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Actually no DA Morgan. I use Monte Carlo Simulations every day to evaluate sports prediction models that I have. Working out probabilities of teams finishing in finals, and with variances included. This is predicting not the analysis of games gone past.

With regards to analysis past temperature, this is not prediction, and I need not use Monte Carlo simulations to do this.

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G'day all,

Wow, a science based, climate (sort of) thread. Terrific!


Scientific Orthodoxy and Research Being Published

OK, Count, to your question. How do I prove a negative? If critical articles are not published just where is the evidence of their non publication? I'd have to have access to the journals and their correspondence to look at their rejections and just why they were rejected.

I have been reading "Kicking the Sacred Cow" by Hogan and while a lot of it is sailing over my head because I'm not an astrophysicist (although I once wanted to be but that is a rather different thing) and do not know a great deal of the fundamentals of biology at the level of the construct of immune systems and just how sight works at the molecular level, it still is a fascinating book. A great deal of it is to do with "unfashionable" science. I don't have the book beside me and today I'm not able to move much at all so I'm not going to go get it but there was a scientist who's expertise was plasma [Mind finally kicked in, his name was Alfven, maybe Han or something similar as the first name]. He seemed a clever fellow but for almost all of his career whatever he did, he was not only ignored but often called names. Now his theories were so impressive and because his entire approach was on the basis of what was observed driving the theory rather than postulating a theory then trying to find a world that matched the theory, eventually a number of his theories had to be accepted into the mainstream. The point isn't who this fellow was at all but rather the orthodoxy of science and just how extremely good scientific endeavours can be completely ignored.

Alfven was attempting to persuade a theoretician about his theories. I remember he was from Cambridge but that?s all. I do remember what he said though because it just amazes me how arrogant scientists can be when they think their theories are so sound that it is beneath their dignity to even look at any suggested alternative. Mr Hogan makes the point that peers of Galileo refused to look through his telescope and that this Cambridge fellow was keeping the tradition alive and well. Alfven had set up some sort of experiment in his basement to show by observation what he was getting at. The reply was: "It was beneath my dignity as a mathematician to look at a piece of laboratory apparatus!" Sort of reminds you of our Mr Morgan, doesn?t it. [No offence, Dan, just couldn?t help the playful dig]

Alfven was awarded a Nobel prize in 1970, partly for a theory he didn't agree with! Despite this, a major work that had been accepted for publication by the New York Magazine in the 1980s was rejected by the New York Times science writer because Alfven was "a maverick" and not well accepted in the science community. It would seem that winning a Nobel prize isn't even enough to get something published! By the way Alfven was not the author of the paper. He just helped with it and his theories underpinned much of it. I think the article was by Lerner but my memory from a book I read last night isn?t that great so those that know their astrophysics and find that I have attributed various things incorrectly, please forgive the errors. The point is not about astrophysics but about the orthodoxy of science, even in the modern era.

Normally, the examples used about problems getting research published relate to people as far back as Galileo. My normal example is the theory of plate tectonics but even this is early 1960s. I rather like the Alfven example because it is in the ?modern? era of science.

A highly modified form of the article was published some years later, when further research by others started to bring the whole theory of plasma as a driving force in the creation of galaxies etc, around to the original theory proposed in the rejected publication.

So, Count, I cannot readily prove a negative. I use the Oreskes example because it does relate to Climate change. It is in the modern times and there are considerable documentation on the Internet to support the effort to show how blatantly biased the original research was or at least that it had major flaws. I also use it because the Oreskes research is still very often used to ?prove? that global warming has long ago been accepted by all those in Climate Research and by the general scientific community. Bugger the fact that later research shows that real climate scientists, that is scientists that are in the business of studying climate, are far from convinced about global warming and it is only when you move away from those that specialise in the science that you get a vast majority that support it. A bit like so many scientists willing to sign their name to some letter or other condemning some aspect of modern life, except those scientists who are actively involved in that area of research.

It has happened to me personally, but that isn?t proof because obviously I could be making this up. It has happened to people with whom I?m acquainted but if they make a living in climate science they generally do not want anyone to know they had research rejected for publication. It is a very good way of ensuring you get no further funding.


Regards


Richard


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Richard, yes there are cases where scientists have been ridiculed who turned out to be correct.


