From Wikipedia:
Polar amplification is the greater temperature increases in the Arctic compared to the earth as a whole as a result of the effect of feedbacks and other processes. It is not observed in the Antarctic, largely because the Southern Ocean acts as a heat sink and the lack of seasonal snow cover. It is common to see it stated that “Climate models generally predict amplified warming in polar regions”, e.g. Doran et al.
Now with this paper, blowing the surface data out for AGW effects, what are they going to do?
Via the Hockey Schtick:
New paper finds only 1 weather station in the Arctic with warming that can’t be explained by natural variation
A paper published today in Geophysical Research Letters examines surface air temperature trends in the Eurasian Arctic region and finds “only 17 out of the 109 considered stations have trends which cannot be explained as arising from intrinsic [natural] climate fluctuations” and that “Out of those 17, only one station exhibits a warming trend which is significant against all three null models [models of natural climate change without human forcing].” Climate alarmists claim that the Arctic is “the canary in the coal mine” and should show the strongest evidence of a human fingerprint on climate change, yet these observations in the Arctic show that only 1 out of 109 weather stations showed a warming trend that was not explained by the natural variations in the 3 null climate models.
Note a “null model” assumes the “null hypothesis” that climate change is natural and not forced by man-made CO2 or other alleged human influences.
GEOPHYSICAL RESEARCH LETTERS, VOL. 39, L23705, 5 PP., 2012
doi:10.1029/2012GL054244
On the statistical significance of surface air temperature trends in the Eurasian Arctic region
Key Points
- I am using a novel method to test the significance of temperature trends
- In the Eurasian Arctic region only 17 stations show a significant trend
- I find that in Siberia the trend signal has not yet emerged
C. Franzke
British Antarctic Survey, Natural Environment Research Council, Cambridge, UK
This study investigates the statistical significance of the trends of station temperature time series from the European Climate Assessment & Data archive poleward of 60°N. The trends are identified by different methods and their significance is assessed by three different null models of climate noise. All stations show a warming trend but only 17 out of the 109 considered stations have trends which cannot be explained as arising from intrinsic [natural] climate fluctuations when tested against any of the three null models. Out of those 17, only one station exhibits a warming trend which is significant against all three null models. The stations with significant warming trends are located mainly in Scandinavia and Iceland.
Introduction
[2] The Arctic has experienced some of the most dramatic environmental changes over the last few decades which includes the decline of land and sea ice, and the thawing of permafrost soil. These effects are thought to be caused by global warming and have potentially global implications. For instance, the thawing of permafrost soil represents a potential tipping point in the Earth system and could lead to the sudden release of methane which would accelerate the release of greenhouse gas emissions and thus global warming.
[3] Whilst the changes in the Arctic must be a concern, it is important to place them in context because the Arctic exhibits large natural climate variability on many time scales [Polyakov et al., 2003] which can potentially be misinterpreted as apparent climate trends. For instance, natural fluctuations on a daily time scale associated with weather systems can cause fluctuations on much longer time scales [Feldstein, 2000; Czaja et al., 2003; Franzke, 2009]. This effect is called climate noise. Even very simple stationary stochastic processes can create apparent trends over rather long periods of time; so-called stochastic trends [Cryer and Chan, 2008; Cowpertwait and Metcalfe, 2009; Barbosa, 2011; Fatichi et al., 2009; Franzke, 2010, 2012]. On the other hand, a so-called deterministic trend arises from external factors like greenhouse gas emissions.
[4] Specifically, here I will ask whether the observed temperature trends in the Eurasian Arctic region are outside of the expected range of stochastic trends generated with three different null models of the natural climate background variability. Choosing the appropriate null model is crucial for the statistical testing of trends in order not to wrongly accept a trend as deterministic when it is actually a stochastic trend [Franzke, 2010, 2012].
