I don't normally post entire press releases here at Not PC, but I'm reposting below a press release from Dr Vincent Gray because of its importance and incisiveness on a subject in which statists are looking to warmists to justify an increase in their power. Dr Gray is, in effect, saying, "Now hold on just a moment..." -- PC
NEW REPORT SAYS GLOBAL WARMING IS NEGLIGIBLE, SHORT-LIVED, AND NOW ENDED -- Dr Vincent Gray
The draft “Summary for Policymakers of the Fourth Report of the Intergovernmental Panel on Climate Change has been widely leaked to the Press. Its crucial conclusion is as follows:
“It is very likely that anthropogenic greenhouse gas increases caused most of the observed increase in globally averaged temperatures since the mid-20th century.”The widely available graph of the globally averaged annual temperature anomalies between 1857 and 2005 shows, for the period since the mid-20th century:
The above statement considers that it is very likely that most of this 0.53ºC was caused by anthropogenic (human-induced) greenhouse gas increases. “Most” of this would be between 0.3ºC and 0.5ºC, the amount that the statement considers to be due to human influence.
- No warming between 1950 and 1978.
- No warming between 1998 and 2005.
- The only ”observed” warming over the period is from 1978 to 1998, 20 years only, out of the 55 years.
- The actual warming involved over this short period of 1978 to 1998 was 0.53ºC.
This temperature rise is negligible. None of us would notice if it happened instantly, let alone over 50 years.. It is below the amount considered in the weather forecasts. Yet this small temperature rise over 55 years is routinely blamed for all manner of climate disasters.
The IPCC pronouncement is not a certain one. The term “very likely” is defined as amounting to a probability above 90%. In other words, there is one chance in ten that they are wrong. Also, the probability is based on the opinion (or guess) of “experts” who are financially dependent on an expectation of positive results.
Finally, there has been no “warming” at all since 1998, now eight years. “Global Warming” seems to have come to an end.
This temperature record is quite incompatible with the computer climate models [which are now the only place in which warming exists], so why should we believe their pessimistic forecasts for the future?
It should also be noted that there has been negligible warming in New Zealand since 1950. The mean temperature for 2006 was 0.7ºC below that for 2005. According to the temperature record for Christchurch, there was no warming since 1910, with a maximum temperature in 1917.
RELATED: Global Warming, Science, Politics-World
29 comments:
The main problems with the IPCC report were the heavily reliance in statistical inferences techniques being used. The whole report is full of those models. Causations is still completely illusive & exclusive from those models being published in the IPCC report. There is no single model in the IPCC report that has established a direct or indirect causation between CO2 and Global average temperature and everything are inferences.
Causation modeling techniques which are widely adopted in Physics & Engineering establishes a flow-diagram of causes & effects, which are what the 'laws of physics are basically about', in a chain relationship of variables such that a cause 'x' produced an intermediate effect 'y' which in turn acts an intermediate secondary cause to produce an intermediate secondary effect 'z', which it then acts as a third intermediate cause to produce third intermediate or final effect 'w', and on, and on, ...
Here is a simple open loop of a causation diagram of the above example (common terms used by engineers & physicists is called block-diagram).
x --> y --> z --> w
Climate physical realities are not open loop as above but a dynamical feedback close loop system as one of the possible structural variable relations shown below:
Modlel #1
---------
x --> y --> z --> w
^ |
| |
.<----.
Modlel #2
---------
x --> y --> z --> w
^ | |
| | |
.<--- + <---.
Modlel #3
---------
x --> y --> z --> w
^ |
| |
.<----------.
Modlel #4
---------
x --> y --> z --> w
| ^
| |
.-----------.
Modlel #5
---------
x --> y --> z --> w
| ^
| |
.-----------.
All the causation models depicted above (if my diagrams will be parsed & drawn exactly as I post this message) established a cause & effect between input X which is the 'cause' and output W which is the effect. The intermediate variables Y and Z are unobservable, the only observables are X and W, while Y and Z are not visible to us.
FACTS:
-----
#1) In black box statistical inferences modeling you have something like this:
x --> ? --> w
The question mark depicted in the above diagram establishes nothing about the physics (ie, cause & effect) , it is just pure induction of trying to correlate cause 'x' & effect 'w'. The question is where is the physics?
We do have the data for both X & W (cause-&-effect), but we know very little or nothing else of what are the intermediate steps between input X (cause) and output W (effect) in a climate dynamical systems. Also we know nothing about of which structural variable relation as depicted in Model #1, Model #2, etc, of which is the correct ones, even if the unobservable variables Y and Z have been identified.
