Climate Science Glossary

Term Lookup

Enter a term in the search box to find its definition.


Use the controls in the far right panel to increase or decrease the number of terms automatically displayed (or to completely turn that feature off).

Term Lookup


All IPCC definitions taken from Climate Change 2007: The Physical Science Basis. Working Group I Contribution to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, Annex I, Glossary, pp. 941-954. Cambridge University Press.

Home Arguments Software Resources Comments The Consensus Project Translations About Support

Bluesky Facebook LinkedIn Mastodon MeWe

Twitter YouTube RSS Posts RSS Comments Email Subscribe

Climate's changed before
It's the sun
It's not bad
There is no consensus
It's cooling
Models are unreliable
Temp record is unreliable
Animals and plants can adapt
It hasn't warmed since 1998
Antarctica is gaining ice
View All Arguments...

New? Register here
Forgot your password?

Latest Posts


Chaos theory and global warming: can climate be predicted?

What the science says...

Select a level... Basic Intermediate

Weather is chaotic because air is light, it has low friction and viscosity, it expands strongly when in contact with hot surfaces and it conducts heat poorly. Therefore weather is never in equilibrium and the wind always blows. The climate is mostly explained by equilibrium radiation physics, which puts the brakes on variations in global temperatures. Effects from weather, the Sun, volcanoes etc. currently only causes a small amount of chaotic behavior compared to the deterministic, predictable greenhouse gas forcing for the next 100 years"

Climate Myth...

Climate is chaotic and cannot be predicted

'Lorenz (1963), in the landmark paper that founded chaos theory, said that because the climate is a mathematically-chaotic object (a point which the UN's climate panel admits), accurate long-term prediction of the future evolution of the climate is not possible "by any method". At present, climate forecasts even as little as six weeks ahead can be diametrically the opposite of what actually occurs, even if the forecasts are limited to a small region of the planet.' (Christopher Monckton)

One skeptic claim is that if weather is chaotic, then surely the climate must also be chaotic because "climate, of course, is very-long-range weather". This view seems to logically render all skeptic non-human-causes of global warming worthless, since all predictions would be equally futile. As everybody knows, weather is both chaotic and strongly seasonal. Air temperatures undergo significant daily variations, at times varying unpredictably by more than 20°C in a given location within a few days. Climate indeed varies non-linearly, but this has not prevented scientists from making good predictions. Here, we peek into chaos and why climate is rather predictable over both decades and centuries

In 1963 Edward Lorenz was studying the patterns of rising warm air in the atmosphere. It was known at the time that air could start to move if it came into contact with a warm object. The properties of air are such that it expands a lot when heated, it is a good insulator and it flows with relative ease - technically speaking, it has a high Rayleigh number. Think of a large hot air mass in the atmosphere as rising like a hot air balloon in the shape of a mushroom cloud (!). Based on known hydrodynamics Lorenz derived a set of simplified equations for this movement and found something amazing. For certain values of the parameters, the overall movement of the atmospheric air was oscillating unpredictably (Lorenz 1963):

Lorenz equations, oscillation air patterns
Figure 1: The simplified Lorenz phase space equations of air convection (top) and some numerical solutions (below, separated for clarity).

A major concern was that for small changes in starting conditions the system would always have an unpredictable outcome. This was the discovery of deterministic chaos and we knew there and then that we would never know the weather more than 10 days ahead without using disproportionate computing power with very little pay-off. Naturally, scientists knew about chaos from studying turbulence, which is not both smooth (deterministic) and unpredictable.

When Lorenz looked closer at his graphs, something exciting happened. A peculiar regularity emerged when he plotted the curves against each other: they were attracted to something never leaving a boxed volume. It was strange, because it was not a simple shape, but rather an entire subspace of points strangely smeared into three dimensions.

Strange Attractor
Figure 2: The numerical solutions of Lorenz' equations plotted in the same coordinate system. The curves are functions of time, so imagine them as a roller coaster tracing an invisible object called a strange attractor.

