New paper finds the climate to be ‘highly nonlinear’

But, we already knew that from experience. However, a lot of models still treat climate as a mostly or near linear process, and that’s why they aren’t performing particularly well at even predicting the present.

(via the Hockeyschtick) A paper published July in Science says “the climate system can be highly nonlinear, meaning that small changes in one part can lead to much larger changes elsewhere.”

“Some proposed mechanisms for transmission of major climate change events between the North Pacific and North Atlantic predict opposing patterns of variations; others suggest synchronization. Resolving this conflict has implications for regulation of poleward heat transport and global climate change.”

“When the climates of the more local high-latitude Pacific and Atlantic sectors varied in parallel, large, abrupt climate fluctuations occurred on a more global scale.”

One of many examples would be the interactions of the Pacific Decadal Oscillation [PDO] and the Atlantic Multidecadal Oscillation [AMO], which are sometimes aligned in the same positive phase to produce abrupt global warming, sometimes aligned in the same negative phase to produce abrupt global cooling, and sometimes in opposite phases which “cancel” their net global effect.

Systems which are “highly nonlinear” and chaotic are extremely difficult to impossible to predict or model. The projections of current climate models show that the models really boil down to just a simplistic 1:1 linear function of CO2 levels:

Needless to say, modeling the “highly nonlinear” and chaotic global climate system using a linear function of a single independent variable – CO2 – is nonsense and an essentially worthless exercise. Damaging the entire global economy and basing policy decisions upon such models is pure insanity.

From the AAAS Journal: http://www.sciencemag.org/content/345/6195/444.short

Science 25 July 2014: Vol. 345 no. 6195 pp. 444-448 DOI: 10.1126/science.1252000

Abstract:

Some proposed mechanisms for transmission of major climate change events between the North Pacific and North Atlantic predict opposing patterns of variations; others suggest synchronization. Resolving this conflict has implications for regulation of poleward heat transport and global climate change. New multidecadal-resolution foraminiferal oxygen isotope records from the Gulf of Alaska (GOA) reveal sudden shifts between intervals of synchroneity and asynchroneity with the North Greenland Ice Core Project (NGRIP) δ18O record over the past 18,000 years. Synchronization of these regions occurred 15,500 to 11,000 years ago, just prior to and throughout the most abrupt climate transitions of the last 20,000 years, suggesting that dynamic coupling of North Pacific and North Atlantic climates may lead to critical transitions in Earth’s climate system.


 

Editor’s Summary:

Climates conspire together to make big changes

The regional climates of the North Pacific and North Atlantic fluttered between synchrony and asynchrony during the last deglaciation, with correspondingly more and less intense effects on the rest of the world, researchers have found. The climate system can be highly nonlinear, meaning that small changes in one part can lead to much larger changes elsewhere. This type of behavior is especially evident during transitions from glacial to interglacial conditions, when climate is affected by a wide variety of time-varying influences and is relatively unstable. Praetorius and Mix present a record of North Pacific climate over the past 18,000 years. When the climates of the more local high-latitude Pacific and Atlantic sectors varied in parallel, large, abrupt climate fluctuations occurred on a more global scale.

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86 thoughts on “New paper finds the climate to be ‘highly nonlinear’

  1. “But, we already knew that from experience. However, a lot of models still treat climate as a mostly or near linear process, and that’s why they aren’t performing particularly well at even predicting the present.”

    Care needs to be taken not confound two different things. Some individual climate phenomena are highly non-linear ( like tropical storms which have strong internal positive feedbacks ) . That does not prevent the cumulative regional effect of TS on SST being a negative , probably roughly linear feedback.

    IMO that is not the principal reason why computer models are near useless at present.

  2. Non-linear. So the theory that just adding CO₂ increases global temps may not be correct after all. Who knew?

  3. The main reason models are not working is that the whole venture was set out to ‘prove’ a foregone conclusion and data have been ‘corrected’ to fall into line with that worldview.

    None of this has anything to do with science and has wasted most of the effort and resources of the last 30 years.

    Volcanic effects have been grossly mis-calculated and misinterpreted. Beyond the initial surface cooling that lasts just a few years, there is an opposite and more durable effect. This is most clearly seen in the stratosphere, where there is a lot less climate “noise”:

    https://climategrog.wordpress.com/wp-admin/upload.php?item=902

    Stratosphere cools after major eruptions and stays cooler. Follow links in the text for how this relates to surface warming.

  4. North Atlantic indices also display so called ‘non-stationary’ correlation, ie the ‘time domain’ is stretched and squeezed by number of years (mind boggles!). When that is taken into account then the related parameters ( here atmospheric pressure and SST ) can be brought into a linear (time domain) correlation.

  5. The initial cooling of volcanic forcing as estimated from atmospheric optical density measurements has been ‘adjusted’ to fit model output:

    http://climategrog.wordpress.com/?attachment_id=884

    The original Lacis et al paper ( on which Hansen was a co-author ) did an estimation based on atmospheric physics and observational data most from El Chichon eruption. They scaled AOD by 33 W/m2

    A few years later the same team changed this to 21 W/m2 in order to better agree with model output

    The correct scientific approach would have been to reduce the sensitivity of the model to agree with the data.

    This would avoid the excessive warming post 2000 which failed to materialise.

    I really don’t think the major problems are to do with non linearity.

  6. I would have thought this kind of paper with its conclusion would have come out several decades ago and every “climate 101″ class would have referenced it. It is all so self evident I am befuddled. Maybe it will be the basis for a new generation of “excuse” papers for the pause. I am just a rookie having followed the issue closely for only 6 years or so, but the developments over that period certainly confirm a lot more of the skeptics view than the warmists view. This “non-linear” concept was about the first thing I learned from reading comments by skeptics.

  7. So the paper says
    “the climate system can be highly nonlinear, meaning that small changes in one part can lead to much larger changes elsewhere.”
    Of course, they could also have written “the climate system can be highly nonlinear, meaning changes can be self-correcting” but for some reason they chose not to.

  8. You mean systems with multiple variables, complex and interacting susbsystems with numerous oscillating and resonating elements and which can include both positive and negative feedbacks related to a parameter and rates of change of parameters might be NON LINEAR?????