#2) All the structural variable cause-&-effect relations depicted in Model #1, Model #2, Model #3, and so forth above could be functionally THE SAME. This means that you could apply the same input (cause) X and output (effect) W in to the dynamical systems to be modeled which fits the data to a high degree, however selecting which of the 5 models , ie, Model #1, Model #2, and so forth that fits physical reality (causality) is another different matter, which is still unknown today. This basically says that there are many possible causation models that fit the data, but only one will represent physical processes that govern the climate dynamics and this single process has not been identified yet.
Important Notes:
----------------
a) The variable structural relations depicted in Model #1 to Model #5 are not exhaustive, I could have come up with more, but I think 5 are enough to make my point. I also used 4 variables for simplicity, where as in reality the number of variables is huge, where most of those are still unknown.
b) Any of Model #1 to Model #5 is called a 'dynamical system' or 'closed-loop feedback or feedforward dynamical system'. Currently it is not known how many of such systems are there in climate dynamical systems. The other point is, scientists have no idea of of how these independent 'closed-loop feedback or feedforward dynamical systems' are structurally related to each other. Some of these sub-systems are coupled to each other. The atmospheric systems & oceanic systems have now been coupled together in a still yet simplistic model by climate scientists.
c) Model #1 to Model #5 are SISO (single input - single output), which I simplified to make my point clear, but in reality, climate is MIMO (multiple input - multiple output).
d) If you have a huge number of potential climate variables, where the majority are to be discovered and a huge number of independent 'closed-loop feedback or feedforward dynamical systems', then image how complex when you hook-up each and every variable and every closed-loop system to form a one holistic climate earth systems and this is what you call PHYSICS.
Now, if anyone thinks that Falafulu is a nutter & denier, please read what this NASA sponsored workshop proposed in improving the climate modeling by adopting physics of causations rather than black-box statistical inferences.
"WORKSHOP ON CLIMATE SYSTEM FEEDBACKS"
http://grp.giss.nasa.gov/reports/feedback.workshop.report.html
The person who chaired the workshop above was Dr. Rossow of NASA and here is one of the first peer review papers to be published relating to the issues of problems in climate modeling which they raised during the workshop. Here is Dr. Rossow's paper, I recommend that you read the problems he cited in his paper , just skip the mathematical derivations part, and concentrate on the non-math part which still make it readable to non-expert in maths or engineering.
"Inferring instantaneous, multivariate and nonlinear sensitivities for the analysis
of feedback processes in a dynamical system: Lorenz model case-study"
http://pubs.giss.nasa.gov/docs/2003/2003_Aires_Rossow.pdf
If you're curious about the theory behind feedback dynamical systems, then here is some diagrams from wikipedia to take a peek at.
"Control theory"
http://en.wikipedia.org/wiki/Control_theory
You can see Falufulu Fisi's post with diagrams at this page.
Sorry for the double post, but this was meant to go here.
Try this...
Take a large container and throw in a layer of ice. Now put a lid on the container and place the whole thing on the front lawn and in the sun.
What will happen to the temperature inside the bin?
Not a hell of a lot, because the ice inside the container will absorb most of the energy from the sun, melting the ice in the process. Over time the rate at which the ice melts will increase and only once all the ice has melted will you observe significant increases in temperature.
What does this tell us kids...?
That's right, measuring global temperatures by themselves is irrelevant.
Falafulu Fisi said...
Anon said...
[That's right, measuring global temperatures by themselves is irrelevant.]
Hello Anonymous kid. Are you talking about the interpretation of the physical measurements or the theory of causation in physics. I suggest you re-read my previous posts which is exactly what I briefly stated already of what is called MIMO systems (Multiple Input - Multiple Output). Global temperature can be one of those many output variables to be measured. MIMO is stated here, see link below, but it is not so detail. If you want detail of what MIMO dynamical systems is, just post back here kid, so that the teacher (myself) will quote you appropriate publications so that you can dig in deep & learn in order for you to understand "evolving dynamical systems"
"Control Theory" http://en.wikipedia.org/wiki/Control_theory
Ok, that's all for our lesson today class & Anonymous kid, and always remember to do your homework for tommorow, complete it before watching your kid's show "The Simpsons".
Anonymous kid said...
[Over time the rate at which the ice melts will increase and only once all the ice has melted will you observe significant increases in temperature.]
Ok, listen up kid, the master will give you a hint about the Physics of causation relating to the physical process that is undertaken in the above example. The hint is, "everyone should look it up on Google about the term called Latent Heat or Energy".
That's all for today, and remember, before you cross the road, you must stop and look to your left & to your right and see if a vehicle is coming or not. When it is clear then you can cross the road. Remember to complete your homework for tomorrow which is Latent Heat, before watching your "Simpson's Show" tonight.
falafulu - I never mentioned causal relationships. I'm simply pointing out that measuring global temperatures is fundamentally flawed. No amount of clever mathematics will ever make up for poor measurement.
By the way, if you are the teacher, God help the class. You have a knack for turning the fairly straight forward into something unnecessarily complex.
