volcanic data is getting especially accurate over the past few years with high-resolution ice-core data from both hemispheres that give us a pretty good idea what size of the forcing was from volcanoes.”
No argument over the vastly improved data on land volcanos, but how about undersea volcanic activity?
The current assumption (I think) is that about 75%, more or less, of all volcanic activity occurs under the ocean.
Do we really have a good idea how many km^3 of magma and other superheated fluids (and megatons of CO2, of course) is emitted by undersea activity, where it is emitted, how it is distributed, how these emissions affect the temperature gradients of the ocean and the contours of the ocean floor, and by extension the patterns of ocean currents? Not a rhetorical question, by the way.
Also, can we quantify the changes to the shapes of the ocean floors due to tectonic plate movements and/or earthquakes and how those changes affect the patterns of ocean currents?
Or is it known that all the ongoing subsurface activity has negligible impact on the ocean circulatory systems and temperature contours?
Bob, I looked into this a bit. There really is not a good estimate of undersea volcanic activity let alone heat release. I looked particularly hard at the mid Atlantic sea floor spreading Ridge. Difficult science waiting to be done.
And techtonic shape changes are so slow, and so newly understood (remember Wegeners correct continental drift hypothesis first published in 1912 was vehemently rejected by geologists until the 1960s when magnetic polarity reversals were found along the midAtlantic spreading ridge). The best estimate is a global GIA (including techtonics) of 0.3mm/yr SLR. For reference, since on my computer and this is iPad time. google Gia Colorado and you will get to the official explanation websites).
One cannot say techtonic/ volcanic ocean impacts are negligible. A prevailing theory is that techtonic closure of the Panama Isthmus inaugurated the Pleistocene Ice ages by altering circulation between the Pacific and Atlantic. That was 2.5 million years ago and the human species did not emerge until much later.
What one can say with a fair degree of confidence is that the ocean heat capacity is so great, and the thermohaline global circulation conveyor so vast, that subsea volcanism is extremely unlikely to have much if anything to do with ocean heat content, natural variability, or climate cycles since 1900–except locally or transiently (pinatubo).
Hardly the last word, but a good faith reasoned opinion from a non-expert (ecept at scepticism and critical thinking) who looked hard at the evidence available. Your very reasonable questions probably fit two of the famous Rumsfeld categories: we know we don’t know the specifics, but we do know we know it probably isn’t significant.
What is you that asked me a question on volcanoes on a previous thread? I noticed it in passing but did not have time to comment.
Volcanos from the contemporary observations appeared to have a limited impact on past climate even though their emissions are thought to be six time bigger than was recognised a decade ago. The Ipcc take into account the land based volcanoes but make very little calculation of the sub sea ones.
According to Skcptical Science, the co2 from undersea volcanos get absorbed by the lava on the sea floor. However that is based on previous calculations of a very tiny contribution from this source.
IF and I must stress IF there are 10000 times more volcanos underwater than previously thought, this will have an impact on what co2 emissions MIGHT make their way to the surface and vent into the atmosphere, but also on the acidification of the oceans.
Volcanos above and below the ocean have been emitting c02 for far longer than man and if it hangs around in the atmosphere for many centuries it must have an impact IF the apparently increased emissions that have now been found turn out to be correct.
As it stands the current thinking based on science of a decade ago is that mans co2 far outweighs that of the emissions from Volcanos.
This is another one of the climate science subjects that has not been settled.
I think an article from a volcanologist would be very timely here as all these things must ultimately impact on such things as the Stadium wave.
There are so many “it’s worse than we thought papers” about CO2, it is about time we had one about the effects of underwater volcanoes. When it happens, I”ll know some balance has occurred in climate science.
Regarding volcanoes and the stadium-wave– it is interesting to note that independently other researchers have come to the conclusion that air-sea-ice interactions and feedbacks acting over multi-decadal timeframes can cause large volcanoes to have a greater influence than just the cooling of the troposphere that occurs during the first year or so after a large volcanic eruption. Given that these air-sea-ice interactions are certainly key to the the stadium-wave dynamic as well (should it turn out to be a real Earth system dynamic), I should think that a very fruitful area of research would be to study the affects of the large volcanic eruptions on behavior of the stadium wave.
I don’t think they could affect OHC directly, but indirectly by changing circulation and mixing in the deep ocean. Imagine a current slows and the deep ocean takes less heat from the surface causing the surface to warm.
I think we are both agreed that volcanoes are an important element of climate-how important we might disagree upon. However there is no doubt that it is an area of research that appears to be in its infancy as regards the numbers, location and effect of volcanoes.
IF there are many more underwater volcanoes than had hitherto been suspected, that is likely to have an effect on the acidification of the ocean and the amount of co2 available to outgas and perhaps other effects we are not yet aware of.
IF the emissions from land volcanoes are far greater than suspected a decade ago it is likely their share of the emissions remaining in the atmosphere from eruptions a century or more ago is likely to be much greater than we had thought.
In short, I would certainly like to see a post about land and sub sea volcanoes that gives us the latest thinking on their impact.
That is an interesting aspect as well
Is it also plausible that ionized particles might be moved by magnetic field and influence currents?
Considering alternatives to the cloud crf, I thought that perhaps high energy cosmic rays might also ionize molecules in the oceans and magma and be influenced by changes in magnetic field. I have no idea if this is plausible.
@ Rud Istvan
“What one can say with a fair degree of confidence is that the ocean heat capacity is so great, and the thermohaline global circulation conveyor so vast, that subsea volcanism is extremely unlikely to have much if anything to do with ocean heat content, natural variability, or climate cycles since 1900–except locally or transiently (pinatubo).”
I certainly agree that undersea discharges are unlikely to have any measurable impact on OVERALL ocean heat content, but my suggestion was based on the fact that the discharges, particularly the volcanic ones, are massive point source heat injections which, while they don’t raise the temperature of the overall ocean measurably, can create steep local thermal gradients and strong local upwelling that can potentially modify the currents. Also, seamount building and other such activity changes the contours of the ocean floors. Enough to modify the ocean currents and cause observable impact on the climate? I don’t know, but the thermal gradients, local upwelling, and contour changes demonstrably occur, whether or not their impact is reflected in climate changes.
@ Rud, Tony, Aaron
More on underwater volcanos.
Robert Felix (http://iceagenow.info/2014/07/million-underwater-volcanoes-wrong/ ) just published a note this morning linking to this paper:
which addresses the geologic CO2 question.
It also prompted this ‘blast from the past’ regarding the unwarranted precision often found in ‘scientific’ papers:
Time to fire up the ‘Wayback Machine’ and return to 9 April, 2010, when we had the following discussion:
“3,477,403 Underwater Volcanoes EXACTLY?
9 Apr 10 – Reader calls me on my numbers
I can understand the ‘Watermelons’ publishing glaringly stupid data, but please don’t fall prey to the same temptation yourself.
The article that precipitated this note appeared on your site on 31 March and included this helpful bit of information: “3,477,403 Underwater Volcanoes”. Not 3,477,402 or 3, 477, 404, but 3,477,403. Exactly. No more or no less. Extrapolated from a survey of exactly 201,055 undersea volcanos. +/- 0. (See Acid Oceans Due to Underwater Volcanoes?)
This reminds me of the the following gem: “…….a January 12, 1999 Associated Press article by Randolph E. Schmid, titled “Researchers: 1998 was the hottest year on record.”: “The NASA findings indicate a mean worldwide temperature of about 58.496 degrees F., topping the previous record, set in 1995 of 58.154.”
I particularly like the touch of using ‘about’, followed by a world temperature quoted to 1/1000 degree F. One wonders how they would have done if they had gone for precision. I also find it amusing that NASA was cited as the source of the temperature figures. I wonder if they weigh the shuttle to +/- one grain when doing their launch calculations?
Now I don’t doubt for a minute that undersea volcanos are contributing a huge amount of heat and acidification to the ocean, that the location and amount of heat contributed varies randomly with the whims of the volcanos, that the random injection of heat pulses causes equally random ‘nudges’ to ocean current flows, with all that that implies, and that the heat and CO2/SO2 injections swamp ANY contributions by human civilization. But publishing the number of undersea volcanos with a precision of +/- 3 parts in 10^7?
Please remember that paper and computer files are defenseless; they will let you write anything on/in them that you want, no matter how patently senseless. Don’t embarrass them needlessly.
* * *
You are correct, of course. The thought that anyone knows exactly how many
volcanoes lurk beneath the seas is ludicrous. We know more about the moon
than we know about underwater volcanoes.
But that number does help bring attention to my point, namely, that
underwater volcanoes are heating the seas.
I’ve been saying “more than three million underwater volcanoes” for several
years, so it’s nice to see a scientific study that helps confirm my statements
even if the numbers are absurdly precise.
In 1991 when I began my research for “Not by Fire but by Ice,” scientists
thought there might be 10,000 underwater volcanoes in the entire world. Even
with that small number, they believed that 80 percent of all volcanic activity
Then, in 1993, marine geophysicists aboard the research vessel Melville
discovered 1,133 previously unmapped underwater volcanoes off the coast of
Easter Island. (I know, I know, there’s one of those exact numbers again. But
that’s what they said.) Some of the newly discovered submarine volcanoes rose
as much as a mile and a half above the seafloor.
All this in a comparatively small area of only 55,000 square miles, about the
size of New York state.
To go from 10,000 underwater volcanoes to more than three million in less
than 20 years shows how little we knew – or know – about nature. I shudder
to think of how much we must still have to learn.
To try to control so-called global warming, to think that we can control
something that we don’t begin to understand, is foolhardy beyond belief.
Thank you for your interest.
The Atlantic oscillates on a multi-decadal time scale. Hence, AMO. The oscillation noticeably affects the climate. Good so far.
Has not the obvious occurred to anyone? I. e. the AMO is an EFFECT–of some physical process, not a CAUSE. It affects the temperature/climate, obviously, but WHY does the Atlantic oscillate with a period of multi-decades and what is driving the oscillation?
Oh, it is ‘natural variability’? The Atlantic just oscillates, for no apparent reason? So, presumably, with no external inputs, it will soon damp out and stop oscillating? What is the rate of damping; how many more ‘cycles’ before the process decays and the Atlantic ceases oscillating and becomes static? If the oscillation is expected to continue indefinitely, where is the source of energy? Can we predict the drivers of the AMO well enough to predict the AMO, and by extension the climate effects of the AMO?
The trouble with disentangling forced from intrinsic variability is that ALL variability is ‘forced’. By something. The problem is that Climate Science, collectively, cannot provide an exhaustive list of all the physical processes that affect the climate (temperature, since that is what we are arguing about), nor guarantee that it can list the ones that it IS aware of in rank order, with the proper signs (Do clouds, for example, drive the TOE up or down?) of their respective influences on the temperature.
Is it really CO2 and its ‘radiative forcing’ effects, all the way down? And if not, where does CO2 fall on the rank order of influence?
Bob, what both you and Marcia are pointing out in different ways is that until one has a fairly complete list of cause/effects, even rank ordering them let alone attribution to CO2 is very difficult in the idiomatic Japanese sense. What the MWP and LIA and stadium wave show is that many of these must be natural rather than anthropogenic (CO2, CFC, black soot, methane, whatever) since they they predate significantly. And ice cores and other evidence show it isn’t volcanic aerosols. Those facts by themselves blow CAGW predictions out of the water, which is why Mann and his Warmunist cohort try try so hard to disappear those facts. And now that the pause is falsifying the latest and greatest GCMs in CMIP5 precisely because they do do NOT incorporate these other drivers–whatever they may turn out to be–all of a sudden the debate is over and the science is settled. NOPE.
In addition to to the fascinating science still to be done, the process has been a separate education. I can think of one other instance, minor in scope and scale but similar politically (including illegitimate tactics). That is the US classroom size debate concerning improved public education. It was a major example in my last book. There, the NEA played the role of Mann and his ilk. Simpler, experimentally testable, more obviously self serving, yet the canard still got enormous traction, for example a Florida state constitutional amendment that has cost $20 billion over a decade and accomplished nothing since the underlying premise is experimentally false even if intuitively appealing.
The AMO is a current reality as well as having a historical footprint. Wyatt et al incorporates AMO oscillations into an Arctic ocean atmospheric pattern with global influence; i.e. the stadium wave hypothesis. Mann, pooh poohs this construct as an effect of wrong statistical manipulation. We are left to wonder.
What I am left with, what is the testable prediction. Will the Northern Annular Mode (NAM) produce a warmer or cooler winter 2015? What I am looking for is an observable outcome to either Mann’s debunking or Wyatt’s hypothesis.
Am I so naive that such predictions can’t be made?
RiHoo8, I don’t think the stadium wave enables year out stuff. But if I recall correctly, our gracious hostess is on record (at least here) saying it implies something like the pause will continue until something like 2030. That is a very testable prediction, just not in your next year time frame. Better the stadium wave authors speak for themselves, as they are ‘present’.
“The AMO is a current reality as well as having a historical footprint. ”
Of course it is.
What I was asking was ‘Is the AMO a cause-er, or, like the variations observed in ‘global temperature’, just another cause-ee? Of something else, like Alistair Riddoch’s variations in gravitational stresses, for example?