    OMG, my paradigm just shifted. Where’s my mommy?

  9. The HockeyShtick writes: “One of many examples would be the interactions of the Pacific Decadal Oscillation [PDO] and the Atlantic Multidecadal Oscillation [AMO]…”

    If the use of the PDO is a referral to the PDO data available through the JISAO website, there is no mechanism through which the PDO (the spatial pattern of the sea surface temperature anomalies of the extratropical North Pacific) alters global surface temperatures since the PDO does not represent the surface temperatures of that region in the North Pacific. The PDO only represents the spatial pattern. For further info see:

    http://bobtisdale.wordpress.com/2014/04/20/the-201415-el-nino-part-5-the-relationship-between-the-pdo-and-enso/

    If the use of the PDO in the article is a reference to the multidecadal variations in the sea surface temperatures of the North Pacific, which do run in and out of phase with those of the North Atlantic…

    http://bobtisdale.wordpress.com/2013/05/14/multidecadal-variations-and-sea-surface-temperature-reconstructions/

    …then the variations in the North Pacific do contribute to or suppress global warming, like the AMO. But the use of the PDO that way adds unnecessary confusion to those new to the topic.

  10. Greg

    Nonlinear does not just mean the relationship between parameters a and b is not a straight line. It is much more than that. At the heart of what it means for climate is this:

    http://journals.ametsoc.org/doi/abs/10.1175/1520-0469%281963%29020%3C0130%3ADNF%3E2.0.CO%3B2

    DNF 63 is in my view the starting point of meaningful climate science. It showed, by one of tbe very first and still probably the most important climate computer simulation, that a simple model of climate with just a handful of inputs, displaying nonlinear chaotic dynamics, as it evolved will fluctuate in a complex manner with no change to its external parameters .

    Reflection on the significance of DNF63 by Lorenz will show how deeply problematic the term “forcing” is in climate science. It will reveal that for any climate change, the null hypothesis is that the climate has changed itself without the need of any external forcing.

  11. ” Assessing bias corrections in historical sea surface temperature using a climate model, Folland”
    ftp://ftp.wmo.int/Documents/PublicWeb/amp/mmop/documents/JCOMM-TR/J-TR-13-Marine-Climatology/REV1/joc1171.pdf

    “The tests are important because SST corrections considerably affect estimates of the magnitude of global warming since the late 19th century. ”

    ” Over Australia, the model may have reconstructed LSAT changes using bias-corrected GISST with greater accuracy than the observations before about 1910.”

    So feeding ‘corrected’ SST into an atmospheric model does not agree with observations, but that “may” mean that the observations are wrong and the corrections and model have “greater accuracy”.

    … or maybe not.

    And this is what passes as “validation” of the bias corrections to SST. We are long way from worrying about non-linearities in the system. The whole game is being rigged to fit their preconceptions.

  12. I thought the IPCC already stated in it’s many reports that climate was a complex, non-linear, chaotic system? Doesn’t it seem that this paper is redundant?

  13. So, you type in at one end, “show a rise in temperature for added CO2!”, & out the business end you get, “temperature increase if more CO2 added!”, it must therefore be right!!! Wow, what great deductive reasoning.

    phlogiston says:
    July 25, 2014 at 3:34 am
    New study finds the Pope to be Catholic.

    Does the Pope know? Was this the result of a model?

  14. Thanks phlogiston, it’s worth keeping in mind the way a deterministic but ‘chaotic’ system behaves. Lorentzian attractors may be a good explanation for the irregular flips between glacial and inter-glacial, as well as other smaller scale glitches like the Pacific climate shift around 1976.

    Even something as trivial as “random walk” can produce time series that are very similar looking to some climate data.

    However, there a certain things that can be seen to have a direct physical cause that it does not need chaos theory to explain.

    http://climategrog.wordpress.com/?attachment_id=902

  15. dccowboy says: “I thought the IPCC already stated in it’s many reports that climate was a complex, non-linear, chaotic system? Doesn’t it seem that this paper is redundant?”

    They put that is thier 2001 report that climate was chaotic and could be predicted… and this did. They’ve gone a bit quiet on that aspect since.

  16. phlogiston says:
    July 25, 2014 at 4:07 am

    Habibullo Abdussamatov has identified 2014 as the first year cooling will be identifiable. Last year he was more tentative. This year he is definite. Visit this page

    http://www.oarval.org/ClimateChangeBW.htm

    And look for this image:

    “Figure 1. Variations of both the TSI and solar activity in 1978-2013 and prognoses of these variations to cycles 24-27 until 2045. The arrow indicates the beginning of the new Little Ice Age epoch after the maximum of cycle 24.”

  17. “Before it is safe to attribute a global warming or a global cooling effect to any other factor (CO2 in particular) it is necessary to disentangle the simultaneous overlapping positive and negative effects of solar variation, PDO/ENSO and the other oceanic cycles. Sometimes they work in unison, sometimes they work against each other and until a formula has been developed to work in a majority of situations all our guesses about climate change must come to nought.”

    from here:

    http://www.newclimatemodel.com/the-real-link-between-solar-energy-ocean-cycles-and-global-temperature/

    May 21, 2008

    Note that I agree with Bob Tisdale who points out that instead of referring to PDO in this context we should really refer to the Pacific Multidecadal Oscillation (PMO)

  18. M Simon says:
    Volcanic activity also seems to correlate with solar activity in the latest interglacial:

    That’s not a “correlation” , it’s a picture !

    If you have evidence of a correlation please post it, not crappy hand made graphics which actually show nothing and can be read however you want to read them.

  19. Anthony Watts
    Posted on July 25, 2014:

    Systems which are “highly nonlinear” and chaotic are extremely difficult to impossible to predict or model.

    Needless to say, modeling the “highly nonlinear” and chaotic global climate system using a linear function of a single independent variable – CO2 – is nonsense and an essentially worthless exercise.
    —————–

    Right you are, …. and one would have no better success with the impossible task of modeling the “highly nonlinear” and chaotic path of a single (1) Pachinko “ball”, …. to wit:

    A pachinko machine resembles a vertical pinball machine, but has no flippers and uses a large number of small balls. The player fires balls into the machine, which then cascade down through a dense forest of pins.

    http://en.wikipedia.org/wiki/Pachinko

    ——————-

    Thus, it really was/is, …. “pure insanity”, …. if their original intent was to create realistic and/or accurate computer modeling software for predicting future climate conditions.

