From the NATIONAL CENTER FOR ATMOSPHERIC RESEARCH/UNIVERSITY CORPORATION FOR ATMOSPHERIC RESEARCH
BOULDER — The recent trend of increasing Antarctic sea ice extent — seemingly at odds with climate model projections — can largely be explained by a natural climate fluctuation, according to a new study led by the National Center for Atmospheric Research (NCAR).
The study offers evidence that the negative phase of the Interdecadal Pacific Oscillation (IPO), which is characterized by cooler-than-average sea surface temperatures in the tropical eastern Pacific, has created favorable conditions for additional Antarctic sea ice growth since 2000.
The findings, published in the journal Nature Geoscience, may resolve a longstanding mystery: Why is Antarctic sea ice expanding when climate change is causing the world to warm?
The study’s authors also suggest that sea ice may begin to shrink as the IPO switches to a positive phase.
“The climate we experience during any given decade is some combination of naturally occurring variability and the planet’s response to increasing greenhouse gases,” said NCAR scientist Gerald Meehl, lead author of the study. “It’s never all one or the other, but the combination, that is important to understand.”
Study co-authors include Julie Arblaster of NCAR and Monash University in Australia, Cecilia Bitz of the University of Washington, Christine Chung of the Australian Bureau of Meteorology, and NCAR scientist Haiyan Teng. The study was funded by the U.S. Department of Energy and by the National Science Foundation, which sponsors NCAR.
Expanding ice
The sea ice surrounding Antarctica has been slowly increasing in area since the satellite record began in 1979. But the rate of increase rose nearly five fold between 2000 and 2014, following the IPO transition to a negative phase in 1999.
The new study finds that when the IPO changes phase, from positive to negative or vice versa, it touches off a chain reaction of climate impacts that may ultimately affect sea ice formation at the bottom of the world.
When the IPO transitions to a negative phase, the sea surface temperatures in the tropical eastern Pacific become somewhat cooler than average when measured over a decade or two. These sea surface temperatures, in turn, change tropical precipitation, which drives large-scale changes to the winds that extend all the way down to Antarctica.
The ultimate impact is a deepening of a low-pressure system off the coast of Antarctica known as the Amundsen Sea Low. Winds generated on the western flank of this system blow sea ice northward, away from Antarctica, helping to enlarge the extent of sea ice coverage.
“Compared to the Arctic, global warming causes only weak Antarctic sea ice loss, which is why the IPO can have such a striking effect in the Antarctic,” said Bitz. “There is no comparable natural variability in the Arctic that competes with global warming.”
Sifting through simulations
To test if these IPO-related impacts were sufficient to cause the growth in sea ice extent observed between 2000 and 2014, the scientists first examined 262 climate simulations created by different modeling groups from around the world.
When all of those simulations are averaged, the natural variability cancels itself out. For example, simulations with a positive IPO offset those with a negative IPO. What remains is the expected impact of human-caused climate change: a decline in Antarctic sea ice extent.
But for this study, the scientists were not interested in the average. Instead, they wanted to find individual members that correctly characterized the natural variability between 2000-2014, including the negative phase of the IPO. The team discovered 10 simulations that met the criteria, and all of them showed an increase in Antarctic sea ice extent across all seasons.
“When all the models are taken together, the natural variability is averaged out, leaving only the shrinking sea ice caused by global warming,” Arblaster said. “But the model simulations that happen to sync up with the observed natural variability capture the expansion of the sea ice area. And we were able to trace these changes to the equatorial eastern Pacific in our model experiments.”
Scientists suspect that in 2014, the IPO began to change from negative to positive. That would indicate an upcoming period of warmer eastern Pacific Ocean surface temperatures on average, though year-to-year temperatures may go up or down, depending on El Niño/La Niña conditions. Accordingly, the trend of increasing Antarctic sea ice extent may also change in response.