[5] There are two paradigmatic null models for representing climate variability: short-range dependent (SRD) and long-range dependent (LRD) models [Robinson, 2003; Franzke, 2010, 2012; Franzke et al., 2012]. In short, SRD models are the most used models in climate research and represent the initial decay of the autocorrelation function very well. For instance, a first order autoregressive process (AR(1)) has an exponential decay of the autocorrelation function. LRD models represent the low-frequency spectrum very well, have a pole at zero frequency and a hyperbolic decay of the autocorrelation function. One definition of a LRD process is that the integral over its autocorrelation function is infinite while a SRD process has always an integrable autocorrelation function [Robinson, 2003; Franzke et al., 2012]. In general, both stochastic processes can generate stochastic trends but stochastic trends of LRD models can last for much longer than stochastic trends of SRD models. This shows that the rate of decay of the autocorrelation function has a strong impact on the length of stochastic trends. In addition to these two paradigmatic models we will also use a non-parametric method to generate surrogates which exactly conserve the autocorrelation function of the observed time series. Figure 1 displays the autocorrelation function for one of the used stations and the corresponding autocorrelation functions of the above three models. It has to be noted that there are a myriad of nonlinear stochastic models which can potentially be used to represent the background climate variability and the significance estimates will depend on the used null model. However, I have chosen the three above models because two of them represent paradigmatic models for representing the correlation structure and one conserves exactly the empirical correlation structure.
Figure 2. Map of stations: Magnitude of the observed trend in °C per decade.
Results
[17] Figure 2 displays the location of all stations and the colour coding indicates the magnitude and sign of the temperature trends. The first thing to note is that all stations experience a warming trend over their respective observational periods. The largest trends (more than 0.4°C per decade) are in central Scandinavia and Svalbard. Most of Siberia experienced warming trends of about 0.2–0.3°C per decade.
[18] After finding evidence for warming trends we have now to assess their statistical significance; do the magnitudes of the observed trends lie already outside of the expected range of natural climate variability? The above three significance tests reveal that 17 of the 109 stations are significant against an AR(1) null model (Figure 3a), 3 stations are significant against a ARFIMA null model (Figure 3b), and 8 stations are significant against a climate noise null hypothesis using phase scrambling surrogates (Figure 3c). All these trends are significant at the 97.5% confidence level. This shows that while the Eurasian Arctic region shows a widespread warming trend, only about 15% of the stations are significant against any of the three significance tests.
Figure 3. Stations with a statistically significant trend against (a) AR(1), (b) ARFIMA, (c) phase scrambling null model and (d) stations with a significant trend: blue: weak evidence, green: moderate evidence and red: strong evidence.
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That lone red dot on South West Iceland is bang on the mid-Atlantic ridge where there is plenty of very hot water on or not far below the surface.
http://www.randburg.com/is/or/
It is also home to the ISAL aluminum smelter which uses close to 3,000 gigawatt hours of electricity per year, or 17% of the electricity used in Iceland. The Company’s output of aluminium is approximately 190,000 tonnes annually.
http://www.riotintoalcan.com/documents/ISAL_Sustainable_Development_Report_2011.pdf
Deco79 says:
December 11, 2012 at 2:30 pm (responding to)
Gail Combs says:
December 11, 2012 at 1:32 pm
People keep saying the Arctic is ‘warming’ so how come the Length of the Arctic Melting Season is getting SHORTER?
Hi Gail. A quick experiment…Take a 1kg piece of ice out of the freezer and put it in a room that is say 18C. Then take a smaller piece of ice out and put it in a room slightly warmer than 18C. Time how long it takes for both pieces of ice to melt. That will give you your answer.
Hmmmn.
But Gail, the DMI daily measured temperatures at latitude 80 north – where the ice actually is at the time of minimum sea extents in mid September each year – shows that “the Arctic” is not getting hotter.
Since 1958, the DMI reports measured arctic air temperature through the summer ice melt season – up where the ice actually is, not down in the mid-tundra 1200 km further south near mid-Canada’s “red spot” – is not only steady (within 1/10 of one degree, but recent arctic summer temperatures have been getting colder!