    Me thinks that Willis E’s “emergent phenomenon” are akin to having ….. dozens of bugs n’ viruses …… scattered throughout the software code of said computer model.

  20. Bob Tisdale:
    “If the use of the PDO is a referral to the PDO data available through the JISAO website, there is no mechanism through which the PDO (the spatial pattern of the sea surface temperature anomalies of the extratropical North Pacific) alters global surface temperatures since the PDO does not represent the surface temperatures of that region in the North Pacific. The PDO only represents the spatial pattern. ”

    Oh, here we go again.

    PDO is a time series. One value for each date so it is not a “spacial pattern” since it contains no spacial data. It is time and temperature data only.

    A map of correlations with PDO is a spacial but NOT a time series. Neither is it a particularly constant map when calculated at different dates, so that would be a variable spacial pattern. Again that is quite distinct from PDO being a spacial pattern.

    In the sense that it is temperature difference ( SST of a geographic area of N.Pacific minus global average ) , some care is needed in inferring what physical effects it may have.

    Since there are a large (variable) areas that appear to correlate ( or anti-correlate ) with PDO, It is probably more sensible to regard it as a symptom rather than a cause. As an ‘index’ of something else that does have global scale impact on temperatures but not necessarily in the same direction in different places. .

  21. Peculiar curve, normally for each ppm CO2 increment the temperature increase should be smaller, especially in the tropics. At higher latitude there should be one which is straight, in the polar regions the temperature increase would be progressive. But overall, because of the surface areas, the effect
    should show an initial steep rise and a gradual decrease in slope and finally approaching an asymptotic value at high CO2 concentrations.
    Can somebody explain me if I am correct??!

  22. Highly nonlinear systems that stay in stable state for 1000s of years? If it is nonlinear, then it must be slammed at a rail.

    We must get either weather “like this” weather “like ice age”, rendering runaway global warming about impossible if it hasn’t been seen in 1 billion years.

  23. ““But, we already knew that from experience. However, a lot of models still treat climate as a mostly or near linear process, and that’s why they aren’t performing particularly well at even predicting the present.”

    Care needs to be taken not confound two different things. Some individual climate phenomena are highly non-linear ( like tropical storms which have strong internal positive feedbacks ) . That does not prevent the cumulative regional effect of TS on SST being a negative , probably roughly linear feedback.

    IMO that is not the principal reason why computer models are near useless at present.”

    #############################
    Yes when the story starts with a declarations of why models dont work I’m relatively sure that whoever wrote it is stupid.

  24. Highly nonlinear systems that stay in stable state for 1000s of years? If it is nonlinear, then it must be slammed at a rail.

    Chaotic systems typically have islands of stability. Look at bifurcation diagrams. Chaos can be, and usually is, bounded.

    And of course if you zoom out far enough things look smoother.

  25. AndyL says:
    July 25, 2014 at 3:49 am

    So the paper says
    “the climate system can be highly nonlinear, meaning that small changes in one part can lead to much larger changes elsewhere.”
    Of course, they could also have written “the climate system can be highly nonlinear, meaning changes can be self-correcting” but for some reason they chose not to.
    ====

    Indeed, it is easy to arrive at some sort of scientific fatalism, that we cannot make any predictions about climate nor make any attributions.

    Drawing vague correlations over century long time series with huge measurement uncertainties, sampling bias, and “bias correction” bias , this may be the case.

    However, attributions derived from short term variations drawn from recent higher quality data are less prone to this problem. That I what I have linked to above.

  26. M Seward says:
    July 25, 2014 at 3:56 am
    You mean systems with multiple variables, complex and interacting susbsystems with numerous oscillating and resonating elements and which can include both positive and negative feedbacks related to a parameter and rates of change of parameters might be NON LINEAR?????

    Equally a very simple system can be non-linear,e.g. the Lotka-Volterra system is just two equations and two variables. However a very complex system of chemical kinetic equations with non-linear terms can also be very predictable.

  27. Kevin, “chaos” in mathematics does not mean the same thing as in common language, ie total disorder. The Lorentz attractor, that I mentioned above shows a behaviour that may well apply to the glacial / inter-glacial pattern or geologically ‘recent’ climate.

    http://en.wikipedia.org/wiki/Lorenz_system

    It’s is totally deterministic, generated by differential equations, no random numbers being added.

  28. Greg Goodman says:

    More importantly, climate is not only non-linear it is also non-predictable since there are many causal variables in the mix which are themselves not predictable with current technology and may never be predictable, though never is a long time. When, and with what strength, some of these variables come into play can determine the end result of climatic conditions. Some of these variables are not even quantified, like total heat added to the oceans by under sea volcanic activity at any given time. Much of the “scientific” analysis broadcast, both pro and con climate change or global warming or whatever the hell it is presently called, is swinging at mosquitoes with statistical sledge hammers and of little meaning or consequence beyond the harm done to our world economy by politicians using such to redistribute income..

  29. Mark twain springs to mind.
    Endless speculations from such small facts.
    Climatology is the speculation of linear trends from cyclic and chaotic weather patterns.
    Or non patterns. As in “seeing information in white noise.
    The value of these linear trends was demonstrated by the tides; “If the tide continues to rise at its incoming rate, the world will be submerged by Next Easter.”
    (Some conditions may apply).
    Bottom line, the data does not support the speculation.
    The obsessive fascination, with picking authoritive linear trends from a sine wave, on the part of Climatology is amazing.

  30. From Greg Goodman on July 25, 2014 at 6:21 am

    Oh, here we go again.

    PDO is a time series. One value for each date so it is not a “spacial pattern” since it contains no spacial data. It is time and temperature data only.