Even stranger, the structure is occupying not just a two dimensional surface but something which is more than two dimensional and less than three dimensional: it is two-dimensional plus a fraction. It exists in a so called fractal dimension. It never truly intersects itself thus committing every trajectory to infinite solitude. The object was therefore aptly dubbed a strange attractor.

A closer look reveals where the unpredictability arises. The blue and the magenta curves are closely following each other for a time. Suddenly the magenta curve takes a wild hike and quickly finds itself far away from its companion curve. This is known as sensitivity to initial conditions, which is seen in everyday weather.

Demonstration of chaotic effect
Figure 3: Illustration of deterministic chaos. Imagine two systems started at slightly different initial conditions. They will follow each other closely for some time, but within a short time our ability to predict them breaks down (front and side view of the Lorenz attractor).

This is what skeptics claim must happen in climate as well. Beyond variations in the solar cycles, airborne particle numbers and volcanic eruptions, most variability in the climate is due to changes in heat transfer between the atmosphere and the oceans. Water has a smaller Rayleigh number than air making it hard to obtain fully developed chaos in ocean currents. However, oceanic climate indices (the heat transfer) can exhibit small-scale chaos as we shall see below.

Ocean cycles. North Atlantic Oscillation, East Atlantic pattern, West Pacific pattern
Figure 4: Ocean cycles. North Atlantic Oscillation (blue), East Atlantic pattern (green), West Pacific pattern (red) (NOAA)

Looking at three of the leading climate indices we recognize the same problem that Lorenz faced. Actually proving that these indices are chaotic is exceedingly difficult, but Tziperman et al. (1994) showed in a simple model how El Niño is likely a seasonally induced chaotic resonance between the ocean and the atmosphere. Therefore, the climate system as a whole does exhibit some inherent minor unpredictability (Hansen et al. 2007). However, even though the El Niño of 1998 was a whopping 10% of the total heat content anomaly since 1950, it passed quickly. The greenhouse effect, on the other hand, works throughout the period.

Returning to the temperature record (normalized to the period 1950-1980) we can now put names on things. Chaotic influences from oceans and volcanoes etc. makes both weather more unpredictable and creates the unpredictable part of the 'wiggles' around the average trend in climate. The climate is definitely non-linear, but also not chaotic in this plot.

GHCN & HADISST1 global temperature record + moving average performed with lowess filter
Figure 5: GHCN & HADISST1 global temperature record. The moving average is performed with a lowess filter.

On the timescale of decades, every planetary object has a mean temperature mainly given by the power of its star according to Stefan- Boltzmann’s law combined with the greenhouse effect. If the sources and sinks of CO2 were chaotic and could quickly release and sequester large fractions of gas perhaps the climate could be chaotic. If the Earth's orbit was affected by a moon of comparable mass to the planet itself, then the orbit and thus the Solar forcing could cause some amount of chaos in the climate. As it turns out the Moon is relatively small and actually stabilizes the rotation axis, which is considered a favorable condition for life on Earth.

To sum up, the weather is chaotic because it can run free, climate is on a leash. Pull the leash hard enough and the climate responds.

11-year moving average of global temperature with Lorenz attractor superimposed
Figure 6: Artistic rendering of the rising global temperatures carrying a small, slightly growing Lorenz attractor up along with it.

Guest post by Jacob Bock Axelsen
Jacob Bock Axelsen is MSc in biophysics and PhD in complexity studies, both from the Niels Bohr Institute, Copenhagen. He has worked twice as a visiting scientist in USA and subsequently as a postdoctoral fellow at the Weizmann Institute of Science. He is a contracted physicist at Centro de Astrobiologia in Madrid. His interest in climate science is purely non-professional.

Last updated on 4 November 2016 by Jacob Bock Axelsen. View Archives

Printable Version  |  Offline PDF Version  |  Link to this page

Argument Feedback

Please use this form to let us know about suggested updates to this rebuttal.


