From the GWPF
By Dr David Whitehouse
This new paper does not affect the fact that the temperature databases, with their own allowances for data-free regions, show no warming for 16-years, or at the very least no warming for about 95% of the globe for 16-years.
The ‘pause’ seen in the land and ocean global surface temperature during the last 16 years is one of the major talking points of climate science. It has been said by some politicians and journalists that ‘sceptics’ have used the ‘pause’ to undermine climate science. Actually there are a great many scientists and others working hard to understand the ‘pause.’ The ‘Pause’ IS climate science.
Many factors have been put forward as an explanation such as the warming going into the oceans, soot in the atmosphere, natural decadal variability, El Nino/La Nina variations, solar effects, and fluctuations in stratospheric water vapour to give just a few.
The ‘pause’ is seen across databases. It is a remarkable property of the HadCrut4, NasaGiss and NOAA surface temperature datasets and the UAH and RSS satellite lower atmosphere observations.
As we have said before in these pages, it is very curious that the global surface temperature for the last 16 years is flat given the increasing pressure of greenhouse forcing from the ever-rising concentrations of greenhouse gasses. We have also pointed out that the 16-year duration of the pause is not cherry-picked but comes purely from the properties of the data, and contrary to the belief of many the super El Nino year of 1998 makes no statistical difference to the length of the pause because of the following two cool La Nina years.
Even if there are currently more explanations for the ‘pause’ than can possibly be the case (or combine curiously to produce a straight line for 16 years) other explanations are to be welcomed and scrutinised. Hence the interesting new paper by Cowtan and Way in the Quarterly Journal of the Royal Meteorological Society.
Its central premise is not new. Global datasets might not be properly accounting for the recent warming Arctic due to poor sampling. Arctic temperatures are increasing faster than the global average. This would make such datasets cooler than they should be by a factor that depends upon the temperature rise and the area concerned. Cowtan and Way consider HadCrut4 which has gaps in its polar coverage. It should be noted that NasaGiss does carry out some extrapolation to infill missing Arctic data, and HadCrut4 takes into account the missing data in its uncertainty estimates.
In addition to the uncertainty estimates due to polar gaps the shift in 2012 from the HadCrut3 temperature database to HadCrut4 (which included more than 400 extra weather stations in Arctic regions to improve its polar coverage) resulted in an extra 0.04 deg C in warming in the global figure between 1998 and 2010. That extra warming has since been reduced because subsequent years have been cooler than 2010. HadCrut4 turned out to be a little warmer than HadCrut3 post-2005, though statistically it was actually flatter post-1997 than its predecessor.
To illustrate the lack of coverage problem Cowtan and Way take the global surface temperature datasets and reduce them in area to the coverage given by Hadcrut4 and compare before and after, their Fig 2. Click on image to enlarge.
This gives an estimate of the potential bias which is of the order of 0.02 deg C. Three datasets are shown though most researchers in this field use only Giss and UAH. I do not agree with the researchers comments: “All the global series show a rapidly increasing cool bias over the past few decades and a sharp decline starting around 1998.” The minor deviation seems to be at 2005 to me.
Access Denied
Cowtan and Way wanted to find a way to infill the absent data from the Arctic. It’s not an easy thing to do as there are spatial and temporal variations in all the data sets. The researchers used two methods, an infilling method to estimate missing data called Kriging, and a method based on satellite data. They determined a relationship between satellite and ground data and used it to estimate the ground temperature in regions where there is satellite but no ground data. Both techniques have to be applied very carefully.
The researchers created what they call a hybrid global temperature dataset from the satellite and ground data. When ground data is available they used that. When it was not they adjusted the satellite data over that region to produce an estimate of the ground data. They created global temperature databases based on their two approaches. They also removed data at the start and saw if their method was any good in reproducing the deleted data.
Their Fig 3 shows the differences between estimates and observations. Click on image to enlarge.
