Question on whether climate is chaotic or not

[Andre]

Please keep posts on-topic, which is about "whether climate is chaotic or not".

However, the OP states:

...Their argument is more or less that because climate changes over longer periods they don't need to treat it like a chaotic system (with all the inherent unpredictability that comes with a chaotic system).

But then on the other hand, they claim that a moderate increase in Co2 will cause this "tipping point" to occur causing run-away global warming...

It appears that the intention was to discuss contradictions between chaotic behavior and triggering runaway conditions.

 

[vanesch]

Ok, let us get some definitions right.

Chaotic system: I think the wiki entry on it is pretty good.
http://en.wikipedia.org/wiki/Chaos_theory

A chaotic system is first of all a deterministic dynamical system that has initial conditions of its state one can specify and starts out from there.

The main property is indeed "sensitivity to initial conditions", but there's also another important condition, which is "topological mixing" (the image through dynamics of any open subset comes arbitrarily close to any point of the considered phase space). Sensitivity to initial conditions alone is not really sufficient, although if the phase space is bounded, sensitivity to initial conditions everywhere (usually or always?) also leads to mixing.

Divergent systems are sensitive on initial conditions, but not necessarily chaotic. A run-away system for instance, is not chaotic, because it lacks this mixing property.

So my personal "feel" for a chaotic system is that it "diverges but comes back pretty close but not exactly". I don't know how close that gut-feeling definition is in agreement with what is the right definition of a chaotic system.

Note that these properties are properties of the dynamics of the system, and have nothing to do with any properties of any input signal. So strictly speaking, a system is not chaotic because it receives external "chaotic" signals (you cannot really have "chaotic" signals, you can only have chaotic dynamics and eventually output signals of a chaotic system, but it is hard/impossible to find that out).

But it is worse: a dynamical system can also only be chaotic in certain subspaces of its phase space, and non-chaotic in others.

Related to this discussion are the questions of whether current climate models are chaotic in the range of validity and interest where they are used.

That really shouldn't be difficult to find out, by running those models with different initial conditions. Point is, most of these models are stochastic, so strictly speaking the definition of chaos doesn't even apply.

It is even pretty evident that running climate models cannot be chaotic exactly where they are used, because otherwise they would generate widely different results from run to run and it would not be possible to draw any conclusions from that.

In how much that this has anything to do with the real climate dynamics is very hard to tell. Historical data will probably (my opinion) not be of much use, as we probably don't know the external inputs.

 

[vanesch]

It appears that the intention was to discuss contradictions between chaotic behavior and triggering runaway conditions.

First of all, I don't think any serious climate scientists considers a run-away climate. But even a run-away climate would not be a chaotic dynamics.

A bifurcation in a dynamics is also not chaotic, but it is true that there is a small region of phase space that is then extremely sensitive to initial conditions, namely all the open sets around the trajectory that hits the bifurcation, because they are split in (at least) 2 pieces.

So a "tipping point" (= bifurcation ?) by itself would not indicate any chaos in climate dynamics by itself.

It is very well possible that long-term dynamics of the climate turns out to be chaotic, but that will be on a time scale much longer than what is of interest in the AGW debate.

Note for instance that the solar system is believed to be chaotic (see http://www.sciencemag.org/cgi/content/abstract/257/5066/56 ) but nevertheless allows for extreme precise predictions of orbits over millions of years.

 

[Astronuc]

Tipping point is about stability, and there seems to be some confusion between chaos and stability.

Chaos refers to uncertainty and noisiness in the system behavior.

I wasn't referring to the choatic or random inputs, but the response to those inputs.


Earth's climate is also not a closed system, and not only are the boundary conditions variable (noisy) and non-linear, the system itself is non-linear - but it's bounded somewhat - or at least part of the system is bounded.


Another matter is the definition of choas theory or chaotic system. Traditionally or conventially, "Chaos theory is an area of inquiry in mathematics, physics, and philosophy which studies the behavior of certain dynamical systems that are highly sensitive to initial conditions." What initial condition do we apply to today's climate?