However, I imagine you do that to make yourself feel important. Sort of like a cat or bird puffing up their fur or feathers. Ultimately it is fairly unsubstantial underneath.
Anon said...
[No amount of clever mathematics will ever make up for poor measurement.]
Yes clever mathematics can make it up. How do you think that Michael Mann, the hockey stick inventor and others who used the same data to analyse global temperature data? In that dataset there were some missing data caused by poor measurements or instrumentation malfunctions. They used clever mathematics to fill-in those missing data prior to formal analysis.
Anon said...
[You have a knack for turning the fairly straight forward into something unnecessarily complex.]
Can you explain of what is fairly straight forward? BTW, it is not unnecessarily complex, can't you see the simplicity of the explanations and some very simple diagrams? What is complex there? Anyone can see & understand the diagrams.
Anon said...
[I imagine you do that to make yourself feel important.]
No, I don't do that to feel important. Feel important about what? I simply stated of what are the hurdles & problems in current climate modeling, where the simple models written for the IPCC are telling us we are doom. What is your problem with me stating the obvious and that is the shortfall in the current modeling of climate systems ?
Anon said...
[Ultimately it is fairly unsubstantial underneath.]
Ok, if you think that what I have pointed out is unsubstantial, then I suggest you email Dr. William Rossow of NASA and challenged him about that.
His email is listed here:
http://grp.giss.nasa.gov/members.html
Anon said...
[By the way, if you are the teacher, God help the class.]
I think that you're throwing a tantrum because I referred you as a kid. Your comment was disrespectful to me & others kids, therefore I treated you in the same manner. The class do now know something about climate modeling, not necessarily deep, but some rough ideas.
Final point. When I debate on important issues like climate warming, I always collect & read about my scientific facts and not follow blindly some anti or pro global warming websites, newspapers, TV, etc,... I like to be well informed so that I can face the critics of us skeptics face to face on facts and not on second hand views from John Cambell or Al Gore.
Ok, Anon, stop being cry-baby when you face scientific facts. I am happy to simplify the explanations cited in Dr. Rossow's paper, for every one to see, such as 'parameter for climate feed-back' is currently treated as a constant. Rossow pointed out that this simplistic view is wrong as climate is a dynamical process, and that is the climate feed-back parameter is also dynamic.
I find it interesting that PC is so against any idea of climate change. Why? No skin off his nose surely? Political partisanship surely.
Someone close to me would like to alert to you to the blueing of the oceans.
"The colour of the ocean is directly related to the amount of phytoplankton in the water. The greener the waters, the more phytoplankton, the bluer indicates less.
The phytoplankton is an indication of the amount of plant life in the ocean. In fact the phytoplankton is the equivalent of the grass on land. When there is more phytoplankton, the ocean has more food to support the food chain. Furthermore, phytoplankton is essential for enabling the ocean to sequester excess carbon in the atmosphere.
The sea is one of nature's "carbon sinks", which removes carbon dioxide from the atmosphere and deposits the carbon in a long-term store - dissolved in the ocean or deposited as organic waste on the seabed. The vast quantities of phytoplankton in the oceans absorb huge amounts of carbon dioxide.
What scientists have found is that during the past decade, the amount of phytoplankton has tracked directly to the warming of the oceans. During the late 90s, the amount of phytoplankton increased leading to greener seas. But since then, the oceans have been growing bluer indicating a harsher environment for phytoplankton.
Ocean plant growth increased from 1997 to 1999 as the climate cooled during one of the strongest El Niño to La Niña transitions on record. Since 1999, the climate has been in a period of warming that has seen the health of ocean plants diminish.
The new study also explains why a change in climate produces this effect on ocean plant life. When the climate warms, the temperature of the upper ocean also increases, making it "lighter" than the denser cold water beneath it. This results in a layering or "stratification" of ocean waters that creates an effective barrier between the surface layer and the nutrients below, cutting off phytoplankton's food supply. The scientists confirmed this effect by comparing records of ocean surface water density with the SeaWiFS biological data".
This is mainly due to El Nino - but mankind is distorting the effect. But it's all rubbish to the great scientist Cresswell of course, and his mathematician friend.
Try asking someone who actually knows something.
Yes clever mathematics can make it up
I said 'poor measurements', when I should have said 'wrong measurements'. Yes, you can impute missing data, but maths cannot turn wrong data into right data.
Can you explain of what is fairly straight forward? BTW, it is not unnecessarily complex
and
'parameter for climate feed-back' is currently treated as a constant. Rossow pointed out that this simplistic view is wrong as climate is a dynamical process, and that is the climate feed-back parameter is also dynamic.
I think you have just answered your own question. And you're right, it's not unnecessarily complex, but unnecessarily verbose. Most of your posts are long and rely on gratuitous use of formulae.
You know what is really funny, I largely agree with you position.