    How breathtakingly ignorant of you.

    http://www.ncdc.noaa.gov/teleconnections/pdo.php

    In parallel with the ENSO phenomenon, the extreme phases of the PDO have been classified as being either warm or cool, as defined by ocean temperature anomalies in the northeast and tropical Pacific Ocean. When SSTs are anomalously cool in the interior North Pacific and warm along the Pacific Coast, and when sea level pressures are below average over the North Pacific, the PDO has a positive value. When the climate anomaly patterns are reversed, with warm SST anomalies in the interior and cool SST anomalies along the North American coast, or above average sea level pressures over the North Pacific, the PDO has a negative value (Courtesy of Mantua, 1999).

    It’s what happens where that determines the PDO Index. When the PDO is positive that indicates warm SST’s along the Pacific Coast. As seen, the spatial data is there.

    And learn how to stick to normal expected spellings. “Spacial” may be a variant spelling of spatial, but then bitzes is also a variant. Stop the madness!

  31. The initial state of the global climate.
    a. how close or far away is the global climate to glacial conditions if in inter- glacial, or how close is the earth to inter- glacial conditions if in a glacial condition.
    b. climate was closer to the threshold level between glacial and inter- glacial 20,000 -10,000 years ago. This is why I think the climate was more unstable then. Example solar variability and all items would be able to pull the climate EASIER from one regime to another when the state of the climate was closer to the inter glacial/glacial dividing line, or threshold.

    The upshot being GIVEN solar variability is not going to have the same given climatic impact.
    .
    . Solar variability and the associated primary and secondary effects. Lag times, degree of magnitude change and duration of those changes must be taken into account.

    Up shot being a given grand solar minimum period is not always going to have the same climatic impact.

    This is why solar/climate correlations are hard to come by UNLESS the state of solar activity goes from a very active state to a very prolonged quiet state which is what has happened during year 2005.

  32. This (in the above)does not just apply to solar but all of the items that influence the climate. Thresholds are also out there and this is why in large part a model approach to predicting climate change is an exercise in futility. Past historical data is much more reliable for my money.

    Not to mention incomplete and inaccurate data and different sets of data form the same items.

  33. What we are all doing here is coming up with reasons( lunar included) that probably are all playing a role in the climate. I think noise in the climate system makes it exceptionally hard to see the reasons we claim that effect the climate are so. In addition to noise the climate system often will have factors going on at the same time which are trying to throw the climate in a different direction and some of these factors at times exert a bigger influence then at other times on the climate and sometimes some of these factors can bring the climate to a threshold which then really makes it next to impossible to see how the other factors are still influencing the climate.
    At the same time the given beginning state of the climate is constantly in flux which then either enhances or moderates all the factors that are playing a role in the climate.
    The end result is we have a discussion with many points of view.
    My best shot once again which I am sure some will agree with , disagree with or half way agree with.
    These four factors either combined or in some combination are responsible for all the climate changes on earth. If one agrees with this then one will also have to agree that global climate change is synchronous.

    MY FOUR FACTORS

    The initial state of the global climate.
    a. how close or far away is the global climate to glacial conditions if in inter- glacial, or how close is the earth to inter- glacial conditions if in a glacial condition.
    b. climate was closer to the threshold level between glacial and inter- glacial 20,000 -10,000 years ago. This is why I think the climate was more unstable then. Example solar variability and all items would be able to pull the climate EASIER from one regime to another when the state of the climate was closer to the inter glacial/glacial dividing line, or threshold.
    ..
    Solar variability and the associated primary and secondary effects. Lag times, degree of magnitude change and duration of those changes must be taken into account. I have come up with criteria . I will pass it along, why not in my next email.
    a. solar irradiance changes- linked to ocean heat content.
    b. cosmic ray changes- linked to clouds.
    c. volcanic activity- correlated to stratospheric warming changing which will impact the atmospheric circulation.
    d. UV light changes -correlated to ozone which then can be linked to atmospheric circulation changes.
    e. atmospheric changes – linked to ocean current changes including ENSO, and thermohaline circulation.
    f. atmospheric changes -linked also to albedo changes due to snow cover, cloud cover , and precipitation changes.
    g. thickness of thermosphere – which is linked to other levels of the atmosphere.

    Strength of the magnetic field of the earth. This can enhance or moderate changes associated with solar variability.
    a. weaker magnetic field can enhance cosmic rays and also cause them to be concentrated in lower latitudes where there is more moisture to work with to be more effective in cloud formation if magnetic poles wander south due to magnetic excursions in a weakening magnetic field overall.

    Milankovitch Cycles. Where the earth is at in relation to these cycles as far as how elliptic or not the orbit is, the tilt of the axis and precession.
    .a. less elliptic, less tilt, earth furthest from sun during N.H. summer — favor cooling.

    I feel what I have outlined for the most part is not being taken as a serious possible solution as to why the climate changes. Rather climate change is often trying to be tied with terrestrial changes and worse yet only ONE ITEM , such as CO2 or ENSO which is absurdity.
    Over time not one of these one item explanations stand up, they can not explain all of the various climatic changes to all the different degrees of magnitude and duration of time each one different from the previous one. Each one UNIQUE.
    .Examples would be the sudden start/end of the Oldest, Older and Younger Dryas dramatic climate shifts, the 8200 year ago cold period, and even the sudden start of the Little Ice Age following the Medieval Warm Period.
    .

  34. drgsrinivas says:
    July 25, 2014 at 4:40 am
    “Climate appears ‘nonlinear’ not because it is fundamentally nonlinear. The ‘observation’ that climate is nonlinear just proves our ignorance.”

    Nonsense. Nonlinear is not a term from sociology. It is clearly defined. A system is nonlinear when the superposition of two input frequencies does not lead to the superposition of those two frequencies at the output, but to something else. Well at least that would be one way of defining it.

  35. Eliza says:
    July 25, 2014 at 6:44 am
    /////////////////

    I guess it probably depends upon the weather up there over the next few weeks, but if it were to cross the 1979/2000 average, I bet there would be strong pressure brought upon MSM not to report on that: Antartic ice at a high, and Arctic ice above the 1979/2000 average both at the same time! And then perhaps a harsh NH winter, it could be interesting.

    As you rightly say, a close eye should be kept on this season’s recovery

    Stand ready to hear something about a sensor error, algorithm error etc..

  36. Eustace Cranch says:
    July 25, 2014 at 7:06 am
    ////////////////////

    But one problem is that we are zooming in.

