Climategate II

Posted in Environmentalism, Globalism on December 13th, 2009 by Jacob
13 December, 2009

As expected, Climategate has done nothing to temper the enthusiasm of the climate ideologues in the funfest of Carbonhagen, even the Danish sex workers harnessed themselves to the task of ensuring a successful event by opening their hearts (and their legs) to the delegates.

Climategate has NOT taught us anything we had not known before, it merely added another level of confirmation that global warming is a fraud of gigantic proportion. I shall explain that later.

The main stream media, who finally could not ignore the story went into a “yes but” mode, glossing over the fact that the “robust science” is a work of scientists who are more preoccupied with politics s and funding that with science. I is all a sceptic stunt to undermine the Crapenhagen conference, and the global warming is still as real as ever and the current cooling is only a natural variability after a long warming and still 2008 was the fourteenth hottest year since …. etc etc etc, whoopee!

Natural variability hey? and what would you call the warming of the 20th century after the Little Ice age that ended at the end of the 19th century? If you go by Climategate that has never happened — Prof Michael Mann, the father of the Hockey Stick theory (as we saw in Climategate I) religiously prefixed the terms Medieval Warming Period and the Little Ice age with the words “so-called” as if they had never happened. And they call us “deniers”(?!)

Sure, the Hockey Stick theory is now truly buried, even by the dogmatic IPCC. I was shown to be a plain scientific hoax but the charade goes on.

The Climate Models

The global warmers tell us ad-nauseam that the climate models (there are about six versions) provide the scientific proof to global warming.

Let me explain what a model is.

A climate model is a mathematical model, or model for shot. A model is a set of mathematical (including statistical) calculations, known as algorithms, attempting to simulate the real world. A model is as good, or bad, as the rules and the data put into it, for example:

Suppose I want to model trains time table; I know the distances between stations, I know what speed the train can do, therefore I know how long it takes a train to get from one station to the next. I allow 2 or 3 minutes for every stop and bingo I have a model that simulate the run of one train. But this only a start.

My aim to provide service to the travelling public so I need more than trains, I know how many passengers I need to carry thus I can work out how many cars each train will have (consistent with the length of platforms), I space the trains and run my model to ensure that the no two trains reach a station at the same time, or meet each other in the opposite directions, if they use the same tracks on both direction.

But I also know that the vast majority of the travelling public require to travel to and from work in the morning and the evening, so I run more and longer trains during rush hours. As more people need to get on and off the trains, I need to allow more time at stain stops, meaning yet more trains — it is getting complex but manageable because ,so far, I have dealt with known factors.

The difficulties starts emerging when I deal with known unknowns; mechanical breakdowns (trains and signals), accidents, weather delays (floods, snow, heat waves). I use probabilities that I work out from past records (data) and build it into my model, I then run “what if” scenarios (called sensitivity analysis).

Eventually I will have a model simulating the whole railway network in a quite reliable MODEL, the technology to do it exists, it was done successfully many times in the past, so far so good. BUT,

How successful would be my model if I try to do it for a city in a country that has never had trains before?

Not much because I don’t have the required data to construct my model — I would need to rely on guesstimates and experiences in other places and ASSUME that it is relevant. In technical wards, I built assumptions into my mode.

As I don’t really know the size of the train travelling public, I would try and estimate it from other available data, say, buses statistic – The bus data becomes my “proxy”, that proximates my train travelling public, is the yardstick by which I guess the size of the travelling public, it is not perfect but it the best I have.

You can now see, that usefulness of such model is limited by my lack of data, my confidence in my model would be shrunk by comparison to the earlier model.

What all this has to do with climate? I hear you ask; the climate models akin models that simulate trains that have never run (as yet). They rely on data, such as tree rings, ice core samples (called boreholes), and other proxies to simulate temperatures for the times when there was no methodological collection and recoding of climate data on earth which is the whole of the planet’s 4.55 billion years history barring the last 200 years at the most.

Climate Proxies

There is a legitimate debate about how well the various proxies represent past climate data. Such debate is a matter for the science to resolve and I am not going to buy into it.

This is not a criticism on the use of proxies, science has to use what is available to it, but we must bear in mind that whilst the bus travelling public may give us a good clue as to how many train passengers it is only an indication, that may or MAY NOT come to fruition.

In my second train model I would take bus data and CALIBRATE it. I would try to run my model a number of times with different assumptions such as 50% 60% 70% of the bus passengers will travel by train whiles it start running.

The climate science does just that, so as you can clearly see, it is an educated estimate, at best, and with all the care I take, I would not stick my house on being 100% right, would you?

It may take some 10 or 15 or twenty years before the new trains, which I just modelled, will start running. Would you now, base on my MODEL, commit yourself to be at the station at 8:17 am on Monday, 2025? of course not. Yet these global warmers not only want us to commit ourselves to be in station that has been built yet but they also want us to buy the tickets, (carbon credits) NOW because the models say so.

But there is more.

Suppose I see a bump in the number of passengers between 2pm and 3:0pm (presumable caused by school kids going home) and I ignore it as a “natural variability” as it does not suit my model. This is exactly what the Hockey Stick theory does — ignore available data because it spoils the model!