My initial comment was not to you but to NotPC. I just wanted to point out that using graphs of changes in global temperature are misleading. There are important 'other variable' and 'other variable interactions' that are at play. However, these are not considered in many/any of the models.
The figures NotPC posted are used by both sides to prove different points. The problem is that these don't tell us anything useful.
By the way, if you look carefully, you'll notice that I wrote my post after yours (the one with the missing diagrams). At that stage NotPC hadn't linked to your diagrams. I thought I would back up your point with a simpler example, given that your post was filled with mumbo-jumbo.
Also, I am not throwing a tantrum. I just find your that your tone in many comments is extremely patronising, ergo the "hey kids, can you say global warming" dig.
Now, can I please go to the toilet Sir?
ps, that last comment from annon was not me.
Anon said...
[I thought I would back up your point with a simpler example, given that your post was filled with mumbo-jumbo]
And that mumbo-jumbo is? God, I didn't know that mentioning feedback & feedforward are mumbo-jumbo? Are you saying that a whole field of academic (Control Systems) is littered with mumbo-jumbo? Are you reverting to labeling the facts in technical terms which are beyond your understanding? When someone cannot understand they will defend themselves saying that the other person is using mumbo-jumbo, and that is exactly you, my student.
Anon said...
[Now, can I please go to the toilet Sir?]
Yes, my dear student , but remember always to flush the toilet.
*sigh*
I am talking about the diagrams that did not come out in your original post.
x --> y --> z --> w
^ |
| |
.<----.
x --> y --> z --> w
^ | |
| | |
.<--- + <---.
x --> y --> z --> w
^ |
| |
.<----------.
x --> y --> z --> w
| ^
| |
.-----------.
x --> y --> z --> w
| ^
| |
.-----------.
I'm sorry, but this is mumbo-jumbo to me.
Anon said...
[I'm sorry, but this is mumbo-jumbo to me.]
I am sorry Anon, but that is the problem with the PC bloc parsing of text that you post, not my problem. It is the real science that I posted, or shall I say, factual science that I have mentioned?
Anon said...
[I'm sorry, but this is mumbo-jumbo to me.]
That's what the post with the diagrams, that PC posted in the other link for. It is not mumbo-jumbo, it is science. If you want me to explain it to you, I am happy to do so.
Oh, by the way, if anonymous commenters don't want be confused for other anonymous commenters, then can I invite all anonymous commenters to choose a name under which (or over which) their comments are posted.
Is that so complicated?
An Anonymous commenter said, "Take a large container and throw in a layer of ice. Now put a lid on the container and place the whole thing on the front lawn and in the sun." The suggestion is that the temperature inside the bin will remain relatively constant until the ice melts, after which it will skyrocket, and the clear implication we are invited to draw therefrom is that:
a) the earth is like a large container in the sun, in which our temperatures are relatively stable (this, at least, is true);
b) once the sun melts all the ice, we're all going to die.
In other words,
c) despite the temperature record showing itself to be nothing especially frightening, numerous scary models (adduced without evidence) and complicated computer projections therefrom (performed beyond any realistic level of certainty) show us that we're all going to die.
What does this tell us then?
It tells us that warmists are less reliant on the historical temperature record (since it doesn't really support their alarmism) than they are on computer models, which as many have pointed out (including Falufulu Fisi), are trying to form too advanced a conclusion from too many coupled variables.
In other words, the only place that 'catastrophic warming' can be found is not in reality but in the models, and in the many, many proxies posed as substitutes for there being no catastrophic warming in the temperature record; and those proxies (such as the spate of hurricanes in 2005, the reports of drowning polar bears, and the melting of the snows on Kilimanjaro) are all too frequently all too unrelated or too spuriously connected to be relevant -- or just plain wrong -- and all those computer models have too many unknowns to be either valid or reliable.
And what does that tell us, kids?
...after which it will skyrocket
I never said that.
...and the clear implication we are invited to draw therefrom is that:
b) once the sun melts all the ice, we're all going to die.
And I never said that. Just goes to show you spin like the best of them.
I was merely pointing out that using global surface temperatures as an argument for or against global warming is wrong wrong wrong.
By the way, I am agnostic when it comes to global warming.
Falafulu
As I said earlier, I posted my original comment before PC linked to the correct diagrams (actually it appeared afterwards, but when I started writing it that link wasn't up yet).
By the way, I have absolutely no problem following the maths or science. However, I maintain that you have turned a relatively simple point into something extremely convoluted. I wonder why you do that?
"I never said that."
So what's your point? "..that using global surface temperatures as an argument for or against global warming is wrong wrong wrong"?
So what do you suggest is used? Global average shoe size?
And what's wrong with using a name to make your comments?
Anon said...
[However, I maintain that you have turned a relatively simple point into something extremely convoluted. I wonder why you do that. I wonder why you do that?]