The North and South poles take turns “pressing down” on the poles. A few of the maps, that fully show this are displayed together here:
The data on the maps comes from NASA’s GRACE mission that deteects gravity anomalies. They are significant to the understanding of north-south ocean and ice redistribution. And probably to air currents, like the polar vortex. You can see all the gravity anomaly maps here:
They also have information on water thickness. But I haven’t paid it a lot of attention yet. So this is find what ye may… :-)
The features of 1/f noise processes offer important new insights into the field of population biology, greatly helping our quest for understanding and for prediction of ecological processes. 1/f noises
account quite satisfactorily for the observed nature of ecological fluctuations.
Thank you for the interesting reference to 1/f ‘pink noise’ in ecology of populations.
Long ago, I recast the classic two species predator/prey equations three equivalent ways: simple algebraic, less simple partial differential calculus, and most complicated stochastic Markov chains. Details differed, but the solution envelopes (and predator prey oscillations) did not. (To the perplexed, this is the classic simplified rabbits and foxes problem. Not enough foxes results in too many rabbits, eventully resulting In too many foxes that then eat too many rabbits. The foxes then starve and decline until a lack of foxes results in too many rabbits… Then the cycle repeats).
It is interesting, and relevant to climate, because it sets up natural oscillations (just like the stadium wave topic of this thread) that are themselves quite sensitive to boundary conditions like reproductive success (translation, how many rabbits does a rabbit have when a rabbit does have rabbits?)
Maybe one linkage producing the previous unified P/P result was this sort of underlying ‘pink noise’ speculated about for the stadium wave topic here? Going to need to ponder that a bit mathematically, because not intuitively obvious in the proven equivalent Markov Chain purely stochastic version of the P/P model where noise per se does not even exist. There were only discrete probability descriptions (of course summing to 1 across all defined possibilities) of stochastic transitions to the next possible state increment. Something to chew on the next while.
Natural Climate Variability
These researchers are not up to speed about what we now know were also major retreats of alpine glaciers 2000 and 4000 years ago.
I am in Las Vegas, Nevada, at the ninth International Climate Change Conference. It ended this afternoon. This was a fantastic event. I am wondering why more of you were not here. Some of my favorite Climate people were here. Look on the Heartland Institute Website for more information and you can look at all you missed.
Herman, two very different answers to your post.
First and most important, some of us are otherwise preoccupied and/or financially constrained. For specifics, I imagine I am amongst the former and JoNova is amongst the latter. So hit her tip jar while I finish my next ebook with a promised forward from our gracious hostess.
Second, I do not wish to be associated with Heartland and the rest of what it represents. You can read my previous book on that. Or ponder the Roy Spencer award from an organization that lobbies for teaching Intelligent Design as a legit alternative to Darwinian evolution in all schools. ID is bs. Read my last book for details. Roy is mentioned both with respect to peer review and ID . You decide where you then stand. All that information proves is guerilla warfare makes strange bedfellows, as Syria at present.
I personally chose not to play those distasteful games.
Stupid award. If they insisting on reminding everyone that Dr. Spencer embraces Intelligent Design, they should have done it in some other venue. They did the skeptics no favors. Spencer ought to know that.
What a klown show that was. I watched a bit of streaming. Who is that Lord character ?. He dropped into doing Monty Python and I figured Graham Chapman didn’t die after all.
Or was that Marty Feldman with the googly eyes?
You might mean Barney Google with the goo-goo-googly eyes. Not his biggest fan, though I must say I don’t hold his looks against him. Enough characters on your side without us adding to them.
After watching some of the Heartland streaming videos, it reinforces the thought that I am may not be conversing with sane people on this blog. Those Heartland presenters have serious deficiencies when it comes to presenting any kind of science.
What exactly separates you from them?
I find the Heartland people to be good, educated, intelligent, willing to discuss and debate and they welcome people who disagree with them. Heck, they disagree with each other, because they are Skeptics and that is what Science is supposed to do. If some of you are not willing to engage with people who disagree, you are the problem. The Heartland Conference was full of some of the best Climate Scientists that I have ever listened to or talked to. The science is not settled, but many of the Heartland people are closer to the truth than anyone else.
The question the Consensus Science. They Question the Science they hear from each other. They Question their Own Science. That is how Science is supposed to work.
Work with Heartland to figure this all out or remain useless for any progress in science.
I rather like the HI as well. It’s just to bad they’re so clueless when it comes to optics.
The Heartland conference was not a typical scientific conference. It was more of a pep rally for a junior debate squad.
What a klown show. The visual equivalent of what goes on in the denier blogs. It just shows what people will do to (1) stroke their ego, (2) make a living at the expense of their pride, (3) pursue their delusional fantasies, (4) desperately try to fit in to some clique, or (5) participate in a bizarre form of “entertainment”.
For the committed denier, watching that parade of dunces should be like looking in a mirror.
They seem to be following Lord Chris down his world government rabbit hole to a greater degree this year. Even Spencer ended with a hint of that, and usually he is quite sane.
Jim D – Spencer is reasonable on climate science/skepticism. Motivated….but reasonable. Get him outside physical sciences and I’m not so sure.
No matter what the reality may be the billboard controversy forever tainted Heartland. It is probably viewed now as the John Birch Society of climate science. I doubt it will ever be taken seriously again.
No one who disagrees with consensus is taken seriously by the Extreme Alarmist Consensus Group. In the rest of the people, many take Heartland Seriously. They promote True Skeptical Science. Consensus Science is Not Any Kind of Real Science. A majority of people do not take the Consensus Crowd Seriously. I talk to people about Climate, almost every day, and I find a very small percent support the Extreme Alarmist Consensus, more CO2 will be a disaster, Climate Theory. Seventeen Years of Model output getting more and more and more different from real actual data is exposing the Flawed Theory and Models. People can look at what the Alarmists say and look at what Heartland says and see that Heartland follows the Data, Alarmists follow the Model Output and try to “adjust” data to match Model Output.
People can see this. Well, many people do see this.
Like I said, the perception may not be the reality. To an outsider like me the consensus folks and their media surrogates IMO have successfully knocked of Heartland as anything other than an extremist group and can now simply ignore it. It is also their intention to do the same to all skeptics. They will now devote their attention to what they view as a real threat. I don’t mean to insult you but I think you may have the same problem with Pope’s climate theroy. I have read that several times and find it quite credible. However by dismissing CO2 radiative physics, you too will not be taken seriously. It may be disconcerting but it is just the way of factions painting their foes in a corner. The future may dicredit alarmists but they are set for battle now and winning most of them.
@ Herman A (Alex) Pope
Dr. Wiliam Briggs (Statistician to the Stars http://wmbriggs.com ) had a couple of posts on his site about his experience at the conference.
You may be interested.
It is interesting to me that the global and NH detrended HADCRUT4 are a similar amplitude to the AMO and lead it slightly. This implies that there are global forcing variations with an 0.1 C amplitude that drive the AMO. Allowing for the small area where the AMO is defined, there is much more energy in these global signals, which must therefore be the driver. I think that the global forcings can account for this with an early-century solar decline and return, global dimming from aerosol growth mid-century, and enhanced CO2 emissions late century. This would predict the final rise to be continuous and not oscillate back down again with CO2 emissions rising. Having said that, I don’t think linear detrending by 0.7 degrees makes sense when the signal left is only 0.1-0.2 degrees. This seems to be throwing out most of what really is going on to focus on a remnant.
Yes, that one leads the AMO too.
Furthermore, AMO (or other temperature indices) and PDO are not the unrelated. We know that positive PDO means warming and negative PDO cooling. So, PDO is basically the slope of the temperature series.
I mean “are not unrelated”
Here’s another plot to ponder. Detrending everything we see this.
From this we see that CRUTEM4 (land) leads the AMO and HADSST (global ocean) for almost the last century, and not by a small phase. How to explain this? One explanation is that there is an external forcing that impacts both the ocean and land, but the land responds to it faster due to its lower thermal inertia. This casts doubt that the AMO is an internal and local ocean mode because it seems to lag land changes and is in phase with the global ocean.
Surface temps more clearly follow Pacific Ocean SST for good reason.
Isolating the AMO in the conext of the stadium wave makes no sense.
Land temperatures precede the AMO. How can the AMO be setting the pace when the land temps precede them? Either the land temps are setting the pace, or, more likely, subtle forcing changes are setting the pace even for this 60-year oscillation.
Interested in the timing of ocean, air current, and moisture content oscillations, that would resemble a stadium wave pattern, and act differently, during different phases of our orbit, I think you might be some of the people that would be most interested to note the patterns of gravity anomalies at the GRACE mission portal
(GRACE is a pair of satellites in low orbit, chasing one another, with the distance between them being very accurately measured, as the lead and then the chase satellite respond to the variations in amounts of gravity they are passing over, and relate it to the prior passes to build a monthly snapshots of gravity anomolies, in detail down to 25km.)
Their interactive maps can be viewed here:
I’m quite sure they are important, but do not want to keep harping on about them and get sounding like a broken record.
I think that the space earth heads into should be viewed as an egg carton of “pushes” and “pulls” and like the surface of a pool, has many standing waves in it, that reflect the motion of the other significant bodies of gravity, especially within the Heliopause.
This pattern of waves, would seem to me, to be painted on the surface of the earth, for all to see. Note that the pattern, cannot be regionally created, and have the same persistence. Note that the pattern cannot be purely internal and still have a 22-23 year cycle matching the solar flips. Note that the phase change of Greenland is on the top of the sphere of “interference” pattern in space interacting with earth. As such, it is in phase, or out of phase, based on polarity of the sun. This matters.
I don’t have evidence, or see it’s availability, but am guessing the south pole sometimes acts in synch with the north pole, and sometimes in opposition, as the strength of the sun’s field rebuilds after a polarity reversal, such that during the “fall” and “spring” phases of the solar cycle, is the period during which the actions of the poles will likely “mirror” each other.
The relation between magnetism and gravity, or the mechanism, might be questioned, but the relationship is their, is external, is relatively unaffectable by humanity, seems to at least match some of the mystery periods of warming and cooling of the past. Seems to make things make more sense.
I’m hoping to spark the interest of others, so I won’t be diatribing, on the subject.
And to spark debate as to why it might not be important, to double check it’s importance.
cause I think it is the key. (and hope so, so everyone could finally calm down about the subject!)
Hoping someone sees it, and uses it. That’s what keys are for.
I’ll be surprised if the rate of radioactive decay, or spread of magma, or volcano frequanecy/flow, or lightning rates, or cloud formation/density/duration, location, and the jet stream, polar vortex, ocean currents and heat buildup/dispersal, geology changes, tectonic plate movement, and the semi random influence of CME’s aren’t all found to play a part in the climate, and the culmination of their combined impact be found to be way in excess of CO2 and other human related contribution.
I hope others start to see it too. Consider it in their research. If it is appropriate and helps.
If others see reason to be interested, I hope it will help make the potential clearer and more quantifiable.
Set the pace for what?
At any rate the land/ocean divergence is determined by
changes in moisture availability over land. An artifact with no significance. You don’t ever seem to get that.
Global Average land temps. These are nothing but a myth. What are the local land temperatures that produce this effect, and how do they interact with the AMO?
The point to remember is that these are indices. The mechanism(s) that drive these indices are as yet undetermined. Whatever elements are involved in the mechanism(s) behind the AMO probably involve land temps (“African” dust anyone?), and may well lead the index that’s technically used for the AMO.
Rob Ellison, you ask “set the pace for what?” as if you haven’t read the article. Pacing the stadium wave. The forcing is pacing the stadium wave, or at least the land temperatures are. Look at the graph again. Look at which index is leading the wave. It is CRUTEM4. This hasn’t been seen before, apparently, or at least not mentioned yet.
I will concur there is some sort of effect like a stadium wave in effect acrross Canada. The temperature delta in Calgary, almost always preceed a similar trend in temperature 5-6 days later in Toronto. This probably has to do with the speed of the jet stream, which in the end is an average speed because of energy and sphere dynamics, but I haven’t dug deep enough to say for sure. This trend seems to happen most, if not all of the year.
AK, it seems to me that if they are saying something is setting the tempo for the stadium wave, and something else leads that by about a decade, it would be that which sets the tempo instead, obviously, yes? You say dust. OK, that is not what the stadium wave idea says, because it implies that the leading wave is the AMO, so you can take that one up with them too.
NO. That something else may well be just an artifact, or an index of whatever is actually driving the AMO. Global average temperatures don’t do anything, they are just artifacts of our mental inability to conceive of an actual integration across the temperature field. Only local temps do anything. Now, compare your “something is setting the tempo for the stadium wave” with this from the main post:
What this envisions (if I understand correctly) is a partly defined mechanism for propagating the signal of the AMO along other indices with various lag times. The description of this hypothetical mechanism (actually a set of mechanisms) begins with the AMO; it doesn’t address the origin of the AMO signal.
Of course, anybody who really understands the dynamics of hyper-complex non-linear systems will be led to speculate that there is a lagged feedback from some part of this delay chain back into the AMO, producing a natural oscillation that doesn’t require any outside “forcing”. This is typical of many systems of this type, for example nerve cells that naturally produce a regular sequence of action potential firing. Such cells can produce this regular signal without any outside influence to drive their timing, although outside influences can also determine the firing rate, and even whether the regular signal is produced.