In fact, it is worse than that, the global warmers goes further and tell us that the trains are already running. Yet a mere 8 years into their predictions and the trains are running indeed but in the wrong direction!!! yet they insist that the model is 95% accurate.

This bring us to the question of:

How Certain Are The Models?

We often hear that the accuracy of the models are within 95% probability. No, it is Not!!!

The warm mongers are in fact referring to the statistical term known as degree (or level) of confidence, (also Confidence Interval) which measures the accuracy of their models.

That term has little to do with probability. It is a statistical measurement of an interval , a “window” around the model result into which a certain percent of the eventual and real life events expected to falls. It is typically 95% or 97.5% but it can be any number under 100%. I’ll give an example

Taking the trains again, it means that within a certainty of, say,95% a train will arrive within a time” window” around the schedule time. In other words, 95% of trains will arrive within a certain time before or after the appointed schedule time. Naturally, it stand to reason that the larger the time window is the more trains will be “on time”.

As you can see 95% confidence interval is meaningless without knowing what is the actual interval — it is one thing if 95% of trains arrive within one minute of the time table and a completely different story if 95% of trains arrive within three hours of the schedule time and still “be on time”.

Climate is a lot more complex than my trains model example and whilst in the case of running trains we know all there to know about what affect the trains running on time , when it comes to climate science, we don’t even know that the track is reaching the next station let alone the our final destination.

The best science do is forecast the weather reasonably accurately for FOUR DAYS into the future, any further then that is an educated guess and they want to tell me that they can tell the weather in 2050?

Enjoy you cold showers in the dark if you still think that you are saving the plant.

All aboard!

© copyright Jacob Klamer 2009 — all right reserved

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Climategate I

Posted in Global Warming on November 29th, 2009 by Jacob
29 November,2009

Can you imagine that you are about to go into a dangerous military mission just to discover that the intelligence reports on which you mission is based, are fraudulent, would you still go on that mission?

Can you imagine that you are about to board a plane and just to discover that the licences your pilots are holding are forged, would you still board that plane?

Can you imagine that the new breaking system just fitted on your car is based on a mathematical model which was never been road tested, would you still take your car for a spin?

The answers of course are no, no and no.

Yet our politicians are going to Copenhagen to agree measure to combat global warming, in a complete disregard to the fact that the globe is cooling, in a complete disregard to the fact that NONE of the climate models used by the IPCC (the UN Intergovernmental Panel on Climate Change) forecasted the current cooling and in a complete denial to the recent discovery of Climategate.

Climategate is the term given to the posting of email files on the Internet, files that were hacked from a computer of the Climate Research Unit (CRU) of the University of East Anglia (UEA) in the UK.

These exchanges show, beyond a shadow of a doubt, that the science behind global warming is controlled by a relative small group of scientists, activists, journalists (surprise surprise) and bureaucrats whose motivation is anything but science. The pear review we heard so much about is a sham, akeen to the police investigating itself, the member of the clique review each other, reciprocate kudos and not only exclude any opposing science from the “reviw”, but use their clout to silence it.

Here is an example, on 14 October 2009, Tom Wigley, a senior researcher with the University Cooperation for Atmospheric Research (UCAR) wrote:

Dear folks,

You may be interesting in this snippet of information about Pat Michaels. Perhaps the University of Wisconsin ought to open up a public comment period to decide whether Pat Michaels, PhD needs re-assessing?

In a classic approach of the global warmer ideologues of “kick the man, not the ball”, Prof Phil Jones of the UEA replied (inter-alia):

I recall Pat [Michaels] wasn’t very good at writing stuff up.

What was Dr Michaels’s sin that necessitates a re-education Mao style ? Apparently Dr. Michaels had the audacity to publish a (PhD) thesis on the relationship between crop and climate that contradicts findings of one of the group members. So What? you ask, in simple words, it means what we all know intuitively and that is that (global) warming is beneficial to crops and we can have that, can we?


On 9 October, 2009, Paul Hudson, a climate correspondent, wrote on the BBC web site an uncharacteristic (for the BBC) article titled What happened to Global Warming? , he wrote:

This headline may come as a bit of a surprise, so too might that fact that the warmest year recorded globally was not in 2008 or 2007, but in 1998.

But it is true. For the last 11 years we have not observed any increase in global temperatures.

And our climate models did not forecast it, even though man-made carbon dioxide, the gas thought to be responsible for warming our planet, has continued to rise.

So what on Earth is going on?

He goes on to suggest, what many of us already know, that perhaps the 1990’s warming was part of a natural cycle as indeed is the current cooling.

The ensuing email discussion revealed that, other than a few guesses, the scientists don’t really have an answer to the current cooling. Dr. Kevin Trendberth of the National Centre for Atmospheric Research (NCAR) was honest enough to say that:

The fact is that we can’t account for the lack of warming at the moment and it is a travesty that we can’t. The CERES data published in the August BAMS 09 supplement on 2008 shows there should be even more warming: but the data are surely wrong. Our observing system is inadequate.

