Bringing Skillful Observation Back To Science

Wholly agree that selecting a short segment of a long, squiggly line and declaring that whatever trend that segment shows will extend forever into the future is a sin.
But I am not too clear about Szilard ‘discovering nuclear fission.’ I thought that was Hahn. Do you mean, Szilard’s insight into the explosive implications of uncontrolled fission?

How interesting. The 1967-2010 graph looks just like this one:
http://www.robertb.darkhorizons.org/SnowOnBally.GIF
the last snow on a peak north of my town from 1902 to 1983 (the readings stopped on Aug 3rd, so I don’t know if the snow ever melted that El Nino year).
Snow cover varies, and has been doing so quite well, all by itself, long before AGW came along and threw dirt on it.

Some people are not climatologists and others have no clue about statistics.
However, some climatologists complain if non-climatologists talk about climate.
But why are those climatologists all the time dealing with statistics? And even try to be creative in a rather stupid way?
Wasn’t McIntyre and the Hockey Stick story not lesson enough for them? Ridiculous.

Talk about serendipity – here and here and here (Newton’s telescope) and there’s more but too much to explain.
Perhaps I need to change the link under my name. The wiki is growing, albeit slowly.

Very nice. This article is a keeper.

Szilárd discovered nuclear fission while sitting at a red light.
There was a time when observation was considered an important part of science.
Er, how did the red light help?

Of course there is nothing magic about the 90% level of confidence, but having set that to be his own level of confidence, Tamino is well within his right to state that he doesn’t believe that snow extent hasn’t increased since 1989. His analysis is really straightforward.
The reason this data doesn’t convince Tamino’s (that is, why it doesn’t exceed the 90% confidence level) is that the snow extent is so variable. Looking at the second chart you have posted one can see that variability. Would I bet it’s going to be higher next year? Not after seeing this graph and reading Tamino’s analysis.
Statistics is all about trying to stop arguments such as “…it is abundantly clear …”, which always tend to generate more heat than light, and I for one will not fault Tamino from going there.

Steve,
You will be pleased to know that the propaganda disguised as science routinely fed to school children doesn’t always get through to them.
On the BBC’s Countryfile tonight a Herefordshire school was was featured showing off its newly erected wind turbine. John Craven was desperately trying to get one of the pupils to say that the turbine was a good thing because it would prevent global warming and save the planet, but all he got was a rather befuddled girl suggesting that it might help the ozone layer!

Robert (12:09:01) :
You usually have a point to make.
Nothing jumped out at me, so I’ll attempt to translate:
Folks can’t possibly understand science unless they become scientists.
If that was it, it spells real trouble. Science, along with a lot of other subjects, is rapidly disappearing from the classroom.

@ Robert (12:09:01)
I’ll take what you say about needing a 95% confidence limit on the actual snow extent from 1989 to 2009. It looks to this simple maths grad’s eye that it is obviously upward, but what the heck. It’s Sunday night here in the UK and after a nice meal with nice wine I can’t be bothered to do anything that requires more than a Mk 1 eyeball.
So, let’s agree that there’s no confidence in that observed result.
Now, did the models predict that NH snow extent would decline over this period? It’s 20 years so you can’t pull the “it’s just weather” option.
I assume to get the output of those models published the predictions must have shown a 95% or better confidence limit. Otherwise it would, surely, be meaningless to publish. Just going off what you said here.
No? If not, then what was the point of them being published (we can all “make stuff up”)?
If they did have such confidence limits then the models must be (in sound scientific terminology) “pure crap”.
I look forward to hearing your iPhone’s response.
Dave

Leif Svalgaard (12:02:45) :
Suppose you are in a geography class and are asked to measure the height of one of the hills
The question is meaningless unless you first have specified the height above what?.
I’ll go with the obvious for $1,000, Leif. Where the geography class lives.
In the case of current climate, we have mulitple generations all living at the same time. Measuring climate changes would only become believable if all present were taken into account.

Leif Svalgaard (12:02:45) :
Suppose you are in a geography class and are asked to measure the height of one of the hills
The question is meaningless unless you first have specified the height above what?.

In civil engineering and geotechnical circles the measurement is usually expressed as height AMSL (above mean sea level). A good engineer will qualify the measurement, for example, as 1,023m AMSL. So if the person answering the question doesn’t qualify their answer then it is the answer that is meaningless.

Leif Svalgaard (12:02:45) :
Suppose you are in a geography class and are asked to measure the height of one of the hills
The question is meaningless unless you first have specified the height above what?.
————–
But isn’t that how the AGW questions are framed?

Leif Svalgaard (12:02:45) : Leif, you postulate: “The question is meaningless unless you first have specified the height above what?”. The answer is: above (relative to) a chosen reference point; in this case, relative to the other hills. All reference datums are relative, whatever the scale, throughout the universe. This includes dubious datums, such as the hyperthetical global average temperature, against which “anomolies” are plotted. Regards, Bob.

The heading says ‘SKILLFULL’. English (UK) spelling is ‘skilful’, English (US) spelling is ‘skillful’ (according to WORD spellchecker).

Surely confidence intervals are designed to show that a particular pattern, or trend is not the result of just noise, and is not necessarily to do with whether or not the future can be predicted.
It is possible for the “trend” to be rejected at the 95% confidence interval, or even 90% or 80%, but yet still continue into the future. Similarly, a trend could show a very high >95% confidence level, but attempts to predict the future may be totally confounded when the “trend” reverses.
In other words, confidence levels and trends don’t really help except in one way – in order to compare predictions against observations. In the case of the graph of snow cover, it may be the case that snow cover has increased in the period shown, but what does that tell us about theories of climate change? Not a lot. No more than a similar period of decreasing snow cover or decreasing arctic ice.
So, if the publisher shows increasing snow cover and uses that to falsify global warming, then someone like Tamino is correct to object on the grounds of confidence levels. But if the publisher is merely saying, look, snow cover has increased, then that is a fact of observation and as long as it is within the error bars of measurement (I assume that it is), then Tamino must accept that as a fact. But then he may ask, What’s your point?
And I find myself asking the same question. What is the point of this article. It’s like saying “the sun is hot” or “the sea is wet.”

A little snarky Dr. Svalgaard. Kansans have more at stake in the science of
climate and its integrity then most. You might want to get out more.

Leif Svalgaard (12:34:51): “I’m tired of my children’s science education being controlled by people with a political agenda.” … Move to Kansas.
Dear Leif, No offense intended, and this is not personal so don’t take it that way, but…
Modern “science” is a big welfare game. Too much science is taxpayer supported, with no benefit to taxpayers or society. It’s much worse than taxpayer-supported “arts”. Armies of pseudo-scientists and even real scientists are living high on the hog on handouts from the rest of us, justified by false dire reports and false claims that the “science” being performed has any pragmatic value whatsoever.
You don’t pay my salary; I pay yours. And I am getting zip for my money, or worse than zip. That offends me, and hurts me, and harms my family and community.
I want every “scientist” on the public dole to provide the taxpayer with a valid reason for funding him or her. And “the furtherance of human knowledge” doesn’t cut it with me. I want practical results, not phony claims, not Chicken Little bull crap. And if they cannot justify their expense, then off with their funding.
Get a real job, one the free market values and is willing to pay you for. Do “science” in your garage in your spare time. I’m tired of footing the bill and getting BS in return. Will society collapse if taxpayers stop funding “science”? I doubt it sincerely.