1  2  3  4  5  Next

Comments 1 to 25 out of 120:

  1. I suspect you have largely ignored variations in solar cycles on the earth's climate, whilst focussing on internal effects/variations of the earth's climate (El Nino, volcanoes etc). Increase radiation from the sun and you get non-linear chaotic effects on earth (references needed). The earth does not respond in a linear fashion to changes in the sun's output (references needed). You have assumed the sun/solar variations have a more or less peripheral/minor effect. They don't; any solar variation is hugely amplified on earth, and also, importantly, chaotically amplified (non linear response). Isn't it a bit like droppping a pebble into an already turbulent stream; the external influence is not only amplified, it creates even more chaos?.
  2. I concede that climate is not long term weather. However, I find it hard to believe that the forcing functions of climate are not non-linear feedback systems themselves. If they aren’t, they would be a rarity among naturally occurring phenomenon. I’ve seen temperature plots over millions of year in Jim Hansen’s book “Storms of My Grandchildren” and other sources that look very chaotic to me. The trend behavior shown in "Figure 5: GHCN & HADISST1 global temperature record" is unconvincing since a 130 year record is simply inadequate in the scheme of things. I could replicate this chart easily with a two function chaotic attractor. Trends often turn out to be oscillations on a different scale. Any practitioner of finance can attest to that. Chaotic behavior is independent of scale. Plots of stock prices taken every 5 minutes for a day, taken every hour for 12 days, taken every week for 2 years or taken every month for 8 years, each having roughly 100 data points, will all look similar. Could it be that the “leash”s pull on the climate is chaotic on a much large time scale.
  3. Dave, put a large pot on the stove and heat it from bottom. The surface temperatures and convection that result will be very complex - but the overall, over time, the pot heats up. Whatever games you play in maths have to be consistent with physics. Thingadonta - explain to me why if the forcing is solar, then why isnt the pattern of observations (esp. upper stratospheric cooling) consistent with solar?
  4. DaveU wrote "The trend behavior...is unconvincing since a 130 year record is simply inadequate in the scheme of things. I could replicate this chart easily with a two function chaotic attractor." DaveU, you are leaving out the physical, causal mechanisms, and the empirical support for them. Anthropogenic global warming predictions most certainly are not based only on statistics of temperature observations. The theory and its predictions date back to the 19th century before there there even was a set of global temperature observations in which to look for patterns. The observations came later, supporting the predictions and the underlying physical theory. Both the initial simple models and the subsequent general circulation models (GCMs) are physical models, not statistical ones. Statistics are used to validate and improve the physical models. I suggest you get an overview from cce's The Global Warming Debate. With regard to chaos, see RealClimate's Chaos Theory and Global Warming, and Butterflies, Tornadoes, and Climate Modelling.
  5. Whilst weather is not climate is an oft repeated phrase, I'm not certain that we can dismiss it so readily. The bottom line is that whatever the global climate is today, or what it may be at any point in the future, it can only be quantified by the weather conditions that exist at that point. What is global climate? There is not such thing, we have a vast collection of geographical diverse areas all with a completely different range of conditions that are both related to, and independent of the adjoining regions. When we describe the climate for each region we are actually typifying the range of weather conditions that exist for that region. Does this make climate a proxy for the weather, or is the weather a proxy for the climate? If "climate change" occurs then the only way the changes can be expressed in how those changes are exhibited in the weather for each region. So the process is to firstly quantify the typical weather, then classify that as a certain climate, add in the climate change factor, then convert new climate to typical weather conditions.
  6. scaddenp at 08:57 AM, your example assumes that the heat input exceeds the heat loss, but as many campers will tell you, that is not always a given. Apart from math games having to be consistent with physics, they also have to consistent with the physical world. Would the pot theory hold if it became numerous pots of various sizes placed at random on individual burners? All connected to a single fuel source but each fuel line controlled by a thermostat that may be at times be in close proximity to the pot or could be remote, perhaps in closer proximity to a larger, or smaller pot.