Anonymous, I appreciate that comment and I have to say, that you're right in pointing that out, but the readers here ant NOT PC are quite wide relating to different domains of expertise. I am not saying that I am the only one who knows or understand about the peer review publications on climate science, but there are some engineers or physicists who read this blog , such as Dr. Brian Scurfield who had a guest post here last year (2006) in NotPC about Quantum Physics (existence of multiple universe) , Dr. Mark Sadgrove who is a postdoc quantum physicist doing his overseas postdoc work in Canada (correct me Mark if you're still in Canada), Dr Chefen (sorry Chefen that I don't know your real name) from Sir Humphries, and others who know about modeling in Physics. Also there are engineers who frequent this site such as Andrew Bates who did his degree in Communication & Control Systems at Auckland University.
My whole point in posting the peer review paper(s) in climate modeling is for the scientists listed above who can read about it. These scientists can easily understand those concepts described in the publication, that I have quoted and be well informed on the subject in global warming debate.
I am one of the few who read cross-disciplinary journals in science from Signal Processing, Computational Economics, Control Systems, Numerical Analysis, Information Retrieval, blah, blah, blah, because mathematics is universal. It means that when you understand mathematics, you basically know everything and I am not joking here. You can ask me how NASA Shuttle rocket runs and I can tell you the mathematics (algorithms) that is used there. In saying that, it means I am well informed of what is happening in science including the subject of climate change modeling.
The purpose of my post, is for the scientists & physicists (names listed above and anyone else in this blog who understands) to read and make up their own mind. The fact is, scientists and physicists mostly do read only their own respective journals and not other journals from related science disciplines. It is not hard for them to read & understand, but my post here however, gives them the chance to read something they would have never come across before because they only subscribed or read their own related journals but not one from climate modeling journal. I can understand this, because why on earth a quantum physicist, like Dr. Mark Sadgrove be reading scientific papers in 'Climate Journals'. What is the relevancy here for Mark to do that? Nothing. I simply made the post, targeting those scientists, including the general readers here at NotPC and put forward the issues that have been raised by climate scientists themselves such as Dr Rossow from NASA and his fellow researchers about the short fall of current modeling, which tells us that we are doom.
This is the whole reason I did the diagram, because physicists here at NotPC, can see and think, WOW, I never knew that? Again, it is not hard for them to read & understand, it is just that something that I have pointed them out to, as an interesting document to read, which is something that falls outside their main domain of knowledge.
This is the whole point of my post, is that to inform the scientists who frequented this blog, and I am sorry Anonymous if you didn’t understand the depth of scientific facts & models that I have raised here. because my target was for scientists. If those scientists can read about the issues of the global warming debate, then we can have more balanced views about the debate rather than one-sided view from the doomsayer proponents.
FF said, "
I am one of the few who read cross-disciplinary journals in science from Signal Processing, Computational Economics, Control Systems, Numerical Analysis, Information Retrieval, blah, blah, blah, because mathematics is universal."
I should point out to any readers who think FF is saying this just to boast, that he reads this stuff for fun ... and he genuinely can't understand why everyone else doesn't read it all too. :-)
As I said Falafulu, patronising.
I hate to point this out, but this is a blog! B-L-O-G, blog. Scientists interested in GW aren't going to get their information from this blog (no disrespect PC).
and I am sorry Anonymous if you didn’t understand the depth of scientific facts & models that I have raised here
Look, I keep telling you, I do understand them. I also keep saying, your points really aren't that complicated. You just try to make them look complicated by being long-winded and convoluted.
You may know everything because you know maths, but it has become patently obvious that reading comprehension isn't your strong point.
NotPC said
So what do you suggest is used? Global average shoe size?
Well, according to Falafulu, yes because, and I quote "clever mathematics can make it up".
In the case of my example, the amount of ice left in the container would probably be a better indicator.
And no, I am not going to build an ark and collect two of each animal.
Bob
Bob said...
[I hate to point this out, but this is a blog! B-L-O-G, blog. Scientists interested in GW aren't going to get their information from this blog (no disrespect PC).]
Yes, that is why Dr. Chefen is a participant at Sir Humphries, because physicists are not going to get their info from his posts, but it is for the average Joe who are going to benefit from knowledgeable people like him. Chefen's post ranges from describing the over-reliant by climate scientists in using black-box techniques such as Neural Network, etc. Average Joe does benefit from such post because how, many out there who know Neural Network? It is the same here. I make my post to target knowledgeable readers in this blog and I also try to make it easy as much as possible, so that non-expert readers can comprehend.