Before we can even attempt to try and get back on the right track (namely the truth) with climate research, we have to get rid of many of the leading “scientists” that corrupt, twist, hide and/or distort the data and findings. If this doesn’t happen then there is no hope getting back on the right track. That should be pretty obvious if one thinks about it. Now, the only way to get rid of those people is to charge with fraud, and if found guilty put behind bars. If this doesn’t happen then the previous goal will never happen. This is clear from the avalanche of revelations showing that AGW in its present form is a hoax and a fraud. This too should be pretty obvious if one really thinks about it.

With all due respect, this post appears to have little to do with observation as a part of science. Someone skilled in the scientific art of observation would simply objectively observe and possibly record data points. All the line-drawing stuff and subsequent analysis would be left to others.

Suppose you are in a geography class and are asked to measure the height of one of the hills.
This sounds like an ideal reason to take the students on a surveying expedition! Take an assortment of modern and classical surveyor’s tools and some appropriate camping gear, and engage in some real hands-on field work. But I guess I’m too old-fashioned, since a few minutes with Google Earth would probably give a good-enough-for-climate-science value. ;->

“You usually have a point to make.”
Yes, I do. The point is that science being for everybody does not mean that it does not require knowledge and skill to do it effectively. Everything worth doing has a learning curve, and it take a basic part of science like seperating trends from noise and dismiss it as “elitist” because you don’t immediately understand how it works is, to borrow a phrase from Rush, retarded.
@Dave: I lost you when you started speculating about what climate models predicted for snow extent, while admitting you didn’t know. If you care, look it up. Don’t ask me to respond to a controversy that exists only in your imagination.

bbc’s latest ‘science in action’ prog continues on its merry AGW way:
Public perception of science
Can we trust science and scientists? It’s a question that is increasingly being asked by the media, and the public, after some high profile apparent mistakes. Did UK scientists manipulate data on global warming? Is the International Panel on Climate Change credible after it admitted that it had made a mistake in asserting that Himalayan glaciers could disappear by 2035? In the past few years there have also been false claims about stem cells, and erroneous warnings about vaccines. Michael Specter is the author of “Denialism”, where he asks why we have begun to fear scientific advances instead of embracing them. He was speaking at TED – Technology, Entertainment, and Design – a conference in California billed as some of the biggest thinkers coming together to spread ideas. This year the theme was “what the world needs now”. Jon Stewart went along to find out more…
If you’d like to attend TED, the next one is in Oxford, England, in July – there a more details on the Science in Action website. There is a fellowship programme, which focuses on attracting people who have world changing ideas, living or working in the Asia, Africa, the Caribbean, Latin America and the Middle East.
Ocean acidification
The oceans are becoming more acidic and at a faster rate than previously measured. This could lead to a massive extinction in the deep seas, according to new research. The ocean is what is known as a carbon sink – it has taken up between a quarter and a third of all atmospheric CO2 since the start of the industrial revolution. A study published in the journal Nature Geoscience shows that the increase in carbon dioxide in the atmosphere is leading to a similar increase in the oceans today. But it is believed that the process is making the seas much more acidic which is damaging the delicate shells of organisms that are critical to the marine food chain. In fact the rate of acidification is now the highest in 55 million years. Danniella Schmidt from the University of Bristol, one of the scientists behind the work, joins us on the programme.
http://www.bbc.co.uk/programmes/p00673xy
btw specter didn’t mention AGW in spite of the opening remarks of presenter, John Stewart. he talked of vaccines and GM food and said “trust the scientists”.
Nature Geoscience: Past constraints on the vulnerability of marine calcifiers to massive carbon dioxide release
Andy Ridgwell & Daniela N. Schmidt
http://www.nature.com/ngeo/journal/vaop/ncurrent/abs/ngeo755.html
Stephen Cauchi in Australia’s Age newspaper, reported the following, which sounds like a Greens’ response to Geoffrey Lean’s ‘rally the green troops’ piece in the UK Tele last week:
21 Feb: Quadrant: Doomed Planet
Assault on reason
The Age reports on a closed meeting by wealthy Green groups to plan their attack on climate sceptics:
Australia green groups have called a strategy meeting to devise ways to hit back at the climate sceptics movement, amid fears they are losing the PR war.
The groups, including Greenpeace, the Wilderness Society, World Wide Fund for Nature, Australian Conservation Foundation and Friends of the Earth, have acknowledged that the public mood has shifted following the collapse of the Copenhagen climate talks and blows to the credibility of the IPCC.
James Norman, of the Australian Conservation Foundation, said the strategy of ignoring climate change sceptics had not worked as it had been taken as confirmation of their claims. ”The stakes are too high to remain silent or disorganised in the face of this systemic disinformation campaign,” Mr Norman said.
He said the global campaign was being funded by anti-climate-change think tanks such as the American Atlas Economic Research Foundation and the British International Policy Network, which had both received grants from oil company ExxonMobil.
”I wouldn’t be surprised if they (ExxonMobil) have connections here in Australia as well,” he said.
Think tank the Climate Institute, lobby group Get Up, and the Liquor Hospitality and Miscellaneous Union will also attend the Sydney meeting, which is not open to the public or the media.
Greenpeace spokesman James Lorenz said the meeting was ”a good opportunity for environmental organisations to put their heads together and have a think about what’s going on”…
http://www.quadrant.org.au/blogs/doomed-planet/2010/02/assault-on-reason

@steven mosher (13:23:57) :
A trend that doesn’t reach 95% confidence (or sometimes 90%) is not statistically significant by definition. Your question is akin to asking if I demand that all triangles have interior angles totaling 180 degrees. We’re talking definitions here.

Stuff like this is why ‘climate’ scientists don’t design machines. Machines have to actually work. That ain’t easy in the real world.

Tamino has a good sense of humor. His t-tests are based on untenable assumptions and can be dismissed.

Right!
Last night I saw the excellent presentation of Dr. Lindzen, and I would like to ask a question to Dr. Lindzen. Therefore I would really apprectaite if you Anthony could forward this question to Dr. Lindzen.
Dear Dr. Lindzen,
In your presentation you stated that a couple of months or years with accurate observations of climate dynamics and radiation balance possibly could reveal the most important mechanims in our climate. Now, given that many ocean cycles are multi decadal, how could it be possible to determine the governing mechanisms in the climate with a fraction of the samples required to reproduce the various climate signals?
http://en.wikipedia.org/wiki/Nyquist%E2%80%93Shannon_sampling_theorem
My opinion has been that at least 100 years of accurate Argo ocean data would be required to reveal the characteristics of our climate, and I would be most happy if you could explain why this is not required.
Yours Sincerely
Invariant

Confidence – or better “confidence intervals” (as I was taught to call them) relate to a the confidence one has in a given probability distribution. In this case, there is a probability of 1.00 that each measured point of historical snow cover extent is correct (assuming each has been measured correctly – if not, then each point has its own probability distribution to do with correctness of measuring – but let’s heroically assume no measurement errors). Note that there’s no confidence interval (or confidence) involved in historical data. The straight line drawn thorugh the graph is a simple first order regression (root of sum of squares of differences of each measurement from the average).
Now, when you project that straight line into the future, for each future time period you calculate a max and min value, based on the historical measured variation of observed points from the historical regression line. The max and mins are calculated based on a given “confidence level”, conventionally 90%. This means you’re 90% confident that the future observed value for any time period will fall between the calculated min and max values for that time period. (Btw, this assumes that future variability is the same as historical variation, but let’s assume – operhaps more heroically – that it is.)
The thing that really annoys me about much of the AGW reporting is the way that the most alarming of the two intervals is always stated: for example, max values for temperatures; min values for Arctic ice extent. That’s not science, it’s flim-flam.