Chaos also looks at system response/behavior to perturbations and noise (periodic and aperiodic), which also include perturbations to boundary conditions or transients, e.g. volcanic eruptions or meteoric impacts, or somewhat noisy inputs like solar-cycles. Add to this long term tectonic drift. The equilibrium shifts. The challenge is to determine why and attempt to predict weather and climate in the long term.

One can look at turbulence in a fluid. Locally the velocity changes constantly, but it is bounded by constraints, e.g. structure or limits on momentum and energy.

 

[Andre]

First of all, I don't think any serious climate scientists considers a run-away climate.

It seems that one of my posts got deleted that introduced somebody like that. Was that illegal?

 

[Monique]

To re-iterate Astronuc's words: let's keep it on the topic of whether the climate is chaotic or not and how that relates to the models Earth scientists use.
The OP explained himself: https://www.physicsforums.com/showpost.php?p=2468484&postcount=13

Off-topic posts were deleted to get the thread back on track.

 

[Astronuc]

One has to look into chaos as applied to multi-input, multi-output (MIMO) systems.

Perhaps the bifurcation is a more rigorously appropriate term.

Bifurcation theory is the mathematical study of changes in the qualitative or topological structure of a given family. Examples of such families are the integral curves of a family of vector fields or, the solutions of a family of differential equations. Most commonly applied to the mathematical study of dynamical systems, a bifurcation occurs when a small smooth change made to the parameter values (the bifurcation parameters) of a system causes a sudden 'qualitative' or topological change in its behaviour.

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

 

[Xnn]

OK; let's focus on the topic.

Wikipedia is not an acceptable source for this site.

So, where is the textbooks, scientific journals, and other peer-reviewed sources
that define a chaotic system?

So far, most post are just about opinion (some more reasoned than others).

 

[vanesch]

Wikipedia is not an acceptable source for this site.

So, where is the textbooks, scientific journals, and other peer-reviewed sources
that define a chaotic system?

We are talking here about elementary definitions of concepts in dynamics that have a clear meaning, so in as far as the Wiki article is serious, it is good enough a source for the clarification of such things, I would say. There is nothing controversial in these "claims" of elementary definitions, like chaotic system or what is a bifurcation. We're in the "let's get the definitions of the words right" stadium.

It corresponds pretty well to what I remember from reading the book "deterministic chaos" http://books.google.fr/books?id=WaEGkJ3XAtEC&lpg=PP1&ots=4tbrm7zFEv&dq=deterministic%20chaos&pg=PP1#v=onepage&q=&f=false which I have somewhere on my shelf but not at hand right now.

 

[Astronuc]

Don't know if this helps.

If the parameter V-m is increased even further, the behavior changes to an apparently random, erratic, and aperiodic waveform. This situation is illustrated in Figure 1.4. Such a bounded aperiodic behavior is known as chaos.

from Nonlinear Phenomena in Power Electronics: Bifurcations, Chaos, Control, and Applications
Soumitro Banerjee (Editor), George C. Verghese (Editor)
http://media.wiley.com/product_data/excerpt/38/07803538/0780353838.pdf

I was thinking IEEE would have a formal definition somewhere, for example

In this article, a nonlinear dynamical phenomena leading to bifurcation and chaos in power systems is explored using a sample power system. After giving an introduction to nonlinear dynamical power systems in section II a basic knowledge to nonlinear dynamics and chaos theory is given. Section III deals with bifurcation theory. In section IV a dynamical power system model has examined. In section V the theories are applied to a sample power system example and various bifurcation and chaotic phenomena are examined.