It is this that makes the whole “stadium wave” hypothesis (or meme) so objectionable to people like Mann: it means that major levels of natural intrinsic variability could be present in the climate, on scales ranging from sub-annual to millennial, that could overwhelm any signal or effect from anthropogenic CO2, as well as combining with such anthropogenic signal in a highly non-linear fashion.
It doesn’t prove that such variability is present, but it does, for many, put the burden of proof on the Mann types that it doesn’t.
AK…”It is this that makes the whole “stadium wave” hypothesis (or meme) so objectionable to people like Mann: it means that major levels of natural intrinsic variability could be present in the climate, on scales ranging from sub-annual to millennial, that could overwhelm any signal or effect from anthropogenic CO2, as well as combining with such anthropogenic signal in a highly non-linear fashion.”
As far as I can tell, truer words have never been spoken.
And well said.
There is no suggestion here or anywhere that the AMO leads surface temperature. It is part of a networked system with a particular multidecadal beat.
The components of the integrated system – which is what it is all about – that clearly lead temperature are in the Pacific
Rob Ellison, if you look at their wheel diagram, they have NHT which is NH surface temperature slightly leading the AMO, but they didn’t separate out the NH land temperature which leads it by even more. Given the relative areas, the land signal is much stronger than the AMO, so I would say that is the one that leads the wave.
The AMO, and other indices may be local manifestations of the system as a whole. I am not sure there are leaders excluding the Sun. The idea of a network is somewhat opposed to their being leaders. Each index may be communicating with the others and negotiating some outcome. The network that is the climate truly is the great communicator. Nothing does it as well.
A quick reply to AK. I hope I’ve put this in the right place. In the Wyatt and Curry paper, the mechanism described in that paper includes feedback from Pacific processes onto the Atlantic, planting seeds of reversal on AMO phase throughout the cycle. The hypothesizes mechanism is in section 4. I think the manuscript is posted on a former Climate etc blog to which Judy has posted the link (above). I think that might be helpful or interesting, in light of your question. As to the origin of the AMO, many studies look to the deep overturning circulation, the AMOC, but debate on this continues. The big picture on geologic time scales reveals land configuration changes, in particular related to Antarctica’s isolation, contributed to the enhancement of the AMOC. An interconnected puzzle among all oceans, directly and indirectly exchanging salinity and winds effecting regional processes, with remote impacts play leading roles. No easy answer that is devoid of debate on the AMO.
Sorry for the typos on my response above.
Thank you for your reply Marcia.
I had scanned the original article when it was first linked, and vaguely remembered that a complete cycle was hypothesized. However, in this post you left the origin of the AMO’s signal open.
Personally, I find it almost inconceivable that a hyper-complex non-linear system of this sort wouldn’t have just this type of cyclical feedback chains, probably linked into a larger network. The search for direct links between “forcing” and the observed behavior of the system seems highly simplistic to me. Especially given the short time-frame of the “forcing” being hypothesized.
Thus, IMO, the stadium wave hypothesis seems much more plausible as an explanation for observed changes during the 20th century than “forcing” from increased CO2. Although, of course, at this point neither can be ruled out.
There is no difference between land and ocean energy flux – and you still don’t get it.
The ‘wheel’ shows Atmospheric-Mass-Transfer anomalies leading to changes in Pacific sea states, to NHT changes and – ultimately – AMO variability – and around again.
I simplified your graph so that I could read it:
Here’s Wyatt: “A warm North Atlantic promotes a multiple-decade trend of cooling hemispheric surface average temperatures. A cool North Atlantic triggers a multiple-decade interval of warming hemispheric surface average temperatures.”
Around the peaks or troughs of the AMO in the graph above, the GAT changes direction.
I am not sure I am understanding the first paragraph of this:
http://www.wyattonearth.net/thestadiumwave.html temperatures. h It
It seems a warm AMO melts ice and cools. The AMO may work by controlling Arctic ice.
“…the PETG dictates equator-to-pole transport of heat, converting the initial ocean signal-polarity to the oppositely signed atmospheric signature.”
This warm creates cool by removing ice insulation, as I read it, it’s very good.
I realized how important it was that a lake freezing over in the Winter, retains heat. And the more brutal the Winter, the thicker the insulation.
Ragnaar, Thanks for that info somehow I missed that important point previously.
When I looked at the stadium wave again at Wyatt’s site, I understand why Mann would be concerned.
I knew about the AMO driver but I kept waiting for the N Atlantic to cool checking the anomoly regularly and I thought there was something wrong there. I had gotten the wrong impression from misreading the phase change part.
… “forcing variations with an 0.1 C amplitude”…
it’s just kind of bizarre that solar and aerosols would pick up where each other left off so to speak.
“…leading to speculation that the AMO’s reach is hemispheric, perhaps global.”
It’s definitely global – good that the professional scientists are catching up. Here the comparison of the detrended North Atlantic SST (the so-called AMO) with the detrended southern hemisphere surface temperature:
So, AMO is a misnomer – it’s a pattern of climate variability found globaly. The secular trend removed from the AMO is just another ‘oscillation’, with lower frequency.
I have been wondering how a solar minimum might effect the waves. When the current down cycles complete in the late 20s suppose the next solar cycle is really flat or non-existant. One (stadium) would suggest warming the other (solar) would suggest cooling. I also wonder if the band width of the stadium waves may show up differently if they were seen over a greater time period running through previous warm periods and ice periods.
Please consider the oscillations in the gravity field through which Earth travels, and the impact they have on stadium wave speed of travel around the globe.
Easily viewed here: http://geoid.colorado.edu/grace/dataportal.html
I recommend viewing monthly gravity anomolies, setting the smoothing radius to 25mk, and checking out maps from 2002, 2008, and 2013. Paying special attention to Greenland’s up/down bounce, which is probably on a 23 year cycle, and the pattern of “ripples” across the continents, and their obvious “polarity” change, seasonally.
I like to think of gravity as an egg carton, (with varying hieght peaks and valleys, mashing into the side of earth, as it spins, orbits, and flies throught space. And the egg carton moves up, and down, as earth flies through it.
I believe this is relevant to the topic of discussion here, and is a potential underlying driver, for a stadium wave phenomena, that has been ignored/unrecognized, to date.
What an excellent post Dr. Wyatt. You have clearly stated Dr. Mann’s paper and given an excellent rebuttal.
I find this topic somewhat difficult to unravel. Questions:
1) is the idea that forcings (such as industrial CO2) to the climate would cause a noticeable and similar response in the output of the climate (as if it were a purely linear system)? And so we try to subtract this output to see the underlying signal?
2) is not the Trenebeth argument about the pause and deep ocean warming stating that the forcing is in fact going into the ocean of ad opposed to ‘being shown on the face’ of the climate?
3) Are these not contradictory positions?
From my own dynamical systems background I see no reason why external forcing of a nonlinear system should manifest itself with a similar output. That is linear thinking.
Am I missing something? I always have trouble understanding these model studies because my mind goes straight to numerical error….
1) is the long term trend, while 2) is occasionally what happens in short periods, like recently, to delay the long-term tendency. Not contradictory, just different time scales. Skeptics are very focused in on the short blips without seeing the big picture, so Trenberth felt compelled to explain that blip to them.
Thanks for trying but I didn’t get much from the answer…
I’m going to talk some alka seltzer and try to read the Mann paper again. Wish climos would lay out their mathematical assumptions as they go. But I guess they’re writing the papers for other climos who all have the same assumptions….
“C dT/dt = S(1-a)/4 + Frad -A-BT”
I find this assumption mind boggling.
In a way, perhaps this is the crux of the debate. Just how nonlinear or linear is the climate system.
Talking to myself i guess…..
nickels | July 10, 2014 at 11:20 am |
Just how nonlinear or linear is the climate system.
One some scales, linear is close enough. Maybe that is the debate. We hear, close enough, let’s move along now.
Neckels, that equation is too simple, it should actually look like the heat equation. But they don’t use the heat equation for illustrative purposes because it is not as easy to solve as a first-order differential equation.
“Thanks for trying but I didn’t get much from the answer..”
That’s because he didn’t really answer, he just cast aspersions on people he has applied to a stereotype he invented.
Nickels: I find this topic somewhat difficult to unravel.
I sympathize. Multivariate nonlinear coupled dynamical systems are naturally difficult to understand. Keep working at it. Some things become clearer after a while.
Thanks for the patronizing comment.
The difficulty is in the way climate literature glosses over the mathematical setup and assumptions (because the community has them all in their heads).
Further, when a paper begins with an mathematical assumption that you do not stomach, it is very difficult to make it through the rest of it.
nickels: Am I missing something? I always have trouble understanding these model studies because my mind goes straight to numerical error….
Probably not missing anything. A long-term multivariate climate time series has trends of multiple quasi-periodicities due to multiple mechanisms, plus naturally varying processes independent of what the main trends are (essentially “random”, meaning non-predictable and non-reproducible; called “noise” or “background variation”.) Every statistical method yet applied (co-integrated polynomially related vector autoregressive process, for example) has been shown to have liabilities in identifying quasi-periodic multivariate signals. If there is an excellent method, I have not read it yet (and I would appreciate it if denizens could alert me.) In the multivariate case, as in the univariate case, if you know the signal you can eventually estimate the noise, and if you know the noise you can eventually estimate the signal; without adequate knowledge of at least 1 of those, your outputs depend on your “working hypotheses”, as illustrated by the Mann et al study under discussion, and on the statistical methods used.
Mann et al show that if their model of the main trends is correct, the statistical method used does not estimate the AMO accurately; that means that if the estimate of the AMO is correct, that statistical method shows their model of the main trends to be incorrect. Whether any two of those three should be taken as reliable is open to doubt, as shown in Marcia Wyatt’s post. Of the three, it seems to me that the case for the AMO estimate used by Wyatt et al is the most solid.
But at present, I do not think there is an adequate statistical methodology our there for separating “forced” from “unforced” variation, and adequately separating multivariate monotonic trends (recovery from LIA?) from quasi-periodic multivariate trends with long periods.
Whether in addition there is numerical error in the computations of the model outputs or statistical summaries is something I suspect but have no knowledge of.
nickels: Thanks for the patronizing comment.
I apologize. I responded to what you wrote, but I did not intend to be or to seem patronizing. Prof Curry uses the phrase “wickedly difficult” to describe the problem.
Just how nonlinear or linear is the climate system.
An author recommended to us by the frequent contributor Robert I Ellison is Henk A. Dijkstra, who wrote “Nonlinear Climate Dynamics” and “Non-linear Physical Oceanography”.
You are not talking to yourself. But neither did you formulate this “crux of the debate” first in this blog.
You switched from multivariate dynamical system ti multivariate time series, which is exactly the thing thats difficult in the paper for me.
Im trying to work through it anyway. I dont think we are totally disagreeing here although the assumption that linear statistical analysis applies to the nonlinear system (or can be used as method of exploring an inverse problem) is something I would make a much bigger deal about.
“nickels: Thanks for the patronizing comment.”
Okay, my bad. Shields are up all over the place for obvious reasons!!
Thanks for the references.
Hat’s off to you guys for the way you are interacting, a step above many of the interactions I have seen here. :-)
nickels: Shields are up all over the place for obvious reasons!!
I hear you.
I try to be mindful of the “etext effect”, in which even the mildest comments come across as insults. At least you didn’t WRITE IN ALL IN CAPS!
The polynomial co-integrated vector autoregressive processes used by Beenstock et al are at least non-stationary and non-linear. As shown by them and their critics, the method can show that either CO2 is not needed in modeling 20th century temperature, or that CO2 is needed. It depends on details in the implementation.
The statistical literature for analysing multivariate time series is vast. I only know part. There was a famous paper on modeling chaotic systems with the title “How far you can see depends on where you are”, and of course “where you are” is not known, and must be guessed or estimated from the data!
The interdisciplinary component of climate is brutal! Statistics, dynamical systems, then of course all the physics…. I hypothesize the science could make a lot of progress with more cultivation of that aspect…
Beenstock is not physics, it is econometrics.
Climate is not chaotic. “Periodic external force acting on a chaotic system can destroy chaos and as a result a periodic regime appears.”
This is from the reference quoted frequently by Tsonis called Synchronization in Oscillatory Networks.
All one has to do is look at all the periodic climate phenomena to see this. The daily cycle. The seasonal cycle. The tidal effect. The Quasi Biennial Oscillations. The Southern Oscillation. All externally forced creating either periodic or quasi-periodic regimes in the hydrodynamic fluid of interest.
The role of CO2 is to act as a control knob forcing the climate in to a warmer regime. Chaos will not destroy this trend contrary to what the Heartland klowns will have you believe.
Have you had a chance to view the data at the GRACE mission data portal:
specifically checking 2002, 2008, 2013, at a smoothing radius of 25km. Looking at pattern changes. Especially in Greenland, and Africa, relative to pattern changes elsewhere on the globe.
you mention a lot of cycle observations. I think the gravity anomaly maps may give you an added insight? and hope so.
“Climate is not chaotic.”