The typically degree plus differences to my mind suggests there is too much uncertainty to draw any detailed conclusions.
No infilling technique was consistently the best performer. The hybrid method was the best when there was no data, in general kriging was better for the rest of the world. However, looking more carefully shows that the hybrid system was generally best for land whilst neither of them showed any predictive skill over Antarctica.
It is slightly worrying that the researchers then picked the best reconstruction method for various parts of the Earth to create a mosaic of methods to represent global reality. They call this “blended” data. To a paper that wanted to infill missing data in the polar regions, and to a lesser extent Africa, this selection of models to represent other regions of the world as well adds a new layer of complexity if not a biased selection effect.
Ultimately does this reconstruction make any difference?
Looking at their Fig 6 the result is that the temperature period 1997 -2005 remains unchanged and flat. Click on image to enlarge.
That of 1997 – 2007 could have an extra 0.02 deg C warming, and 1997-2011 (the last year they consider) perhaps an increase of 0.03 deg C. Looking at HadCrut4 over this period puts those changes into perspective as they are about 5% of the interannual variations. Click on image to enlarge.
The claim has been made that when the adjustments are taken into account the post-1997 trend is two-and-a-half times higher for HadCrut4 than it was, increasing to 0.12 deg C over the period as opposed to 0.05 deg C – still not statistically secure with one sigma errors of about 0.08 deg C. That’s still considerably less than a degree per century, though closer to the IPCC’s canonical 0.2 deg C per decade.
Given that Antarctica shows no overall warming and that the missing Arctic region is a very small section, about 6 per cent, of the globe, it is curious, perhaps even a fluke that such a small region of the Earth has come to the rescue of climate science from the undermining ‘pause?’
This new work doesn’t affect the fact that the temperature databases, with their own allowances for data-free regions, show no warming for 16-years, or at the very least no warming for about 95% of the globe for 16-years. That in itself is inconsistent with the climate models.
This research is interesting but doesn’t live up to the headline that it explains the ‘pause.’ It also does not warrant such an extensive press release, complete with explanatory videos. It is clear that it has been used as a political tool to deride ‘sceptics’ who rightly see the ‘pause’ as significant. By aiming at ‘sceptics’ such an approach also derides many working scientists who are trying to explain the ‘pause.’ This is regrettable.
Feedback: david.whitehouse@thegwpf.org
elmer says:
“Why the big pause?”
Well, I thought it was natural variability.
You can usually tell how strong the evidence is by what Steve Connor of the Independent has to say about it. When I read what he had to say this morning I assumed that the story was overblown and waited to see whether analysis would emerge which confirmed that hunch or not.
What a coincidence that this comes up at the Warsaw jamboree time.
If it was serious, it would have been released at a different time.
It doesn’t really strengthen the warmists’ case, does it??
So now I’m confused. I thought the missing heat was hiding in the deep ocean. Now I learn that polar bears have been keeping it a secret–perhaps by interfering with the thermometers.
From a purely strategic viewpoint, I think the warmists should have stuck with the deep ocean. It will take years to get good measurements there and while that happens, they can just keep pushing it deeper and deeper until their models say it’s cookin’ at the bottom of the Mindinao trench and threatening the extinction of some obscure deep trench life form.. But blaming it on the polar bears is dangerous because people can actually get there with thermometers.
Dr David Whitehouse remarked “We have also pointed out that the 16-year duration of the pause is not cherry-picked but comes purely from the properties of the data,…”.One might take the view that /any/ data selection other than the complete available data might also be regarded as a form of cherry picking. One can also suppose that any form of data manipulation, in particular smoothing, is an attempt to influence the perception of the data by the intended readership. However, smoothing is widely regarded as legitimate and informative, and I fully agree with this.