  7. Tom Dayton at 09:10 AM, re "Anthropogenic global warming predictions most certainly are not based only on statistics of temperature observations." Given most models can only be validated by backcasting, what else is there other than statistics of recently observed, but more so, reconstructed temperatures? Even though CO2 concentrations can be measured from ice cores, these still have to relate to reconstructed temperature statistics. Take away temperature statistics as a means of validation and what is left?
  8. johnd > Take away temperature statistics as a means of validation and what is left? Tom's post specifically pointed out that statistics are used to validate the output of the models. What he is saying is that the output itself is not generated from pure statistics, it comes from simulations of the underlying physics. As such, you cannot analyze the significance of the results using pure statistics (by which I do not mean comparison to observations, just statistical analysis all by itself). Some good discussion of the topic here.
  9. Johnd - while you are right, the pot will not heat if input exceeds loss, but once an equilibrium has been established, then increasing the heat (in our gas add GHG) will definitely raise the temp. As to how we know that heat loss does not equal heat gain - well the TOA energy imbalance persists no matter how how complex the energy exchanges below it.
  10. I'm particularly taken with DaveU (2) and his mention of share prices. Share price movement is quite unpredictable for an individual share over days. Indeed, even over long periods an individual company might go broke. However, when you take the whole share market, and look at it over any 30 year period, it goes up. It goes up because there is an underlying driver (productivity growth) always pushing in one direction - up. So yes, the share price index bounces around, sometimes making no gains over a 10 year period (just like global temps?), but in the long term it goes up and up and up..... Chaotic, but predictable.
  11. John Brookes at 18:35 PM, productivity growth is only an indirect driver. The direct driver is the overall consensus of the market sentiment which in turn is driven not what any individual component is valued at today, but what it is likely to be valued at at some point in the future, ie the anticipation that positive growth will continue unabated. Of course overall consensus can create a situation that often results in the market diverging from the underlying fundamental drivers until a correction takes place that catches by surprise all those who were of consensus, but not those who had been examining those relevant indicators that had been ignored by all bar a few. Generally it is those few who accumulate a disproportionate amount of the wealth over time.
  12. I should add to my post that the same principle applies when the anticipation is that negative growth will continue unabated as does also occur from time to time. OT a bit, but those who do accumulate the wealth transferred from others generally consider that it is made at the time the shares are bought, not at the time of selling.
  13. Responding to Norman from another thread. Read the above. WHAT have you read that says climate is chaotic? This is an open research question with likelihood that it is not.
  14. #13 scaddenp I will link you to a Scientific American article (1995). It is titled "Chaotic Climate" and to my surprise it had information that might be of great interest to you. "Cores drilled through several parts of the Greenland ice cap show a series of cold snaps and warm spells, each lasting 1,000 years or more-that raised or lowered the average winter temperature in northern Europe by as much as 10 degrees Celsius over the course of as little as a decade." Talk about Climate Change! Is Climate chaotic? This author believes it is.
  15. #14: "It is titled "Chaotic Climate"" Wallace Broecker's work. Perhaps you might be interested in learning that in 1997 he was deeply concerned that atmospheric CO2 was the key trigger of these events: Might the ongoing buildup of greenhouse gases in our atmosphere trigger yet another reorganization of the climate system? Were this to happen a century from now, at a time when we struggle to produce enough food to nourish the projected population of 11 to 16 billion, the consequences could be devastating. ... Clearly, if we are to prepare properly for the consequences of the buildup of CO2 and other greenhouse gases in the atmosphere, we must greatly improve our knowledge of the deep water formation process. To me, it is the Achilles heel of the climate system. ... Everyone would agree that the smaller the CO2 buildup the less the likelihood of dire impacts. But this is old news. In 2008, Broecker was so concerned about increasing atmospheric CO2 as the primary driver of climate change, he was writing extensively about developing CO2 sequestration technologies (see 'Fixing Climate'). A big-scale technological fix for a complex system? Sounds like its not all that chaotic after all.