As an aside for Leif Svalgaard – I researched a comment you made in an earlier post and found your assessment to be correct. Sorry for misunderstanding – Mk

After inferential statistical testing a 95% confidence level means that for every 100 times an experiment is conducted and if for only five times the result differs from the rest this means that those five are likely to be by chance. A 0.05 p-value is the same thing noted as a probability and is the usual threshold value for psychology experiments. If an hypothesis is supported by the experimental evidence at the 0.05 level then we can say it is moderately reliably supported, we can trust the findings. For experiments testing the safety of new medicines much more stringent p-values are required, 0.01 or 0.001, because peoples’ lives are at risk. Such simple stats deal in how often you think your results are by chance-as others have said, how much ‘noise’ versus how much ‘signal’.
The big problem with the alarmists is that we can’t apply such tests to their data because their theories do not generate testable hypotheses. Much like the theories of Freud, which I call a typical ‘expanding bag’ theory, whatever observations or results you toss into the bag it just expands a little more and is proclaimed to explain everything. Heavy snow is generated by global warming, heat waves are generated by global warming, much as in Freudian theory you may be diagnosed with a desire to sleep with your mother and when you reject that diagnosis you are told you are in denial, that whatever you say simply goes to convincingly prove this incestuous desire.
Don’t even get me started on the gigantic expanding bag which is religion…

I love this post. It is a classic.
Sceptics have spent a huge amount of effort trying to show that evidence of global warming is not significant. But now there might be a cooling trend and “85% would be a pretty good number for betting. A good gambler would bet on 55%.”
So which is it? Does evidence for climate change have to be proven beyond any doubt, or should we take action on a 55% probability?
“Secondly, the confidence number is used for predicting future trends.”
Wrong.

“Science is for everyone, not just the elite who collect government grant money. I’m tired of my children’s science education being controlled by people with a political agenda.”
This is not a scientific statement, merely a political cheap-shot. Skeptics should practise what they preach and stick to the science.
So if I Follow through on the logic of this article, there has been warming since 1995 as defined by Jones in his recent BBC interview (0.12C per decade), being that “statistical significance” is apparently not significant.

“There was a time when observation was considered an important part of science. Climate science has gone the opposite direction, with key players rejecting observation when reality disagrees with computer models and statistics. Well known examples include making the MWP disappear, and claiming that temperatures continue to rise according to IPCC projections – in spite of all evidence to the contrary.” -SG
________________________
Integrity. An insignificant collection of letters. A word that is, as Humpty Dumpty would say, “what you want it to mean”. It plays in the dealings of the individual with his craft. It plays in the dealings of the craftsman with his peers. It plays in the dealings of the trade with its members and with the world with the trade.
Many, if not most, “Scientists” –and the lessor order called “scientists”– believe it does NOT apply to them or their craft. That it only applies on a case by case basis, and lately only to a group called “Climate-ologists”.
To bring skillful observation back to Science today, one needs a long strong 4″x4″ — or a Baseball Bat. When all Scientists have the integrity of all scientists all is lost and we are as we are today, in Wonderland.

1. My heart is broken by Scientific American, once the best magazine in the world and now whore for AGW. Not just AGW, but no debate or discussion of skeptics….a real tragedy.
2. In big Pharma, we see every day the result the moneyed interests cheating their brains out on drug evaluations. The most recent examples are so obvious and despicable that I am amazed more of these researchers don’t end up in jail.
3. Even in mechanical situations, such as Toyota, the cheap fix of the throttle problem has a major software component that Toyota does not mention. Several of the accidents had no problems with the pedals as the problems were likely caused by a malfunction in the drive by wire.
4. A temp chart from two thousand years ago, shows a natural variation, and that we are leaving an ice age.
5. A temp chart of 400,000 years show temp changes that show sunlight due to orbit, inclination, and possibly cosmic radiation and solar wind are part of the temperature equation, certainly no AGW.
6. The computer model for AGW including its scientific basis has been shown to be completely false. This seals it for me. The issue of temp change is unimportant. The AGW facts are shown t be worthless, and their proponents are total cheaters. That is where the science is at.

As pointed out by others, “confidence” is an important statistical term with a very precise definition, and I should add that it has nothing to do with betting or with gut feelings or eyeball readings. Your argument is indefensible, as there is (currently) no statistically significant trend in winter snow cover, regardless of the dates you pick.
On the other hand, the trend in decreasing NH spring snow cover IS statistically significant (see Dery and Brown, 2007), and this is what climate models project (IPCC WG1, or, if you prefer their reference, here: http://www.acia.uaf.edu/PDFs/ACIA_Science_Chapters_Final/ACIA_Ch06_Final.pdf).
You conveniently overlooked this fact when you generalized that “the climate models were wrong”. Hopefully, future posts will address this oversight.

I can’t find Tamino’s article to which you refer. Could you supply a link? TIA.

“Robert (15:42:53) :
[…]
The models say the Arctic ice cover will decrease, and it’s decreasing. The magnitude of the decrease is greater than expected. ”
Your iPhone must be Al Gore.

A number of the comments here display the very lack of observational ability that this article is about.mmMark Twain said “There are three kinds of lies: lies, damned lies and statistics.”
Winter snow cover has been increasing for the last twenty years. From 2001-2010, 7 out of 10 years have been above 45,000,000 km2. But from 1989-2000, only 3 out of 11 years were above 45,000,000 km2. The current year is the second highest on record.
http://wattsupwiththat.files.wordpress.com/2010/02/dec-feb_snow_ext.png
BTW- Tamino calculated 99% confidence for that graph before applying his undocumented “cherry picking test.”
Here is an exercise for Robert et. al Show me statistical significance in the geologic record between CO2 and temperature. Good luck with that.
http://i224.photobucket.com/albums/dd137/gorebot/Geological_Timescale_op_927x695.jpg

I see a lot of willful misunderstanding of Steven’s article here by the scientists. as Dr Anthony Fallone (15:10:13) tells us: “After inferential statistical testing a 95% confidence level means that for every 100 times an experiment is conducted and if for only five times the result differs from the rest this means that those five are likely to be by chance. A 0.05 p-value is the same thing noted as a probability and is the usual threshold value for psychology experiments. If an hypothesis is supported by the experimental evidence at the 0.05 level then we can say it is moderately reliably supported, we can trust the findings.”
This 95% confidence interval, then applies to 1) laboratory trials in an experimental situation or 2) a hypothesis that builds on a specific theory that is to be tested observationally, as in the case of climate science, the validity of which is borne out by future observations. Where, in this post, is Steven putting forward any predictions of future conditions? He specifically states: “Can we infer that snow cover will continue to increase? Of course not.” He’s not conducting experiments either. The entire point of his article is historical: he has the historical data that shows that Tamino and the AGW scientists have got their predictions wrong. Does history need a confidence interval? If so, that’s news to me.
I’d like to see you geniuses go back and prove why the fisheries science models from the 1980s were right, with all their statistical confidence intervals built in, and then tell me where all the Northern cod on the Grand Banks went to.