In my preliminary assay of a new data set I invariably look at the complete available data. Sometimes some data are missing. I avoid inserting artificial data whatever the complexity or sophistication of the method used. Kriging can readily be thought of as a method that could be described by both these terms. It may be useful. It may be effective when real observations are unavailable, but I nevertheless have serious reservations about believing that all the algebra and arithmetic produce a reliable substitute for real data.
The method I use is to form the cumulative sum using every available data item using the mean of the data as the cusum basis. This ensures that the cusum will start close to zero and finish exactly at zero. Any other choice will produce an overll general slope in the cusum plot. A missing point simply produces a small gap in the cusum and its (trivial) effect is ignored. We are, after all, interested in large scale and long lived phenomena (it’s climate, not weather) and in a long time series a substantial proportion of missing data seem to be of little influence on the grand scale appearance of the cusum. This is easily verified by introducing missing values, and re-calculating the cusum series. Try it for yourselves.
Plotting the cusum against the time axis is essential, and is very rewarding and revealing. The general structure of the original data is immediately obvious. It is not appropriate here to go into the methods for examining cusum plots because, though quite simple, they require careful explanations, which I me very willing to make given an appropriately sized slot. Experience can reveal hidden history of the data (has it been pre-processed, for example), as well as the possibilty of abrupt changes, the durations of steady states and other features of potential interest, such as periods of rather unstable climatic conditions. Famously, cusums /cannot and must not/ be used in an attempt to forecast the future. They are extremely highly auto-correlated and they merely reflect the past. Moreover, they have convinced me that detailed forecasting of climate for particular geographical areas is likely to be spectacularly ineffective. The possible onset of an abrupt change is virtually impossible to detect before it has occurred. That is what forecasting is about. I fear that at the practical (useful) level it doesn’t work.
Robin
Even IF HadCRUT4 is allegedly running cool by 0.03 degrees C due to insufficient capture of the Arctic, it’s surely running warm by a FAR higher value due to insufficient adjustment for UHI and other siting issues, plus land-use changes?
Those claiming that C&W eliminates the ‘pause’/downturn probably need to look at some other biases, not least their own, before making ironic use of the ‘cherry-picking’ insult.
Further to the cherry-picking allegations: the periods of no warming measured by the various temperature indices are calculated by going BACKWARDS from the PRESENT, not by picking an arbitrary unusually-high point in the past to make the climate appear to be doing something that it is not.
The fact that, 15 years later, 1998 is still described as an unusually high point, rather shoots down the oft-heard line of the last decade that 1998’s figure would be seen as normal by about now.
the Arctic is not warming….
The polar bear went down to the radio station to look for a job. They said, “You don’t meet the requirements.”
“What requirements? the bear asked.
“Wee paws for station identification.”
And even the tiny adjustment of the HadCRUT data do not bring the temperatures up to where the models claim they should be.
The CAGW hypothesis is still failing its principal test.
So great are the uncertainties in the global surface temperature record, that for all we know, the “pause” may have lasted since 1880, or even 1850.
http://gst-fiasco.blogspot.co.uk/p/the-elusive-absolute-surface-air.html
“Extensive press release”? Here in the UK only one newspaper, the Independant, has picked up on it at all. The BBC apparently has yet to hear of it.
The wheels are definitely falling off the AGW bandwagon.
CodeTech says:
November 19, 2013 at 2:37 pm
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Bingo on all points!
I would love to see a before and after adjustment graphic of the 30’s temp trends pulled forward.
I probably should have searched here a bit deeper prior to typing that {°¿°}
The planet stopped warming more than a decade ago. Meanwhile, since 2001 the CO2 level has increased by 29% of the increase prior to 2001. Change to the level of atmospheric carbon dioxide has never had a significant influence on climate and never will. At http://averageglobaltemperature.blogspot.com/ see an eye-opening graph and a simple equation that, with only one external forcing, calculates an average global temperature anomaly trend since 1610 and, with 90% accuracy (correlation coefficient = 0.95), calculates measured average global temperature anomalies since before 1900. See why the LIA and Global Warming both ended. CO2 change had no significant influence.