Perhaps you are right. Then again maybe not…
I would be as inclined to believe (maybe even more so) a prediction from a simplied model over an overly complex GCM if there was some reason to believe one anyways…
“Hat’s off to you guys for the way you are interacting, a step above many of the interactions I have seen here. :-) ”
Ha ha. Ah the good old days of free for all. Being respectful is too much responsibility :p.
‘What defines a climate change as abrupt? Technically, an abrupt climate change occurs when the climate system is forced to cross some threshold, triggering a transition to a new state at a rate determined by the climate system itself and faster than the cause. Chaotic processes in the climate system may allow the cause of such an abrupt climate change to be undetectably small.’ NAS
Climate is pushed past thresholds by control variables at which stage the shift is determined by interactions between system components. The ‘beat’ of this ‘periodicity’ is 20 to 40 years and the potential exists for extreme shifts with large changes in albedo and atmospheric composition possible. It seems indeed possible to offset greenhouse gas forcing.
The model is a transition between regimes – that influences the climate of days and nights and of seasons. Changes in greenhouse gas forcing are minor over 20 to 40 years – and certainly not distinguishable against natural variability. Shifts between regimes set a new climate baseline.
The shifts involve changes in the frequency and intensity of ENSO events. It suggests intriguing possibilities for the aperiodic forcing – but simply saying that forcing destroys chaos in the context of climate means less than nothing.
The last century worth of observational data completely destroys the chaotic regime change thesis.
The control knob of CO2 is gradually increasing the thermal forcing and we are seeing this in the observational data.
Anastasios Tsonis, of the Atmospheric Sciences Group at University of Wisconsin, Milwaukee, and colleagues used a mathematical network approach to analyse abrupt climate change on decadal timescales. Ocean and atmospheric indices – in this case the El Niño Southern Oscillation, the Pacific Decadal Oscillation, the North Atlantic Oscillation and the North Pacific Oscillation – can be thought of as chaotic oscillators that capture the major modes of climate variability. Tsonis and colleagues calculated the ‘distance’ between the indices. It was found that they would synchronise at certain times and then shift into a new state.
It is no coincidence that shifts in ocean and atmospheric indices occur at the same time as changes in the trajectory of global surface temperature. Our ‘interest is to understand – first the natural variability of climate – and then take it from there. So we were very excited when we realized a lot of changes in the past century from warmer to cooler and then back to warmer were all natural,’ Tsonis said.
Four multi-decadal climate shifts were identified in the last century coinciding with changes in the surface temperature trajectory. Warming from 1909 to the mid 1940’s, cooling to the late 1970’s, warming to 1998 and declining since. The shifts are punctuated by extreme El Niño Southern Oscillation events. Fluctuations between La Niña and El Niño peak at these times and climate then settles into a damped oscillation. Until the next critical climate threshold – due perhaps in a decade or two if the recent past is any indication.
Tsonis always references this book:
G. V. Osipov, J. Kurths, and C. Zhou, Synchronization in oscillatory networks. Springer, 2007.
That book includes this passage:
‘What defines a climate change as abrupt? Technically, an abrupt climate change occurs when the climate system is forced to cross some threshold, triggering a transition to a new state at a rate determined by the climate system itself and faster than the cause. Chaotic processes in the climate system may allow the cause of such an abrupt climate change to be undetectably small.’ NAS
Skippy Ellison said:
“…triggering a transition to a new state at a rate determined by the climate system itself and faster than the cause.”
Illogical. Causes to new climate states can be extremely short with the resulting transition sometimes considerably longer. Think about an asteroid strike or an ice dam breaking and releasing meltwater.
So the NAS committee on abrupt climate change – consisting of a who’s who of climate science – is illogical in their core definition.
Just phucking incredible Randy.
Moderator: Randy Gates Simpson replied to Rob Ellison addressing him as Skippy Ellison. I find that to be offensive.
David, Rob sometimes uses the handle generalisimoskippy.
Now I understand where the juvenile Aussie logic comes from. At first I thought Skippy Ellison was using that nickname because he favored kangaroos.
Now thanks to your incredible knowledge I know the real story.
I have never ever heard that racist connotation. Skippy is just a kangaroo in general, or more specifically the animal hero of that 1970’s tv series.
They carried it in the UK but perhaps not the States? I think skippy is a completely harmless term and we shouldn’t bring connotations into it that were never intended.
“Wop” in the US is “WithOut Papers” and also an insult to a certain mediterranean heritage. At least, unless it’s a revisionist acronym. What would a “Wog” be WithOut?
I’m facetiously being over-sensitive to R.Gates and any name calling. Ellison never, so far as I know, used the name Skippy Ellison. In fact Generallisimo Skippy pointedly denies being anyone else as I recall. So since R.Gates chose to be offended when I called Pekka Pirila ‘dingbat’ I chose to be offended when he called Ellison ‘Skippy’. Dingbat and Skippy are about equally offensive.
“Technically, an abrupt climate change occurs when the climate system is forced to cross some threshold, triggering a transition to a new state”
Resorting to using “Chaos” as a description of the climate is actually way overkill to impinge seriously on the computability of climate. These transitions (quote above) are really where the problem lie. For instance, a major change in ocean circulation (stepping a little out of my comfort zone here) that is triggered by crossing the boundary between two regimes… If small numerical errors put you on the wrong side of this transition (as opposed to the true solution) it is all over.
What one typically sees using aposteriori error analysis is that the numerical errors accumulate pretty much a linear pace until one of these transition areas is encountered. In that region numerical errors grow exponentially….
So chaos is not needed to make the computational unstable. These instabilities occur in other ways…
Oh, and, interestingly (might already know this) Lornez equations are, of course, the first few fourier components of the Boussinesq equations, and the two attractor ‘lobes’ actually correspond exactly to circulation of the flow in either the clockwise or counterclockwise direction….
“Technically, an abrupt climate change occurs when the climate system is forced to cross some threshold, triggering a transition to a new state”
Resorting to using “Chaos” as a description of the climate is actually way overkill to impinge seriously on the computability of climate. These transitions (quote above) are really where the problem is. For instance, a major change in ocean circulation (stepping a little out of my comfort zone here) that is triggered by crossing the boundary between two regimes… If small numerical errors put you on the wrong side of this transition (as opposed to the true solution) it is all over.
What one typically sees using aposteriori error analysis is that the numerical errors accumulate pretty much a linear pace until one of these transition areas is encountered. In that region numerical errors grow exponentially….
So chaos is not needed to make the computational unstable. These instabilities occur in other ways…
I guess this could become its own topic….
hope this post isnt a repeat, it seemed to disappear
Abrupt climate shift is the key – and numerical computation is not really the point.
Btw – skippy is a generic reference to wallabies and kangaroos – stemming from the TV show. Skippy as we all know was mostly a claw on a stick – because wallabies and kangaroos are dumber than your average anthill and can be trained to eat grass and – no that’s it – eat grass. It is really an elaborate and prolonged joke on the rest of the world. Unlike drop bears – which are real.
Generalissimo (Retired) Skippy was a climate warrior who was field promoted from Captain Kangaroo. And as the Generalissimo has said – we are all wogs now. It is a sign of an especially successful multi-ethnic society. The theory is that we just don’t give a phuck.
It seems to me that all the many and various attempts to subtract out some part(s) to get a handle on other part(s) are actually superposition ( as in ODEs, PDEs ) in reverse. Lack of applicability of superposition is the essence of the inherent difficulties with solving non-linear ODEs and PDEs. If it’s chaotic, it’s non-linear. If it’s chaotic, its averages are chaotic.
. . . my mind goes straight to numerical error…. . Because of the very coarse temporal and spatial discrete increments, I suspect the application order of the numerical solution methods is less than 1.0. Chaos, of course, somewhat complicates this issue :-)
Okay, thanks, so I wasn’t crazy to be wrestling with this….
Dan Hughes: Lack of applicability of superposition is the essence of the inherent difficulties with solving non-linear ODEs and PDEs.
If in addition the background variation is “long-memory”, “red”, “1/f”, “non-stationary”, etc, the estimation problem is all the harder.
That is a mistruth. Nonlinear equations such as Mathieu when applied to such behaviors as hydrodynamic sloshing can be composed as superposition of the forcing functions.
See Section 1.1, pages 2-4 of W. F. Ames, Nonlinear Partial Differential Equations in Engineering, Academic Press, New York, 1965.
Climate is not chaotic. “Periodic external force acting on a chaotic system can destroy chaos and as a result a periodic regime appears.”
The criticality important word here is ‘can’. Thus it does not universally apply unconditionally. E. N. Lorenz has already looked at this in the 1980s and 1990s. E. N. Lorenz,”Irregularity: a Fundamental Property of the Atmosphere”, Tellus, Vol. 36a, pp. 98-110, 1984. E. N. Lorenz, “Can Chaos and Intransitivity Lead to Interannual Variability?”, Tellus, Vol. 42A, pp. 378-389, 1990. Roger A. Pielke and Xubin Zeng, “Long-Term Variability of Climate”, Journal of the Atmospheric Sciences, Vol. 51, No. 1, pp. 155-159, 1994.
Likewise, including accounting for the conversion of mechanical energy into thermal energy by means of viscous dissipation into the original basic Lorenz models can lead to equilibrium states. Valerio Lucarini and Klaus Fraedrich, Symmetry-break, mixing, instability, and low frequency variability in a minimal Lorenz-like system,” Physical Review E, Vol. 80, 2009.
Finally, even the original Lorenz system of ODEs from the 1960s do not exhibit chaotic response for all values of the parameters in the system. Edward N. Lorenz, “Deterministic Nonperiodic Flow”, Journal of the Atmospheric Sciences, Vol. 20, pp. 130-141, 1963.
All externally forced creating either periodic or quasi-periodic regimes in the hydrodynamic fluid of interest.
Within the framework of temporal chaos as exhibited by the Lorenz models of the 1960s and 1970s, this statement is not correct; see above.
Weather is said to be chaotic. Climate is said to be the average of weather. Averages of chaotic trajectories are also chaotic.
As far as I am aware, it has yet to be demonstrated that the discrete approximations of the complete equation systems used in any GCM satisfy requirements for chaotic responses. The eye-ball estimate, It looks like chaos, is not sufficient. See also, R.M. Corless, C. Essex and M.A.H. Nerenberg, “Numerical Methods can Suppress Chaos”, Physics Letters A, Vol. 157, No. 1, pp. 27-36, 1991.
Because the discrete approximations are just that, approximations to the continuous equations, and the potential for contamination of any chaotic signal by the associated numerical solution methods, it is the numbers from these that are required to be investigated relative to chaotic response.
I think about the best we can say is that weather and climate might be chaotic, or they might not be, in the physical domain. And, is less understood in the discrete approximation/numerical solution domain of GCMs.
In response to …Climate is not chaotic. “Periodic external force acting on a chaotic system can destroy chaos and as a result a periodic regime appears.”
You said…..The criticality important word here is ‘can’. Thus it does not universally apply unconditionally.
Have you seen and considered an interference pattern in gravity, as painted across the planet in pictures at this web site:
(if you look, please take the time to view Greenland in 2002, 2008 and 2013, as well as making note of the ripples and waves, and phases. I suggest using a 25km smoothing radius, it is important).
I know Lorentz could not have considered this information in 1989, because the satellites were not launched until 2002.
I think it is relevant to research looking for a chaos smasher and re-calibrator.
Well, just take a look at the YouTube clip on the synchronized metronomes that someone linked to elsewhere on this thread.
What Osipov et al are getting at is precisely that behavior.An external force applied in a relatively inviscid environment can counteract chaotic tendencies and lead to periodic or quasiperiodic behaviors.
You sound like a smart guy Hughes, why don’t you contribute your ideas to the El Nino prediction project going on at Azimuth? http://azimuth.mathforge.org
I’ve seen the video. A finite dimensional mechanical-energy dominated system uniformly forced by mechanical energy.
Got any examples of synchronization of thermal-energy dominated systems non-uniformly forced by thermal energy and for which gravity is an important factor in the motions?
re: “Got any examples of synchronization of thermal-energy dominated systems non-uniformly forced by thermal energy and for which gravity is an important factor in the motions?”
If I understand your question correctly, I think the gravity maps from the GRACE mission data portal, will show a relationship between gravity and cycles of ice accumulation/loss in Greenland. I believe gravity is showing itself to be inversely proportional to the sunspot cycle via magnetism, and perhaps sphere dynamics (standing waves of energy transport) inside the earth.
At an rate, there seems to be a gravity interference pattern, within the earth running horizontally in one hemisphere, and radially in the other, and it seems to gets in sync or out of sync (phase maybe the better term??) with gravity/magnetism from the sun, primarily.
But I prefer you take a look at:
using monthly anomalies, at smoothing radius of 25km and see for yourself if what you see is of interest to you or not. I particularly note variations from 2002, 2008, and 2013 as being indicative of solar influence. And movement of “gravity” anomalies related to the equator.
Hope this was the relevant to the question asked, and hope you find the answer interesting.
Tides and measurements of GLAAM.
The Chandler Wobble is partially explained by deep ocean modulation.
Check to see how synchronized QBO appears.
