Statistical Significances – How Long Is "The Pause"? (Now Includes September Data)

“Well she was just seventeen,
Now we know flat’s the mean…”
Apologies to Paul McCartney…

It’s an upside down greenhouse effect.

No-one seriously believes that their data really is a linear trend with AR(1) fluctuations
I’m not sure that I believe this staement, Nick.

“The Pause”.
Sounds like a Stephen King novel. But I guarantee it’s keeping some people awake at night filled with fear. They wonder if their gravy train has finally gone off the rails.
It’s a travesty, really.
(Pause, cyclical Peak, tomato, toMAHto)

Well, and then there is what happens if you add in the error bars in the underlying data. Let’s take HADCRUT4, for example, which has a claimed sigma of around 0.15 C for the period(s) graphed above. RSS is trickier — they estimate error with Monte Carlo, and the result varies with latitude, but sigma errors appear to be in the range 0.03C to 0.05 C (it is reasonable that satellite observations would be more systematic and would have smaller error bars than any of the mostly-land based estimates of e.g. GASTA. And let us not forget — we’re still dealing with the claim that GASTA is known to order of a few tenths of a degree at the same time NASA openly acknowledges that GAST is unknown more accurately than order of a full degree C even in the modern era, a proposition that I find rather dubious (but more dubious when supposedly connected back over 100+ years than over the satellite era).
With admitted uncertainty in the actual data the trend is a lot more difficult to compute, not just from persistence of supposedly irrelevant autocorrelation but from the fact that we cannot possibly know measured quantities precisely and the quantities in question are globally extrapolated averages from (usually remarkably sparse and imprecise) measure quantities sampled irregularly in space and time. The most correct statement one can make about the pitifully short data intervals pictured above is that a) they are nearly trendless; b) the uncertainty in the data, and hence the trend, is great. Since historically climate data has repeatedly exhibited trended stretches of fifty years or more with gains in GASTA (according to e.g. HADCRUT4) that almost precisely match the warming observed in the late 20th century — for example in the early 20th century — talking about “95% confidence intervals” for any purpose but falsifying the GCMs used to predict catastrophic CO_2-linked warming is rather pointless. With regard to the GCMs, a significant fraction of the models contributing to CIMP5 are manifestly inconsistent with all of the anomaly predictions. This doesn’t disprove CAGW, but it does prove that most if not all of the GCMs are unreliable and that to the extent that predictions of CAGW rely on them, the correct answer is that we currently have no idea if CAGW is a correct hypothesis, but it is rather LESS likely to be true as opposed to more likely.
rgb

No-one seriously believes that their data really is a linear trend with AR(1) fluctuations, [but we all use that anyway]
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Forgive me, Nick, but isn’t that rather like me saying “I know I can’t really drive through rush houor at the speed limit, but, for convenience, I’m going to model my commute as if I can” and then telling the boss it’s him in the wrong when I’m consistently late for work?

Richard M says:
November 3, 2013 at 3:39 pm
I think it’s now pretty obvious that we will pass the 17 year mark when RSS comes out with their October numbers.
The anomaly was 0.257 in September. It only needs to be 0.265 or less in October so the chances are over 50% that it will happen when October’s numbers are out.

Thanks, Werner, JustTheFacts, Nick. Very good article.
Yes, it is a long time now, too long to dismiss anyway. But the future will be as nature pleases.

Nick Stokes says:
November 3, 2013 at 4:30 pm
“It doesn’t need to perfectly predict how your journey will go, but it needs to give average variation.”
Then after 6 months of commute and not getting to work reliably the responsible employee ditches the model and starts using actual observational data.

Is Dr. Phil Jones getting worried now. It’s all happening right now for ya.

Dr. Phil Jones – CRU emails – 7th May, 2009
‘Bottom line: the ‘no upward trend’ has to continue for a total of 15 years before we get worried.’