“As the IPO transitions to positive, the increase of Antarctic sea ice extent should slow and perhaps start to show signs of retreat when averaged over the next 10 years or so,” Meehl said.
###
So if we do some creative arithmetic with GCM models we can conclude that despite the obs showing increasing ice extent, actually there is a global warming ice melt signal going on, but you can’t see it because natural variability? Very clear. Got it.
That’s what I got. Where are the comics?
I see that we are all in agreement on this one. Although, who was that who was recently stating that natural variability was not an answer for anything climate related?
Dunno about the modeling, but it makes sense, actually.
I could be wrong …… but I seriously doubt that the context of the following quote “makes any sense” to the authors themselves, ……. because, IMO, the authors don’t have a lick of scientific sense to begin with.
So sayeth the NCAR research authors, to wit:
“The sea ice surrounding Antarctica has been slowly increasing in area since the satellite record began in 1979. But the rate of increase rose nearly five fold between 2000 and 2014, following the IPO transition to a negative phase in 1999.”
Forget the models. To me, this is the money quote. The actual data show Antarctic sea ice area increasing even during a positive IPO, and a negative shift just sped it up. The underlying natural variation was expansion – positive slowed it down, while negative sped it up, but it was 100% of the time expanding the sea ice extent.
Notice that they make no attempt to explain the record breaking increases from 2013 through to 2015. That is when the major increase occurred. They simply say look at the average between 2000 to 2014.
“When all of those simulations are averaged, the natural variability cancels itself out. ”
Huh?
Not if its chaotic and/or not periodic. If this was the case, chaotic RF noise (i.e. background noise from the Universe) could be cancelled out and every radio receiver would have an infinite signal to noise ratio. Besides, the simulations do not simulate natural variability which for all intents and purposes is largely unknown.
If you are looking for a periodic signal and average across multiple periods, that periodic signal can emerge from the noise, so the best they can say is that averaging multiple simulations that can pull the periodic seasonal response out of the data (which is pretty obvious to begin with) and all that’s left is the chaotic noise (i.e. natural variability) which we also call anomalies.
Wow ! Such a breakthrough. Whoever would have guessed that climate can change all by itself without instructions from humans ?
Move over Einstein waves; there’s a new front cover story that upstages you !!
g
Sam Cogar is right on. The average of 262 guesses doesn’t mean sh*t and in no way cancels out natural variability. I completely loose any faith in a researcher’s scientific logic once they employ such laughable pseudoscience.
Not to mention, north of the Amundsen Sea into the Pacific is not the only place that sea ice is expanding around Antarctica, its expanding on all sides. And there was no negative trend in Antarctic sea ice from 1979-1999 like you’d expect if they were correct at all. They must be invoking the CAGW dogma of natural variability can not currently be a positive climate forcing.
They are likely hoping no one remembers that little fact of no negative trend since the satellites have been watching.
stop sipping, start drinking…..
yes the increase in ice has something to do with the drop in temperatures which has something to do with what happens on the sun.
It seems to me that when the sea ice melted back to the average trend line that it has greatly affected ssta conditions as a result. The big change point was at Drakes Passage. Note that the waters off of the east side of SA have greatly cooled as compared to conditions over the last 4 years. I get the impression that this will lead to cooling in the So Atlantic which will then spread northward.
What was it that RGB@duke said about averaging a bunch of simulations and assuming that the result would matter? Hmmm. Maybe I’ll forward his WUWT link to these authors as they seem to have missed the memo.
Do you think they would understand? Maybe if we sent them a hundred or so reasons why they are wrong, then they could average those out to discover why they are wrong. Potentially.
” Bob Shapiro July 5, 2016 at 6:26 am – The actual data show Antarctic sea ice area increasing even during a positive IPO, and a negative shift just sped it up.”