For example in the other thread, I described of using digital filter algorithms to eliminate high frequencies thus leaving the lowest frequency component from typical temperature climate pattern in order to find out the long-term evolving pattern instead of just using the simple linear regression (which is obviously misleading). Simple linear regression is just completely inappropriate, since climate temperature pattern evolution is stochastic. Does the average Joe know about this? NO. Would any reader benefits from such hints? YES. Would any scientist come here to look for such answer? NO. They get their info from reading their own peer review journals. Blogging is just one way for hooking up people from all walks of life (different level of knowledge). Can someone make an argument, by avoiding technical language? NO. If someone argues a point where technicality is avoided, then the argument is very difficult to be presented, since everything falls into something like this:
------------Example #1----------
"I don't believe Global Warming".
"Why?"
"Because , it is only a computer model"
"But scientists always build computer models, why would climate modeling be any different"
"But , it is only a computer model"
"Well, but as it has stated above that scientists always build computer models, why would climate modeling be any different"
"Again, but , it is only a computer model"
"So, you're saying that it is a computer model, then we should dismiss it?"
"Yes, something like that"
"As it has been stated previously and repeatedly that scientists always build computer models, why would climate modeling be any different"
"Again, my answer is not going to change but , it is only a computer model"
------------------------------
Now hypothetical argument presented above is everywhere around the blogosphere. Now, tell me if anything could be solved from such simple circular argument? NO. When you throw in a bit of technicality to the debate such as the hypothetical argument presented above the diaglog is going to be something like:
------------Example #2----------
"I don't believe Global Warming".
"Why?"
"Because, the models used in the IPCC report are all black box statistical inferences and not physical realities"
"Can you give an example?"
"Yes, I can give heaps, but I wanted to start with these 2. Using Naive-Bayes algorithm is unreliable. Using Monte-Carlo simulation is also unreliable, because they establish no physical causation at all, just pure black box inference. Climate is a physical process, obeying the laws of physics which are causal in their nature. There has never been a discovery of any 'laws of physics' in the history of science that was found out by way of statistical inferences. NEVER."
--------------------------------
Can you see how the argument changes from , Example #1 to Example #2 ? Which is more informative to the reader? I know your pick, which is Example #1. How about giving the subject some technicality avoiding complexity but also make it informative to the general readers? That is what I have done here and I am sure that if you find it too complex, then it is your problem and not mine. Falafulu tries to reach out to the wider community of readers, if I can make complex topic as climate change more understandable (highly technical & but explainable and simple), then it is a good thing.
Bob said...
[Look, I keep telling you, I do understand them.]
What did you understand? Can you explain the solving method, that Dr. Rossow described in his paper? He quoted Rk4 (Runge-Kutta of 4th order) as one of the algorithm to use?
Give me a full description of why Rossow wants to use Rk4 and its possible shortfall as well?
If you're here to argue scientific facts, then lets do that, but if you're here to argue for the sake of arguing and not discussing science, you're wasting my time.
Falafulu
I agree, example 1 is a stupid pointless argument. However, argument 2 is just as pointless to the lay person. Personally, I am familiar with linear, non-linear and stochastic models, Bayes theorem, Monte-Carlo methods etc etc. But Joe Blogs probably isn't.
I suggest to you there is an example in between example 1 and example 2. It's called a happy medium.
What did you understand? Can you explain the solving method, that Dr. Rossow described in his paper? He quoted Rk4 (Runge-Kutta of 4th order) as one of the algorithm to use?
Give me a full description of why Rossow wants to use Rk4 and its possible shortfall as well?
Ah, so you are saying I wasn't meant to understand anything you wrote, and you were trying to make things difficult. If not, please explain that comment. If so, I rest my case.
Bob
ps, you're choosing to waste your own time. I'm not forcing you to respond to my comments.
Bob said...
[I am familiar with linear, non-linear and stochastic models, Bayes theorem, Monte-Carlo methods etc etc. But Joe Blogs probably isn't.]
Bob, familiarity with something is completely different from really knowing that thing. You are familiar while I know and that is the difference. Look there are lots of people like you who are familiar with the stuff quoted above. Ask, if he/she know how to code complex equations, they say no. Why I know? Because numerical computing (scientific computation) is my specialist area. I can see a mathematical model's validity, limitations, potential improvement, inside-out.
You probably use a software package, such as Excel. I do develop my own codes. Don't try and pass yourself as expertise in those areas listed above, because, you don't. You use packages, while I write the real software codes to be used by people like you, who have heard about some models or familiar with the names but have no clue of how to develop the algorithms.
Now, as you claim that I put forward an example that is too complex. If you think that it is too complex, please explain the example, including Dr. Rossow's publication to the readers of this blog, and see if you can do it better than me.
FF
1 - Don't presume to know what I do and do not know. When I say familiar, I mean I know what I am talking about.
2 - No, I am not an expert, but I do know the maths behind the working models. Yes I use packages (although not excel), but I also write code. As you know, the packages are extremely limited in what they will handle. Admittedly, I write less now than I used to, but that is because the packages are getting better.
3 - The more you write, the more you prove my point.