Professor Michael E Mann of Pennsylvania State University (PSU), Mr Hockey Stick (more about him later) ,suggested a real scientific way to resolve the quandary and that is to put Paul Hudson in his rightful place, he said:

extremely disappointing to see something like this appear on BBC. its particularly odd, since climate is usually Richard Black’s beat at BBC (and he does a great job). from what I can tell, this guy was formerly a weather person at the Met Office.

We may do something about this on RealClimate, but meanwhile it might be appropriate for the Met Office to have a say about this, I might ask Richard Black what’s up here?

You see, these people not only run the global climate fraud, they also in bed with the liberal media.

* * * * *

There are over 1,000 Climategate email files, mostly with more than one message in them (because of the apparent use “Reply” and “forward”) going back to 1996. I do not pretend to heave read them all, or even a significant number of them, nor do I claim to understand many of the scientific arguments and counter-arguments made, from these that I studied, somewhat randomly, it is abundantly clear that a lot of scientists’ time and efforts is devoted to sheer ideology and politics rather than to science.

Whilst there is nothing new in the fact that the science of global warming is heavily tainted by ideology and politics, a claim that had been made by many reputable scientists, we now have the smoking gun as a proof, if we even need one.

Too often we are told that the science (of global warming) is settled and passed the scrutiny of peer review. It appears that this is not so! It is more like the scientific consensus was brought about by peer pressure, rather than by peer review.

Let me pick a subject.

The Hockey Stick Theory

Had you watch Al Gore’s Inconvenient Truth, you would no doubt recall this scene where Al Gore stand in front of two large graphs.

Al Gore & The Hockey Stick Graph

The left graph depicts the Northern Hemisphere’s (NH) variation from (a long term) average temperatures going back to 1,000 years and on the right one, the average carbon dioxide (CO2) concentration in the atmosphere. You can clearly see that the temperatures were relatively stable until the twentieth century as it shot up, resembling a hockey stick on its side, hence the term.

The so-called hockey stick theory was a brain child of Prof Michael Mann (albeit not by name), the very same Prof. Mann I cited earlier. So powerful were those graphs that when shown by Al Gore they swayed many uncommitted into the global warming believers camp, I personally know a few.

The graphs, together with Prof. Mann’s theory made their way into the IPCC report with the blessing of the climate scientists and, naturally, activists, journalists, bureaucrats and the politicians.

In his book Heaven + Earth, Global Warming: The Missing Science, Prof Ian Plimer of the University of Adelaide (Australia) described how two Canadian mathematicians, Steven McIntire and Ross McKitrick, obtained Prof. Mann’s raw data (despite great obstacles put him) and concluded, amongst other things, that the data does not support Mann’s conclusions, or in their words:

due to collation errors, unjustifiable truncation or extrapolations of source data, obsolete data, geographical location error, incorrect calculation of principal components and other quality control. defects.

[- Page 90]

So much for peer review scrutiny.

In fact, Prof. Mann somehow missed two significant climatic events in the last 1,000 years, the Medieval Warming Period (MW or MWP) of 900-1300 AD (when Greenland was green and and grapes were growing in northern England) and the Little Ice Age of 1280 to 1850 AD (when the Thames was frozen solid).

Here is a comparison between the hockey stick theory and the real climate history of the Northern Hemisphere (at least).

The Hockey Stick Vs. The Real History

By 2006 the Medieval Warming period and the Little Ice Age that had been expunged from the IPCC report in 2001, miraculously reappeared with no explanation.

Was it just an error in good faith on the part of Prof. Mann? Not so according to Climategate.

Apparently two honest scientists, Dr Edward R Cook and Dr. Jan Esper, both tree rings specialists, had raised the existence of both the Medieval Warming Period and the little Ice Age with Dr. Mann back in May 2001.

(If you open the link, read it from the bottom upward, last message first. Don’t worry too much about the science itself but rather note that: a) The existence of both the Medieval Warming period and the Little Ice Age was proven by 2001, and b) How “moderate” peer pressure was applied on those who strayed from the orthodox path)

This is what Ed cook says to Michael Mann in a message dated 2 May 2001, inter-alia:

Jan [Esper] also had to compare his record with the hockey stick … the [Jan] Esper series shows a very strong, even canonical, Medieval Warm Period – Little Ice Age – 20th Century Warming pattern, which is largely missing from the hockey stick

You would have thought that the existence of a study that contradicts his previous scientific findings would trigger Prof. Mann’s scientific interest. No fear, as we say down under, Professor Mann is not interested in the science, politics is far more important, Prof. Mann replied that:

I’m just a bit concerned that the result is getting used publically, by some, before it has gone through the gauntlet of peer review [meaning: pressure]. Especially because it is, whether you condone it or not, being used as we speak to discredit the work of us, and Phil et al, this is dangerous.

Translation: Don’t you ever publish results that we don’t approve of! It is dangerous (for you) to do so.

As professor Plimer said in relation to climate data: “If the data does not fit the model, you torture it into submission” (or words to that effect). Now, who are the real climate deniers?

Why is it that I feel that Climategate will keep me busy for week?

© Copyrights Jacob Klamer – all rights reserved (except images and clips).
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