An application of chaos and bifurcation in nonlinear dynamical power systems
Kuru, L. Kuru, E. Yalcin, M.A.
http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=1344840
Intelligent Systems, 2004. Proceedings. 2004 2nd International IEEE Conference
Publication Date: 22-24 June 2004
Volume: 3, On page(s): 11- 15 Vol.3
ISSN:
ISBN: 0-7803-8278-1
INSPEC Accession Number: 8109177
Current Version Published: 2004-10-25


Another issue, and an important one, is - when does weather become climate?

Parts of North Africa (Algeria, Tunisia, Libya(?)) were once the bread basket of the Roman Empire. Now it's mostly desert.

More recently, the Horn of Africa (W. Somalia and E. Kenya) are suffering a third year of drought, but just to the north (N. Kenya and Uganda), they've had devastating floods.

Australia now has persistent drought in the south, and that's a lot different from when I lived there 43+ years ago.

 

[seycyrus]

A chaotic system is first of all a deterministic...

*deterministic* is also problematic in that is can be misconstrued, to imply arbitrary predictability. Certainly the system itself knows it's own dynamic evolution, but that doesn't help out any onlookers.

...Sensitivity to initial conditions alone is not really sufficient, although if the phase space is bounded, sensitivity to initial conditions everywhere (usually or always?) also leads to mixing.

In class,it was taught that neither *usually or always* can be assumed.

...So my personal "feel" for a chaotic system is that it "diverges but comes back pretty close but not exactly".

Eventually.

...So strictly speaking, a system is not chaotic because it receives external "chaotic" signals (you cannot really have "chaotic" signals, you can only have chaotic dynamics and eventually output signals of a chaotic system,

I was wondering about using those outputs of a chaotic system as inputs for another systems. I.E. the sun's output (postulated as chaotic) into the Earth's climate (questioning the chaosticity (woot woot!) of this system)

Thinking about it, I believe that such chaotic inputs cannot drive another system "chaotic". it is either chaotic or not from the get-go. Of course this just begs the question about whether it is correct to consider any systems as independent from another.

But it is worse: a dynamical system can also only be chaotic in certain subspaces of its phase space, and non-chaotic in others.

Difficulty amplified again by the requirement that the attractors be dense.

 

[Astronuc]

Try to define the Climate (system) statepoints, inputs and outputs.

Also try to define the climate system and it's boundaries.

 

[seycyrus]

OK; let's focus on the topic.

Wikipedia is not an acceptable source for this site.

So, where is the textbooks, scientific journals, and other peer-reviewed sources
that define a chaotic system?

So far, most post are just about opinion (some more reasoned than others).

Vanesch has got it right.

1) Sensitivity to initial conditions.

2) In the phase space around the attractors, it has to topologically mix.

3) The orbits are dense.

 

[Astronuc]

Interesting article - Chaos and stability of the solar system
http://www.pnas.org/content/98/22/12342.full

In its scientific usage, chaos is not a synonym for disorder, rather it describes the irregular behavior that can occur in deterministic dynamical systems, i.e., systems described by ordinary differential equations free of external random influences. Chaotic systems have two defining characteristics: they show order interspersed with randomness, and their evolution is extremely sensitive to initial conditions. Extreme sensitivity to initial conditions is quantified by the exponential divergence of nearby orbits. The rate of such divergence is characterized by the e-folding time scale called Lyapunov time. A second characteristic time scale is the escape time, which is the time for a major change in the orbit.

So if one applies the requirement that the evolution (of Earth's climate) is extremely sensitive (or at least sensitive) to 'initial conditions', then climate may not be chaotic. What are the initial conditions?

It does represent a dynamic with both periodic and aperiodic behaviors.

 

[seycyrus]

Interesting article - Chaos and stability of the solar system
http://www.pnas.org/content/98/22/12342.full

Nice find. I wonder what the lyapunov and escape time scales are for the weather/climate. I failed with google.

What are the initial conditions?

I always understood initial condition to be those you stipulate at t0, any t0. Or are you pointing out that we don't even know which variables are required inputs?