    If you were to zoom out and put CO2 in the context of Earth’s history, or today’s temperatures in the context of Earth’s history (and on an absolute not anomaly basis), then of course the present bluster would be lost, because you would be hard pressed to see late 20th century change.

  37. Eliza says:
    July 25, 2014 at 6:44 am

    Keep a real close eye on this
    http://ocean.dmi.dk/arctic/icecover.uk.php It is possible that the AGW powers to be will insist that DMI close down or not post this graph. It really would be a major major blow to the whole AGW theory
    ======

    Yes, this is a little strange. Antarctic sea ice was showing a similar glitch, that was covered here a few days ago. I just did a data grab from NOAA and the NH is not showing the same glitch , contrary to what you pointed out at DMI.

    It seems someone thinks NH need correcting and SH not so much.

    If anyone has a data source for DMI grab a copy quick, and to a screen cap of their graph.

    Goal posts may be due for repositioning. ….

  38. richard verney says:
    July 25, 2014 at 9:31 am
    Eustace Cranch says:
    July 25, 2014 at 7:06 am
    ////////////////////
    But one problem is that we are zooming in.
    If you were to zoom out and put CO2 in the context of Earth’s history, or today’s temperatures in the context of Earth’s history
    >>>>>>>>>>>>>>>>>>>.

    Here is a real easy link to demonstrate the “zoom in” problem:

  39. Rolo says:
    July 25, 2014 at 7:25 am

    So, finally people got to read the Lorenz 1963 paper … ;) A little late, no ? …

    It is nice to see Lorenz mentioned. The potential irony is that the climate system maybe fully as simple to describe as the most optimistic “linear” modeler would want, and yet still be as impossible to forecast Lorentz shows. The systems that Lorentz and Mandelbrot discuss are fully determinant, yet the outcome of recursion is not predictable. I suspect that a number of quasi-cyclic patterns(e.g. PDO, AMO, ENSO) that have been identified conform to Lorenz’s Butterfly effect, and that a great deal of the debate about whether there are cycles or not would go away if more attention were given to that aspect of “highly nonlinear systems.”

  40. Steven Mosher:

    Your post at July 25, 2014 at 6:58 am says without explanation

    Yes when the story starts with a declarations of why models dont work I’m relatively sure that whoever wrote it is stupid.

    Your post provides an interesting coincidence.

    Yes when a post starts with a declaration that it is from Steven Mosher I’m relatively sure that whoever wrote it is stupid.

    Richard

  41. “Highly nonlinear” does not necessarily mean “not predictable”, at least to some level. The quantum mechanical equations of motion are ungodly complex and nonlinear for even a small arrangement of atoms. Yet, Newton’s laws describe the macro world quite well, as demonstrated by the theorem of Ehrenfest. The Langevin equation provides a specific, rigorous means of modeling macro behavior which changes only slowly with respect to micro relationships.

    I believe the climate system can be modeled. I just don’t believe they have the right equations.

  42. “Highly Non-Linear” systems can be very stable.

    Tipping Points are non-linear events and they have been part of the catastrophic AGW mime since day one.
    WAPO, June 23, 2008, James Hansen: Twenty Years Later

    Tipping Points are non-linear positive feedbacks or a breach into another domain of a strange attractor. But not all non-linear systems are dominated by positive feedback. Negative feedbacks can be linear or non-linear.
    Every electric motor, every internal combustion engine, even the pendulum of a clock depend upon non-linear feedbacks to function.

    Just looking at first (linear) principles, the period of a pendulum ought to be a function of the size of its swing, the bigger the swing, the longer the period. One of Galileo’s greatest discoveries was that the period is insensitive to the length of swing arc. The pendulum owes its stability to non-linear force dynamics.

  43. Mosh,

    Here is why models don’t work. It is very simple.

    X = 4*(1-X) where initial x is >0 and <1. Start with any number between .1 and .9. Now predict the 100th iteration within 1%. Without looking.

  44. M Simon says:
    July 25, 2014 at 10:47 am

    Or try this simple experiment. Start with .3000000 and .3000001 and tell me how far apart the the 100th iteration of those two numbers will be.

  45. A little more about the pendulum.
    Its constant period does indeed come from a largely linear system.
    Twice the displacement means twice the force means twice the acceleration.
    But not twice the velocity, or the kinetic energy at the bottom of the swing would exceed the potential energy at the end of the swing.

  46. @Steven Mosher 6:58 am
    Yes when the story starts with a declarations of why models dont work I’m relatively sure that whoever wrote it is stupid.

    What a breathtakingly stupid model you have created, Steven.

  47. richard verney says:
    July 25, 2014 at 9:25 am
    Eliza says:
    July 25, 2014 at 6:44 am
    /////////////////

    I guess it probably depends upon the weather up there over the next few weeks, but if it were to cross the 1979/2000 average, I bet there would be strong pressure brought upon MSM not to report on that: Antartic ice at a high, and Arctic ice above the 1979/2000 average both at the same time! And then perhaps a harsh NH winter, it could be interesting.

    As you rightly say, a close eye should be kept on this season’s recovery

    I wouldn’t worry about that too much. Current CT sea ice area=5.23, the average minimum=4.72,
    dropping about 0.08/day.

  48. Bart says:
    July 25, 2014 at 10:41 am
    “I believe the climate system can be modeled. I just don’t believe they have the right equations.”

    Long term predictions could only be potentially possible if Earth’s climate is dominantly controlled by outside systems – like the sun – and for some reason we learn to predict those controlling systems.

    Left to its own devices Earth’s weather and climate is chaotically oscillating, and the definition of chaos is that no model with finite resolution can predict the real chaotic system perfectly; the deviation of the states of the chaotic system and the simulation grows exponentially over time. This is the definition- there is no shortcut around it.

  49. Who knew ??

    Any time you have an “occasionally” (not necessarily periodically) measured property of say “the climate” ; or anything else for that matter, where you cannot predict, even the direction of movement, from your most recent measured value, to the next measured value you observe, then you have by definition, a “non-linear” function.

    So yes, I believe the climate is non linear.