Interesting observation there and if we know how much it was increasing during the positive phase of the IPO and about half way through the negative phase we could get a more accurate line on the amount of natural variability. Of course it has been increasing so that means that ALL other factors (CO2, soot, solar cycles, etc) are either not affecting it significantly enough to make it decrease or are forcing growth even during positive phases. That wouldn’t sit well with them.
Too funny.
” What was it that RGB@duke said about averaging a bunch of simulations and assuming that the result would matter? Hmmm. Maybe I’ll forward his WUWT link to these authors as they seem to have missed the memo.”
1. Send the memo to Bob tilsdale. He uses the model means.
2. Averaging models leaves you with the forced response. Nothing more or less. The issue is testing against that mean to validate.
Samuel: if I understand that passage correctly, they are basically saying that per their models, absent man-made warming, there is NO LONG TERM NATURAL CLIMATE CHANGE, natural variability cancels itself out.
I have a MAJOR problem accepting the correctness of that conclusion.
Rw.
Averaging models does cancel out natural variability.
That is why you don’t see El Niño in the model mean.
Pretty basic.
S Mosher
The idea that GCM models significantly reproduce climate natural variation/oscillation is so bizzare and unusual as to be a cause of concern as to your wellbeing.
First show us the GCM that can reproduce this over the last glacial cycle. Then start talking about GCMs having some relationship to the earth’s climate.
http://s12.postimg.org/9ctilkusd/NGRIP_NEEM_EDC_Global_135kya.png
No Sir, you are mixing up averaging models and averaging multiple runs of the same model (Monte-Carlo method) You can run multiple copies of the same model by using different random starting points. That is a correct procedure, but that is not what they are averaging in this case. They are averaging different models, with different parameters hoping that averaging 100 wrongs will make 1 correct answer. There is no way you can guarantee that. It is impossible if you take into account that there is a huge belief bias (only the models that provide the answer that fits the AGW hypothesis are chosen)
It is like trying to calculate where a bullet thrown by a cannon will land by averaging multiple calculations where in every one a different value of g (force of gravity) is used, and where these values range from 20 to 40 m/s². You will not get the correct answer because you are not using the correct value for the force of gravity. No matter if you make the calculations on the back of an envelope or on a multimillion dollar supercomputer, or if you are calculating the trajectory once or you are averaging 10000 calculations, if you are using the wrong range of values for g, the result is going to be wrong.
Same happens here, all models use a value for the sensitivity constant that seems to be too high. Averaging the results will not give the correct answer if in every model you are using the wrong value.
Well a different ” model ” of a real system is more properly described as a ” model ” of a different real system.
The real system is in this case the continuous function that describes the weather over time of the real planet (earth in this case), and that function has at least two continuous variables.
One is simply the time, from some past epoch upt to the present, which is as far as we can have data.
The other is the complete volume of space occupied by the earth’s weather system, presumably the atmosphere and the oceans.
To the best of my knowledge, nobody has ever measured weather / climate variables inside the solid volume (rocks) of the earth in any long term formal way.
For various practical reasons, weather / climate data measurements are usually made at points on a conformal map of the roughly spherical earth’s surface, often at some prescribed altitude, in that complex three dimensional object.
It isn’t possible to measure the complete continuous function, so for practical reasons, the continuous function is sampled at chosen locations, and at chosen times, and the time sampling and spatial sampling are not co-ordinated in any formal way. Measurements made at any particular spatial co-ordinate are in no way synchronous in time with measurements made elsewhere.
Clearly in satellite based measurements so form of scanning regimen can be followed, so data is gathered in sequence for different locations as they come into view of the measurement system.
So the model behavior is followed only as a sampled data system, since it is not practical to make measurements at every possible point and at all possible times.
Subsequent recovery and reconstruction of the original continuous multivariable function can only be achieved if the continuous function is band limited for all of its variables, and only if those variables are sampled in accordance with the requirements of the Nyquist sampling theorem, which requires the interval between samples to be no greater than one half of the period of the highest frequency signal component of the band limited continuous function, for all sampled variables.