 

[Astronuc]

I always understood initial condition to be those you stipulate at t0, any t0. Or are you pointing out that we don't even know which variables are required inputs?

In the context of Earth's climate, I wondering at what point one takes the initial, or perhaps more appropriately, the reference time. The climate has constantly changed - sometimes slowly, sometimes abruptly.

In the context of today's climate, do we look back 100 years, 200 years, 400 years, 1000 years, 5000, 10,000, 100,000, 1 million, 10 million.

Also - what is the system (which defines statepoints) and what are the inputs, and more importantly - what are the 'natural' inputs/perturbations, and what are the 'anthropogenic inputs/perturbations - and what are the relative magnitudes of these inputs/perturbations?

 

[Xnn]

Vanesch has got it right.

1) Sensitivity to initial conditions.

2) In the phase space around the attractors, it has to topologically mix.

3) The orbits are dense.

Okay;

Then how can we answer the question if we don't know if
there are tipping points or how close we are to them?

 

[turbo]

PBS hosts a nice article on weather, climate, and chaos:

http://www.pbs.org/kcet/wiredscience/blogs/2007/10/climate-chaos-and-confusion.html

The explanation of how weather and climate are described by the illustration of Lorentz attractors is a good one, IMO, though greatly simplified, since weather and climate have a LOT of variables.

 

[seycyrus]

Okay;
Then how can we answer the question if we don't know if
there are tipping points or how close we are to them?

We really need for that nonlinear-mathematician friend of a poster to swing by ...Maybe if we are lucky, he will be a "Chaotician" (I cringed when they used that word in Jurasic Park)

Perhaps your question reflects the uncertainty the one scientist in question (Gavin??) meant to reflect upon when he said it "might" be chaotic.

How does one label a natural system as chaotic when one cannot formulate and solve expressions that correctly model the observed behavior? Does being able to model the sensitivity to initial conditions suffice to say that the natural system being modeled is chaotic? Not in a strict mathematical sense.

It's more straightforward for a simpler system. One can write down the equations for a double pendulum and compare the results with a *physical* double pendulum. One notes the behavior of the real beast and says
"Look at that pendulum go! It's all crazy-like!"
and then
"Wow, when I map out the trajectories in phase space solved from my equations of motion they get pretty crazy too! Why, they look just like that swinging contraption!"
and then
"I can show that these equations describe a chaotic system, therefore it seems fair to induce that the *real* double pendulum is chaotic."

But doing it for the weather ...

I'm liking the *might be* answer more and more.

 

[turbo]

I'm liking the *might be* answer more and more.

I think I'd like that answer even more if it were qualified with *on some scales*. Certainly the Younger Dryas event shows that global climate can take some pretty rapid swings. It brought on an ice age in the northern hemisphere, and much warmer temperatures in the southern hemisphere, so the results of that event were divergent N-S.

 

[Astronuc]

Then how can we answer the question if we don't know if
there are tipping points or how close we are to them?

That's the proverbial $64 million or now $64 billion (or maybe it's $6.4 trillion) question.

In order to know how to procede, one needs to understand the path/trajectory and the tipping points/pitfalls. If one makes the wrong assessment and/or wrong prediction, things might get dicier.

 

[Andre]

I was trying to shed some light on that but the post about that got deleted.

 

[Xnn]

Personally, I'm not fond of "We don't know" as an answer.

Here is an article from Scientific America which suggest that the
Earths climate becomes chaotic at around 1000 ppm CO2.
Fortunately, that is not expected to occur for at least 200 years.

http://www.scientificamerican.com/article.cfm?id=impact-from-the-deep

 

[vanesch]

Okay;

Then how can we answer the question if we don't know if
there are tipping points or how close we are to them?

But there are 3 different aspects:

- chaotic behaviour of the inherent dynamics of climate
- eventual existence of bifurcations (tipping points)
- relatively short term (a few centuries) predictability.