Again, no matter how you slice the charts or rationalize it away, it takes MORE heat, not less to create heavy snowfall. The coldest place on earth is also one of the driest (in terms of annual precipitation) and that’s Anarctica. These are the basic laws of physics…it takes heat to evaporate moisture, we have very high temps right now in the oceans and troposphere, and when you combine that with a negative AO– bingo, you snow, and lots of it in places not normally seen.
So if the trend toward more snow covrer (DURING WINTER) is accurate, then in can only mean that on average we are seeing more moisture and thus more heat and evaporation from the oceans during these months. How that discredits AGW in any way is beyond me…

I am 6 feet tall. I’m standing at 5,000 foot elevation. Therefore my height is 5006 feet. Think I will put that on my driver’s license application.

Did anyone read what Steve wrote?! And did anyone read the text describing the model predictions of snow cover?! Steve said he chose 1989-2010 because that’s when the trend turned upward. The observations are the observations. The trend from 1989-2010 is clearly upward at 100% confidence. If you add years before 1989 or after 2010, of course the trend will be different, but Steve was clear he was talking about 1989-2010. The models clearly predicted a downward trend in snow cover from 1989-2010 – look at the graphs. Summer snow cover, full year snow cover, blah blah blah is all irrelevant. The model predictions were for JANUARY snow cover, hence the use of WINTER OBSERVED snow cover as the comparison. Steve’s point was clear, that “North American snow models miss the mark – observed trend opposite of the predictions”, and he showed you why.

R. Gates,
Do you understand the difference between snow depth and extent? Extent increases when it snows in Florida. Snow in Florida is not due to heat – it is due to cold.

“The trend from 1989-2010 is clearly upward at 100% confidence.”
I’m sorry. That’s just not how it works.

This is reminiscent of the controversy that surrounded the claim that snowpack in the Cascades shrank by 50 percent in the last half century. The statistic was used by government and advocacy groups to push their climate change agenda in Washington State. The only problem is that the statistic was dead wrong. The unfolding scandal revealed extensive corruption of the science by one researcher, Philip Mote, at the University of Washington. The Seattle Times published a good summary of the story when it first broke a few years back:
http://seattletimes.nwsource.com/html/localnews/2003618979_warming15m.html
The same story was revisited by the Air Vent in July of 2009 and Jeff Id carefully dissected the methods used by Mote et al to reach their fraudulent conclusions. The article is well worth reading given the many similarities between Mote’s dubious methods and the methods purportedly being used to discount NH snow extent:
http://noconsensus.wordpress.com/2009/07/21/snowmen/
It’s also interesting to note that just a few months ago, the odious NPR environmental reporter, Richard Harris, gave an extremely distorted picture of the Climategate scandal on the NPR program “All Things Considered”. That by itself is not terribly surprising. However, what shocked me most during the segment was how Harris completely misrepresented John Christy’s contention that his research paper on Sierra Nevada snowpack melt had been suppressed for political reasons. Harris casually concludes that Christy’s concerns were simply a matter of paranoia stemming from Christy being personally attacked in the CRU emails.
Please read the transcript (below) and carefully note who actually reviewed and rejected Christy’s paper on snowpack melt. Then reread the article I posted above on the Cascade snowpack fraud. Finally, revisit Christy’s contention that his paper was intentionally suppressed for political reasons. See if you reach the same conclusion that Harris does and report back.
TRANSCRIPT:
That said, many of the complaints about the journal review process come from people who think mainstream science is overstating climate hazards. John Christy is at the University of Alabama at Huntsville. He accepts global warming is happening, but he says there’s a lot of uncertainty about its causes and impacts. And he says he has trouble getting some of his results published.
Professor JOHN CHRISTY (Director of the Earth, System Science Center, University of Alabama, Huntsville): I’ve done a pretty thorough study of snowfall in the Sierra Nevada mountains of California. And the Southern Sierra show no downward trend in snowfall.
HARRIS: That’s important because snowfall is forecast to decline due to global warming. And that would seriously affect California’s water supply. Christy says he’s tried three times to get his paper published. So far it’s been rejected, and he suspects it’s because scientists are trying to stifle his message.
Prof. CHRISTY: Everyone from the secretary of energy who has talked about the snowfall in the Sierra going away will not find any comfort in the fact that the trends in snowfall are essentially zero for the last hundred years.
HARRIS: So is it being suppressed? Philip Mote at Oregon State University was one of the scientists who reviewed the paper. He said the science in the paper was fine.
Dr. PHILIP MOTE (Oregon Climate Change Research Institute, Oregon State University): To my knowledge, there’s no suppression going on. It’s simply that it’s not news.
HARRIS: Mote himself published a paper four years ago showing that snowfall in the Southern Sierra hasn’t diminished. In fact, he says there are about 10 papers on the subject, certainly not identical to Christy’s but still reaching that same broad conclusion.
Dr. MOTE: It’s not controversial because it’s already well known.
HARRIS: Still, it’s easy to see why Christy suspects deeper motivations. The stolen emails contain sharp personal attacks against him. He says the politics inside climate science are making life harder for him, not just in publishing papers but in getting money to do research. Mote says dissent is important in science. He doesn’t agree with everything Christy says, but he says he should have a voice.
—-
Full transcript can be found here:
http://www.npr.org/templates/transcript/transcript.php?storyId=120846593

R Gates
“So if the trend toward more snow covrer (DURING WINTER) is accurate”
The trend is moving south. It’s called extent.
That means it’s colder further south, where it was not colder before.
Moisture without cold, is called rain.
When the extent of snow cover increases, that means it’s colder.