  16. "Chaos" has a formal definition, and this doesnt meet it. Non-linear and sometimes highly sensitive to changes in forcing, but its not showing signs of developing in highly different directions for slight changes in conditions. You dont get an iceage because there is a volcano erupting. It is well worth reading Broecker - another one in works - but his work on the sudden hemispheric climate reversal's doesnt give you any reason for thinking the current warming is related to causes of these events. And no reason for thinking these events dont have specific causes. Catch up on some recent literature.
  17. I dont have access to my paper lists (nor to my knowledgeable colleague) at home but if you look at Chp6 IPCC WG1 and look at section on "Abrupt climate changes in the glacial-interglacial record". Note that these are not necessarily global events - indeed some types are hemispherically anti- phased. Look at cites for main review papers. Note that this is very active field with interesting papers in the pipeline.
  18. #16 scaddenp ""Chaos" has a formal definition, and this doesnt meet it. Non-linear and sometimes highly sensitive to changes in forcing, but its not showing signs of developing in highly different directions for slight changes in conditions. You dont get an iceage because there is a volcano erupting." I guess that would depend on what you define as "slight". I am not the Master of Choao theory on the detailed definition. Here is a model of Earth's temp (simple model). It calculates Earth temp based on only solar energy and Albedo. This would be Earth without any GHG warming. But it is useful in demonstrating that Climate is indeed chaotic. Primarily with the Albedo (the Solar energy will not change much). They have lists of Albedo's to put into the calculator. I noticed that if the Earth were mostly forest the albedo would be much lower (oceans would be the same at there low albedo). Put in a lower albedo and see what happens to the Earth's temp even with no GHG effect. And you claim this is not a chaotic system? If the land is grass, desert, snow or forest it makes a huge difference in albedo and the overall temp. Try it and see and if I am wrong explain what is the flaw in my thinking. Thanks. Albedo Earth Temp calculator.
  19. #18: "Here is a model of Earth's temp (simple model). It calculates Earth temp" There's nothing at all chaotic about this model; its just a demonstration of two straightforward equations. One of them just happens to have T4, which makes it sensitive -- not chaotic. Here's a definition of 'chaotic behavior'; note that it mentions 'weather,' not climate. You may be mistaking 'chaotic' with 'sensitive to change.' For example, in this image of a chaotic system, the position of the swinging pendulum (ie, the weather) depends on where it is when the machine starts. However, the envelope of possible positions (ie, the climate) is entirely predictable.
  20. Norman, a "chaotic system" is characterized by non-linear dynamics (yep, lots of those in climate change) and by extreme sensitivity to initial conditions (nope, not the case with climate). The behavior of a chaotic system is very predictable - it will vary around it's attractor. Weather is chaotic, in that it varies hugely around the climate means due to the initial conditions - hence the ever changing state of sun, wind, rain, clouds, etc. The strange attractor for weather provides variability, and the extreme sensitivity to initial conditions (temps, humidity, clouds, etc., which we known only to a certain degree of accuracy) prevents accurate weather forecasts weeks in advance. But climate, as defined as long term averages, is not chaotic. If top of atmosphere IR decreases, there is an energy imbalance, the climate will warm. If the sun decreases it's output, there is an energy imbalance, and the climate will cool. The very nature of a running 20-30 average smooths the chaotic weather effects - and the "climate", although non-linear, is predictable to some degree of accuracy. It's not chaotic.
  21. #20 KR "But climate, as defined as long term averages, is not chaotic. If top of atmosphere IR decreases, there is an energy imbalance, the climate will warm. If the sun decreases it's output, there is an energy imbalance, and the climate will cool." The purpose of posting the calculator was so scaddenp could play with various albedos to see how these cause change in Global temps. There is a nice list of various albedo numbers to try. Global temp can effect these albedo numbers on both land and water. Water can range from a super low albedo in liquid form to a very high albedo in ice and snow form. You can put the albedo number in the calcuator and leave the solar radiation alone. The effect on global temps are far more significant than the 1 to 2 degree range given for CO2 doubling (in absence of feedbacks, justs its own contribution). Global temp can also detemine the types