They are not related. The system can be chaotic with Lyapunov exponents which are of the order of 1/1 million years for instance, which would mean that predictability over centuries or hundreds of millennia isn't going to be a problem by this chaotic dynamics.

Bifurcations don't mean necessarily chaos, and even less "unpredictability". A beam under compression has a bifurcation point (from a certain stress onwards, it will bulge). That doesn't mean we can't calculate beam deformation.

So the argument "they say there might be tipping points, but then it is chaotic, and hence we can't make any predictions" is full of invalid inferences.

Let's first find out the dynamics already !

 

[Coldcall]

PBS hosts a nice article on weather, climate, and chaos:

http://www.pbs.org/kcet/wiredscience/blogs/2007/10/climate-chaos-and-confusion.html

The explanation of how weather and climate are described by the illustration of Lorentz attractors is a good one, IMO, though greatly simplified, since weather and climate have a LOT of variables.

Actually I've read that blog before and Alexi Tekhasski has some interesting points contrary to the author of that blog. Just read some of the comment below re Lorenz attractor.

As that pro-agw blog shows there is a concerted effort by the some in the agw community, including Gavin Schmidt at RC, who for some odd reason, don't want the climate system labelled as chaotic. However the silly part is that their models are indeed non-linear with all the inherent problems about initial conditions.

My whole point has always been that:

1) I am highly suspicious of any scientist who claims a computer model is based on an "unknown" physics. (in other words, if one can't explain the underying physics how can one be confident of the model?) I think i hold a reasonable position and if we were discussing most other scientific (less trendy)topics i think most would agree with that stance.

2) Any computer model which needs to virtualise the real climate system in a realistic capacity probably needs an infinite amount of variables and factors for which we are today probably aware of only a tiny fraction. The current models are just way too primitive to accomplish that.

3) I don't accept this idea (often stated by some in the agw community) that while these computer models may not be able to predict shorterm climate, they can predict long-term averages. This goes against very fundamental science known and demonstrated in chaotic systems, which states that small inaacuracies in initial condiions grow exponentially and irregularly the longer the clock runs. Remember that climate is longterm weather, no mattter what sort of clever semantic one wants to use to define "climate".

4) The climate is open ended and affected by cosmic phenomenom so the idea we can create and idealisation of the climate in a model is a non-starter.

So I am not arguing that Co2 does not affect the climate or we are not having climate change, or perhaps even some warming depending on what time scale one uses as a boundary.

I'm simply saying that with our current knowledge of the scientific fundamentals which MUST be adhered to in any theory, there is too large an uncertainty and unpredictability factor for claiming anything is settled.

That is how i am sceptical.

PS: The burden of proof is on the computer models to confirm and validate their predictions as with any scientific theory. They have not done so, and in fact, their models did NOT predict the post 98 cooling period. So those models have failed at the first hurdle.

 

[Coldcall]

Some professional references for some of my points above:

[moderator note: blogs do not count as references]

http://rsta.royalsocietypublishing.org/content/365/1857/2145

Another paper challenging the predictability of these models. Len Smith, one of the authors from LSE works on climate models and is constantly trying to get his colleagues to tone donw the hubris about predictability.

"Over the last 20 years, climate models have been developed to an impressive level of complexity. They are core tools in the study of the interactions of many climatic processes and justifiably provide an additional strand in the argument that anthropogenic climate change is a critical global problem. Over a similar period, there has been growing interest in the interpretation and probabilistic analysis of the output of computer models; particularly, models of natural systems. The results of these areas of research are being sought and utilized in the development of policy, in other academic disciplines, and more generally in societal decision making. Here, our focus is solely on complex climate models as predictive tools on decadal and longer time scales. We argue for a reassessment of the role of such models when used for this purpose and a reconsideration of strategies for model development and experimental design. Building on more generic work, we categorize sources of uncertainty as they relate to this specific problem and discuss experimental strategies available for their quantification. Complex climate models, as predictive tools for many variables and scales, cannot be meaningfully calibrated because they are simulating a never before experienced state of the system; the problem is one of extrapolation. It is therefore inappropriate to apply any of the currently available generic techniques which utilize observations to calibrate or weight models to produce forecast probabilities for the real world. To do so is misleading to the users of climate science in wider society. In this context, we discuss where we derive confidence in climate forecasts and present some concepts to aid discussion and communicate the state-of-the-art. Effective communication of the underlying assumptions and sources of forecast uncertainty is critical in the interaction between climate science, the impacts communities and society in general".