“Show me statistical significance in the geologic record between CO2 and temperature.”
Here you go. Somebody else has done the work:
http://4.bp.blogspot.com/_KfE5s-4q1s4/S0PxgIwS7BI/AAAAAAAAAD0/ydkuhHeRAZg/s1600-h/co2vstemp_glacial.jpg
You will note that R^2= 0.79, and n = 799. That’s about as significant as they come. Cf this handy chart:
http://www.mega.nu/ampp/rummel/uc.tab9.2.gif
Description of the analysis: http://moregrumbinescience.blogspot.com/2010/01/co2-and-temperature-for-800000-years.html

I think this is funny. Does anyone remember why statistical analysis and confidence levels and so on are so important? I shall answer my own question.
Human being percieve data differently than computers do. The value of computers is that a) they can manipulate data FASTER than human beings can and b) they can manipulate MORE data than human beings can. The problem this creates is that we no longer percieve the data directly, we percieve it through the limitations of the computer analysis that manipulates it for us. Anyone who has worked for example, in a custom metal fabrication facility, knows that drawings come in from engineers who used Autocad that could have been far simpler to fabricate other ways. I know a professor of architecture who sends his students to a particular building here in town and asks them to use Autocad to draw the stairwell. They can’t, which is the purpose of making them try and do it. Computer tools allow analysis that human beings could never accomplish with calculators or pencils and paper. But it also means we need mechanisms to validate that what we see in the computer analysis output is what we thing it is. Hence statistical analysis and confidence levels to understand if the graph we are looking at, which may be several generations of analysis from the original data, says what our human perceptions believe it says. There’s too much data for us to look at several million measurements, a graph the computer built, and go… yeah, that looks about right.
The point of that ramble, is that human perception and analysis is still superior to that of a computer program, provided that the data being observed and considered is small enough for us to “fit it in our heads”. In Steve Goddard’s example of the hills, this is exactly the case. Take ten thousand altitude measurements across those hills, and a computer program will in fact tell you that the average is flat, that there is no trend, that the variability is within error, and it will be correct. That’s how computers see data and that’s why it is so easy to take big chunks of data and get answers that are technicaly accurate and totaly meaningless.
Anyone can look at the graph of the hills and answer the question. Yes they need to say compared to what? the valley? see level? where I’m standing? But it is obvious that saying there are no hills at all, its flat, could be accomplished ONLY by computer analysis, not by a human being looking at it.
I don’t need a computer to analyze 40 years of snow extent data. I might have some questions as to how it was measured and so on, but having been satisfied that the data collected is valid…. looks to me like snow extent is highly variable, that there was a declining trend from the beginning of the graph that was accompanied by decreased variability, followed by an increase in snow extent at the end of the graph that seems to be accompanied by increasing variability.
We’ve gotten so used to looking for the errors that poor math or bad data in conmputer models can produce, that we forgot the purpose was to ensure we were looking at what we thought we were looking at, and if the data set is something we can percieve in its entirety without a computer, then there is no need for the statistical analysis. We can actually just look at it.

‘There is 100% confidence that the trend from 1989-2010 is upwards.’
I’m intrigued by this statement Steve. The main problem I have with this graph is the lack of error bounds. In my experience I have seen many wonderful ground breaking trends which magically disappear once I add the error bound along with my hopes of a tier 1 journal paper.
Even with empirical data there is still the question of how well it represents reality. This is why I disagree with another statement you made about statistics only being for predicting future trends. Carl Popper says that we use statistics to make up for a lack of knowledge and I’m sorry to say that I like his interpretation better.
If you make three observations under the same conditions and get different results then there is something you don’t know. Now you want to change the conditions and see if you can measure a change in the result. The problem is that the result changes even when you don’t change the conditions because of what you don’t know. So how can you say anything about changes in results due to changing conditions when results change without conditions? Well we all know the answer to that one and it is statistics. You compare the changes that occur under constant conditions (what you don’t know) with the changes that occur under changed conditions (the sum of what you do and don’t know) and compare them to see if you know enough to make inferences.
I don’t think this process involves predicting future trends, its simply analysing past events for significant patterns.

I’d just like to state for the record that the Wikidpedia picture of Sir Issac Newton looks remarkably like a guy who works in my community theatre.

Robert (12:09:01) :

A confidence interval is about distinguishing a random distribution from a pattern. By convention, you need to be 95% confident in your trend in order to reject the null hypothesis. 90% is on the bleeding edge of acceptable.

Excellent. Then we can ignore the IPCC AR4 almost completely, as it almost never reaches 95% (“extremely likely, by their assessment) confidence levels.
Thanks.
Can I interest you in a game of chance, by the way, only $10 a point…..

This is reminiscent of the controversy that surrounded the claim that snowpack in the Cascades shrank by 50 percent in the last half century. The statistic was used by government and advocacy groups to push their climate change agenda in Washington State. The only problem is that the statistic was wrong. The unfolding scandal revealed extensive corruption of the science by one researcher, Philip Mote, at the University of Washington. The Seattle Times published a good summary of the story when it first broke a few years back:
http://tinyurl.com/259rsh
The same story was revisited by the Air Vent in July of 2009 and Jeff Id carefully dissected the methods used by Mote et al to reach their fraudulent conclusions. The Air Vent discussion is well worth reading given the many similarities between Mote’s dubious methods and the methods purportedly being used to discount NH snow extent:
http://tinyurl.com/ydp58zf
It’s also interesting to note that just a few months ago, the odious NPR environmental reporter, Richard Harris, gave an extremely distorted picture of the Climategate scandal on All Things Considered. That by itself is not terribly surprising. However, what shocked me most during the segment was how Harris completely misrepresented John Christy’s contention that his research paper on Sierra Nevada snowpack melt had been suppressed for political reasons. Harris casually implies that Christy is a conspiracy theorist and that his paranoia stems from being personally attacked in the CRU emails.
Let’s do an experiment. Since Richard Harris is apparently an incompetent journalist, let’s revisit Christy’s contention that his paper was intentionally suppressed for political reasons. First, please read the article linked to above about the fraudulent claims made by Philip Mote regarding an increasing trend in snowpack melt in the Cascades. Next, please read the NPR transcript below and carefully note who actually reviewed and rejected Christy’s paper on the lack of a downward trend in Sierra Nevada snowfall. Finally, see if you are able to reach the same conclusion as Richard Harris and report back.
_____
TRANSCRIPT:
That said, many of the complaints about the journal review process come from people who think mainstream science is overstating climate hazards. John Christy is at the University of Alabama at Huntsville. He accepts global warming is happening, but he says there’s a lot of uncertainty about its causes and impacts. And he says he has trouble getting some of his results published.
Professor JOHN CHRISTY (Director of the Earth, System Science Center, University of Alabama, Huntsville): I’ve done a pretty thorough study of snowfall in the Sierra Nevada mountains of California. And the Southern Sierra show no downward trend in snowfall.
HARRIS: That’s important because snowfall is forecast to decline due to global warming. And that would seriously affect California’s water supply. Christy says he’s tried three times to get his paper published. So far it’s been rejected, and he suspects it’s because scientists are trying to stifle his message.
Prof. CHRISTY: Everyone from the secretary of energy who has talked about the snowfall in the Sierra going away will not find any comfort in the fact that the trends in snowfall are essentially zero for the last hundred years.
HARRIS: So is it being suppressed? Philip Mote at Oregon State University was one of the scientists who reviewed the paper. He said the science in the paper was fine.
Dr. PHILIP MOTE (Oregon Climate Change Research Institute, Oregon State University): To my knowledge, there’s no suppression going on. It’s simply that it’s not news.
HARRIS: Mote himself published a paper four years ago showing that snowfall in the Southern Sierra hasn’t diminished. In fact, he says there are about 10 papers on the subject, certainly not identical to Christy’s but still reaching that same broad conclusion.
Dr. MOTE: It’s not controversial because it’s already well known.
HARRIS: Still, it’s easy to see why Christy suspects deeper motivations. The stolen emails contain sharp personal attacks against him. He says the politics inside climate science are making life harder for him, not just in publishing papers but in getting money to do research. Mote says dissent is important in science. He doesn’t agree with everything Christy says, but he says he should have a voice.
_____
Full transcript can be found here:
http://tinyurl.com/ydk64bu