Relatively new here, so do not want this to sound like a dumb question. Is there a standard definition for “Arctic” that is being used? I understand Arctic Ocean when it is mentioned, but some “Arctic” research of late, like the Baffin Island moss, seems to be in areas barely north of the Arctic Circle. A resident of Norilsk, Russia, may consider Baffin Island a “banana belt.” Temperature data from large cities, like Murmansk and Norilsk possibly benefits from UHI effects.
But, I do know enough to catch a geography problem with the children’s Christmas movie, “Polar Express”, that my granddaughter was watching last weekend. The train with the children seemingly crosses the Arctic Circle and then arrives at the North Pole within minutes. (As the little girl says, “it’s a magic train.”)
Re the apparent warming in the Arctic. Several factors are at play here.
Firstly, aircraft movements across the polar region have increased significantly over the past few decades. This has led to an increased instance of persistent contrails in the Arctic sky – which, in turn, trap heat (rebounded long-wave radiation) beneath a cirrus-like cloud cover.
Secondly, there is a significant push by the US, Canada, Norway, Denmark, Britain, the Netherlands and Russia to develop oil and natural gas reserves in the Arctic Ocean and adjacent coastal regions. This has contributed to localized heating across northern Alaska, in the Chukchi and Beaufort Seas, and the Barents Sea on the Russian/Scandinavian side of the ocean.
Thirdly, rising land temperatures have triggered the release of methane gas in coastal regions – leading to further heating.
Finally, there has been a concerted effort to open the shipping lanes (e.g., the Northwest passage) year round. Indeed, Hycom’s Arctic Sea Ice Concentration graphics frequently reveal the movement of ice-breakers traversing between the North American and Siberian sides of the Arctic.
Greg Beasley
(Prospect, NSW)
1998 is “cherry picked” because it is a pivot point that delineates a meaningful trend change. The warming from 1979-1998 that caused all the hoopla is equally “cherry picked”.
Shortest joke ever:
“A baby seal walks into a club…”
I strongly think there is no “pause”, “hiatus” or whatever they call it. Plain and simple: The warming period ended.
Louis, nice try.
But Henny Youngman’s “Take my wife, please” is shorter.
There are others:
Venison’s dear, isn’t it?
Stationery store moves.
Dwarf shortage.
So, the missing heat is not really in the deep oceans? It is in the Arctic? Have they told Trenberth?
The sad work of these two in trying to confuse the issue is not going to help the AGW movement like the authors hoped.
Good post, fine distinction, it is the data base we were assured is the gold standard, when it showed warming.
Now that the same data shows less warming, flatlining and possibly slight cooling, it is not suitable and requires enhanced data, pulled out of the Mann,Lew..whatever, system and perfectly timed for the IPCC gabfest.
I am sure the duo are perfectly normal Team IPCC (TM) ‘Climate Scientists”.
So the earth has warmed at .12C/decade? Or has there been no warming? You say both. You’ve done nothing to show that combining UAH data in the arctic with global HadCRUT4 data is a bad method. Warming of just .04C/decade is consistent with climate models IF you are excluding the fastest warming part of the globe.
Combining UAH arctic data with HadCRUT4 surface data seems like an excellent method to me. In fact, I developed and used this method for the first time myself 5 or 6 years ago on another forum.
The Gin and….Tonic joke is simply unbearable.
There cannot be a pause because the models did not predict one. The data simply must be wrong. There is no other explanation. We must adjust the data to fit the models. After all, we know that our model results are correct with 95% certainty and besides, 95% of Scientists agree that the models are correct. So the data must be wrong. Or are you suggesting that 95% of Scientists are wrong? I just cannot believe that scientists could be wrong, nope, it is definitely the data.
Did you check the temperature in my office? There is no weather station on my desk and it is rather hot. I suspect that is where the missing heat is.