The challenge is to tie periodic forcings to the seemingly erratic oscillations of ENSO.
“I find this topic somewhat difficult to unravel.”
The difference is you are honest.
The climate skeptics on this blog however. A lot of them will say “great rebuttal Wyatt! That showed Mann!”, but actually they don’t at all understand what either Mann or Wyatt have said on this matter.
“Great rebuttal” means that a mathematician did the math to show that the Mann hypothesis was not correct. She laid out a concise counter position and obvious challenge.
Now Mann has the ability to counter (if he can or wants to do the work). It seems that Dr.Wyatt has a vision, a talented multidisciplinary team and brains if you read her work.
FRESHING APPROACH TO DISAGREEMENT
It is obvious she distains talking louder, politics and pedantic positions in science (the curse on both sides in this argument). She even included some compliments to Mann! Her objective was to challenge Dr.Mann’s flippant response to her work. I can like her effort without appreciating all the beauty and complexity of the hypothesis.
I would contrast the Wyatt style to those that hand wave, eviscerate or claim higher authority. She challenged Mann with a mathematical approach which identified a basis of potential error in Mann’s critique (pretty straightforward?). The Wyatt approach is simple “I am up to the challenge, lets present our respective research and may the better science/scientist win”.
The clarity of the Wyatt challenge would indicate (to most people that have worked in science) that she likely has substance to support her hypothesis? Getting out of Colorado with Dr.Trenbeth looking over shoulder likely helped her prepare good arguments. In poker the challenge to Dr. Mann is called ” I am all in”. What is not to like about getting right to the point?
Big assertion. Some evidence, please. At least as to whether myself, Tony Brown, and numerous others posted above are in your ‘a lot…’
I think not, and your providing another ad hom equaring to stupidity, rather than contributing perspectives, references, ideas to this thread as most above have, says much about you. But not very complementary.
lolwot: A lot of them will say “great rebuttal Wyatt! That showed Mann!”, but actually they don’t at all understand what either Mann or Wyatt have said on this matter.
For the fun of it, quote (exactly) something you think displays misunderstanding, and write out a correction.
O the obfuscation
of mirrors and smoke,
the tangled web,
it’s such a joke.
Those shamen on the hill
with metaphors of shadows
on the cavern wall
that only some,
we precious few,
may interpret fer
the rest of yew.
Meant ter say … ter lolwot.
Meant ter say, ter lolwot.
There is actually very little math in Wyatt’s work. It is more of a premise backed up by parsimonious registration of climate indexes. Nothing wrong with observational evidence but it only takes you so far.
Admittedly I’m not really connecting with the Mann paper, but my gut reaction synopsis:
“1) Assume the climate is linear so that superposition and linear statistical analysis is relevant. Conclude that internal variability is low by many experiments (which we could have concluded anyway since we have assumed the climate is nonlinear).”
It would really help people outside climate to read these papers if there was actual math notation used to develop the concepts and frame the experiments in the paper. (Not that any climateoligists care)….
Mann’s approach also begs the question of how much CO2 forcing is baked into the model. And more to the point, are the feedbacks resulting from the extra CO2 accurately modeled. I suspect not, since those aren’t well understood in the first place and it is well known that clouds aren’t well modeled, partly due to too-large griding due to a lack of computing power.
Ooops, that line should have been:
since we have assumed the climate is LINEAR
And I probably mangled Climatologist….
Well, the fact that the model parameters have likely been fitted to the forced signal…..
There are so many interdependencies to unravel its kind of overwhelming.
The lack of a running mathematical expository and acknowledgment of the mathematical assumptions always makes me feel like I’m being snowed….
Maybe Im just dumb though, hahaha
Hi Marcia. Great post.
I actually prefer the Trenberth and Shea method of presenting the AMO to show that the AMO occurs naturally…that it is not a forced component. We can use multi-model ensemble-member mean (basically the forced component of all of the models) of the CMIP5 simulations of North Atlantic and global sea surface temperatures, subtracting the simulated global SSTa from the simulated North Atlantic SSTa. Comparing that result to the data-based results, we can see that the simulated North Atlantic sea surface temperatures do not have the additional variability that exists in the data:
Obviously, the AMO is not a forced component of the models.
That graph is from the following post:
“I actually prefer the Trenberth and Shea method of presenting the AMO to show that the AMO occurs naturally…that it is not a forced component.”
This is not the issue Bob, and Marcia I think clearly spoke to that point. The AMO may occur naturally and have both internal and external forcing components, and it really makes no difference in term of it being the “pace-setter” for the stadium-wave, which is the real issue. The real issue is whether of not the stadium-wave is a real Earth system dynamic and the AMO is the “pace-setter” for it. What internal and external components make up the AMO is the subject of multiple lines of other very interesting research as has been amply discussed.
R,Gates: Thank you for quoting me out of context. If you had read further, you would have noted that my comment was primarily about climate models and how poorly they simulated the AMO.
And yes I do realize the overall intent of Marcia’s post, but like many commenters on a thread here at ClimateEtc. I went off on a minor tangent.
Have a good day.
What is the proof that using world’s oceans as a representative of the forced SST is valid? Is there a paper or other study?
“Mann et al. interpret the stadium wave as a challenge to their forced signal. This conclusion seems unfounded.”
I agree–the phenomena probably should be seen as a product of necessary circumstances that come together and take on a life of their own, resulting in a sort of harmony amidst the chaos like the synchronization of coupled oscillators. The stadium wave might be compared to a haboob –e.g., a wall of sand involving the Earth’s surface like an organized leading edge of an invasion of army ants, as contrasted with a sandstorm that is more a boil of dust everywhere.
Maarcia Wyatt, well done and thank you.
Will (Kravtsov et al. submitted) become available for downloading?
Matthew, excellent question. Your question does expose the chicken-egg caveat inherent in our assumptions.
The Pacific negatively feeds back on the Atlantic, as do more regionally situated sea-ice and related atmospheric processes in the Atlantic sector of the Arctic, processes that are strongly influenced by the AMO. And we have not unraveled the exact role of the Southern Hemisphere. So there are assumptions, good ones, but assumptions nevertheless that underlie our crowning the AMO as conductor setting tempo.
It is better to say the stadium wave tempo. And by convention, describe the chain of events as they clearly seem to occur with the strong influence of the AMO: cold ocean to increased ice cover specifically in the eurasian arctic marginal seas, beginning with the Greenland and Barents Seas. this, along with related increases in snow and ice cover leads to an increased meridional temperature gradient, promoting strong meridional basin scale wind flow, augmenting warm air advection from lower latitudes north and east, with simultaneous changes in sea-level pressure, impacts on sea ice and heat flux to overlying atmosphere and effects on arctic temperature and local and regional SLP, the anomalies of which expand into the Pacific sector, with changes in sea ice continuing along with changes in atmospheric processes with local and remote impacts, including those on the ITCZ. It is worth note that sea ice variability is strongly multidecadal in Atlantic sector of Eurasian Arctic. The variability east of the Kara Sea becomes progressively less so, and more strongly interdecadal, as the signal is carried toward the Pacific boundary of the Eurasian ice. See section 4 of Wyatt and Curry.
So while that is the skeletal recap of the envisioned mechanism, it is also a really long winded way to say I really can’t know for sure!
BTW, we hope to be able to post the Kravtsov et al paper soon. It has been submitted. I’m sure Judy will post it when it is available.
Oops. I put the reply to Matthew too high in the thread. Could someone tell him? Still a rooky at this. Marcia
Marcia Wyatt, good answer. What’s the best reference, other than section 4 of Wyatt and Curry, for these narrations. I hope you are not bothered by the word “narrations”. Leroux’s book “The dynamic analysis of weather and climate” has a bunch of them, and I find the narrations to be informative.
and thanks to Brandon Shollenberger for directing me here.
Could tracking your Stadium Wave and lags in the ocean help distinguish between radiation driven forcing changing clouds and ocean driven cloud changes changing radiative forcing? cf Roy Spencer chicken/egg natural/anthroprogenic forcing question.
Oceanic Cloud Decrease since 1987 Explains 1/3 of Ocean Heating
Spencer, R.W., and W.D. Braswell, 2014: The role of ENSO in global ocean temperature changes during 1955-2011 simulated with a 1D climate model. Asia-Pac. J. Atmos. Sci., 50(2), 229-237.
Spencer, R. W., and W. D. Braswell, 2011: On the misdiagnosis of surface temperature feedbacks from variations in Earth’s radiant energy balance. Remote Sens., 3, 1603-1613; doi:10.3390/rs3081603
Marcia Wyatt (this time, only 2 “a”s in Marcia), I do have one question: How can you tell the AMO “sets the pace”?
Matthew R Marler, Marcia Wyatt responded to you, but she placed her response in the wrong spot. You can find it here.
I have never like this climatology habit of linear detrending since it assumes that there is something linear in climate to be subtracted without anyone every saying so explicitly and saying what it is.
There is no reason to fit a linear model to surface temps therefore the whole evercise has no statistical legitimacy. Also there’s no reason to assume the 60y “cycle” is harmonic. In fact a folded ( or rectified ) cosine is a better fit.
However, if we’re going to play that game how can it best be done.
1. fit a linear trend + const to the data you have and subtract it? Since there are significant long period variabilities the result this exercise will depend upon where you start and finish even with the same dataset. Not so good.
2. Fit a 60y model and linear + const at the same time? This is a bit better since it will avoid fitting the trend to incomplete cycles and reducing correlation (and hence amplitude) of the 60y model.
3. Fit a 60 model + const to rate of change? This will reduce any linear trend to a fixed offset ( absorbed by the const ) which will not affect the correlation to cycle model.
4. Pick something like SSA, whose mathematical properites and limitations you don’t really understand. You’ll look like a maestro. Sure to stop too many difficult question at peer review.
A. Use “anomalies”. Always good emphasis the fact that any change in any climate metric is abnormal. It’s worse then we thought.
B Use a good filter like gaussian or triple running mean to remove annual cycles.
C. Use a “filter designer” fn in Mathlab to design a Butterworth filter. This won’t tell you whether is it suitable, how long it takes to converge but you don’t need to talk about that.
D. Don’t filter, let the least squares average out annual cycle.
i understand why we would back out forcings, say as related to “Milankovitch” cycles, as being unimportant to the determination of CO2 being bad or not.
I don’t know how we think we manage to back out things like a 10,000 year rebound of the land under 3 great lakes, or the continuing impact of the opening of the Bering Strait that proceeded that.
Nor when something like the niagara gorge digging it’s way through another 23,000 years worth of dolomite ridge, and emptying a drastically reducing a lake or 3.
But we can’t be aware of all “slow forcings”. So how can we pretend to be able to back them out. Statistically, the likelihood that we have properly recognized, analyzed, and therefor can predict the duration and effects of each of them, would seem to me to be a nul probability.
Which makes me wonder, how it is that the IPCC cannot be more aware of the things it is that they don’t know??
Greg I find your comment to be an odd mix of real criticism and sarcasm. Can you clarify which is which?
Another effort to impart the likely impact of Gravity/magnetism.
Gravity is viewed, simply, as a straight down force. But in reality, if we imagined a plastic ball around our head, and coloured it dark and light, for which direction had the strongest pull, although we are pulled in every direction, the sum of all the pulls put together, with opposite sides negating each other, is the direction we “want”to go.
Then imagine standing beside a mountain. At this point in 3d space, there would be a noticeable coloration on the plastic sphere, representing the mountain off to one side. But the moon, the sun, the planets, the galaxy, and all of the stars, are each pulling on one side of the planet, speeding it up, and almost balanced on the other side, slowing it down.
So the actual realized gravity on the earth, is a constant redrawing of the total realized gravitational force, as pulled in every direction, for EVERY point in 3d space, around the earth, being considered. And an instant later, you have to do it again.
Gravity itself, the constancy of the most obvious and over-riding influence, the earth, lures us to ignoring the other matter in the universe, that in a constant, omnipresent part of the choice your body makes, to be pulled downward. The magnetism in light, is not enough to affect you directly. But it is enough to “tip” the scales, for the lightest particles, that are most on the fence, most ready to “listen to new direction”. Water draining down a hole, atmosphere “roiling” in Hadley cells, hurricanes and tornados. They all show a “propensity to roil”, unidirectionally. For a reason. Path of least resistance. It is “natural”.
Consider the complexity of measuring gravity, at a given moment in time, for the entire earth. Heat dissipation/distribution is similar. It is relative. It always is dependent on the relative heat of adjoing particles/collections of particles. and the heat arriving at that point, and it’s speed of approach, from all vectors. Every point in 3d space being measured/considered, is constantly in the process, of being affected by all the other particles, within the 3d system being examined (which in the case of the climate, extends out to the earths magnetosphere, and further to the Sun’s Heliopause, and further, to include relevant bodies of mass within our relevant sphere of influence. Because all of them cause ripples, in the energy the Earth receives. In the “lift” of matter, from the surface of the earth. The counterbalance to earth’s gravity.