  50. “””””…..Stephen Rasey says:

    July 25, 2014 at 10:43 am

    “Highly Non-Linear” systems can be very stable.
    …………………………………….
    Just looking at first (linear) principles, the period of a pendulum ought to be a function of the size of its swing, the bigger the swing, the longer the period. One of Galileo’s greatest discoveries was that the period is insensitive to the length of swing arc. The pendulum owes its stability to non-linear force dynamics…….””””””

    Not true at all. The period of a simple pendulum, is indeed a non-linear function of the amplitude of the swing.

    Constancy of the period, presumes the restoring force is exactly proportional to the displacement. (and sin(x) = (x) = tan (x) )

    d2x/dt^2) =-kx is the governing differential equation of simple harmonic motion. And (k) is a constant; and in this case is NOT Boltzmann’s constant.

    If the length of the pendulum is near infinite, then the period of oscillation is totally independent of the (near infinite) length .

    In fact the period is about 84 minutes, for any near infinite length.

    That also is the period calculated for a simple pendulum, whose length equals the radius of the (assumed uniform) earth.

    And the cognoscenti, will immediately recognize that the same 84 minute period, is the orbital period of an earth satellite orbiting at the surface, of an assumed airless planet.

    Gyro stabilized platforms suffer from a “hum” noise disturbance; well that hum has an 84 minute period.

    Well at least that was true, back in the days, when they actually taught you something in school.

  51. Courtney.
    If you or anyone else knows specifically why models don’t work then collect your Nobel prize.
    You don’t. The op doesn’t.
    And claims to knowledge require some proof.

  52. @george e. smith at 1:50 pm
    I don’t understand your objection.
    For the general case of a real pendulum, finite length much less than the radius of the earth, the equation of the pendumum is a highly non-linear harmonic equation, even without air resistance.
    But for the frictionless small-angle assumption, point mass, you can discount some of the non-linear terms, and determine the period T (sec) is approximately = 2*Pi()*sqrt(L/g), where L is the length (meters) of the pendumum and g is the accel of gravity, a value independent of the mass and the arc.

    It is a stable, non-linear system. Even in the small angle approximation, with some linear assumptions, it winds up as a non-linear stable harmonic system.

  53. “””””…..Stephen Rasey says:

    July 25, 2014 at 2:23 pm

    @george e. smith at 1:50 pm
    I don’t understand your objection……”””””

    Well Stephen, make up your mind.

    You offer the simple pendulum as an example of a “highly non-linear system”; just now repeated essentially; but you claim the period is NOT dependent on the swing amplitude; so presumably it is independent of that swing amplitude.

    But then you introduce the “small angle approximation” which in airlessness removes the system from the “highly non-linear” category, and makes it a “highly linear” system instead.

    The small angle approximation is not a highly non-linear system; which is the ONLY reason its period is amplitude independent (for small amplitudes)

    A straight SF-LA vacuum tube tunnel has the same 42 minute travel time (one way), as does a straight LA-NYC tunnel.

  54. Mosher:

    Your post at July 25, 2014 at 2:14 pm displays your usual ignorance, arrogance and stupidity when it says in total

    Courtney.
    If you or anyone else knows specifically why models don’t work then collect your Nobel prize.
    You don’t. The op doesn’t.
    And claims to knowledge require some proof.

    There are very many critically important faults with the models that are documented in the literature so there is no possibility of anyone getting a Nobel Prize for adding to the long list.

    Anyway, I choose to again state the specific reason why the models don’t work that I was first to determine and to publish. And I explain Kiehl’s important extension of it.

    None of the models – not one of them – could match the change in mean global temperature over the past century if it did not utilise a unique value of assumed cooling from aerosols. So, inputting actual values of the cooling effect (such as the determination by Penner et al.
    http://www.pnas.org/content/early/2011/07/25/1018526108.full.pdf?with-ds=yes )
    would make every climate model provide a mismatch of the global warming it hindcasts and the observed global warming for the twentieth century.

    This mismatch would occur because all the global climate models and energy balance models are known to provide indications which are based on
    1.
    the assumed degree of forcings resulting from human activity that produce warming
    and
    2.
    the assumed degree of anthropogenic aerosol cooling input to each model as a ‘fiddle factor’ to obtain agreement between past average global temperature and the model’s indications of average global temperature.

    More than a decade ago I published a peer-reviewed paper that showed the UK’s Hadley Centre general circulation model (GCM) could not model climate and only obtained agreement between past average global temperature and the model’s indications of average global temperature by forcing the agreement with an input of assumed anthropogenic aerosol cooling.

    The input of assumed anthropogenic aerosol cooling is needed because the model ‘ran hot’; i.e. it showed an amount and a rate of global warming which was greater than was observed over the twentieth century. This failure of the model was compensated by the input of assumed anthropogenic aerosol cooling.

    And my paper demonstrated that the assumption of aerosol effects being responsible for the model’s failure was incorrect.
    (ref. Courtney RS An assessment of validation experiments conducted on computer models of global climate using the general circulation model of the UK’s Hadley Centre Energy & Environment, Volume 10, Number 5, pp. 491-502, September 1999).

    More recently, in 2007, Kiehle published a paper that assessed 9 GCMs and two energy balance models.
    (ref. Kiehl JT,Twentieth century climate model response and climate sensitivity. GRL vol.. 34, L22710, doi:10.1029/2007GL031383, 2007).

    Kiehl found the same as my paper except that each model he assessed used a different aerosol ‘fix’ from every other model. This is because they all ‘run hot’ but they each ‘run hot’ to a different degree.

    He says in his paper:

    One curious aspect of this result is that it is also well known [Houghton et al., 2001] that the same models that agree in simulating the anomaly in surface air temperature differ significantly in their predicted climate sensitivity. The cited range in climate sensitivity from a wide collection of models is usually 1.5 to 4.5 deg C for a doubling of CO2, where most global climate models used for climate change studies vary by at least a factor of two in equilibrium sensitivity.

    The question is: if climate models differ by a factor of 2 to 3 in their climate sensitivity, how can they all simulate the global temperature record with a reasonable degree of accuracy.
    Kerr [2007] and S. E. Schwartz et al. (Quantifying climate change–too rosy a picture?, available at http://www.nature.com/reports/climatechange, 2007) recently pointed out the importance of understanding the answer to this question. Indeed, Kerr [2007] referred to the present work and the current paper provides the ‘‘widely circulated analysis’’ referred to by Kerr [2007]. This report investigates the most probable explanation for such an agreement. It uses published results from a wide variety of model simulations to understand this apparent paradox between model climate responses for the 20th century, but diverse climate model sensitivity.