Reconstruction of the original continuous function is NOT the aim of weather / climate data gathering, so only limited information is sought to be recovered; most often just the average values over time, at a location or the average values over the entire spatial range of the system.
Those average values are simply the zero frequency component of the signal spectrum of the continuous function.
The Nyquist criterion requires that the sampling interval between samples of the band limited continuous function must not exceed one full period of the highest signal frequency component of that band limited continuous function.
This condition is required, because when a continuous function is sampled at a frequency of 2 B , or with a maximum sample interval of 1 / 2B , the presence of a signal component at a frequency of B + b in the continuous function, results in a recovered signal component from the samples at a frequency of B – b which is a signal that was NOT present in the original function, and comprises a noise that corrupts the value of the recovered information.
So if the value of (b) is equal or greater than (B), then the introduced aliasing noise component is now at a frequency of B – B in the recovered signal, which is the average value that was being sought.
So under-sampling by just a factor of two in frequency for periodic sampling, or at a sample spacing equal or greater than 1 / B for a random sampled signal, will result in not even the average value of the continuous function being determinate from the captured samples.
In effect, such samples are not valid data even if only the average value is sought.
junk, would be a suitable description of such machinations. One can’t even describe them as ” information “.
When so-called models of earth’s weather / climate system, don’t even conform to the laws of sampled data system theory, it matters not how many such models one has to average. No credible conclusion can be reached from such a process.
Consider the absurdity of making observations / measurements of say 100 different species of organisms found at a wide variety of locations, and over a long period of time, and attempting to obtain from that, the average value of any parameter, say the spacing of the eyes (if they have eyes), as if that has any informational value at all.
Well presumably one would not include both elephants, and spiders in the same data pool, as they are clearly not models of the same real system.
But even restricting the model variation to include nothing but spiders, from everywhere and all time epochs, the average eye spacing tells one nothing much about spiders. Too many other variables interact with what may seem like a simple measurement.
I can see applying statistics to the results of multiple runs of the simulation of a given model of a real system, but not to runs of entirely different models of the same system.
And of course, as in all statistics, the result is only interesting to statisticians, as it is entirely a consequence of their algorithms, and is applicable to any predefined data set of real finite numbers.
G
Since natural variability swamps manmade warming, that means that less than half the observed warming is due to AGW.
The evidence continues to pile up that CAGW is a crock.
I thought global warming was so powerful that it was going to over power all natural variation?
At least that’s what the IPCC claimed.
At a global level . Yes. Regional is not global.
That is why looking at global sea ice is not a good idea.
And of course no possible suggestion that the melting in the Arctic could be anything to do with natural variation despite positive phases being at work.
I especially like how he can refer to them as “model experiments”. They keep using that word, but I do not think it means what they think it means.
Tom B. I honestly think climate researchers have lost sight of the fact that models are really just someone’s opinion of how the climate works quantified. They aren’t based on any kind of experimentation or even validation. Just best guesses that are being treated like the Stone Tablets.
Tom,
Rhoda,
Not only are the models unverified and disconnected from the data, the modeled behavior isn’t even driven by the laws of physics and instead, are driven by heuristics that have so many knobs and dials you can make the model behave however you want. When actual physics enters in to the models, its often qualified with bad assumptions. Most models seem to be directed open loop models, rather than converged closed loop models. Evidence of this is that they need to run models many, many times and average the result. Whenever I’ve modelled real feedback systems and I get a different answer each time, it usually means there’s an uninitialized variable somewhere. In fact, one of the tests I use to verify a model of a system driven by physical laws is that when you change the initial conditions and re-run the model, it should always eventually converge to the same answer!
Would this team be available to help with my income tax return?
“When all of those simulations are averaged, the natural variability cancels itself out. For example, simulations with a positive IPO offset those with a negative IPO. What remains is the expected impact of human-caused climate change: a decline in Antarctic sea ice extent.