 

[Coldcall]

But there are 3 different aspects:

- chaotic behaviour of the inherent dynamics of climate
- eventual existence of bifurcations (tipping points)
- relatively short term (a few centuries) predictability.

They are not related. The system can be chaotic with Lyapunov exponents which are of the order of 1/1 million years for instance, which would mean that predictability over centuries or hundreds of millennia isn't going to be a problem by this chaotic dynamics.

Bifurcations don't mean necessarily chaos, and even less "unpredictability". A beam under compression has a bifurcation point (from a certain stress onwards, it will bulge). That doesn't mean we can't calculate beam deformation.

So the argument "they say there might be tipping points, but then it is chaotic, and hence we can't make any predictions" is full of invalid inferences.

Let's first find out the dynamics already !

Sorry but i think your point about:

"The system can be chaotic with Lyapunov exponents which are of the order of 1/1 million years for instance, which would mean that predictability over centuries or hundreds of millennia isn't going to be a problem by this chaotic dynamics."

Is wrong form a foundational perspective re chaos. In any complex open ended system in a state of non-equlibirum there is just no way you can expect super longterm predictions to be accurate without having actually run the model for that amount of time then observed correlations with what really emerged from that chaotic system. And the model must be not an idealisation but an exact simulation of all the factors that will effect that chaotic system. The initial conditions must be known to an almost infinite degree of accuracy. All these things are an impossibility from the perspective of known and tested scientific theory of chaos.

What you are suggesting is that we freeze reality as it stands today and extraploate that into the future ad infinitum idealising a status quo. Whereas we know this is not practical nor useful in predicting long range behaviour of a chaotic system open to external influences of which we have little information.

Im sorry but every text on chaos theory will support my view. I suggest any of the books by Davies, Gribbin's (Complexity), Ian Stewart, and even Gleicks original book on chaos theory.

 

[Coldcall]

Personally, I'm not fond of "We don't know" as an answer.

Here is an article from Scientific America which suggest that the
Earths climate becomes chaotic at around 1000 ppm CO2.
Fortunately, that is not expected to occur for at least 200 years.

http://www.scientificamerican.com/article.cfm?id=impact-from-the-deep

"We don't know" is the answer Gavin at RC has provided every time he is asked to define the physics behind a) the climate system. and b) his models.

If one cannot define the physics any idea of accurate predictions is just a logical fallacy.

However, the truth is that their models are chaotic. Its a mystery why they won't admit it, but my suspicion is that they won't admit it because they know what it implies for any hopes of accurate prediction.

Actually the IPCC report has a section called Basic Science where they state this unpredictability in the oddly semantic "surprises". But then they go on to ignore the basic fundamental science and pretend the uncertainty is less than 10%! That is a figure they have pulled out of the air. Its a nonsense.

 

[D H]

Sorry but i think your point about:

The system can be chaotic with Lyapunov exponents which are of the order of 1/1 million years for instance, which would mean that predictability over centuries or hundreds of millennia isn't going to be a problem by this chaotic dynamics.

Is wrong form a foundational perspective re chaos. In any complex open ended system in a state of non-equlibirum there is just no way you can expect super longterm predictions to be accurate without having actually run the model for that amount of time then observed correlations with what really emerged from that chaotic system. And the model must be not an idealisation but an exact simulation of all the factors that will effect that chaotic system. The initial conditions must be known to an almost infinite degree of accuracy. All these things are an impossibility from the perspective of known and tested scientific theory of chaos.