    And, importantly, Kiehl’s paper says:

    These results explain to a large degree why models with such diverse climate sensitivities can all simulate the global anomaly in surface temperature. The magnitude of applied anthropogenic total forcing compensates for the model sensitivity.

    And the “magnitude of applied anthropogenic total forcing” is fixed in each model by the input value of aerosol forcing.

    Kiehl’s Figure 2 can be seen at

    Please note that the Figure is for 9 GCMs and 2 energy balance models, and its title is:

    Figure 2. Total anthropogenic forcing (Wm2) versus aerosol forcing (Wm2) from nine fully coupled climate models and two energy balance models used to simulate the 20th century.

    It shows that
    (a) each model uses a different value for “Total anthropogenic forcing” that is in the range 0.80 W/m^2 to 2.02 W/m^2
    but
    (b) each model is forced to agree with the rate of past warming by using a different value for “Aerosol forcing” that is in the range -1.42 W/m^2 to -0.60 W/m^2.

    In other words the models use values of “Total anthropogenic forcing” that differ by a factor of more than 2.5 and they are ‘adjusted’ by using values of assumed “Aerosol forcing” that differ by a factor of 2.4.

    So, each climate model emulates a different climate system. Hence, at most only one of them emulates the climate system of the real Earth because there is only one Earth. And the fact that they each ‘run hot’ unless fiddled by use of a completely arbitrary ‘aerosol cooling’ strongly suggests that none of them emulates the climate system of the real Earth.

    Richard

  55. Steven Mosher,

    The only thing that matters is if a model can reliably predict. If it can, it is a good model. If it can’t, it is worthless.

    Really, what else matters?

  56. Steven Mosher said:

    “If you or anyone else knows specifically why models don’t work then collect your Nobel prize.”

    The models do not acknowledge that the amount of conduction (and thus convection) within an atmosphere varies inversely with the radiative capability of the atmosphere.

    Leakage of energy to space by radiative means from within the atmosphere causes the amount of energy returned to the surface in convective descent to fall below the amount of energy removed from the surface in convective ascent.

    DWIR from radiative gases simply offsets the reduction in energy returned to the surface via convective descent and so DOES NOT add energy to the surface.

    Where do I collect my prize?

  57. Lorenz appears in this enlightening documentary from 1989:

    The experiment at 26:26 shows non-linear “tipping points” in a Taylor-Cuoette fluid flow system. The result is somewhat analogous to global air circulation, with zonal and meridional patterns emerging at different thresholds.
    The latests schizophrenic rant at the Aussie Con suggests that we are probably in a meridional cooling pattern:

    https://theconversation.com/the-pre-holocene-climate-is-returning-and-it-wont-be-fun-27742

  58. “Taylor Couette” is what I meant so say:
    =============
    “Taylor showed that when the angular velocity of the inner cylinder is increased above a certain threshold, Couette flow becomes unstable and a secondary steady state characterized by axisymmetric toroidal vortices, known as Taylor vortex flow, emerges. Subsequently increasing the angular speed of the cylinder the system undergoes a progression of instabilities which lead to states with greater spatio-temporal complexity, with the next state being called as wavy vortex flow. If the two cylinders rotate in opposite sense then spiral vortex flow arises. Beyond a certain Reynolds number there is the onset of turbulence.

    http://en.wikipedia.org/wiki/Taylor%E2%80%93Couette_flow

    ==================
    Wavy vortex flow over previously glaciated regions:

    https://www.google.com/search?hl=en&site=imghp&tbm=isch&source=hp&q=polar+vortex+2014

  59. Non-linear, chaos, the Lorenz attractor, quasi-stability, … Yet with our limited state knowledge and boundary conditions, even knowing when the next divergence will occur is Impossible… Until after it is apparent… Then human hindsight and reconciliation takes over. Climate states are non linear and state transitions are un predictable. Man induced CO2 concentrations are secondary to natural cycles that mask the CO2 signal change. Deal with it Climate Scientists. Predicting the next 60 years climate is about as dubious as calling for a day of rain in 2 months hence present.

  60. Steven Mosher says:
    July 25, 2014 at 2:14 pm
    “Courtney.
    If you or anyone else knows specifically why models don’t work then collect your Nobel prize.
    You don’t. The op doesn’t.
    And claims to knowledge require some proof.”

    Mosher. Your English Major shows. First, you should try to understand the DEFINITION of CHAOS.
    After that, it will become obvious to you that by that very definition it is impossible to predict a chaotic system with a simulation of limited precision over longer periods.
    This is not political science; it is mathematics.
    Read the paragraph here, it will show you that Chaos Theory is slapping you right in the face.

    http://en.wikipedia.org/wiki/Chaos_theory#Introduction

  61. If it’s non-linear, any predictability is an illusion. At first it’ll seduce you with the appearance of predictability, but as soon as it builds your huberis, it drifts away from preditability. Non-linear systems seem to act of their own capricious volition, but it’s not volition, it’s just the nature of the mathematics. Deterministic nonperiodic flow is the seminal work, “Chaos: Making a New Science” by James Gleick brings the concepts into the reach of us mere mortals.

  62. Bart says:
    July 25, 2014 at 10:41 am

    I believe the climate system can be modeled. I just don’t believe they have the right equations.
    ———————

    YUP, and I truly believe that next year’s Super Bowl game can be modeled ….. based on all the factual statistics of past NFL and Super Bowl games.

    And likewise, I just don’t believe they have the right equations to do said.

    Eritas

  63. Climate models ( all of them) does not matter if either solar based or co2 based will never be able to predict the climate because of limited inaccurate data, thresholds that exist and the non linearity of the climate system.

  64. I want to, temporarily, come to the defense of Climate Models in the realm of chaos. It is certainly true that atmospheric processes on a spinning night-day globe are highly non-linear and are so chaotic that they defy detailed predictions on afternoon thunderstorms to next weeks rainfall predictions. But given the chaos of weather, it does not necessarily follow that climate is chaotic.