In this case, you'll probably be more successful if you go with the orthodox approach and show that it is wrong. E.g. you could simulate typical data for weather stations, satellites etc. based on an artificial model that describes a situation where there is no trend toward higher average temperatures. You then analyze that fake data using exactly the same methods as are normally used...

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G'day Count,

I actually wrote a rather long post about exactly what I was aiming to do with my research. This included obtaining the raw data where only monthly averaged data is currently available and the avareging technique does not accord with a "standard" I wish to impose or is unknown. It also includes having several data sets. Starting with the raw data. There would be a set weighted for concentration just like the Monte Carlo bit here suggests and there would be adjusted data for urban effect and other adjustments used in a standardised form as well the method currently adopted by various groups. The whole idea would be to show the effects of adjustments and whether they are necessary to get to a more accurate figure or just manipulate the data. I would also like to include a data set where all known effects on the weather station are recorded and their effects analysed. This, however, would have to be a very small subset because of the immense amount of work required. I have gone to the trouble of obtaining histories of weather stations and it takes a massive effort. Often the detail is just not known and you have to snoop around with town historians, very old members of a community, retired postal managers, etc. This is not something you can do for 7,000 weather stations or even 700. I was hoping that by setting up a standard averaging data set that representative locales for each region could be selected and those could be examined in great detail but am not sure whether this is feasible and whether I will receive any assistance or not.

My biggest problem is I have no expertise in the analysis of data. I freely admit I had never heard of Monte Carlo (except as a gambling location) before this thread. My expertise lies in looking for flaws in other's work with data. It is not the same thing at all.

At no point have I thought to use similations. You may think it the "orthodox" approach but I consider similulations another name for guessing and cloaking it so it appears to be science.

I do not even understand your reasoning in similuting "typical" data for weather stations that shows no trend up. I wouldn't know "typical" data for a weather station if it jumped up and bit me.

I sort of understand your point in using some made up set of data and applying the adjustments made by NASA, and various other institutes to see what happens but the trouble is I'm sure that if I created five different data sets, I'd get five extremely diverse results. I could create a data set that showed the adjustments caused huge increases in the trend and I'm sure someone else could create data that showed the reverse. It would depend on what the data was.

I do know for instance that the majority of weather stations show a cooling trend. It seems that the trend upwards is because those that show a warming trend do so at a higher rate than those showing a cooling trend. The other problem is that very cold climates have much wider variations than say the tropics, where the variations are very small. So having a great many tropical weather stations showing a very slight cooling trend can be completely obliterated by adding in only a small number of arctic stations that show a pronounced warming trend.

So the data set that showed no trend could be devised that had an even distribution of upward trends and downward trends. Applying the adjustments would then give you a certain result. Another set showing no trend could be closer to the real world, with a higher number showing a cooling trend of a smaller amplitude than the smaller number showing a warming trend with the overall result of no trend. It would not take much actually to change the current data to show a cooling trend. You only have to change a few intense warming trend stations down to negatives. But doing the same adjustments would yield quite a different result.

I believe that all this would show is that the bias inherent in the production of the false data in the first place would determine the result that was obtained, and thus any analysis could be rightly discredited.

I do not hold much hope for raw data, consistently averaged and using standard adjustments applied in a rational fashion, even if it shows no cooling trend, in the unadjusted raw data, in the averaged data, in the adjusted data, will be widely accepted. But at least a better alternative data set will be available for the few that do realise that there are serious flaws in the current data set. With time it might actually start to be used, especially if the climate catches up on those that are so sure of global warming and a cooling trend turns up.

That is a big fear of mine actually. You'd think I'd welcome a sudden cooling trend because it would support my arguments about the flaws in the research and data. But today there was a major article in our local paper about fish stock depletion. This is a serious problem. Overfishing could have horrendous concenquences for other reasons than simply fish will disappear from the tables of people. Actually fish will not disappear as a great deal of it is now farmed but overfishing is still a very serious problem. Whole species are disappearing and may completely disappear or take centuries to regenerate. But this whole article had to mention global warming as a big issue in that the loss of fish would mean that the oceans would be more susceptibla to global warming. That slant will doom this research and similar research to being ignored if global warming is shown to be a fantasy.