“But for this study, the scientists were not interested in the average. Instead, they wanted to find individual members that correctly characterized the natural variability between 2000-2014, including the negative phase of the IPO. The team discovered 10 simulations that met the criteria, and all of them showed an increase in Antarctic sea ice extent across all seasons.”
Hold on – does this mean that the average of a gazillion faulty models doesn’t actually result in a single spot-on model?!
I need a drink. My whole world just turned upside-down, and the cognitive dissonance is more than sober me can bear…
Shut up and read the comics.
I am sipping on a beer even now as we speak and ponder.
Those of us who do not drink have to just suffer through the pain as-is.
*ouch*
I do not sip much beer anymore, perhaps several bottles a month on average. The good part about that besides feeling better is that I really enjoy the one or two beers.
Do you get your water out of the air when you breathe or does it come from your food ?
g
Beer should never be sipped, let’s start with that. Quaffed.
I used to quaff. Now that I drink very little I tend to sip.
Don’t you just love the all new “Genuine imitation natural variation”? Brought to you by the climate model programmer believers.
Back in the past, some yuppies wore T-shirts printed with “Save the nauga-dog puppies! Boycott naugahyde!”
Now we have, “Have faith in absurd unnatural climate models! Boycott Mother Nature!”
I always wondered how many rich Corinthians it took to make “rich Corinthian leather”.
Said in my best Ricardo Montalban imitation.
Nooo!
Keep that commercial from echoing in my mind again!
For a few seconds there, I was afraid that commercial jingle would start up as background noise in my head again.
Absent mindedness has a purpose!
What was astonishing were how many people stopped my cousin when he wore that ‘boycott naugahyde’ shirt to tell him they were also horrified about killing nauga-puppies for leather…
Naiveté that ranks right up there with ‘Ban dihydrogenoxide fluid for washing’ and other ignorant elitist beliefs.
ATheoK, Actually, I think NSIDC is boycotting Mother Nature. Has anyone looked at the U of IL data for Arctic ice extent? They are reporting a surprising jump in Arctic sea ice when it should be decreasing. NISDC found its satellite was giving spurious data just when U of IL’s data showed an unseasonal jump which is STILL continuting.
Arctic Basin, see 2d graph http://arctic.atmos.uiuc.edu/cryosphere/IMAGES/recent365.anom.region.1.html
U of IL re Bering Sea Ice: in Dec 2015 it was .1 million sq km below the 1979-2009 mean. Since mid April 2016 it has hovered near .6 mil sq km of ice above it. http://arctic.atmos.uiuc.edu/cryosphere/IMAGES/recent365.anom.region.2.html Again scroll to the 2d graph.
U of IL re Barents Sea: May 1, 2016 .4 mil sq km below the mean. TWO WEEKS LATER May 15 .05 above the historical mean ice extent . Now in July nearly .5 mil sq km of ice above the mean and still climbing. http://arctic.atmos.uiuc.edu/cryosphere/IMAGES/recent365.anom.region.6.html
My fave: Recycle your breadcrumbs! Save the wheat!
Penelope on July 6, 2016 at 12:28 am
Well I think I’ll rather trust true specialists of that matter…
http://ocean.dmi.dk/arctic/icecover.uk.php
No model is spot on. By definition.
The important thing is beating the best skeptical model.
This was done in the 1930s.
Models that can be validated against reality are useful.
The aeronautics industry for example.
Those that can’t are nothing more than opinion,and should be treated as such.
“The important thing is beating the best skeptical model.
This was done in the 1930s.”
Well, I guess I’ll just shut up, then. I mean, what possible response could there be to such a powerful, well-reasoned, air-tight argument as that?
Seriously, though, this oft-repeated theme of yours that we should embrace these models, no matter how faulty they are, because (you say) they are the least faulty we have, is ridiculous. There is no compelling reason we MUST remake the world around ANY climate model, or any set of them. If they’re bad, they’re bad – no matter how bad any others purportedly are – and basing policy on bad models is madness.