of plants that grow on land. Forests have very low albedo, desert fairly high and grass in the middle. Combinations of temperature, long term wind patterns, evaporation rate and all go into determining what type of land coverage will take place. The albedo effects the Global Temp in a major way and the Global temp can effect various albedo numbers in a major way. This in itself creates and unpredictable loop...What type of land form will favor a warming Earth? If it is desert than the sand will actually reflect a lot more solar radiation than forest and work to cool the Earth (Sahara desert acts in this fashion...learned that when taking a Meteorology course in College). Forests absorb a lot more solar energy but they also pull water up from the ground and cause evaporation which cools the local environment but can cause heating in the upper atmposphere when the humid air condenses back into water.
  22. #19 muoncounter If you read my response to KR...You say "For example, in this image of a chaotic system, the position of the swinging pendulum (ie, the weather) depends on where it is when the machine starts. However, the envelope of possible positions (ie, the climate) is entirely predictable." Use the calculator and move the albedo bar from one extreme to the other (both albedo ranges are possible on Earth, from a water world to an ice and snow world). With our current level of solar insolation the low albeo point would have a globe at 35F At the high albedo side the Earth woud be -138F. That is a 173 difference in Global temp based upon albedo. Now tell me how do you predict what the albedo will be if the Earth warms 10F? Will there be more relflective clouds? Of the 30% of the Earth that is Land what type of albedo will there be? If it becomes a desert that will shift it from the current estimate of 0.3 albedo to 0.37 and will cool the Earth more than it is currently being cooled. On the calculator if you slide the albeo bar to 0.37 it creates a cooling factor 0f -12F compared to 0.3 abledo. It means a warming climate in this case would end up cooling the Earth. If you can explain to me how this is not chaotic and how you can predict it then I am all ears. I can't see how anyone could predict what type of albedo will take place with a warming Earth, and if you can't predict that major factor, how can you predict a future trend?
  23. Norman, fail to see how this demonstrates any chaotic behaviour at all - a no-atmosphere earth has fast extremes so dont get fooled. You are entertaining this idea because you wish demonstrate the climate cannot be predicted despite the success of models in doing just this. I dont need a calculator to know the effect of a fourth power on sensitivity. This demonstrates nothing about supposed chaos. Furthermore, you would wish to hypothesize that current warming is a dynamical effect - an internal heat movement that is part of a larger cycle. I am still waiting for you tell me where this heat is being moved from that is causing the heating. Chaotic system still have to obey the laws of physics. Will your alternative model explain all the other observed features (which happen to fit our existing climate model). Lets suppose that climate IS chaotic. Now what is the time scale for predictions to fail for imprecisely known systems? For weather, its about 4 days. For the solar system?? Successful model predictions would suggest that it is not chaotic on scales so far worked on. Do you seriously think that your questions about albedo etc. are not built into the climate models? Could be time to study them.
  24. #22: "move the albedo bar from one extreme to the other" The earth's average albedo is given here as 0.30 or 30%. We do not go 'from one extreme to the other'. Here is a prior SkS article on the question of albedo. Look at the graph (figures 2 and 3) of measured albedo anomalies in that article; a big anomaly is on the order of 1%. That limits the plausible range of your slider bar considerably. We do not live in a world that is all desert one day, all ice the next, all forest the day after that. Look at the graph in figure 1; as scadden points out, albedo variation is already taken into account in the models. Sorry, this dog won't hunt.
  25. Norman, you still have not understood that there is a formal definition of "chaos" that is not the same as the normal English meaning. You have been pointed to the definition by other commenters. You should have read the Intermediate version of the post at the top of this page. Until you understand what "chaos" means, neither you nor anyone else will benefit from discussions with you on this topic.

1  2  3  4  5  Next

Post a Comment

Political, off-topic or ad hominem comments will be deleted. Comments Policy...

You need to be logged in to post a comment. Login via the left margin or if you're new, register here.

Link to this page

The Consensus Project Website


(free to republish)

© Copyright 2024 John Cook
Home | Translations | About Us | Privacy | Contact Us