And, just to confuse Deco79’s day even further, each square kilometer of sea ice that melts below the long-term sea ice minimum of 7 million km^2 seems to increase the cooling of Arctic waters even more!
(Now, recent all-time record high Antarctic sea ice DO reflect more energy from the sun, and DO add to the global cooling in the southern hemisphere. So he can’t claim he’s all wrong.)
It is good to see that someone is considering the consequences of a broader class of statistical models to test whether or not (relative to each class of model) there has been a statistically significant secular trend in temperature. To re-iterate a statement made in the paper, models that exhibit long-range dependence (LRD) can spontaneously give rise to apparent trends lasting on decadal timescales – even when the underlying statistical process has (by construction) no secular trend. And since historical surface temperature data (whether this be a global average or more local measure) does exhibit LRD, we are forced to conclude that, based on a detailed examination of the statistics of those time series alone and given their relative brevity, it is not practicable currently to distinguish a secular trend in the temperature record from endogenous noise for those statistical models that do exhibit LRD. [N.B. Yes, of course, the temperature record shows an increase over the last 50 years or so. That isn’t in dispute. But also that isn’t the issue.]
feet2thefire says:
December 11, 2012 at 11:27 am
My first comment was going to be this:
If 1 out of 109 canaries dies in a mine – who the hell empties out the men from the mine based on that?
Not all what the CAGW theists want to do in that coal mine.
They want to shut down the coal mine, throw all of the workers and their families out in the dark to starve to death from the cold and wet because that first canary MIGHT die in the coal mine … sometime in the next four years!
@RACookPE1978
“They want to shut down the coal mine, throw all of the workers and their families out in the dark to starve to death from the cold and wet because that first canary MIGHT die in the coal mine … sometime in the next four years!”
Of old age.
RockyRoad says:
December 11, 2012 at 8:26 am
Explaining jokes is bad form and wasted on both those who got it and those who didn’t.
DaveE.
rgbatduke says:
December 11, 2012 at 12:12 pm
Strange you should mention the middle of Death Valley.
The station of record used to be pretty much there at Furnace Creek until they moved it to the edge of the valley at Badwater
DaveE.
l think one of the big drivers of climate change is the jet stream and the effects it can have on the gulf stream. lf there is a link between the two, then that would help to put in place the rapid climate change that’s been seen in the past. Because any change in the jet stream that lasts for a number of years will also effect the wind patterns on the earth’s surface, which in turn will have its effect on the gulf stream.
Now if these two did change together within a fairly short space of time, then that would have a big impact on the climate.
All I can see when watching Antonys glorious Sea Ice Page is that in exactly the same area as the 17 stations reporting “some warming” are situated, there’s a MASSIVE upwell of warm water to be seen in the surface temp pics, the surface water-anomaly there being up to plus 8 degrees centigrade warmer-than-normal.
But where’s a warm sea, there’s warm air, I would suppose, according to Willis Eschenbach’s most-entertaining lectures on oceanic heat content and sea-atmosphere-interaction.
So perhaps, scientists should stop asking themselves why the air is warmer-than-normal in the Arctic Ocean in these areas, but rather, why the sea is…?
That single warming station wouldn’t be the busy Keflavik International Airport, would it?
@rgbatduke
This is quite important:
Are you familiar with the writings of Tomas Milanovic at Climate Etc.?