This is what I believe:
You are a pompous, self-important, and patronising git. You have an over-inflated view of your own intelligence, and you under-estimate the skills and knowledge of others. You post convoluted, incomplete and at times inaccurate information, in an attempt to hide your own inadequacies and to look smarter than everyone else.
If I am wrong I withdraw and apologise.
However, deep down inside you will know if what I describe is true.
Good luck to you!
PS, an explanation to the example.
A statistical model might show that variable x predicts variable y (oops, I mean y-hat).
However there are potentially an infinite number of variables between variable x and y (oops I mean y-hat) that that interact with each other and may feed back into any number of other variables. Unless you know every relevant variable between x and y and their complex interactions and feed-back patterns, there is no way of knowing what the true relationship between x and y is. It is therefore impossible to know that x, mediated by a potentiallly infinite number of other interacting variables) caused y.
or in Falafulu speak:
________________________
| ______ |
| | | |
| --> x --> ??? --> y -->|
|______|
Bob said...
[You have an over-inflated view of your own intelligence.]
No, I don't, it is your own limited sphere of knowledge that makes you say that. This is typical, rather than attacking the scientific knowledge I have pointed you out to, you feel incompetent by your own standard and try to attack me personally, rather than the way I presented scientific facts to you.
Bob said...
[..you under-estimate the skills and knowledge of others.]
No, I didn't underestimate the skills of others. Again, when you feel incompetent to answer scientific facts, then of course, it is obvious that you're going to revert to such accusation just to shut me up. That's right, if you can accuse me, of under-estimating others, then I should shut-up.
I have simply pointed out the concern of 30 scientists who attended the NASA sponsored workshop and they also raised the problems with current climate modeling where Dr. Rossow chaired. You came up with ridiculous comment saying that what I have actually pointed out in Dr. Rossow’s paper is unsubstantiated. I had suggested Dr. Rossow's email to you to challenge him, and you haven't done that. Your disputes are with Dr. Rossow's and the scientists who attended this workshop and not with Falafulu. If you want to challenge Dr.Rossow, go ahead my friend, I have already shown the link for his email address in one of my previous posts. Come back & tell us here his reply to your challenge.
Bob said...
[Yes I use packages (although not excel), but I also write code.]
Everyone these days can write codes, including PC. Just grab a programming book on Java or C# from Border Bookshop and that person is on his way. Scientific computing is a completely different beast altogether and it is very complex. I can teach Peter Creswell to write JSP pages or some web applications; however, it is really hard to teach him how to write numerical simulation software.
Bob said...
[As you know, the packages are extremely limited in what they will handle.]
Yes, that is why I write my own stuff. Algorithms, that are straight out of recent peer review papers, I implement them, even those new ones are still unheard of in the industry and let alone even seasonal experts in a specific domain have never heard of them. My job is to advise them on algorithm limitations and also on new ones that have been available recently from literatures. The decision is then made on the robustness of each algorithm. Some decisions are based purely on the claim of that specific author of how robust of his/her algorithm and at times, it has to be proto-typed first and test to confirm the author's claim. The best one is always used for application development.
Bob said...
[However there are potentially an infinite number of variables between variable x and y (oops I mean y-hat) that that interact with each other and may feed back into any number of other variables.]
Now, after your ranting against what I have posted here, I see that you've agreed all along. So, I can't understand of why then you opposed points I made that you already accepted as facts.
Bob said...
[Unless you know every relevant variable between x and y and their complex interactions and feed-back patterns, there is no way of knowing what the true relationship between x and y is.]
This is where your knowledge has a hole. The field of System Identifications (SysID for short) in the non-linear domain does address this exactly as described by Dr. Rossow in his paper, is this emerging field of SysID that deals with such situations. Now, I am gonna give you some technical tutorial in Control Systems just in case you don't know. You have the data for input X and also the output W and what is missing is the Systems Transfer function, which it could be represented in analogue form (Laplace transform) or digital form (Z Transformation). The SysID algorithms identify the climate system transfer function. (It might help if you refer to the wikipedia link I provided for Control Theory). Once the transfer function is in place, then the model can be tested against possible structural relations as depicted in diagrams for Model #1 to Model #5. Re-arranging the loop diagrams WILL NOT change the frequency response of the climate system. The challenging part is to select the structural relations (or canonical form as it is called in Control literature). The model will throw out many different possible structural relations, including variables that you never know it is possible exist. These causal canonical relational structures of different variables can then be manually examined closely to see what physical realities that it might correspond to. This is why this field is called System Identification, is to use algorithms to identify possible causation structures including the unknowns in the data. Some guess work is also needed to interpret what are the relevancies of the many possible canonical structures that the model had spewed out, since computer are not God to foretell things that we have no knowledge about. The idea is to match the possible physical realities against the best fit any of the model's canonical structural relations.