If you want to argue we should be guided by them because they’re good, in an absolute sense, knock yourself out, and good luck with that (you’ll need it). But this stuff about however bad they might be, they’re not as bad as others – so (by implication) we should allow them to guide our public policy-making – is weak on its face and not at all worthy of any good-faith effort to advance knowledge.
I don’t at all mean to be personal. Rather, I’m respecting you enough to actually lay out a bit of an argument that you could actually rebut, if you cared to, and in so doing make a potentially useful contribution to the discussion. I hope you’ll agree that’s a lot more than the content-free drive-byes so commonly found with your name at the beginning.
Sincerely,
Brad Crawford
Can you point me to a non-mauinstream model that gets anywhere close to predicting reality?
In contrast, the climate models published by the likes of the Met Office are pretty good.
http://www.metoffice.gov.uk/media/image/q/3/fig4_dp2015_map_obs_fcst_stipple.png
You want a non mainstream model that works? How about the Stefan-Boltzmann LAW. It’s not just a model, its the LAW!
http://www.palisad.com/co2/tp/fig1.png
All the little dots are 3 decades of measurements from satellites, adjusted per GISS (ISCCP data set). The solid green line is the prediction of a Stefan-Boltzmann gray body model with an emissivity of 0.62..
CO2isnotevil. You will have to explain how your model relates to the climate. It could be a curve fitting exercise for all I know. Where did the emissivity of 0.62 come from? It is not hard to fit data to well known physical laws. It is hard to put them into context to produce something useful. If you can show how your model has been used to produce a prediction about global temperatures (or anything other global indicator) anywhere near as good as the Met Office one I will take note. Stefan Bolltzmann has been around long enough for this to have been done decades ago. Yet no prediction have I seen.
Seance1,
There is no curve fitting involved. Each little dot is the monthly average of the surface temperature and emissions into space for a 2.5 degree slice of latitude. What the SB model predicts is the sensitivity (i.e. the slope of the relationship between forcing and surface temperature), which is somewhere between 0.19 and 0.3 C per W/m^2 and which bounds the sensitivities measured or calculated by nearly every skeptical scientist who has made such an effort. My plot also demonstrates that the IPCC sensitivity of 0.8C per W/m^2 arises as a linearization error that neglects the T^4 dependence between emissions (which in LTE is equal to total forcing) and the temperature.
The SB law has exactly 1 free variable, which is the equivalent emissivity, but this is not really unbound and is the ratio between the total accumulated radiant forcing (239 W/m^2) and the average radiant emissions by the surface (385 W/m^2) which when you do the arithmetic you get, 239/385 = 0.62. The models used by the MET office and others have so many knobs and dials you can make them behave however you want. Accusing me of curve fitting is a extremely disingenuous.
The reason you have not seen these predictions before is because they contradict the narrative and in fact, unambiguously falsifies the narrative. Since the IPCC is the gatekeeper of what is and what is not climate science by virtue of what they choose to put in their reports and they need substantial man made climate change to justify their existence, do you really think their self serving consensus will reveal this truth? In fact, consensus climate science arrogantly denies the applicability of this LAW when this contradiction is brought up even as Trenberth agrees with both the 385 W/m^2 and 239 W/m^2 values of radiant emissions by the surface and radiant forcing entering the system.
Seaice1,
I’ve only scratched the surface of the predictive power of this model. Not only does it match monthly data, the larger dots are the averages for each slice over the entire 3 decade satellite record provided by GISS (ISCCP) and matches within a few percent. Keep in mind that whatever you think, this model is nearly exact for predicting the average behavior of a 2.5 degree slice of latitude, each of which is cooler and receives less energy as latitudes move towards the poles. BTW, when the surface temperature is plotted against input power, the slope is even shallower and matches the slope of an ideal BB at the average temperature of the surface (0.19 C per W/m^2), sets the lower bound and intersects the previous plot against output emissions at the planets average state (the climates ‘operating point’). Change the fig1.png in the earlier link to fig2.png to see this.