Indeed, a great deal of science will be looked upon by politicians and the general public with great suspicion. It took years for people to realise that viruses and spyware were not being made up to sell software but rather a problem that really needed tackling simply because most people had been taken in by the Y2K "disaster" predictions and had become much more cynical. Imagine the impact of global warming to be shown as a complete con. Global warming leaves Y2K for dead in the prediction stakes, and in the amount of issues that are now completely tied to it. Environmental groups could find themselves bankrupt very quickly, even those such as WWF or small groups interested in protecting a local species really in severe danger. Who's going to care about pollution in general when the biggest pollutant for years has been said to be CO2, a benefcial gas, that does a great deal of good. DDT at least actually did do some harm, even if it was enormously exagerated. CO2 on the other hand is not a pollutant. It might be contributing to a climate change but otherwise the gas has no detrimental effects in the quantities currently in the air or predicted before carbon based energy starts to peter out.

So a sudden realisation that global warming isn't really based on good science especially considering the huge amounts of money given to the research of the "problem" by various governments, by donations etc, imho, would be a disaster, almost as bad as global warming itself. Unlike an argument over the origins of the universe and the big bang, global warming, is thought by the average person to be a problem that will effect them. So if tomorrow it was shown that the big bang is not likely to be correct, little harm would occur to science. Show global warming to be less than certain, or worse, completely wrong, and the harm will echo for probably decades.


Regards


Richard


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I've finally got a meaningful response from Jonathan and I've replied on his blog:

Jonathan:
"But if you want error bars, the most recent 9pm analysis from 1960 onwards suggests a 0.0046 degree ceclius increase per year +/- 0.0076 which is statistically insignificant."

Count Iblis:
Ok, let's work with this figure. You are 95% sure that any trend is between (0.0046 +/- 0.0076)?C/year = (0.46 +/- 0.76)?C/century.

(Actually, you cannot strictly say 95% sure, for that you must assme a uniform prior on the possible trends.)

The figure given by climate scientists for the temperature increase in the last 100 year lies within your bound.

That's why your analysis is not relevant. It's simply not accurate enough to see the signal claimed by climate scientists.

You can always assume a null hypothesis that says that there is no change, do an analysis that can only yield a significant result rejecting that hypothesis if you have a huge effect and then claim that just because that isn't the case, the null hypothesis is not overruled.

The null hypothesis is already overruled by more accurate research involving many thousands of weather stations and satellite data.

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Richard,

About the simulatons, you could just take actual datra from weather station sampled over a limited time span, say ten years. The statistical distribution can be studied. And then you can let a computer generate simulated data that simulates any trend on top of which there are random fluctuations and short term natural variations like El Ni?o etc.

The simulation does not have to be very acurate, because what you are testing is if the data analysis algorithm can subtract the random fluctuations plus any short term variations to obtain the long term trend. So, if you simulate the smame trend and add a hypothetical 20 year period oscillation, the algorithm should still produce the same result. The algorthm may only fail if you feed it with unrealistic data.

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Finally a meaningful response? I've given you meaningful responses all the time. Did you read my response (I note that you have not replied):

"Well if you want to throw the entire method of statistical research out the door and conclude what you want to make of the results to suit your need then go ahead. But the results are insignificant. There is no evidence to prove an increase or decrease in temperature. But feel free to spend gozillions of dollars on something that hasn?t been proven let alone proven of mans influence.

But if you want to go against the method of science, then here are the results for the times done on the webpage so far:

9am: -0.4 +/- 0.08 (wow a significant decrease!)
3pm: -0.1 +/- 0.1
9pm: 0.46 +/- 0.75
3am: -0.1 +/- 0.2

Hardly conclusive, and in fact, let me remind you again: "There is no evidence to prove an increase or decrease in temperature. Insignificant evidence."

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Jonathan ... are you really and truly of the belief system that essentially all climatologists ... those at colleges and universities throughout most countries, those at CSIRO, those at NOAA, and those at NASA are less knowledgeable than you are?

Do you think them less capable of analyzing data?
Do you think them less capable of drawing conclusions?