I see. So that “alow 10 extra minutes”, just in case, so you will be 95% sure to never understate the time and be late is like the positive adjustments to the temperature records when they are homogenized, the stations sliced, diced and excluded to produce “the product”. 😉

wayne says:
November 3, 2013 at 5:28 pm
I see. So that “alow 10 extra minutes”, just in case, so you will be 95% sure to never understate the time and be late is like the positive adjustments to the temperature records when they are homogenized, the stations sliced, diced and excluded to produce “the product”. 😉
With a gallon of tequila, wayne and I would be the life of the party….
(Or, translating for wayne, wihteoh thgall on tesyksia wanisn and i oule be the lifffr of the preth)

no pause in Hansen’s nuclear advocacy:
3 Nov: CNN: Top climate change scientists’ letter to policy influencers
Editor’s note: Climate and energy scientists James Hansen, Ken Caldeira, Kerry Emanuel and Tom Wigley released an open letter Sunday calling on world leaders to support development of safer nuclear power systems. For more on the future of nuclear power as a possible solution for global climate change, watch CNN Films’ presentation of “Pandora’s Promise,” Thursday, November 7, at 9 p.m. ET/PT…
http://www.cnn.com/2013/11/03/world/nuclear-energy-climate-change-scientists-letter/
***LOL:
3 Nov: CNN: Thom Patterson: Climate change warriors: It’s time to go nuclear
Cavanagh (Ralph Cavanagh of the Natural Resources Defense Council) said the “movie (Pandora’s Promise) attempts to establish the proposition that mainstream environmentalists are pouring into nuclear advocacy today. They aren’t. I’ve been in the NRDC since 1979. I have a pretty good idea of where the mainstream environmental groups are and have been. I’ve seen no movement.”
***Selling nuclear energy to environmentalists is a tough pitch. Hansen acknowledged that many of them won’t easily buy into it. Parts of the community operate like “a religion of sorts, which makes it very difficult,” Hansen said. “They’re not all objectively looking at the pros and cons.”…
http://www.cnn.com/2013/11/03/world/nuclear-energy-climate-change-scientists/index.html
no doubt some will welcome this…but not me.

Nick: “And it mostly works.”
==
and you mostly know why…
In this case…if the temps go down….no one has a clue why
..and if temps go up….no one has a clue why
Face it people, they’ve been flat out lying for 15 years…and they are lying now

Nick Stokes says: “Well, it’s 97% certain :). ”
Nice:))

for James Hansen & Co:
4 Nov: Bloomberg: Pankaj Mishra: India Shouldn’t Buy What Japan Is Selling
Last week in the south Indian city of Pondicherry, I met a friend who had managed to penetrate the security lockdown around Kudankulam, the Russian-built nuclear power station in Tamil Nadu that began partial operations late last month despite strong protests from local villagers.
Kudankulum lies only a few miles away from a coastline that was ravaged by a tsunami in 2004. Opposition to the plant intensified after another intense earthquake and tsunami in March 2011 caused meltdowns at three nuclear reactors at the Fukushima nuclear plant in Japan. Since then, Indian police have deported the few journalists who have tried to report on the protests, sequestered entire villages and levied criminal charges against tens of thousands of locals, some of whom have been accused of sedition and “waging war on the state.” …
It is also true that, as Japan scholar Jeff Kingston points out, the export of technology by Japanese companies is key to Abenomics. Japan is at the center of the global nuclear-industrial complex, which stands to benefit greatly from the continued sale of an outdated and demonstrably dangerous technology to wannabe nuclear powers such as India and Turkey.
Toshiba Corp. owns 87 percent of Westinghouse Electric Co. LLC, which is helping to build a nuclear plant — again, against intense local protests — in the Indian state of Rajasthan; Hitachi Ltd. and Mitsubishi Group are in collaborations with General Electric Co. and the French company Areva SA, whose multiple deals with India make it the real beneficiary of the country’s U.S.-assisted admission to the nuclear club in 2008.
In this scramble for large profits, democratic values such as oversight, accountability and transparency are likely to be trampled into the dust. The case of Tepco shows how a large and networked company can buy the silence of the media as well as of politicians and regulators. Thus, while Fukushima remains volatile, another nuclear catastrophe seems to be developing in India. As in Japan, the full-throated advocacy of nuclear energy by its leaders, and the absence of debate within the Parliament or the mainstream media, reinforces the bitter truth of a line from Slovenian philosopher Slavoj Zizek that Ramana quotes in his book: “It is indeed true that we live in a society of risky choices, but it is one in which only some do the choosing, while others do the risking.”
http://www.bloomberg.com/news/2013-11-03/india-shouldn-t-buy-what-japan-is-selling.html

@jeanparisot.
It’s all mine.

UPDATE:
RSS for October has just come out and the value was 0.207. As a result, RSS has now reached the 204 month or 17 year mark. The slope over the last 17 years is -0.000122111 per year.