“Not discussing evolution [which is a fact, so no discussion needed] …”
Unbelievable! A fact? I’m probably with you in that the preponderance of evidence suggests this is likely correct and I am also an atheist who has no need for supernatural interference. However, the “no discussion needed” is just so AGW like.
Discussion is always needed if only to sharpen the arguments and keep the “priests of science” humble.
And your attitude is, in my humble opinion, just another example of
“science education being controlled by people with a political agenda.”
Just tonight, I watched a lecture about evolution where it was mentioned that Darwin’s justification for validation was the same model taken by supporters of “Huygen’s wave theory of light”
And we see how that turned out.

Robert (15:55:28) :
You can test the hypothesis that CO2 and other GHGs heat the earth by absorbing and re-radiating long-wave radiation by looking at the earth’s emission spectrum

Sure you can. If you ignore all other factors that occur in the real world as opposed a model’s virtual world. Which is precisely why your models are so useless for real life. Interesting exercise, nothing more.

davidmhoffer (17:49:17) :
That’s how computers see data and that’s why it is so easy to take big chunks of data and get answers that are technicaly accurate and totaly meaningless.

BINGO! A sure nomination for quote of the week! It was one of the first things drilled into us when I was learning to be an ORSA (Operations Research Systems Analyst). It’s also the first lesson forgotten as we become enamored with our fancy toolkits.

JLKrueger said: “More like ocean heat content being released to the atmosphere. And from there into space”
Heat content from the oceans “being released” would be called? Yep, find that word…starts with an “e”, and involves a change of state for water. And no, it doesn’t just go from there into space. It enters the troposhere, thus going from the hyrdosphere to the tropsphere via a change of state called evaporation. Once in the hyrdosphere, water vapor joins the other greenhouse gases in trapping heat at the surface.

“Robert,
Nice try. That wasn’t the question I asked.”
You do realize what you wrote is still visible, right? “statistical significance in the geologic record between CO2 and temperature.” Asked and answered. Game over. Nothing shreds your credibility more thoroughly than being completely unable to admit you’ve made a mistake. There is a statistically significant correlation between CO2 and temperature in the geologic record. Deal with the facts.

R. Gates (19:34:08) :
Again, deep snow, more snow, gtreater extent, however you want to measure it has it roots in HEATING of the oceans.
Couldn’t it be due to the winds, maybe currents? Total world-wide humidity is always close to flat. The sun’s output is not way up last time I checked. So where is all of this HEATING you keep speaking coming from? Whereever there is HEATING, there is equal COOLING somewhere else; unless you are speaking of long year+ time periods.

Leif
“None of your cases overturns the old ‘fact’. Newer theories incorporates the older ones as limiting cases. ”
Really? Which is it? Particle theory limits Wave theory or Wave theory limits particle theory?
Robert
“The question was whether the theory of AGW makes testable, falsifiable predictions. It does. ”
I want specific predictions. And Hansen’s 3 scenarios fail, BTW.

Leif
“Except it was the other way around… Einstein put Newton back in the game, and as it turn out both Huygens and Newton had a side of the truth.”
Except that I offered that it was Huygen’s who was supplanting Newton’s “fact” during Darwin’s time…nothing to do with Einstein. No straw arguments please.

Leif Svalgaard (21:28:07) :
Newer theories incorporates the older ones as limiting cases. At the time of Darwin, evolution was not a fact. He didn’t know the mechanism by which it works. We do today, and that is why today it is a fact.
_________________________
Whaaat? Darwin’s name is a household word because he did know the mechanism by which EVOLUTION worked: namely, Natural Selection, which functions through competition for scarce resources between members of the same species. What Darwin did not know was the mechanism that created the variations between individuals that gave some a competitive edge – and when that mechanism was discovered, Darwinism suffered an ‘eclipse’ as people jumped on a Mendelian-Lamarckian variation on evolutionary theory. It was not until population biology added to our understanding of how genes work in populations that Darwinism was fully reinstated, in the late 1950s. Even without that knowledge, evolution became an accepted theory (not a fact) following Darwin, because he provided overwhelming evidence — through hundreds of different observations — that it had occurred. (No stats involved in this one, either.) I agree with the general drift of your comments, though, especially concerning Newton and Huygens.

vigilant fish
“I agree with the general drift of your comments, though, especially concerning Newton and Huygens.”
As I’ve pointed out…which is it?
“Particle theory limits Wave theory or Wave theory limits particle theory?”
In the case of “Newtonian mechanics” vs. “Einsteinian relativity”…Mercury’s precession, anyone?
I have to wonder whether holographic gravitation might play a similar role 100 years from now.

Leif
“They are both correct. We can talk of the wave length and frequency of light and at the same time talk about the momentum of photons.”
” So there are two limits and two limiting cases.”
And that’s my point. One did not limit the other. They became different narratives depending on the circumstances.
In other words, it’s not a “fact” to discuss wave theory in some circumstances and particle theory in others (two slit experiment for example).
It’s contextual…at least thus far.

The Met Office uses climate models to make their (almost always incorrect) seasonal forecasts. They have been consistently wrong since 2007, when they predicted a sizzling summer that turned out to be the most miserable wet summer on record.
http://i224.photobucket.com/albums/dd137/gorebot/Geological_Timescale_op_927x695.jpg
http://ff.org/centers/csspp/library/co2weekly/2005-08-18/dioxide_files/image002.gif

Leif
Particle theory does not explain the two slit experiment, for example. They are accepted facts, yes, but self-limiting with their own domain.
In other words, it still leaves the door open for a better explanation.

Leif Svalgaard (21:40:37) :
You are exactly right. Wish I had never used the word “storage” many posts ago, it might have given other fertile minds the false impression that you could store it away above physics laws and local temperatures. Big wording mistake!
Wish WUWT has a tab on “Common Scientific Truths” that are unquestionable; so those constant realities didn’t have to be said over and over and over again. That re-stating is where one wrong word and here comes everyone to tell you how wrong you are or how little you know, missing the whole point of the comment. I’m not good in wording so I get a good dose of that. I’d prefer to say I know and adhere to the Common Scientific Truths and here’s the real message of my comment.
While commenting to you, don’t you get the sense that some here are trying to sequence items in climate science instead of viewing a continuum of processes? Like, it’s not going to evaporate until … then it will evaporate, and when it evaporates … and then …. Seems they don’t grasp that bulk matter always radiates, bulk matter always absorbs radiation, water always evaporates, and water always condenses, always simultaneously. It is the differential of parameters that matters at the interface and even when the difference is exactly zero, both sides are still happening only in equal proportion.
A clarification of that fact would help many frequenting here. Something like a mini-course you could just point them to; without Wikipedia to scrabble their minds.