Did you read what vanesch wrote? A chaotic system can be quite predictable over time scales much less than the system's Lyapunov time. The solar system is chaotic with a Lyapunov time of 5 to 10 million years. (See the article cited in post #49.) That means that predictions of the state of the solar system over centuries, or even hundreds of millennia can be quite accurate. Problems with the predictions do appear, but only when on the scale of millions of years or longer.

Bringing this back to the discussion of the climate, *if* climate is chaotic, then it can still be quite predictable over time scales of human interest (decades to a century or so) so long as the climate's Lyapunov time is a millennia or more.

 

[Coldcall]

Did you read what vanesch wrote? A chaotic system can be quite predictable over time scales much less than the system's Lyapunov time. The solar system is chaotic with a Lyapunov time of 5 to 10 million years. (See the article cited in post #49.) That means that predictions of the state of the solar system over centuries, or even hundreds of millennia can be quite accurate. Problems with the predictions do appear, but only when on the scale of millions of years or longer.

Bringing this back to the discussion of the climate, *if* climate is chaotic, then it can still be quite predictable over time scales of human interest (decades to a century or so) so long as the climate's Lyapunov time is a millennia or more.

Yes i read what he said very carefully and disagree, for the fundamental points i have raised.

You say they can be "quite accurate". What does that mean? Its not enough to say we can more or less approximate within some defined margin of error. The only way to prove that assertion that "quite accurate" will be good enough is by running the model and making predictions. None of this has yet been done.

You guys are talking about idealisations. Thats not how the real universe works.

I would be convinced that "quite accurate" is good enough for our purposes if predictions were made, confirmed and validated.

Are we not in our right to insist that if agw is to be taken seriously as a science that the correct methodology and process take place to validate or falsify it?

 

[billiards]

Yes i read what he said very carefully and disagree, for the fundamental points i have raised.

You say they can be "quite accurate". What does that mean? Its not enough to say we can more or less approximate within some defined margin of error. The only way to prove that assertion that "quite accurate" will be good enough is by running the model and making predictions. None of this has yet been done.

You guys are talking about idealisations. Thats not how the real universe works.

I would be convinced that "quite accurate" is good enough for our purposes if predictions were made, confirmed and validated.

Are we not in our right to insist that if agw is to be taken seriously as a science that the correct methodology and process take place to validate or falsify it?

Climate models are not meant to be predictive. They are adopting the methodology commonly adopted in the Earth Sciences (and other sciences for that matter) of using a simple model to better understand the behaviour of a complex system.

 

[D H]

You are making multiple claims, Coldcall, and you are mixing them up. You are being a bit chaotic.

Here is what I think your claims are. Correct me if I'm wrong.

• From post #64, "However, the truth is that their models are chaotic. Its a mystery why they won't admit it, but my suspicion is that they won't admit it because they know what it implies for any hopes of accurate prediction."
  
  Claim #1: The climate is a chaotic system and hence is unpredictable (period). In particular, climate is unpredictable over the time span of immediate interest -- the present to 100 years from now.
• From post #66, "The only way to prove that assertion that "quite accurate" will be good enough is by running the model and making predictions. None of this has yet been done."
  
  Claim #2: Climate scientists don't have models and don't make predictions.
• From post #61, "The climate is open ended and affected by cosmic phenomenom so the idea we can create and idealisation of the climate in a model is a non-starter."
  
  Claim #3: Creating a model of the climate is a hopeless endeavor. There are too many "unknown unknowns."
• Also from post #61, "Any computer model which needs to virtualise the real climate system in a realistic capacity probably needs an infinite amount of variables and factors for which we are today probably aware of only a tiny fraction."
  
  Claim #4: A model of the climate is beyond the scope of modern science. There are too many "known unknowns."