If not, you’ll find essential guidance in comments here:
https://tallbloke.wordpress.com/2011/08/21/delve-into-halcrut-at-the-poles/
Koutsoyiannis (2011) wrote: “However, while those laws give elegant solutions (e.g., analytical descriptions of trajectories) for simple systems comprising two bodies and their interaction, they can hardly describe the irregular trajectories of complex systems. Complex natural systems consisting of very many elements are impossible to describe in full detail and their future evolution cannot be predicted in detail and with precision. Here, the great scientific achievement is the materialization of macroscopic descriptions rather than modeling the details. This is essentially done using probability theory (laws of large numbers, central limit theorem, principle of maximum entropy). Here lies the essence and usefulness of the stationarity concept, which seeks invariant properties in complex systems.” (bold emphasis added) http://www.landandwaterusa.com/issues_water/2011_water/6-3JAWRA_HKDynamics.pdf
Be SURE to understand Milanovic. The aggregate constraints are on spatiotemporal chaos (not solely-temporal chaos). The equations are PDEs (not ODEs). Coupling varies in time.
Dealbreaker:
Koutsoyiannis’ approach unnecessarily severely limits achievable insight by being aspatial & temporally-global.
“The decadal ‘‘noise’’ involves coupled variations in the distributions of temperature, mass, and velocity (21, 22) and so is manifested in the steric sea level, moments of inertia, and the Earth’s variable rotation.” (bold emphasis added) http://www.pnas.org/content/99/10/6550.full.pdf (Munk 2002 20th century sea level enigma)
Note: “(21, 22)” refers to the work of Jean Dickey of NASA JPL. (In North America the highest concentration of people with enhanced awareness of aggregate constraints seems to be at NASA JPL.)
Wyatt, Kravtsov, & Tsonis (2011) summarize decadal-timescale northern hemisphere winter coupling in Figure 4:
http://www.springerlink.com/content/p1275t4383874p65/MediaObjects/382_2011_1071_Fig4_HTML.gif
Compare with: http://www.agu.org/journals/gl/gl1218/2012GL052885/2012gl052885-op01.jpg
Caution: The steep gradients of the southern ocean are relatively free of longitudinal deflectors. Bill Illis provides this highly informative illustration:
http://img844.imageshack.us/img844/6939/tempgeog45mlr.png
(circulatory morphology reconfiguration)
For related insight, study Figure 10 here:
Carvalho, L.M.V.; Tsonis, A.A.; Jones, C.; Rocha, H.R.; & Polito, P.S. (2007). Anti-persistence in the global temperature anomaly field. Nonlinear Processes in Geophysics 14, 723-733.
http://www.icess.ucsb.edu/gem/papers/npg-14-723-2007.pdf
“Apart from all other reasons, the parameters of the geoid depend on the distribution of water over the planetary surface.” — Nikolay Sidorenkov
Gail Combs says:
December 11, 2012 at 1:32 pm
People keep saying the Arctic is ‘warming’ so how come the Length of the Arctic Melting Season is getting SHORTER?
It’s warming up but only in the warm period Gail. The warm period is getting shorter and hotter.
Excuse me a moment I have a steering wheel down my trousers that is driving me nuts!
Just to confirm what rgb has been saying, I have the monthly figures for Ross-on-Wye, UK in front of me. The hottest month ever recorded in Ross-on-Wye was July 2006 at an average of 26.8Celsius. This compares to July 2005 at 22.2Celsius and July 2007 at 19.6Celsius. So was that exceptionally warm July 2006 caused by CO2? Well the sunshine hours for July 2007 were 309.6hours (compared with 224hrs and 206hrs for the years either side). It was, in fact, the sunniest month on record for Ross-on-Wye.
Well perhaps this is a trend and Britain is going to get warmer and sunnier! I wish! Sadly 2010 gave Ross-on-Wye one of the cloudiest Julys on record with a meagre 149hrs and an average temperature of 22Celsius.
Basically any attempt to look for the CO2 signal when cloud is present will just confound your measurements. The noise signal caused by cloud even when averaged out over a month is massive. We are talking about 100% variation in monthly cloud averages over a two year time span. If you wanted to really find the CO2 signal you need to remove the sources of noise from your data. Create a computer algorithm that can look for days in the record that are cloud free and have low winds – for the UK this would usually mean looking for days in the middle of a nice long summer high pressure system. Once you have found those days, take a look at the minimum temperatures because that tells you how cold it got at night when CO2 was allegedly providing all that extra insulation to prevent the heat escaping. Now look for days in the record which meet the same criteria at the same time of year and join the dots. If you’ve got a trend and not too much noise remaining it might be CO2 (or then again it could be UHI).