Pasted the wrong link on that Met Office story.
http://www.guardian.co.uk/environment/2007/apr/08/weather.theobserver

Probably best to stop digging, Steve. I enjoy Watts, but your first article was full of holes. This one would have been embarrassing if it had come out of a school statistics class.
(By the way, Szilard didn’t discover fission at a red light. It was the concept of the chain reaction that occurred to him while at a red light. Wasn’t it Hahn and Strassman that discovered fission? In a lab….)

Comments from the director of the Rutgers Snow Lab
http://www.google.com/hostednews/ap/article/ALeqM5g1jo1gT0843vxrD4oRUd1Ufm4F5AD9DRBO880

This is after a month that saw the most snow cover for any December in North America in the 43 years that records have been kept. And then came January 2010, which ranked No. 8 among all months for North American snow cover, with more than 7.03 million square miles of white.
The all-time record is February 1978, with 7.31 million square miles. There is a chance this February could break that. There is also a chance that this could go down as the week with the most snow cover on record, Robinson said.

Wayne said: “Whereever there is HEATING, there is equal COOLING somewhere else; unless you are speaking of long year+ time periods.”
What get’s cool when the solar energy arrives from the sun? What we’re talking about the the exchange of energy. So yes, energy cannot be created or destroyed, only changed in form, and furthermore, we know that the law of entropy will tend to run this old universe down until there is equal cooling everywhere…hundreds of billions of years from now.
Be on earth, since the majority of energy comes from the sun, and this is nuclear energy transformed into EM radiation that travels to earth, enters the atmosphere, and then heats up the land, the oceans, and the molecules of the air itself. All the energy (or at least the vast amount) in the oceans comes from the sun, and unless there was some way for this energy to get released from the oceans, they would get way to hot. In this regards, be thankful for hurricanes and big storms. They release such incredible amounts of energy.
And here is personal experience to illustrate how the HEAT from oceans can lead directily to big snowfalls. Back in the winter of 1982, just a few days before Christmas a big hurricane was brewing out in the pacific. It eventually was downgraded to a tropical storm, but the moisture from that headed in over California and eventually wound up right here in Colorado where I live. That Christmas Blizzard of 1982 was one of the biggest on record, and all started from WARM waters over the pacific, that eventually combined with cold air over Colorado and created a monster storm. In Denver specifically, the SNOWIEST months are usually March and April, when the warmer temps over the oceans can draw up huge amounts of moisture off the Pacific and the Gulf of Mexico and slam it into the cold air over Rocky Mountain. These same storms often head southeast of here over Oklahoma and bring snow, and if the condidtions are right, tornadoes. All this because of WARMTH, not COLD. Cold is lack of energy in the atmosphere, and needs HEAT to bring in moisture before you can get snow…just like the Colorado Christmas Blizzard of 1982, and just like the East Coast storms of 2009-2010.

Leif
“The weather is always changing. I would not call it a climate change if it over 1 day, or one year, or 15 years. Up around 30 years it begins to be climate change. That’s how far my humility goes.”
And this 30 year time frame was established where, precisely? I must have missed that meeting.
So, if I throw out your arbitrary 30 year time frame and pick, oh, say an EON…can I now say that the climate is “always changing”?
I’m not trying to bust your chops…ok, maybe just a bit…but without the appropriate reference frame…these statements are most certainly challengable.

Leif:
IMO, evolution over long periods of time is an observable fact: just look at the fossil record. However, the absence of gradualism in that, at least to my mind, challenges neo-Darwinism as providing a complete theory. Maybe one day it will have its “Einstein” come along to significantly refine it.
Where this relates more to matters in hand is that there are AGW supporters who are just as wedded to orthodoxy as are neo-Darwinists, and any departure from that is a dangerous pursuit for a career scientist. One lot gets labelled as oil-funded deniers, and the other, as crypto-Creationists.
A fellow can’t hold a dissenting view without being vilified, and that is very bad for science in the long run, because some of its most admired geniuses were at one time dissenters. Science can’t evolve without dissension, and sure, what you pay for that is having to put up with some whose dissension is unwarranted.
IMO, neither neo-Darwinism nor AGW can fully explain the past or predict the future. The former doesn’t explain the lack of gradualism and didn’t predict the size of the human genome, and the latter doesn’t explain the past (such as the MWP or LIA), and didn’t predict the increasing snow extent over the period Steve has focussed on. And that, for me, is what I’m getting from his post. I’m not, and I don’t think Steve was (he can correct me if I err), attempting to say much more than that. This kind of stuff is interesting for folk like me who are engaged by the climate controversy, and it doesn’t require me to understand statistics in-depth, which I can’t and don’t pretend to do.
Sometimes, forgive me for saying so, your tone sounds rather haughty and dismissive, and I often don’t quite see what it is you are driving at or why. Folk like me like to be here and to try to learn, and I immensely enjoy the exchange of ideas that go far beyond the obvious, delving into many interesting highways and byways. One learns about much more here than simply climate science, and I feel it’s a shame to disturb convivial debate. If I have misinterpreted your tone, please accept my apologies, but even so, maybe it’s useful for you to be aware of how you are coming across, at least to this one responder.

Steve,
Your anaolgy is useful, but probably incomplete.
The task before us is to determine if the section of the range of hills that we have sampled to date (starting from the West) is actually overlayed on some underlying, larger or longer, hill or valley. I think we can all safely assume that this range of hills cannot continue to rise (or fall) into infinity.

It would be interesting to do a little Hurst analysis on any of the data. It would basically show the length of time a model is good for (if it is good for anything) before it goes to pot. Weather like the Nile floods (which were a product of weather) are a mathematically chaotic process.

Atticus,
Learn how to read a graph before commenting.
http://wattsupwiththat.files.wordpress.com/2010/02/dec-feb_snow_ext.png?w=510&h=291&h=291
Winter snow cover has increased over the last 20 years. Anyone with a high school science or math education can see that.
Comments from the director of the Rutgers Snow Lab
http://www.google.com/hostednews/ap/article/ALeqM5g1jo1gT0843vxrD4oRUd1Ufm4F5AD9DRBO880

This is after a month that saw the most snow cover for any December in North America in the 43 years that records have been kept. And then came January 2010, which ranked No. 8 among all months for North American snow cover, with more than 7.03 million square miles of white.
The all-time record is February 1978, with 7.31 million square miles. There is a chance this February could break that. There is also a chance that this could go down as the week with the most snow cover on record, Robinson said.

Simple explanation from William M Briggs, statistician.

Let’s ignore statistics and turn to plain English.
Suppose, fifteen years ago the temperature (of whatever kind of series you like: global mean, Topeka airport maximums, etc.) was 10 C. And now it is 11 C. Has warming occurred? Yes! There is no other answer. It has increased.

http://wmbriggs.com/blog/?p=1958

Anthony Fallone,
At no point have I ever made any attempt to predict the future of snow cover. I have not made any hypothesis about a cause and effect relationship between the year and the snow cover. I have simply observed the undeniable observation that winter snow cover has increased over the last 20 years. Statistics has nothing to do with it.
Had I made a prediction of how further increases in the X-Axis affect the Y-Axis, then your argument might be valid. But that is not the case.