To treat the rising of temperature in one location, and the associated changes, as NOT affecting the existence of pressure/content, on the other side of the globe, at the same instant, is to not understand the scope of the climate system.
for example, to believe that heating up the earth, doesn’t result in an increased rate of heat flow from that same earth, would be short sighted. to imagine a melting of glacial ice, and not recognize the increased hardness, this provides the ice down below it, would be short sighted. to believe that adding water to the ocean, doesn’t magnify the sinking of the crust under Mariana’s Trench, would be short sighted. to believe that CME’s create auroras, electrical blackouts, and changes to earths magnetic field, and NOT affect the climate would be short sighted. to not recognize the magnitude of heat generated by radioactive decay, and that even the slightest variabilities due to pressure/magnet/gravity/unknown influence [re: sturrock, 2009, stanford], could cause variations in surface temperature far exceeding those attributed to CO2, would be short sighted.
I see lots of folks asserting lots of reasons why the climate does what it does. I think they are probably mostly correct. Yes there is ice change, yes there is ocean movement, yes there is irradiance fluctation, yes there is a stadium wave, yes there is variation in volcanic activity, and along the mid atlantic ridge. yes there is variation in cloud cover, GHG made by lightning, amount of lightning. And so on.
There are LOTS of “RIGHT” people.
The only forcing humanity has “put there money on” mattering, in significance, have been ozone related, and CO2 related.
The ozone hole I believe largely turned out to be a self fluctuating hole, that occurs naturally with fluctuations in Earth’s magnetic field. I don’t know if we made a difference?? I could be enlightened in this area.
My guess is CO2 is a result of temperature. That makes sense. Increase the temperature of a petri dish and you affect life within it, immediately. 50% of ALL life is bacteria. Mostly ocean based I think. This has to be significant, in it’s ability to respond to temperature changes.
The idea that CO2 drives climate with any degree of significance, I highly doubt. I think it is spitting in an ocean. But I don’t exclude the possibility.
As a runaway spiraling control mechanism, in light of the other forcings that control and regulate temperature, as they seem to do, I find the premise of CO2 being a significance statistically preposterous, with ZERO evidence to back up the claim that it is. At least any evidence I find statistically relevant, and that seems to be a common theme among some other people here that have a gift for statistics.
I would suggest, the most significant driver, will be found to be overall energy of the earth, as driven and balanced by light/gravity/magnetism interaction in our solar system, and in reaction to ripples in those energies passing through the space through which the earth passes. And those are most affected/controlled by Solar output, which in turn is driven by changes in the local interstellar cloud, driving the constant balancing of energy between the sun’s equator, and the heliopause, somewhat triggered or scheduled, by the passage of the planets within that sphere of consideration.
The impact of the interference pattern that permeates space, and the pattern on the surface of the earth, that “presents” in response to the interference pattern that omnipresently, and omnipotently, permeates space, can be see by viewing the data from the GRACE mission. Look at North America being “brushed” sideways. Look at Africa with it’s vertical “worm wriggles”. Look at Greenland “bouncing” in a 23 year pattern.
See for yourself the impact of gravity on the planet, at NASA’s GRACE mission data portal, where you can view different “snapshots” from 2002-2013 of gravity anomolies, USE 25km Smoothing Radius, it matters.
imagine the impact of gravity changes on free air, on ice, on tides, on tidal heat energy, on oblatedness (right word is??) and rate of volcanic activity, or plate spread. On localized patterns of barometric pressure.
I just cannot suggest strongly enough, that a patterned global variation in gravity, is a patterned global variation in trailing and leading edges of barometric oscillation, that simply must be a factor in climate creation.
(stopping in case I’ve gone on too much.)
Really hoping to be able to help people with their own areas of interest, understanding a factor that has perhaps been overlooked in relation to that area of interest.
North Atlantic SST ‘oscillation’ (the AMO) is most likely caused by Arctic Atmospheric pressure quasi periodic variability, but also it correlates well with the N. Atlantic tectonic count. Both of these precede the AMO by some years.
Fitting a simple linear + cosine model follows AMO very well. There is no divergence in either direction at the beginning or the end of the fit.
Initially fitting to unfiltered data produced very nearly the same fit parameters, so to aid visual comparison 12mo filtered data is shown.
The suggested folded cosine fits into the troughs and follows the curvature at the end a little better but the differences are minimal.
There is no “acceleration” in the data other than that explained by a simple harmonic function.
Confusion must exist about whether the stadium wave actually ‘moves onward’ in a literal sense as a thing in itself to be reckoned with — like the leading edge of a storm of army ants – or, is it only phenomenal like a wave in an ocean where the wave moves on but the atoms that comprise the ocean do not.
PDO, AMO, the Stadum wave etc. There seems to be no end to these waves or oscillations that have no clear physical reason for existence. The only global oscillation that has an actual physical explanation is ENSO. There is no doubt about its reality because all global temperature curves bear the stamp of its existence as far back as you choose to push them. Its only rival is the Indian Ocean Dipole and there is no sign of its existence in global temperature records. ENSO is a harmonic oscillation of ocean water in the equatorial Pacific from side to side. The oscillation is excited by trade winds, part of the Walker circulation. To understand the principle consider what happens when you blow across the end of a glass tube. You get a tone corresponding to its resonant frequency which is determined by the dimensions of the tube. Make the tube larger and the tone is lower because the frequency is lower. Extend this idea to the size of the ocean and trade winds are now the equivalent of blowing across the end of the tube. And the ocean answers to them with its own resonant tone – about one El Nino peak every five years or so. Other happenings in the ocean can disturb the regularity of these peaks but when things quiet down you see the five year resonant frequency return, as far back as the early nineteenth century. The normal ENSO oscillation starts with the trade winds piling up warm tropical water in the Indo-Pacific Warm Pool between the Philippines andNew Guinea. When the water level there is high enough gravity flow back east starts along the equatorial counter-current. An El Nino wave travels along the counter-current, runs ashore in South America, spreads out north and south along the coast, and warms the air above it. Warm air rises, interferes with trade winds, joins the westerlies connected with the upper air circulation, and we notice that an El Nino has arrived. But any wave that runs ashore must also retreat. As the El Nino wave retreats water level behind it drops half a meter, cold water from below wells up to fill the vacuum, and a La Nina has started. As much as the El Nino warmed the atmosphere the La Nina will now cool it and no permanent climate change is produced. In the absence of any background temperature change the sawtooth of El Nino peaks and La Nina valleys will be horizontal as it can be observed in the eighties and nineties between 1979 and the beginning of 1997. To see the global mean, put a dot at the midpoint between an El Nino peak and its adjacent La Nina valley, and then connect the dots. This can be done with all global temperature curves that are shown with sufficient resolution. From 1979 to 1997 it produces a horizontal straight line, proving absence of warming. But you can only see it in satellite records. Ground-based temperature curves, however, show a global temperature rise of 0.1 degrees Celsius over this temperature range because the entire batch of them is falsified, starting with 1979. Up to now we have described normal ENSO but a variant can happen if, for some reason, the equatorial counter-current is blocked ahead of an El Nino wave. What happens then is that when the El Nino wave hits that block it spreads out on the surface in the middle of the Pacific. This will create an El Nino on the spot. It is called El Nino Modoki or Central Pacific (CP) El Nino. I am not sure how this will balance out with the La Nina that should follow and hence whether some heat loss to the rest of the ocean can happen. There are various locations where water temperature is measured to predict El Ninos, one of which is Nino3.4. It sits right smack in the middle of the equatorial counter-current and watches all the El Nino waves go by. Water temperature at Nino3.4 rises approximately three months before an El Nino can be observed because it takes that long for an El Nino wave in the middle of the ocean to reach South American coast. Finally, the beginning of it El Ninos can be deduced from geologic history. The present configuration of the Pacific current system came into existence when the Panamanian Seaway closed. Prior to that the Atlantic and the Pacific were joined and. currents flowed across the present-day location of the Panamanian Isthmus. This of course rules out any El Nino like Pliocene that some ignorant “climate” scientists have hypothesized.
“This is a reminder of the theme ubiquitously observed in natural systems: network behavior. Network behavior — the exact nature of which depends more on architecture of linkages within the network, and less on the individual behavior of the nodes of the network — gives understanding to an orderliness of interlinked parts. Network parts that are studied in isolation reveal no such order. Parts that are not part of a network, that have no interactive links between them, possess no such order. It seems a message pervasive in nature.”
There’s all kinds of insightful information at the link. Perhaps it’s something like looking for that one thing as the key. We look for the queen bee but that’s not the the complete answer however, the queen may behave similar to the system as a whole.
I hadn’t realized how much ground the paper covered, possibly tying so many things together.
Another interesting thing Wyatt says is that there may be a solar influence, but have a look at it, don’t use my interpretation.
There’s also an understandable description touching on synching that reminded me of Milanovic.
‘Climate is ultimately complex. Complexity begs for reductionism. With reductionism, a puzzle is studied by way of its pieces. While this approach illuminates the climate system’s components, climate’s full picture remains elusive. Understanding the pieces does not ensure understanding the collection of pieces. This conundrum motivates our study.’ Wyatt
That is the significant bit.
Agree with what you wrote above. This is so good I’ll use your phrase, to an accountant it seems cutting edge. However I fear they may straying off the reservation.
I watch a long video by Robert Sapolsky on reductionism over a year ago. I believe he presented things as we should move beyond reductionism, which is easier said than done.
Marcia, you state:
“Thus to clarify: The stadium-wave hypothesis describes a hypothesized intrinsic dynamic of hemispheric signal communication under boundary conditions extant throughout the 20th century (and perhaps for at least a century prior). ”
I was under the impression there was support for the pre-secular hypothesis that the stadium wave was in force, through proxies. This sentence (and a some others) doesn’t make sense to me, the layman reader.
Is Stadium wave a hypothesis that has applicability 1000 years, 100M years, or merely 100 years ago? What do you suspect about the applicability from the proxies?
Arno Arrak “The only global oscillation that has an actual physical explanation is ENSO. There is no doubt about its reality because all global temperature curves bear the stamp of its existence as far back as you choose to push them. ”
There is no proper physical explanation for the origins of ENSO. Your hand-waving blowing across a tube analogy is farcical. Yes, there is a +ve f/b in the form of the trade winds, that does not explain the _origin_ not the periodicity, which if you are claiming a single basic period of “about 5y” is far from the truth.
Neither can water “pile up” in an open basin in a gravitational field. The whole description is infantile.
There are regions in phase and in anti-phase with ENSO, if anything that suggests a common global driver, not 2% of the earth’s oceans wagging the climatic dog.
If there are basin wide oscillations in the pacific on an inter-annual scale, they are likely to be slow tidal waves on the thermocline. If you work out the density difference across the thermocline boundary it is about 1000 times less than the air/water boundary. The surface resonates most strongly to the 12h periodicity in the gravitational driver.
Multiply that period by 1000 and you get 1.4 years. So the thermocline will respond on that kind of inter-annual time-scale. Like the surface there will not be one simple harmonic oscillation but complex resonances reflecting the shape and dimensions of the ocean basin.
If ENSO looks “pseudo-periodic” it is because it is probably nearly as complex as the surface tides.
Trade winds are not root cause of ENSO, they are a feedback, ie a consequence. You have the tail wagging the dog.
Frequency analysis of trade wind data shows both solar and lunar periods:
It’s about time someone in climatology started looking for the _cause_ of ENSO, the fundamental driver, rather mistaking effect for cause and talking of water ‘piling up’.
‘It’s about time someone in climatology started looking for the _cause_ of ENSO, the fundamental driver, rather mistaking effect for cause and talking of water ‘piling up’
What sort of thing MIGHT be causing ENSO in your opinion? Where should people be looking?
La Nina happen because of discharge in the eastern Pacific. Warm water sloshing back across the Pacific hits the coast and moves north and south until the thermocline is again sufficiently shallow to allow cold water upwelling. Upwelling propagates across the Pacific with feedbacks in cloud, winds and currents piling warm water up against Australia and Indonesia. At some stage a relaxation events occurs involving the Madden-Julian Oscillation and water again flows eastward.
Multi-decadal variability in the Pacific is defined as the Interdecadal Pacific Oscillation (e.g. Folland et al,2002, Meinke et al, 2005, Parker et al, 2007, Power et al, 1999) – a proliferation of oscillations it seems. The latest Pacific Ocean climate shift in 1998/2001 is linked to increased flow in the north (Di Lorenzo et al, 2008) and the south (Roemmich et al, 2007, Qiu, Bo et al 2006) Pacific Ocean gyres. Roemmich et al (2007) suggest that mid-latitude gyres in all of the oceans are influenced by decadal variability in the Southern and Northern Annular Modes (SAM and NAM respectively) as wind driven currents in baroclinic oceans (Sverdrup, 1947).
There is a growing literature on the potential for stratospheric influences on climate (e.g. Matthes et al 2006, Gray et al 2010, Lockwood et al 2010, Schaife et al 2012) due to warming of stratospheric ozone by solar UV emissions. Models incorporating stratospheric layers – despite differing greatly in their formulation of fundamental processes such as atmosphere-ocean coupling, clouds or gravity wave drag – show consistent responses in the troposphere. Top down modulation of SAM and NAM by solar UV has the potential to explain otherwise little understood variability at decadal to much longer scales in ENSO.
Longer term modulation of frequency and intensity of ENSO events depends on flows in the Peruvian and Californian Currents.