What Team-AGW are doing now is averaging everything so it looks like they have a trend. That’s just low-pass filtering. It’s like me low-pass filtering a signal on an antenna and expecting that just by this simple process I will be able to pick up BBC Radio 4. They’ve got something that looks like it might be a trend but a trend of what? It could be a trend in cloudiness or wind direction or airport business or volcano activity on Iceland or anything – they have no idea because the measurements they have used are in no way related to the theory they are trying to test.
Ryan:
I agree all you say at December 12, 2012 at 7:54 am.
However, if all of that is needed to discern an effect of increased atmospheric CO2 effect then the effect is so trivial that it can be ignored as a ‘driver’ of climate.
Richard
Kelvin Vaughan says:
December 12, 2012 at 7:18 am
Gail Combs says:
December 11, 2012 at 1:32 pm
People keep saying the Arctic is ‘warming’ so how come the Length of the Arctic Melting Season is getting SHORTER?
It’s warming up but only in the warm period Gail. The warm period is getting shorter and hotter.
>>>>>>>>>>>>>>>>>>>>
So that means we are in deep Kimshee when the NAO goes from warm back to cold now doesn’t it? Ice melts because of the warm sea not the warm air. (Seas control the atmospheric temp not the other way round)
OOPS! looks like it has already flipped.
NAO graph
richardscourtney says:
December 12, 2012 at 8:47 am
Ryan:
I agree all you say at December 12, 2012 at 7:54 am.
However, if all of that is needed to discern an effect of increased atmospheric CO2 effect then the effect is so trivial that it can be ignored as a ‘driver’ of climate.
Richard
Richard,
And that’s basically what I’ve found. Consider the global average daily falling temp is ~18F, and we know there are place on the planet that are 2-3 times that? That says the temps are controlled by water, and water vapor, because when we exclude it the swing is many times larger.
If with little water vapor you can see a +60F drop in temps, with all of that co2, does it even matter if co2 is a fraction of a degree, and water limits it to under 20 degrees drop?
They are caused by complicated and inexplicable feedbacks and the pop up hot spots that show up on NASA plots have nothing to do with creating higher temperatures. Some times I wonder if climate scientists have even IQs of remotely near 50 let alone over 100.
Don’t they even look at files like AMSRE_SSTAn_M and wonder how a tiny average rise can cause such significant temperature rises with all the claptrap about complex feedbacks etc.
Funny also why the end without the hot spots doesn’t get hot. Unless of course they do not learn basic thermodynamics.
Why also did they need to get the BBC to brainwash the public is the science was so sound and worse still to get it to claim to be a private company to avoid FOI requests when that strategy has the risk that it could end their licence funding. There has to be very big levers to get them to go down that route.
Gail Combs says:
December 12, 2012 at 8:56 am
Flipping heck not more cold. I’m freezing, it’s been frosty all day!
From Wikipedia:
Polar amplification is the greater temperature increases in the Arctic compared to the earth as a whole as a result of the effect of feedbacks and other processes…
This definition is incorrect. The only cause of polar amplification is heat transport. Ask the meteorologists. Polar amplification is the greater change in temperature at both poles than the change in the tropics of the mean annual temperature. For every one degree change in the tropics the temperature at the poles changes about three to five degrees.
Ryan says:
December 12, 2012 at 7:54 am
Basically any attempt to look for the CO2 signal when cloud is present will just confound your measurements. The noise signal caused by cloud even when averaged out over a month is massive. We are talking about 100% variation in monthly cloud averages over a two year time span. If you wanted to really find the CO2 signal you need to remove the sources of noise from your data. …. Once you have found those days, take a look at the minimum temperatures because that tells you how cold it got at night when CO2 was allegedly providing all that extra insulation to prevent the heat escaping.