Bob said...
[It is therefore impossible to know that x, mediated by a potentially infinite number of other interacting variables) caused y.]
See my previous point as I pointed out that it is possible. Read Dr. Rossow's paper where he quoted the possible use of non-linear ARMAX (auto-regression-moving-average-exogenous). N-ARMAX algorithms can identify the system transfer function in the first stage of identification process. The second stage is to iterate via a large possible number of canonical structures. Further analysis can then be made to eliminate those vast canonical structural models that they have no possible corresponding to physical reality processes that govern the climate system. Manual examinations are then followed on the remaining possible true models, and so on.
I suggest you should buy a book on System Identification and read about the subject because I know that you are new to it. Here is the widely adopted book in academic & industry from leading researcher in the field of System Identification & Automatic Control, Prof. Lennart Ljung:
"System Identification - Theory For the User"
http://www.control.isy.liu.se/~ljung/sysid/
I thought I have requested you to simplify the points made by Dr. Rossow in his paper and obviously you haven’t. You claim that I made the points that Rossow pointed out, a bit too complex, and you think can explain it better. Now, where is your explanation? You went on about “mediated by a potentially infinite number of other interacting variables” but I have shown you above, that SysID can help out here is identifying those elusive variables. I don’t call that as an explanation at all. Are you going to explain Rossow’s paper in a much simpler way as you have loudly made out here?
Bob said…
[or in Falafulu speak: --> x --> ??? --> y -->]
The model you quoted looks like that of Model #5, where PC reposted it with proper flow diagrams here. The diagrams were really hard to draw in text, because any space will be quashed up by the time you press the button ‘post’:
http://notnotpc.blogspot.com/2007/01/falufulu-fisi-main-problems-with-ipcc.html
Now, the transfer function for that model depicted in the diagram is:
T = W/X = (1 + Z)*Y
It snowed in tekapo between thye 29th of december and thye 31st of january.
On the 29th there was anly a bit of snow on the top of the mountains but by the 31st it was almost half way down at the township end and all the way down to the lake at the other end.
More evidence of global warming
This thread cures my insomnia like nothing else....! ;-)
I would like to point out one of the earlier paper in 'climate feedback control system modeling' which was published by a NASA proponent of global warming, Professor James Hansen, which is interesting to compare it to the paper published by his other fellow NASA colleague Dr. William Rossow, I had quoted already in my previous messages. I will list them again here, and again you can read (avoid the mathematical derivation part) the descriptive part which is still readable to non-expert in mathematics and see how simplistic is Hansen's model compared to Rossow's proposed model. Rossow is more realistic and closer to the real physics than Hansen's simplistic linear model. Some of the model formulations in Hansen's paper are said to be misleading as quoted in Rossow's paper. One example is, Hansen treated feedback sensitivity as a constant (static), while Rossow said it is dynamic, that is, it is a function of time, where its value changes all the time. Hansen's paper is one of the popular 'climate model' that is currently adopted these days. The question to ask is simply, "Does anyone believe that our fate is determined by a very simple linear model?".
#1) "Climate sensitivity: Analysis of feedback mechanisms"
http://pubs.giss.nasa.gov/docs/1984/1984_Hansen_etal_1.pdf
#2) "Inferring instantaneous, multivariate and nonlinear sensitivities for the analysis of feedback processes in a dynamical system: Lorenz model case-study"
http://pubs.giss.nasa.gov/docs/2003/2003_Aires_Rossow.pdf
Shall we wait for the arrival of complex mathematical modeling for the analysis of climate systems which will give us a better understanding rather than pushing for a consensus too soon? IMO , I think so.
Here is an email reply from Dr. Rossow about his view on climate feed-back system.
------------ Rossow's Email ------------
Falafulu, One of the main points of this workshop:
http://grp.giss.nasa.gov/reports/feedback.workshop.report.html
is that the available feedback control theory (at least that used by climate researchers) is based on a linear or linearized formulation that is not appropriate for the climate problem as the climate system is too complex-nonlinear and too poorly observed. As for whether a theory can explain the cause of global warming, I would say that only analysis of observations can establish causal linkages -- some of the needed observations are either lacking, not accurate enough or for too short a time period -- and that, here too, the analysis techniques commonly used are not up to the job, being too simple and linear.
You can find a reference on the NASA GISS website under my name (Aires and
Rossow 2003) that shows why the conventional formulation of feedback won't work
for climate.
------------ End Rossow's Email ------------
Interpreting Rossow’s reply email (“conventional formulation of feedback won't work for climate”), he basically says, Hansen’s model is incomplete and must be dismissed because it does not work.
PC, this post was just too good to summarize so I just reposted the entire thing (with your comment and attribution) in my blog.
I hope you don't mind, but I couldn't find your email addy in order to ask permission.
If you're unhappy about it I'll take the post down. K.
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