I think it is gravity waves and the interference pattern in them. Please look at the pictures here, and see if you agree…
us monthly anomalies, and 25km smoothing radius to see gravity revealed. And imagine that pattern has to come from somewhere. As does the 23 year polar bounce, related to the suns magnetic flips.
It is compellingly plausible, and I believe relevant, and of interest to you.
(sorry if you’ve hear this before. I haven’t heard anyone say they don’t think it is important).
Hi Tony, check the solar plasma velocity at the 1997/98 and 2009/10 El Nino episodes:
Have you paid much attention to gravity phase oscillations as a potential driver for ENSO’s timing, that relate to the solar cycles?
Data can be viewed here:
I see waves, and interference patterns, and frequencies, I think you will too.
I suggest using monthly anomalies maps, with a smoothing radius of 25k, to see high granularity. It reveals more.
I suggest special attention to greenland in 2002, 2008, 2013 as one trend directly related to solar cylce/solar pole flip.
Then pay some attention to the yearly cycles that push and pull up and down from the equator.
I believe you will find information helpful to your research.
“If ENSO looks “pseudo-periodic” it is because it is probably nearly as complex as the surface tides.”
I would put it as:
If ENSO looks “pseudo-periodic” it is because it is (probably ) as complex as the -oceanic crust- ‘tectonic tides’.
I wonder if Jeff Masters appreciates the “ripple effect” physical basis in your Stadium Wave Theory.
He does when it comes to tropical system’s wider reach and lagged impacts.
If either of you have reviewed the maps at the GRACE mission data portal, here: http://geoid.colorado.edu/grace/dataportal.html
(I recommend 25km smoothing radius and viewing monthly anomalies)
Noting the ripples, waves, and the bounce of Greenland, and considering the resultant internal sphere dynamics that will reinforce consistent interference patterns.
As related possibly to the timing of ENSO or other related gravitation/mass/energy distribution patterns and timings?
There seems to be a strong correlation to the Earth and Sun’s magnetic strength, detected neutron flow at the poles, sunspot cycles, and therefore solar activity as a rule.
I would love your comment as your knowledge of the mathematics of the climatic observations is much stronger than my own. :-)
I’m trying to figure out how relevant/significant the patterns would be, and trust your input/opinion in this regard.
I think it strengthens/reinforces the import of a stadium wave, ENSO, etc.
If the Stadium Wave does have an effect on the CET, then in the summer it ‘revolved’ at twice the winters’ rate. Since we have to assume that the CET data is not ‘mangled’ too much, the last 80 or so years have seen almost reversed rolls. Most odd that, see this link .
How accurate are climate models? See–e.g., Global warming computer models confounded as Antarctic…
The warm AMO since 1995 is due to a decline in solar plasma forcing:
Increases in solar or theoretical GHG forcing will increase positive NAO/AO conditions, giving reduced poleward ocean transport, and a cool AMO mode, and cooling of the Arctic ocean:
With solar activity continuing weak, the AMO will stay in its warm phase, and run out of phase with the sunspot cycle:
Since the AMO closely follows the Arctic pressure , it is due for an imminent fall, but it will stay mainly positive until the end of the decade.
I’m saying that it will stay warm until the SC 25 maximum, and cool off slightly then, like it has recently around this solar cycle maximum. It could well do another warm cycle after that before solar forcing picks up enough to cause a cool AMO phase.
To be more precise, I expect the AMO to warm up strongly again from 2015, peaking around the next solar cycle minimum, and then cooling around SC25 maximum. Much like it did from 2000-2014:
I am expecting to see greatly reduced summer Arctic sea ice extent 2018-2023.
The last two solar minima had their coldest run of years between the sunspot maxima of the first two weak cycles (+1 year), 1807-1817 and 1885-1896. Which would be 2015/16 to 2025/26 in solar cycles 24&25. On top of that, 179yr heliocentric analogues show a pronounced sequence of cold events from late 2015 to 2024. See the years 1836 to 1845 on CET: http://climexp.knmi.nl/data/tcet.dat
US drought is strongly associated with warm AMO phases:
“Key role of the Atlantic Multidecadal Oscillation in 20th century drought and wet periods over the Great Plains”
There is crying need here to relate a bunch of vague ideas to the analytic foundations of dynamical sytems. At the very least, a credible physical specification of the Lagrangian governing the propagation of the “stadium wave” needs to be provided, and verified empirically. Without it, Wyatt’s handwaving conjectures are simply an exercise in numerology.
John S.Without it, Wyatt’s handwaving conjectures are simply an exercise in numerology.
Accurate descriptions of phenomena, and accurate descriptions of their quantitative relationships to other phenomena, can precede understanding by decades, and even centuries. Wyatt has provided accurate characterizations, that may in fact guide the research that will lead to the dynamical understanding that you seek.
The method was based on Multichannel Singular Spectrum Analysis. That is – spectral decomposition of multiple time series.
It would to be the appropriate technique for mapping time series.
I am certainly not across the details – but handwaving about vague assertions needs to address the method and not substitute wet dreams about impossible math.
It would seem to be….
Phenomenological analyses using newly developed methods are fine. But Wyatt goes considerably beyond that in claiming a physical “stadium wave” that propagates across the NH. I simply ask the basic physical question about its dynamics, whose import seems lost on some blog stars: what generates it, what is its phase speed and direction?
The fact of the matter is that the various multidecadal oscillations (AMO, PDO etc.) found long ago by various analytic techniques are not strongly coherent, and many individual NH station records (e.g., Baltic Sea region) show no appreciable mutidecadal content in their power spectra. There is a teleconnection aspect, however, since strongly coherent multidecadal oscillations are sometimes found in other regions, separated by thousands of miles, with no such behavior in between. This does not comport with any credible physical concept of a propagating wave
John S. | July 12, 2014 at 5:25 pm |
There is a teleconnection aspect, however, since strongly coherent multidecadal oscillations are sometimes found in other regions, separated by thousands of miles, with no such behavior in between.
If it was a network, what would explain this skip? The wave would go around the unaffected region. Similar to when the internet stops working in a geographical area. The traffic goes around it. Also we are dealing with at least 3 paths. Oceans, Surface level atmosphere, Above surface atmosphere.
This isn’t like an electromagnetic wave. It’s information, in a form vaguely like cause and effect. There’s no reason to suppose that it doesn’t go through the affected area, but in a form that doesn’t show up to “various analytic techniques” or “individual NH station records”.
AK | July 12, 2014 at 6:46 pm |
I was trying to say the wave doesn’t need to steamroll each specific small area. It needs to advance. I am picturing syncing oscillators that find uncooperative oscillators blocking the advance. A melting sync signal is more likely to melt sea ice than the Greenland ice sheet. The wave progresses through the sea ice.
“Emergent from the results was a picture of a climate signal propagating through a sequence of synchronized atmospheric and lagged oceanic circulations across the Northern Hemisphere.”
We might assume a wave passes through the PDO region and affects it. What causes the phase of the PDO? Is it the information contained in a wave? Looking at the stadium wheel, one might see 8 waves but I think only 2 are associated with a PDO sign change. The others may reinforce the 2 sign change ones. When the PDO changes signs I doubt it does it on its own. The other regions must work on it and they do so through a network. The network might be sending overall cool or warm signals that have to wear down or add to the PDOs momentum. The wave may represent successful propagation of signals to change the PDOs sign.
Pray tell, Ragnaar, what are the physical rules that govern the architecture of Wyatt’s “synchronized network of geophysical indices, geographically and sequentially communicated by a chain-like signal transmission through the coupling of ocean, ice, and atmospheric patterns? ” Without any, one is left with vague mumbo-jumbo that can rationalize just about anything. Sound science differs sharply from the art of casting horoscopes, which her “stadium-wheel” quite frankly resembles.
John S. | July 14, 2014 at 7:32 pm |
…what are the physical rules that govern the architecture of Wyatt’s “synchronized network of geophysical indices…
It’s a good question. Here are some of the suggested physical rules of the stadium wave:
“Unique to the Arctic Ocean is its Atlantic-sector juxtaposition to open ocean in winter. This proximity conveys dominant influence to the Atlantic on the feature most critical to Eurasian Arctic sea-ice growth in winter – the halocline. Thus, through the Arctic-Atlantic interface, sea ice extent in the Western Eurasian Arctic shelf seas varies in tandem with the AMO, and by extension, the AMOC. A cascade of positive feedbacks in the first stage of an evolving climate regime occur: changes in ice cover, SLP over the Arctic, in associated wind patterns and consequent sea-ice dynamics. Together, these changes amplify the Atlantic-born signal. In the background, seeds of gradual trend-reversal are embedded. Changing inventory of ice cover governs latitudinal position of the overlying Arctic Front, determining location of delivery of freshwater, upon which the halocline relies.
In the second stage of climate-regime evolution, positive feedbacks slowly are supplanted by negative ones, reversing the polarity Atlantic Ocean signal. Reasoning for this ties back to the halocline. A cold (warm) Atlantic promotes a strong (weak) halocline and increased (decreased) sea ice extent in the Western Eurasian seas in winter, which inhibits (allows) ocean-heat-flux to the overlying atmosphere, cooling (warming) the air at high latitudes, thereby increasing (decreasing) the polar-equatorial temperature gradient, which in turn, encourages (discourages) warm air advection from low latitudes poleward and eastward. Mid-and high latitude temperatures, especially over landmasses at lower altitudes, increase (decrease).”
“And finally, network configuration determines its function. The architecture of the hypothesized stadium-wave network is envisioned to be a chain or ring-like configuration. Local coupling within this network arrangement sets the stage for signal propagation — as in a stadium wave (or a less glamorous vision, our intestinal track)”
“A key point is connectivity. Identifying the key connections within the stadium wave gives insight into stability of the signal propagation. The WC study suggests the Eurasian Arctic shelf-sea ice to be such a key connection. Based on network theory, one might speculate whether too much or too little ice inventory may inhibit signal propagation and/or isolate segments of the network from one another. There is indication of another communication link. This one is in the tropical latitudes, between the Pacific and Atlantic Inter-Tropical Convergence Zones (ITCZ).”
Here’s Milanovik on the stadium wave:
“Tsonis, Swanson and Wyatt with the Stadium wave are examples of this approach which shows promising results. These methods have in common the choice of a finite and small number of observed dominating spatio-temporal patterns, their Fourier modes are then determined and finally one analyses how these modes interact.”
What do you think of what Tomas Milanovik has written at this blog?
The string of mere verbal allusions to various putative mechanisms that you quote scarcely constitutes a specification of a network that would act as a credible analog for multidecadal temperature variations. On the contrary, it’s simply a litany of often empty speculations. This may impress some mathematicians, but adds little to bona fide geophysical knowledge.
What the gimmicky notion of a “stadium wave” totally misses is the inconsistent low-frequency coherence and phase relationship between the Siberian Arctic and temperate/tropical latitudes in the NH. The PDO, in particular, leads the Siberian littoral by roughly a quarter cycle, and Southeast Asia leads by a far more modest phase. That sort of behavior points to heat advection by winds and ocean currents, rather than any wave propagation, acting in conjunction with local variations in cloud cover/insolation as the factors most likely responsible for the quite disparate multidecadal temperature variations observed empirically.
John S. | July 15, 2014 at 10:12 pm |
I think the mathematician is exploring a concept while climate scientists are trying to explore that concept as well.
Here’s an interesting paper mentioning wave-like structures:
“We propose a method to reconstruct and analyze a complex network from data
generated by a spatio-temporal dynamical system, relying on the nonlinear mutual information of time series analysis and betweenness centrality of the complex network theory. We show that this approach reveals a rich internal structure in complex climate networks constructed from reanalysis and model surface air temperature data. Our novel method uncovers peculiar wave-like structures of high-energy ﬂow, that we relate to global surface ocean currents. This points to a major role of the oceanic surface circulation in coupling and stabilizing the global temperature ﬁeld in the
I think these types of studies have a triple benefit for climate scientists. It might explain the climate, it might get the science unstuck from the limits of reductionism, and there may be spin off benefits for other fields.
I do think Tsonis et al 2007 was wonderful, that’s no secret. It’s been cited about 140 times: http://scholar.google.com/scholar?rlz=1C1OPRA_enUS592US592&es_sm=122&bav=on.2,or.r_qf.&bvm=bv.71126742,d.aWw,pv.xjs.s.en_US.JBeEmV5xQY4.O&biw=1280&bih=923&um=1&ie=UTF-8&lr=&cites=11310475724231287986
With the physical processes, do we agree that, “Thus, the polarity of the North Atlantic Ocean temperatures strongly influences winter inventory of sea ice. Sea ice inventory regulates escape of ocean heat, which exerts dominant influence on wintertime Arctic surface temperatures, and by extension, on the polar-equatorial temperature gradient (PETG). In turn, the PETG dictates equator-to-pole transport of heat, converting the initial ocean signal-polarity to the oppositely signed atmospheric signature.”
Which to me means that a warm North Atlantic melts ice and causes lower atmospheric temperatures. This particular sea ice is in a key area and has some resilience. It also has a network characteristic of being either off or on.