Under the conditions you describe, the minimum temperature will occur after dawn, at the point downward solar radiation exceeds upward LWR. This makes the minimum temperature particularly sensitive to clouds, especially low level clouds, because of the long path through the atmosphere of solar radiation at this time.
Even a small amount of early morning cloud will produce a larger effect than the one you are looking for.
I see north “polar amplification” due to rgional high surface albedo feedback.
But what is being amplified? Have a look at:
http://www.metoffice.gov.uk/hadobs/hadcrut3/diagnostics/global/nh+sh/
There is a visible periodic component with a period around 62 years. (It
can easily be unsteady in amplitude and period.) It accounts for about
.21 degree C of the warming from 1973 to 2004.
Much of this appears to me to be Atlantic Multidecadal Oscillation – a
north/south shifting of heat in the Atlantic Ocean. When AMO is in its
north-warming phase, the high positive feedback in and near the Arctic
causes much of the Arctic to warm disproportionally more. When AMO is
in its north-cooling phase, much of the Arctic cools disproportionately.
Because the positive feedback is greater in the northern hemisphere
than in the southern hemisphere, shifting heat northward warms the world,
and shifting heat southward cools the world.
I have noticed that there is a correlation between the temperature above 80°N and the Arctic ice area. Whenever the ice are slows down or shrinks back a bit the temperature has risen and when it is growing fast the temperature has fallen.
It probably is pulses of warm ocean flowing into the Arctic Ocean. That’s my theory anyway!
@Philip Bradley:
Under the conditions you describe, the minimum temperature will occur after dawn, at the point downward solar radiation exceeds upward LWR.
I think you will find that minimum temps always occur significantly before dawn. This is because lightening of the night sky occurs long before the sun breaks the horizon, due to scattering. If you look at a thermometer just before dawn you will see the temperature rise long before the sun appears over the horizon and more or less at the same rate as the sky lightens.
If you have three hot cloudless daytimes in a row in the summer then i think normally you will find the middle day of those three will have a nightime that is cloudless too – so the minimum temp measured at that time will usually give you the temperature that the air managed to drop to before any scattered weak sunlight manages to light the sky. It is not perfect, but taking only these measurements would significantly reduce the impact of cloud and wind as noise sources in detecting a CO2 related signal. Otherwise as my Ross-on-Wye data shows a cloudy summer month or a cloudless summer month can shift the annual average by as much as 0.5Celsius quite easily, and then you have the wind to consider.
The logging I’ve done has the temp still really close to min even a little past sunrise, but it was on the west side of the house.
But the key is that the ground was still warmer than the air temp, today for instance was in the low 20’s F, the grass and everything off the ground was covered with frost, but the ground wasn’t. The air trapped between the blades of grass insulate the ground from the cooling of space. I would bet that when measured over a large grass field vs an open field of dirt, the air will be a few tens colder over the grass.
feet2thefire says:
December 11, 2012 at 10:18 am
“I disagree – in the long term – about the cause and effects being unknown and possibly unknowable. NOW we can’t know them, but have some faith in present and future scientists. We are only 30-35 years or so into the age of computers (counting not from the glacial-speed Eniac but the explosion of Apples and PCs) and about the same for modeling. Even though we do disdain models – in their current state – it is only by models that we will ever be able to know/understand the baselines and the system as a whole. Just because there is garbage now going in, crap understanding of the pieces of the puzzle, and inadequate code/math doesn’t mean someone won’t straighten out the mess some day.
Steve Garcia”
Due to the degradation of our educational system, present scientists include some very poorly educated souls who have the time and money to go to college but not the mental capacity and are able to obtain virtually any type of degree in any event. Don’t see that changing for the better in the future, only getting worse. See the movie, “idiocracy”.