Or do you think they are all part of a huge international conspiracy to defraud you and major corporations of thier profits? In which case you might wish to explain how a bunch of PhDs, harder to herd than cats, could possibly pull this off when it turns out that spy agencies such as the CIA and KGB could not.

It is truly impossible to take you seriously when you can not explain why CSIRO and NOAA and NASA are all wrong and you, wholly lacking in credibility in climatology, are correct.


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Quote:
Originally posted by JonathanLowe:
Finally a meaningful response? I've given you meaningful responses all the time. Did you read my response (I note that you have not replied):

"Well if you want to throw the entire method of statistical research out the door and conclude what you want to make of the results to suit your need then go ahead. But the results are insignificant. There is no evidence to prove an increase or decrease in temperature. But feel free to spend gozillions of dollars on something that hasn?t been proven let alone proven of mans influence.

But if you want to go against the method of science, then here are the results for the times done on the webpage so far:

9am: -0.4 +/- 0.08 (wow a significant decrease!)
3pm: -0.1 +/- 0.1
9pm: 0.46 +/- 0.75
3am: -0.1 +/- 0.2

Hardly conclusive, and in fact, let me remind you again: "There is no evidence to prove an increase or decrease in temperature. Insignificant evidence."
What is inconclusive is your analysis. The error bars you first presented were way higher, b.t.w. So, I'm assuming that that you got them wrong:

http://www.blogger.com/comment.g?blogID=36333052&postID=116250634123923712

As long as the measured temperature increase of 0.6? C +/- 0.2 ?C per century falls within your confidence interval, your results are worthless. You could only have detected a statistically significant temperature increase with your limited amount of data if Australia had warmed up at five times the rate of the rest of the world.

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Hi Morgen, can you point me to the direction that the CSIRO and NOAA and NASA have done analysis of australia's surface temperature data over the past 150 years? I understand there is plenty of research out there proving increased temperatures elsewhere, but there is very limited research into temperatures in Australia (and parts of Antartica).

Surface temperature could well be increasing around the world, but all I am saying is that this is not happening in Australia and in parts of Antartica. I don't believe that this is going against hundreds of papers of research. It just hasn't been done for Australia.

And Count Iblis II, you're arguement is that my results dont agree with what you believe so I must be wrong? Show me the error bars that I first presented? Are you concluding that I concocted the results? I'm happy to give you the original data so you can come up with your own confidence intervals if you want.

And by the way, thanks for pointing out that 150 years of weather data is limited. So why are the world making godzillion dollar decisions based on limited data?

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Also, forgot to mention Morgen,
the fact that you say I am "lacking in credibility in climatology".

This is true, however, I am a qualified statistician. There is no profession better in the world than a statistician to analyse the data given by the ABM's weather stations. Analysing statistics, is after all, what statisticians are experts in above everyone else.

You might think that climate scientists are better, but I disagree. When studying we used to analyse statistics from all sorts of departments from Biology to Politics. THey gave us the data, we gave them the results/predictions/analysis. Because we could do it better than them. Having less knowledge in the area of analysis often helped the analyser from being biased in his analysis.

Essentially, this is what I have done. I have not attempted to prove how or why CO2 effects the environment, or discussed cloud formation, or ocean currents, but have meerly analysed the surface temperature data in Australia to conclude that Australia shows no significant increase or decrease in temperature.

I am not saying why this is, or giving explanations. I'll pass back my analysis to the climate scientists to suggest why there has been no significant increase.

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"So why are the world making godzillion dollar decisions based on limited data?"

That's not why people are concerned about global warming. It's because we are pumping enormous amounts of CO_2 in the atmosphere. And CO_2 is known to be a greenhouse gas. This is not based on climate data that one could argue with, but it is based on "hard physics". You can observe in the lab and calculate from first principles the absorption spectrum of the CO_2 molecule so, you know exactly what its properties are.

The data is only relevant in so far as to validate the climate models. If you pump large amounts of CO_2 in the atmosphere then it is beyond reasonable doubt that it will get warmer. But you want to know exactly how strong the positive and negative feedback mechanisms are to predict the consequences of this.

Even if a particular region of the world would not get warmer that won't necessarily spare it from the negative consequences of global warming.

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Jonathan Lowe asks:
"Hi Morgen, can you point me to the direction that the CSIRO and NOAA and NASA have done analysis of australia's surface temperature data over the past 150 years?"