I am glad I had a chance to try to figure out how it might work. Here’s another paper looking at Synchronization:
Synchronization of polar climate variability over the last ice age: In search of simple rules at the heart of climate’s complexity
“I propose that the simplest explanation of the data is that the paleoclimate oscillations of the Polar Regions are synchronized. To represent polar climate variability I borrow from the work of climatologist Barry Saltzman, who three decades ago showed how climate oscillations of polar temperatures may be explained by the nonlinear interaction between just two variables: sea ice extent and mean ocean temperature. Saltzman’s model explains that mean ocean temperature begins to increase when sea ice reaches its maximum extent. This is because sea ice is a very effective heat insulator, while a large portion of the ocean is still receiving solar heat.”
“…the clocks, coupled by the weak elastic forces along the wall on which they hung, always became synchronized, no matter how different their starting conditions, and so long as their natural frequencies were not too different. Through the slight motions induced on the wall each clock gently forced the other, speeding it up or slowing it down until synchrony was attained.”
“I submit that, dynamically, a key to their long-range interaction may be that ENSO and the Indian monsoon are antipodal to each other (just like the two poles). The earth’s spherical shape has interesting consequences when considering the propagation of climatic influence especially through the atmosphere, as it provides a way to communicate information to the longest distances. Every bit of information released at a source will eventually converge with all other bits (provided it survives dissipation) at their geographic antipode.”
– José A. Rial
Rules for sea ice. When it’s warm, melt to let more heat out. When it’s cold, advance and insulate.
The ‘stadium wave’ is a metaphor for the connections between these network nodes – there is no physical wave as in a wave rolling across the oceans.
Try this one Ragnaar – for another Arctic mechanism.
What Tsonis et al. (2007) do is rely upon a novel measure of correlation distance in examining the relationship between four climate indices. This is an entirely a phenomenological analysis, leaving the physical meaning of the results very much open to interpretation. Inasmuch as the correlation is zero-lag, it is quite limited in what it can reveal about the signal relationship between distinct regions. Cross-spectrum analysis, on the other hand, utilizes the entire cross-correlation function in determining the coherence and phase relationship between signal pairs. And in the case of input and output signals in a linear system, it specifies the complete transfer function as a function of frequency.
That the interpretation in the case of the “stadium wave” is off the mark is evident from the undue emphasis that Wyatt places upon the connection of the Atlantic with the Arctic Ocean, its halocline and the production of sea-ice. But the cross-spectral coherence at multidecadal frequencies between the AMO and the Siberian Arctic littoral is only marginal, at best. Meanwhile there is quite strong coherence with temperatures around the South China Sea. It’s common meteorological knowlege that from there most of East Asia draws its air during the summer monsoon and to that region flows the cold Siberian air in winter.
Alas, physical reality is never a product of a computer program and should not be left to the vagaries of imaginative academic interpretation.
Rob Ellison | July 16, 2014 at 3:20 am |
I think I am drowning here trying to grasp the idea. It’s not like an ocean wave. Looking here:
I am picturing 4 trillion oscillators spread across the globe like network nodes with say 12 major index nodes. The 12 majors have to communicate somehow with each other. It seems they’d use the 4 trillion oscillators to do that. Say the AMO controls the PDO which is another subject but assume that it does. That node has to work on the PDO node for about 30 years before it flips it. The AMO is slowly changing the atmosphere, oceans and ice to do that. I think it may do that by using adjacent oscillators, a long train of them, patiently sending information perhaps as temperature. And this train would in some cases be broad as opposed to narrow. It would have to traverse the distance to the PDO and change it enough. Maybe what changes is the local sea ice or the salinity, or local ocean temperatures. This train would at times be linear but not necessarily direct. This train would seem to have to change what it drove through to get to the PDO, one oscillator at a time.
John S. | July 12, 2014 at 5:25 pm |
Peaks and troughs of the AMO combined with PDO sign changes seem to line up well with GAT regime changes:
So are you saying the Siberian sea ice isn’t coherent? Have you tried lagging it behind the AMO? Rather than there being a week connection between North Atlantic SSTs and sea ice, it see it as the perfect one. Somehow warm cools. That’s the way to make a water planet.
The strength of the North Atlantic might described as the Gulf Stream which makes winters bearable for so many people. A signal originating at the equator telling the sea ice what to do.
Cross-spectral coherence is totally independent of phase relationship. All my references to it concern multidecadal temperature variations in various regions. FYI, they are only a relatively minor component in the Siberian Arctic power spectra, but are the major one on a global station basis. Try as you might to give credence to a handwaving idea, the empirical evidence says otherwise.
I should quit while I am behind. I have a long way to go in understanding network signal propagation.
“The westward propagation of sea surface temperature (SST) anomalies is one of the main characteristics of one of the theories of the Atlantic Multidecadal Oscillation.”
“In this mechanism, the basin-crossing time of the SST anomalies sets the timescale of variability and, based on the observations, it was argued to be 20–30 years [Frankcombe et al., 2010].”
“Indications for westward propagation were found in observed subsurface temperature fields…”
Here’s Tsonis & Roebber:
“A detailed investigation of the coupling architecture of this network reveals that the overall dynamics emerge from the interaction of two interweaved subnetworks.”
Weaved. A broad connection. A weave can be strong because of many small scale connections. Often the point of weaving is stability and strength. I don’t know what they really meant, but I don’t think the backbone carrier is a narrow tunnel.
To come at the stadium wave from yet another direction we have geographic memory. The least amount of memory would be air temperatures. Then we’d have sea ice and ocean temperatures as showing longer term memories. Low northern sea ice amounts would be the earth remembering it’s been hot for awhile. It’s an average of the recent past. This long past time frame would be driving a current result of cooling by removing sea ice insulation. The Gulf Stream that transports heat northwards also could have a memory. Telling the Arctic sea ice how things are down south, and telling the ice what to do.
John S. | July 14, 2014 at 7:32 pm |
…what are the physical rules that govern the architecture of Wyatt’s “synchronized network of geophysical indices…
I am still trying to figure this one out. On page 51 of their paper there’s a map with numbered regions. Region 1 is near Greenland and 6 is near Northern Alaska. As I read it the ice extent or melting ice advances as such: Regions 1-3, 3-6 then 4-6. It’s West to East and covers about half the globe. It’s an extremely slow moving physical wave of sea ice varying in thickness and surface area. Why is the sea ice a good medium for a physical wave? It has mass and resilience. It stores information about past conditions. It has impact as it’s insulation and albedo. It is moldable like clay. If the question is, give me something I can use to make something that matters, the answer is sea ice. Some material that works on these timescales.
I had another thought. The Arctic is going to warm the most. Yes, because that’s where Ghia put a heat radiator. The system is working as intended.
As I mentioned elsewhere on this thread, CRUTEM4, detrended the same way, a global land signal, precedes the AMO by about a decade. This indicates a global driver that is external forcing. When the land leads the ocean, it is external forcing that does it. The likeliest causes are undetrended parts of the growing CO2 signal, the sun, and aerosol changes, which can account for the various parts of this “oscillation”.
When you proceed from nonsense anything after that is nonsense.
Rob, I don’t think John S said it was nonsense, but he had a hard time following the sequence of events, which I think is an understandable attitude for the stadium wave because it is not explained.
Lags it (reversed) by about 5 decades. And the AMO reversal lags by about 6. That doesn’t mean it’s a “driver”.
And as for “a global driver”, that’s nonsense. That “global” signal is made up of a bunch of more localized signals. Have you demonstrated that there isn’t one (or aren’t several, for that matter) actually causing the relevant “global” signal?
Your explanation of land temps is utter nonsense. Your juvenile contretemps notwithstanding.
Theory – btw – exists to explain data and not the other way around.
AK, given the relative areas, CRUTEM4 is a much larger signal than AMO, which is a muted echo of it. You want the AMO signal to hide for 5 decades and then come out in amplified form over the land. Have at it. Good luck finding a mechanism for that. You are trying to run the engine backwards, and are getting a grinding sound.
Land/ocean temperature divergence is the result of changing water availability over land and resultant shifts in the balance of latent and sensible heat at the surface.
The surface temps are more clearly aligned with the Pacific stage of the stadium wave. Isn’t that obvious?
OK, here is CRUTEM4 leading the AMO that I showed before.
AK, wants it to be a 50-year lag rather than a 10-year lead. You can see how that is patently not what is happening if you look at he recent land warming, which AK would blame on the AMO circa 1950.
A perfect example of an obsolete paradigm from an obsolete mind. The sort that would have pooh-pooh’ed plate tectonics in the early ’70’s.
And it hasn’t really been hiding, it shows up as, wait for it, the Stadium Wave!
Actually, I think I should have said a 20-year lag. But when there’s a cyclical process, whether you’re talking about a lag from the most recent phase, or a reversed lag from the even more recent anti-phase doesn’t really matter. I don’t think.
AK, you may notice that they haven’t ruled out that the stadium wave is externally forced.
Not ruled it out, but certainly hypothesized a “wraparound” or delayed feedback that would have made external forcing unnecessary. See Marcia’s reply to my comment here.
In the first paragraph, what do you mean by:
“.. the value of this distinction more readily apparent.”
Thanks for an excellent article.
This is an excellent post. It reads well. The stadium wave hypotheses seem very reasonable to me without understanding any of the statistics involved. Thank you.
Would you be able to comment on the possible ‘cycles’ of warming and cooling displayed in the paleo record of climate in Ireland from 16,000 years ago until present (see figure 15.21, p391 here: http://eprints.nuim.ie/1983/1/McCarron.pdf )
Coxon and McCarron (2009), ‘Cenozoic: Tertiary and Quaternary
(until 11,700 years before 2000)’
I interpret this and other figures as follows:
1. Very rapid warmings occurred in the past before human GHG emissions; in fact, the climate as recorded in paleo data in Ireland, Greenland and Iceland, warmed from near glacial temperatures to near current temperatures in two events in 7 years and 9 years at 14,500 and 11,500 years ago respectively.
2. Life thrived during the warming events (Life loved warming and warmer conditions).
3. There is a periodicity of about 500 to 1000 years represented by minimums at about (eyeballed from the chart):
years before present:
Dr. Wyatt, are you able to comment on whether or not these apparent cycles may be due to stadum waves over longer periods than you have investigated so far. Can you make any comments on them (I accept you haven’t done any analysis on them yet, so just seeking your preliminary thoughts on them).
As a retired structural engineer and programmer, I find the stadium wave arguments very interesting. In conclusion Wyatt noted “Thus, over long timescales, it is hypothesized that ocean, ice, and atmospheric systems across the Northern Hemisphere organize into synchronized (matched rhythms) network behavior.” Several replies have expanded on possible examples of such behavior.
To me it is helpful to make a comparison to the “beat frequency” phenomenon which one may experience on a twin engine aircraft or boat whenever the engines are not properly synchronized. The system presents a powerful cyclical vibration/noise of low frequency which is equal to or a multiple of the difference in engine rotational frequencies. Meanwhile each engine has many components contributing vibrations at other frequencies which may or may not create other patterns of cancellation/augmentation, which could potentially add/subtract periodically to any given beat frequency, to the point that divergence could occur in certain situations.
It would seem that the Earth’s climate picture presents a pattern with similar characteristics ( with the possibility of divergence depreciated by a few billion years of operational experience) If so, then the initial presumption that “For the stadium wave, only a time scale of between 55 and 70 years emerged as being shared by all network members” is perhaps a starting point which limits the search for all possibilities. Of course, it is often an adequate beginning to only examine the obvious patterns, but there are famous cases of structural surprises which resulted from failure to go a step or two further, especially in the case of highly dynamic systems.
Excellent comment. Thank you.
e.g. Tarcoma Narrows suspension bridge failure due to harmonic response to wind.
To expand/clarify(?) on my post above….
Just as a mind game, suppose that there is an energy oscillation between northern and southern hemispheres. Suppose also that there are various periodic processes in each hemisphere which create a beat frequency in each hemisphere with slightly different frequencies. At times these NH and SH oscillations would cancel each other and dampen the primary NH/SH oscillation. At other times they would align so as to amplify the NH/SH oscillation. An exaggerated NH/SH oscillation could induce increased winter landmass snow coverage and alter albedo, leading to a baseline energy reduction over time superimposed on the oscillation. A minimized NH/SH oscillation might do the opposite.
Just a mind game.
In your mind, is the oscillation between North and South have a large bounce and a minor bounce, with the major flip seemingly related to the reversal of the sun’s magnetic poles??
That’s what it looks like on gravity anomaly maps.
I was simply throwing out the simplest and most generic possible example to remind that two or more functions which have slightly different natural frequencies could interact in a way which may then drive another function in non-obvious ways. If only harmonic frequencies are considered, then one could still overlook meaningful periodic variations in the driving force.
I was working with you, not against you. suggesting gravity as “a” driver.
Sorry.. I did not mean that to sound as defensive as it came across! My earlier posts were offered as generalized thought provocation . Maybe they could help examine gravity as a driver, maybe not. I would defer to your knowledge in that field.
limitations of text. no tone. no hand gestures.
no worries. :-)
and me neither.
and I believe so. looking for the ties that bind it – movement of things – to climate, in synch, so it becomes obvious, and irrefutable.
the search continues.
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