Then you have to take into account the data tampering that has gone. Steve Gorddard shows what the NOAA did to September
http://stevengoddard.wordpress.com/2013/11/03/noaa-data-tampering-reaches-a-tipping-point/
I assume werner is using the adjusted data for the NOAA data set

I should have added the following link to my comment on data tampering above. Again from Steve Goddard
http://stevengoddard.wordpress.com/2013/11/02/latest-nasa-global-data-tampering/

We all know that CO2, other items being constant, will reflect a certain band of radiation back to earth. The results should be an increase in temperature.
————
I don’t think we all know that. I don’t think it’s ever been demonstrated that adding *any* kind of green house gas the the atmosphere causes the temperature to increase.
In fact, if you removed the most powerful green house gas, water vapor, from the atmosphere, the temperature wouldn’t go down, it would go *up*! A lot. By about 20 degrees or so, if I remember correctly. This is because water vapor creates clouds which have an overall powerful cooling effect on the planet.
AGW depends on water vapor to get the heating it claims. But the facts are that water vapor has the exact opposite effect: it cools the planet.

Yes, and record adjustments and differential from RSS.
http://stevengoddard.wordpress.com/2013/11/03/noaa-data-tampering-reaches-a-tipping-point/

Don’t know about hiding in the deep ocean, I reckon the missing heat went underground and has appeared through a vent in the centre of Australia.
Still 2 months to go but we are having a warm one:
http://www.bom.gov.au/climate/updates/articles/a003-2013-temperature.shtml
Good news for the alarmists and tax loving politicians who are now vigorously promoting an emissions trading scheme. Doesn’t matter whether Central Europe has had 5 consecutive winters colder than normal or that the Antarctic re-supply ship Aurora Australis is icebound in record sea ice 10 days behind schedule and still 177 nm from her destination.
You will not hear about this on our ABC. All you will hear about is bush fires and heat waves. Yep, global warming for many is all about the cherries in your own back yard.
Last year was looking dicey for the demon CAGW but now we will need at least another 2-3 years of a line that looks more like a sine curve than a straight line on the temperature anomaly chart before it will be endangered here.

How much CO2 does it take to support the AGW industry?

Re Commute to work
When a recession hits, thanks to politicians and bankers, the commute time goes down as does fuel usage and the model can change. For instance you can have a ten minute water cooler chat about the weather. Then there are the seasonal adjustments for school holidays when, in the UK at least, the volume of traffic drops by about 15% and a shorter journey time is the result.
It’s a great analogy.

Good informative post but the way you are representing CO2 is totally misleading. You are delibarately scaling and offsetting so that the slope fills the graph range. You could do that with absolutely anything that has a positive trend and it would not show a damn thing about its relation to surface temps.
You have chosen a particularly useless web tool to show such a comparison because you can do nothing apart from detrending and running means on the data. (Duh!)
Probably the best you can do is scale CO2 to 400ppm full range. This is enough to make the point that it has been steadily rising despite the ‘pause’.
http://www.woodfortrees.org/plot/esrl-co2/from:1975/scale:0.0025/offset/plot/rss/plot/rss/from:1997/trend
Since CO2 “forcing” is supposed to be a log relationship and then you need to consider how to scale it (ie climate sensitivity, which is the big question) this is still not right but at least you are showing the actual quanity of CO2 not rigging it to make your point.

Greg Goodman says:
November 4, 2013 at 2:29 am
Good informative post but the way you are representing CO2 is totally misleading. You are deliberately scaling and offsetting so that the slope fills the graph range. You could do that with absolutely anything that has a positive trend and it would not show a damn thing about its relation to surface temps.
There are different ways of looking at this. According to Nye, the CO2 is rising “extraordinarily fast” as shown by the link below. And if you go by percentages for CO2 versus temperature since 1750, there is no comparison. CO2 went up from 280 ppm to 400 ppm or an increase of 43%. Meanwhile, temperatures went up from about 287.0 K to 287.8 K or an increase of 0.0028%. You raise good points, and while no representation is perfect, in view of the percentages above, I do not agree that my way is “totally misleading”. As a direct result of Dr. Brown’s comments on my last post, I added the following comment to this post:
“The upward sloping CO2 line only shows that while CO2 has been going up over the last 17 years, the temperatures have been flat for varying periods on various data sets.”
NYE: So here’s the point, is it’s rising extraordinarily fast. That’s the difference between the bad old days and now is it’s —
MORANO: Carbon dioxide —
NYE: It’s much faster than ever in history. And so —
Read more: http://newsbusters.org/blogs/noel-sheppard/2012/12/04/climate-realist-marc-morano-debates-bill-nye-science-guy-global-warmi#ixzz2jgCV7ZVs