Lets see how difficult it is:
Step 1: Go to www.google.com
Step 2: Enter "CSIRO" and "Climate"
Step 3: Review the 900,000 hits

If you had to ask you should stay away from the subject.

"the fact that you say I am "lacking in credibility in climatology. This is true, however, I am a qualified statistician."

So given you are a statistician you feel completely comfortable expounding on the subject of climatology? Why not apply your skills to medicine? to quantum mechanics? to geology? to biomechanics? The short answer can be found in something Samuel Clemens wrote 150 years ago.

"There are three types of liars. Liars, damned liars and statisticians."

Meaning you substituted the ability to marshall numbers for actual subject matter expertise. Sad!
Very sad. That you would think manipulating numbers in a computer substitute for the reality of the laws of physics. And the laws of physics are quite clear on the matter.


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Count Iblis II, I'm just saying that Australia and parts of Antarctica have not increased in temperature of the ast 150 years. Period. Nothing else. Whilst it makes sence that Co2 would increase temperatures like it does in a greenhouse, it obviously is making no significant effect on Australia and parts of Antarctica. Let me say once again. There is no evidence to say that Australia and parts of Antarctica are warming up.

DA Morgan,

?So given you are a statistician you feel completely comfortable expounding on the subject of climatology? Why not apply your skills to medicine? to quantum mechanics? to geology? to biomechanics??

Yes, yes and yes. I think you misread what statisticians do. We are given data, we analyse it and send it back. And that is exactly what I have done. Analysed temperature data, proven that Australia and parts of Antarctica have not heated up. I have not said why or how, but that is what I found.

Whilst I could easily google for results as you suggested (I in fact had a go!), you did not answer my question. I am after scientific papers that analyse Australian temperature data to prove that temperatures have increased in the past 150 years.

I am afraid this is getting beyond a joke. So many people quote that famous quote (actually by Benjamin Disraeli later written by Mark Twain), in order to damn any statistician.

And in fact you got the quote wrong, perhaps on purpose. It is: ?There are three types of lies. Lies, damned lies and statistics?. A very big difference. It means that there is an all-too-frequently an intension by a person to interpret data based on the conclusion that they wish to draw.

So just because someone said that, you immediately assume that I have? I have given you my method of my analyse. Feel free to analyse it and peer review it. Perhaps even, as any good scientist should do, try to do the same analysis that I did and see if you got similar or different results ? the key to science.

But do not, and I repeat DO NOT, accuse me of making up, marshalling numbers, and manipulating numbers without any scientific proof whatsoever. Such an accusation without any proof, logic or reason means that you are very lucky to get a response from me at all.

This is hardly a way of conducting scientific discovery. In fact this type of self absorbed talk is in direct contradiction to how science advances. How is science meant to uncover the truth if whenever someone has research that goes against others another?s, you simply toss it away accusing it of all sorts of scientific treason. If I knew you, I should think better. You are lucky that I don?t.

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JLo wrote:
(sorry couldn't resist the pun on your name)
"I think you misread what statisticians do. We are given data, we analyse it and send it back."

Granted. But you've gone one step further. You've drawn conclusions in a field of expertise in which you have no expertise and that is the problem.

Do you think you could do that given data from a collision of pions and electrons? Or tree rings and supernovae explosions?

My point is that you have crossed the line from science to pseudo-science. Had you received the data from a climatologist, performed the analysis requested, and passed it back again for conclusions to be drawn I highly doubt those conclusions would have been the same. And if you disagree why haven't you co-published with someone with expertise in the field?

You seem to think, it appears to me, that your numbers can prove a conclusion that violates physics. That we can warm the oceans but Oz is unaffected. That we can prove general warming of the entire planet but Oz is unaffected.

It is far more likely you are incorrect than that essentially everyone with a PhD in climatology has had one stubby to many.


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I have been given data from the Australian Bureau of Meteorology. I analysed it, and that is what I found. I am currently in the process of making a paper about the results thru my PhD in statistical analysis of climate science. I am just telling you of what I have found.

I ask you again, please point me in the direction of a journal peer-reviewed paper about the analysis of trends in ground temperature in Australia that one can replicate. Please, please do this.