    At the atomic and molecular level, the Brownian motion of particles is chaotic of Nobel Prize winning proportions. But at the macro scale, the Ideal Gas Law is anything but chaotic. Uncertainty in initial conditions do not doom future PV=nRT predictions.

    At the quantum mechanical level, the decay of any group of atoms in unpredictable, but at milligram sized sample the radioactivity can be predicted with high precision.

    The growth of a tree is a mind-boggling, multidimentional fractal exposition of cell growth in varieties we are barely able to enumerate. Yet, foresters can predict with reasonable error bars the board-feet per acre of wood they a company can expect to harvest twenty years hence.

    We might not be able to make weather predictions 3 years out. But we can certainly comfortably make predictions that it will snow in Breckenridge, Colorado, several times in the month of January 2017. Whether the winter of 2017 in Breckenridge will be a good ski season, average, or a bad ski season, the prediction that profits and plans depend upon, is a much tougher, possibly chaotic problem.

    So can macro models of physically chaotic processes make useful predictions within the uncertainty bounds that matter? For the ideal gas law, for radioactivity, for forestry harvests, for the opening of ski resorts, yes they can. They have been proven to make prediction upon which to justify investment decisions. These example have a history of predictions that show they are useful.

    But when it comes to climate models, they are increasingly found wanting in their long term predictions. The models own record betrays them. Whether or not the fault is chaotic process, there is something important missing (or mistakenly included) in the models.

  65. Stephen Rasey says:
    July 26, 2014 at 11:53 am

    Yet, foresters can predict with reasonable error bars the board-feet per acre of wood they a company can expect to harvest twenty years hence.
    —————-

    YUP, and the Ag-Tech’ers can predict with reasonable error bars the bushel per acre of corn that a company can expect to harvest at the end of each season’s planting.

    But if those companies depend upon Mother Nature to “seed” the crop they want to harvest ….. then they are in big trouble.
    =============

    But we can certainly comfortably make predictions that it will snow in Breckenridge, Colorado, several times in the month of January 2017.
    —————-

    YUP, but iffen it doesn’t snow sufficient amounts they have “snow-making” machines to CTA.
    =============

    But when it comes to climate models, ……. there is something important missing (or mistakenly included) in the models
    ————-

    YUP, there are several important things not included in the models, … but more importantly, …. they have included in their models their “junk science” claims about the “warming” affect of atmospheric CO2 ….. in order to prove that their calculated increase in temperatures agrees with the average yearly increase in CO2.

    It is utterly silly to pre-specify what a specific input data (CO2) will have on the output results of a “modeling” process …… if the “modeling” process was specifically designed to determine what effect, if any, said specific input data (CO2) will have on the output results.

    Me thinks one might call that …. “circular modeling”.

  66. Samuel C Cogar says:
    July 27, 2014 at 9:11 am
    ==========================================
    Hello, SamC, are you still hanging around the Vine? I couldn’t take it anymore there, but it was interesting for a time and it did lead me to here.

  67. @ goldminor says:

    And hello to you, too, goldminor.

    Yup, I’m still posting to the Vine. Its part of my daily entertainment, ya know.

    I keep verbally “beating” them down and there are only 2 or 3 of the lefty liberal “hardliners” still pushing their “junk science” agenda.

    It’s amazing how a little “common sense reasoning” will eventually get their “attention” and they realize their self administered embarrassment is not worth the effort.

  68. 1) – long term stability of patterns (Stephen Rasey was right):
    = = = = = = = = = = = = = = =
    The large-scale structure of the atmospheric circulation varies from year to year, but the basic climatological structure remains fairly constant. Individual weather systems – mid-latitude depressions, or tropical convective cells – occur “randomly”, and it is accepted that weather cannot be predicted beyond a fairly short limit: perhaps a month in theory, or (currently) about ten days in practice (see Chaos theory and Butterfly effect). Nonetheless, as the climate is the average of these systems and patterns – where and when they tend to occur again and again – it is stable over longer periods of time.

    http://en.wikipedia.org/wiki/Atmospheric_circulation

    = = = = = = = = = = = = = = =

    2) meridional vs zonal pattern – The Met:
    ===============
    Normally the jet stream runs fairly directly from west to east and pushes weather systems through quite quickly. However, sometimes the steering flow of the jet stream can meander (a bit like a river), curving north and south as it heads west across the Atlantic. This is called a meridional flow, with the more linear west to east flow being called a zonal flow.
    During a meridional flow areas of low pressure can become stuck over the UK leading to prolonged periods of rain and strong winds. [and ice and snow] During the winter the polar front jet stream moves further south leading to a greater risk of unsettled weather, and even snow if cold arctic air masses move south over the UK..

    http://www.metoffice.gov.uk/learning/learn-about-the-weather/how-weather-works/global-circulation-patterns

    ===============

    A year of real world circulation & precipitation:

    The moral of the story is this: if the Russian school of meteorology is correct, we have 30 years (approximately) of colder (on average) weather in store – on average. The UN FAO predicted meridional pattern for around 30 years starting approximately 2004 using the “Russian” pattern matching method. Looks like they got it right.

  69. One thing for pretty sure, …..“if the Russian school of meteorology is correct,”….. then a major socio-economic disaster is on the horizon.

    With the shutdown and/or phase out of coal-fired generating plants, then … “30 years (approximately) of colder (on average) weather in store” …. means there will surely be more cloudy skies, rain, freezing rain and snow …. which is not a good thing for the proper functioning of solar panels, wind turbines and/or the growing & harvesting of bio-fuel producing crops.

    And I have visions of those “wind turbine farms” ……. looking like a “tree farm” after a severe ice-storm did its dastardly deed of destruction.

    I’ll let some mathematician calculate the “added weight” on those 143 ft turbine blades if say ½” or more of ice freezes on their exterior surfaces.

  70. I’ll let some mathematician calculate the “added weight” on those 143 ft turbine blades if say ½” or more of ice freezes on their exterior surfaces.

    While you are at it, ask the mathematician what will happen as that 1/2 inch of ice partially melts and flies off three spinning turbine blades unevenly.

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