This is a just start; you are making more claims than that. This is a problem. Let's keep this thread to claim #1. Raise those other claims in some other thread. Too many issues in a single thread makes for a chaotic discussion.

 

[Coldcall]

You are making multiple claims, Coldcall, and you are mixing them up. You are being a bit chaotic.

Here is what I think your claims are. Correct me if I'm wrong.

• From post #64, "However, the truth is that their models are chaotic. Its a mystery why they won't admit it, but my suspicion is that they won't admit it because they know what it implies for any hopes of accurate prediction."
  
  Claim #1: The climate is a chaotic system and hence is unpredictable (period). In particular, climate is unpredictable over the time span of immediate interest -- the present to 100 years from now.
  
• From post #66, "The only way to prove that assertion that "quite accurate" will be good enough is by running the model and making predictions. None of this has yet been done."
  
  Claim #2: Climate scientists don't have models and don't make predictions.
  
• From post #61, "The climate is open ended and affected by cosmic phenomenom so the idea we can create and idealisation of the climate in a model is a non-starter."
  
  Claim #3: Creating a model of the climate is a hopeless endeavor. There are too many "unknown unknowns."
  
• Also from post #61, "Any computer model which needs to virtualise the real climate system in a realistic capacity probably needs an infinite amount of variables and factors for which we are today probably aware of only a tiny fraction."
  
  Claim #4: A model of the climate is beyond the scope of modern science. There are too many "known unknowns."

This is a just start; you are making more claims than that. This is a problem. Let's keep this thread to claim #1. Raise those other claims in some other thread. Too many issues in a single thread makes for a chaotic discussion.

Well actually most of those statements revolve around the same question. I've just tried to artciulate them in different ways because there appears to be some misunderstandings about what I am trying to get at.

Look, don't take it from me. Here are a load of papers looking at prediction in chaotic systems, and they asll say the same thing, long-term prediction is next to impossible.

http://www.engineeringletters.com/issues_v15/issue_1/EL_15_1_10.pdf

http://sciencelinks.jp/j-east/article/200118/000020011801A0278369.php

http://www.springerlink.com/content/g074k6037tr76906/

http://www.jstor.org/pss/2290510

http://personalpages.to.infn.it/~boffetta/Papers/bc98.pdf

By the way the one called personal pages is a paper, but if its not good enough because the link isn't to anything institutional then delete by all means.

But going back to the original point, as youve requested:

I stand by the statemement that climate is a chaotic system and all the same rules of chaotic systems should apply. As the papers and books i have references will all tell you the same thing about the unpredictability of long term forecasts and it does not matter the system, if its chaotic they all behave this way.

But this is exactly why Gavin at RC won't commit one way or another, because admitting the chaotic nature of the climate basically puts his models into the same problem territory as any other chaotic system.

I don't see how anyone can not notice the game being played with this reticence to admit the chaotic nature of the climate.

 

[Coldcall]

Climate models are not meant to be predictive. They are adopting the methodology commonly adopted in the Earth Sciences (and other sciences for that matter) of using a simple model to better understand the behaviour of a complex system.

You can't expect a simplistic model to accurately describe what will happen in the future re a complex choatic system. But if what you are saying is true then their whole theory is flawed from the start.

Also please don't tell me they are not meant to make predictions because that's exactly what they have done re Co2 forcing in the next decades.

 

[Coldcall]

I've got to leave for the day but i just ask everyone that if they have any referential evidence of a sucessful longterm predictions in chaotic systems please post it.

So far all i have seen in an attempt to contradict the fundamental known science of chaos theory are "could" or "may" or other caveated statements with no proof.

If someone thinks they can overturn chaos physics going back to Poincare please show me the evidence as the burden of proof lies squarely with the detractors.

Of course that doesn't settle the argument over whether climate is chaotic but i think if you ask any scientists properly involved with chaotic systems they will tell you it is indeed chaotic. It seems the only people arguing otherwise are agw proponents.

Gotta go for now.