Also, please tell me how I have "crossed the line".
You claim that I am now Pseudo-Science? Let me clarify what pseudo-science actually means, because I am sure you either do not understand or are looking at mirrors:

"A pseudoscience is any body of alleged knowledge, methodology, belief, or practice that claims to be scientific but does not follow the scientific method"

Exactly what I classified you as in the previous post. Telling someone that they are full of bs, only because they have results that conflict with your point of view, without any evidence to back your own statement up.

Please explain to me how I have not followed the correct scientific method, otherwise, take back your comments.

It is of deep concern that it has got to this. I would have hoped that we would have a critical debate about the results and method. I would have hoped that you would suggest that my results are not correct because I analysed them in a wrong way, used the wrong method, or perhaps even received my data from an unreliable source. But, I?m afraid, all I am getting from you is character assassination. Such a shame. Hardly science.

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Jonathan Lowe wrote:
"my PhD in statistical analysis of climate science."

Forgive me please but a quick review of your posts in this thread include:

1) "Being a statistician I decided to test this. I bought all the data from the Australian Bureau of Meteorology to do some analysis."

2) "Hmm no idea how monte carlo simulations has anything at all to do with temperature analysis, but anyway."

3) "I can admit that some people will obviously respect Climate scientists who are working int he field over me"

4) "I use Monte Carlo Simulations every day to evaluate sports prediction models that I have."

5) "I do know a lot about Monte Carlo analysis. In fact I started my Masters Thesis on it, before changing."

Now your PhD you state is in climate science. You can, perhaps, understand my confusion given that just yesterday you wrote: "Gust of Hot Air is a blog outlining my own statistical analysis of Australian Weather. I am Jonathan Lowe, and have completed by Bsc(hons) in statistical analysis as well as my Master of Science. I have done 2 years of my PhD."

(and to some people don't believe I do research before I post: amazing).

I think you can begin to see why I have a hard time taking what you write seriously. Two years in a PhD program is not a Doctorate. And this is not helped when I read things in the Melbourne media such as: "Andrew Bolt abused my research: climate scientist by Ministry of Truth Tuesday October 31, 2006 at 06:35 PM" in a thread to which you contributed.

I looks to me far more like spin than science. And science that does not correspond with known principals of physics is a very hard sell.


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the meaning of highlighting the 5 quotes? I'm not getting that. I started my PhD in sports analysis only to leave because my own business was suceeding too much. Now that I have my work almost automated I am going back into a PhD from scratch in climate change.

I contributed to Andrew Bolts (dodgy) research??? Please. I have not contributed to anything that Bolt has said, but posted comments on his blog once or twice, much the same perhaps as this forum.

And even if I had, where is the crime? Keep digging Morgan, keep digging.

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Nothing expresses my thoughts better than the statement of the Secretary-General of the United Nations: Kofi Annan.

"Secretary-General Kofi Annan told the U.N. conference on climate change Wednesday that those who would deny global warming or delay taking action against it are "out of step" and "out of time."

"Let no one say we cannot afford to act," Annan declared. The United States, for one, contends that reducing global-warming gases would be too costly to its economy.

The U.N. chief lamented "a frightening lack of leadership" in fashioning next steps in mandatory reductions of global emissions. "I would want leaders around the world to really show courage and to know that if they do, their people and the voters will be with them," he told reporters after his speech.

The chief U.S. delegate, at a later news conference, countered that Washington has been a leader with "groundbreaking initiatives" on clean-energy technology. Those are voluntary programs, not mandatory.

Hundreds of delegates from some 180 member nations of the 1992 U.N. climate treaty were entering the final three days of their two-week annual meeting, where they've been working on technical issues involving the Kyoto Protocol, which obliges 35 industrial nations to reduce emissions of greenhouse gases by 5 percent below 1990 levels by 2012.

The United States and Australia are the only major industrialized countries to reject that 1997 treaty annex."

Source:
http://www.cnn.com/2006/TECH/science/11/15/annan.climate.ap/index.html


DA Morgan
Joined: Oct 2006
Posts: 87
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J
Joined: Oct 2006
Posts: 87
Thanks Morgan, but Australia and parts of Antarctica are still not warming up. Is this a science forum or a politics forum?

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