Nice, simple, straight forward insight.
I’d have thought that any measurement is in the end about whether it leads to something testable and practical. “There are no hills” is obviously an impractical finding.
The focus on the last 200 years or so of surface temps, which ignores the recent 10 or 15 years as “too short”, and ignores anything beyond 300 as “too long ago to matter nor understand” — that focus on the last 200 years should provide us with a hypothesis that we can test and use for practical problem solving. All it seems to have done is produce models forecasting scenarios 100 years out that we can’t test. If we can’t test then what’s the point?
If we can’t test, it is not science. So sure, “we have to do something” — I’d just as well rely on my own intuition. That’s what most people seem to do. You can’t publish intuition, but you can act on it. My intuition says there’s too many good things that might happen in the future which we don’t want to jeopardise by imposing silly resource cuts.

Very late coming to this party 🙂
Robert wrote:
“A confidence interval is about distinguishing a random distribution from a pattern. By convention, you need to be 95% confident in your trend in order to reject the null hypothesis. 90% is on the bleeding edge of acceptable. Less than 90% is not statistically significant by any measure.”
Robert, you need to attend one of my Intro Physics course lab sessions where students routinely show me how they have fit a straight line to their data and the computer spits out a r^2 value of 95%. They then confidently tell me how that has to be the correct result because of that r^2 value. They, like you, ignore what their eyes are telling them about the real data trend which can be a power function, etc. They quickly learn that the 95% confidence interval is a deceptive statistic and being dependent on it leads one to conclusions that are not valid.

Ref – R. Gates (16:29:54) :
“..on average we are seeing more moisture and thus more heat and evaporation from the oceans during these months. How that discredits AGW in any way is beyond me…”
________________________
Seems reasonable, until you beg the question “How that discredits AGW in any way is beyond me..”. AGW doesn’t forecast another 80K year glacial phase, just the opposite, so its likely not AGW “if” the world’s ice increases.
_______________________________________
Observation to all –
Academics is a fine and worthwhile endeavour. To read through all the bits and pieces of discourse here at WUWT is a fascinating way for me to waste time while waiting for the Grim Reaper, but the question of “Are We or Aren’t We causing changes in the Earth’s climate?” is just that “academic”. Just as fascinating –often more so– as the question about the accuracy of the comments, is the so very human emotional component of the discourse. Plato might not hang around here too long, but everyone of you adds a special something to the discussion in my book. Thank you (and I do mean everyone). You make my day:-)

Caveman,
The only reason to establish statistical significance would be to establish a cause and effect relationship between the X-axis (time) and the Y-axis (snow extent). That would be an important piece of information if we were going to try to predict ice extent moving forwards. I am making no attempt to do that however.
Regardless, Tamino calculated 99% confidence before he applied his undocumented “cherry picking” test.
Speaking of cherry picking, a favorite study at Copenhagen was this Greenland melt study, which showed that Greenland melted a lot between 2003 and 2007.
http://www.spiegel.de/international/world/0,1518,661192,00.html
I’m really surprised that Tamino did not apply his cherry picking test to that.

Back in the early 90’s when I was a fresh faced Navy Wx observer,we took old school Airway observations. Then we went to Metar obs, a flawed and not as detailed observation method. Now, except in rare cases, all obs are ASOS generated which won’t report cloud decks below 10K.
I miss the old obs. The taking of them is a lost art and much valuable info is lost.expeciallly cloud type.

I’ve tried arguing this very same argument with AGW believers for some time now, but to no avail. Invariably, when you show that 1998-2009 shows no appreciable warming they will fall back on their “timescale insignificant” trope.
The point is, however, that length of time scale is less significant if you are dealing with cyclical changes. My example is a sine wave. if you have a sine wave with a wave length of 10cm you will get vastly different predictions of future trends with a sampling of anything less than 10cm. Furthermore, predicting the next 5cm of that wave really depends less on the length (below 10cm) and more on the where the sample is taken.
In a blind evaluation a 2cm sample at the apex of the curve would show a down trend while the 5cm sample on the up slope would incorrectly diagnose a rising trend for the next 5 cm. In this example the shorter trend is a better descriptor.

Robert, I read your first comment and I skipped to the end here. I didn’t put on my snowboarding gear, though.
If we accept only 90% confidence interval as *bleeding* edge
Then review the AR4 based on data of similar noise, the merger of multiple types of data and data sets with variable sampling rates and intervals and data populations,
to create first order LINEAR trends
for variable and possibly CYCLIC systems,
and call these first order linear trends climate models,
that they can predict reasonably to 50% into the future of the time that most of our data reasonably goes into the past,
to confidently identify that greenhouse gasses are the largest factor (such that we can discount others to simplify our model,)
and then have people go and attack OTHER people that suggest that 95% confidence interval would be necessary for refuting data,
I am 100% confident that I just crapped my pants.

They might argue that the average slope across the plateau is zero, therefore there are no hills
Or worse, that those hills are the product of curved space or from an entanglement of strings or its differences in level have been caused by the attraction of a tiny nearby “baby black hole”…
So we must get back to straight reason and leave behind all that nightmarish post modern “science”.

Steve,
“Who are you, who are so wise in the ways of Science?”
😀
Mark

Steve
“It is abundantly clear that there are “peaks” on the left and right side of the graph, and that there is a “valley” in the middle. It is abundantly clear that there is a “hill” from 1989-2010.”
It isn’t clear to me. It looks like noisy data points around a fairly steady mean. Flat trend if anything over the time frame shown. But that’s a good thing, IMHO.

Mark Young,
What is the air speed of a swallow?

Oops! Darwin did NOT know about genetics – sorry for skipping the essential word.

Steven Goddard:
Your article was a bit confusing to me. The title indicates that you want to emphasize the importance of skillful observations in science. Specifically you focus on observing the extent of snow cover for the last 20 or so years and point out that snow extent has increased and state that this proves the AGW predictions about snow extent were wrong.
Was it wise for the AGWers to make any predictions about snow extent from 1989 on? Isn’t snow extent for a 20 year period more a weather thing than a climate thing? We can skillfully observe snow extent increasing for the last 20 years but it neither proves nor disproves anything about AGW.
Analyzing ocean heat content trends and measurement limitations and dynamics seems much more relevant to climate (to me).
You mentioned something about relaxing the standards from 90% confidence to 55%. That is exactly the wrong direction to go in this climate debate.
You mentioned that science is for everybody. Not sure what you meant by that. Most everybody can benefit from studying science but few have the ability and preparation to advance science.
Unlike almost everybody who writes articles for this site, I haven’t seen a summary of your background.
The example about the hill height was a great example to show how important context is. As Dr. Leif points out, context is everything. Maybe you are thinking of building a house there and want to know where it is relative to the 100 year flood plain. Maybe you want to know how high it is from where you are standing. If the height of the hill is listed on a map, it is probably listed as distance above sea level.