To see why linear methods underestimate natural variability, consider for a moment the annual cycle of temperatures at some location. plot this on a piece of paper, you get the familiar sin/cos curve from high school math class.
now consider that “the pause” is summertime temperatures. fit the linear approximation and you will get the flat line in the opening graph. Assume that the variability is due to noise, and you will get the “V” shaped lines opening up to the right. This is the 95% projection of where your future temperatures must be.
But what you have is nonsense. Look ahead 6 months and the wintertime temperatures will be lower than the lower bound for your 95% projection, and the upper bound for the 95% projection is so high as to be ridiculous.
The problem is the underlying assumption. the assumption that your data (climate) is linear with noise (weather) is wrong. weather is the result of daily and annual cycles in nature. climate is a similar process, with time scales measured in hundreds, thousands and millions of years.
Our mistake is in seeing climate as the average of weather. It isn’t. We measure climate as the average of weather, so our minds create the illusion that climate is the average of weather, but nature isn’t controlled by our measuring process.
Weather is the chaotic response of nature to short term cycles. Climate is the chaotic response of nature to longer term cycles. Both are inherently unpredictable given our current level of understanding, except to the degree that cyclical systems tend to repeat.

imagine for a moment that you were an extremely long lived creature, that years passed as seconds. each day of your life would be 32 million years long, and your 80 year lifespan would cover about 2.5 billion years.
daily weather would be imperceptible. annual weather would be a 1 second pulse. 100 thousand year ice ages would last slightly more than 1 day. These 100 thousand year cycles would show a warming and cooling cycle very much like we experience day to day. Over time, some “days” would be warmer and some would be cooler – very much like our daily weather. As time scales increase we see hot house earth – summer and we see ice house earth – winter. We see some “months” that are wet and some that are dry – long term climate change.
But in all of this, there is nothing to suggest that climate is the average of weather. Rather, that weather and climate are the same process, differing only in time scales. We create the illusion that climate is the average of weather over time as a result of our measuring process. But this is not the reality.

The mathematical definition of climate as the 30 year average of weather has created an illusion of climate predictability that does not match reality. Because we define climate as the average of weather, we apply all sorts of statistical properties to climate based on our understanding of averages.
For example, we assume that climate can never “naturally” get hotter than the hottest day in summer, or colder than the coldest day in winter. This is how average work. So, when we see climate starting to get hotter or colder than past weather, we start to think something “unnatural” is happening. That humans must be changing the climate.
What we fail to consider is that the formal definition of climate as the 30 year average of weather is a human definition. It is not nature’s definition of climate and nature is not in the slightest bound by our definition.
Our formal definition of climate as the 30 year average of weather is fundamentally wrong. It has led climate science down a path of statistical prediction based on mathematical properties that do not match reality. It has caused us to significantly under-estimate natural variability and to seriously over-estimate our confidence levels in our predictions.
Climate is not the average of weather over time, and thus cannot be reliably modeled using weather averages.

Nick Stokes says:
November 4, 2013 at 7:41 am
Box who famously said – “all models are wrong, but some are useful”.
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“some are useful” means “most are useless”. The IPCC models clearly demonstrate this.

Nick Stokes says:
November 4, 2013 at 7:41 am
ferd berple says: November 4, 2013 at 5:39 am
that pretty much sums up climate science. use a model that everyone agrees doesn’t match the characteristics of the underlying data, and then place your faith in the results of the model.”
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It isn’t climate science – it is standard statistics, used by all sorts of people. In fact, these are Box-Jenkins models. You know, the Box who famously said – “all models are wrong, but some are useful”. These are the models he was talking about.
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Nick, it may be “standard statistics” but standard statistics are useless when misapplied to situations that don’t comply with the fundamental assumptions inherent in them.
The fundamental assumption when plotting linear trends is that the data is inherently linear (even if noisy), or at least has a linear component that we can detect. Fitting a linear trend to primarily cyclic data is absolutely meaningless unless you know the nature of the cyclic behaviour. It’s the sort of basic mistake we were warned against as 14 year olds in O level mathematics!
To suggest that linear trends are suitable, you’re effectively saying that we know all cycles in the climate system over all timescales . Because, if we don’t, then the apparent trend we measure may be part of an “up” or “down” slope of a cycle that we haven’t considered.
Do you really have enough hubris to claim that we know everything there is to know about every climate cycle?