Using radiative transfer codes and average cloud coverage, I can also predict the equivalent emissivity. I can also predict the dip below the green line below 273K and quantify it as water vapors effect increasing and reflection decreasing as temperatures transition across 0C. The steeper slope (sensitivity) during the transition is the result of all W/m^2 of incident power, not just the incremental W/m^2 called forcing, adapting to the new reflectivity and absorption by the atmosphere. This can be seen in data along the isotherms near 273K and is often incorrectly extrapolated (homogenized) to be the sensitivity across all latitudes, when the relevant sensitivity is that at the operating point of the planet. Keep in mind that its only the LTE response of the planet that matters relative to quantifying the sensitivity and this model is better than anything I’ve ever seen.
By plugging this model into the first order LTI differential equation, Po = Pi + dE/dt, where the instantaneous difference between incoming (Pi) and outgoing power (Po) is either adding to or subtracting from the solar energy stored by the planet, E, the average response to seasonal variability can also be predicted to a high degree of precision. Note that the dE/dt term is approximately equal to what the IPCC calls ‘forcing’ and that the time constant is the amount of time, tau, that it takes to emit all of E at the rate Pi. Rewriting, we get,
Po = E/tau + dE/dt which should be recognized as the form of the LTI quantifying the behavior of an RC circuit.
“I’ve only scratched the surface of the predictive power of this model.” You do not seem to have gone even that far. I do not see any predictions. Show me where you have used this to predict temperatures, or anything. You surely must have used this if it is so powerful.
Seaice1,
Please pay attention. Among the many predictions this model makes is the precise LTE response of the surface temperature to variable solar forcing.for each 2.5 degree slice of latitude and predicts the precise LTE planetary emissions as a function of surface temperature for the same 2.5 degree slices. If you think that accurately predicting the precise energy behavior af each 2.5 degree slice of latitude is not representative of the energy behavior of the whole planet, please explain the physics and math supporting your conjecture.
Your diligence is suspect since my logs show that you never bothered to look at figure 2, so I will include it here.
http://www.palisad.com/co2/tp/fig2.png
The green line is the modelled prediction for the relationship between surface temperatures and the resulting emissions into space. The magenta line is the modelled prediction for the relationship between post albedo solar input arriving from space and the resulting surface temperature. The slope of these lines at the average temperature of the planet are direct measurements of the average sensitivity of the surface temperature to change in solar forcing and the average sensitivity of output emissions to changes in surface temperature. These slopes are 0.19 C per W/m^2 and 0.3C per W/m^2 respectively, are predicted by the SB Law and validated with data supplied by the CAGW side of the debate.
What physical law supports a sensitivity of 0.8C per W/m^2, or for that matter a sensitivity of 0.4C per W/m^2 which is the lower bound stated by the IPCC? Please also note that the 0.19C value is most closely aligned with what the IPCC calls the effect of forcing and the fact that the sensitivity of the input path is less than the sensitivity of the output path is an unambiguous signal of net negative feedback.
Keep in mind that emissions of the planet and both pre and post albedo incident power are the most direct signals measured by weather satellite sensors. Only the temperature is not directly measured, but inferred based on a radiative transfer model, which in this case was done by Rossow under the auspices of GISS. The monthly data (small dots) is closer to the predictions than anything I’ve ever seen from the IPCC’s side of the debate and the 3 decade averages (large dots) are so close to the predictions, no reasonable scientist would conclude otherwise. What is your reasoning for disputing this? Please be specific and cite the laws of physics that support your position. Also, please stay on topic and answer the specific questions.
So the Antarctic expansion is natural and so the Arctic shrinkage must be man made.
Tara makes sense to me (sarc)
James Bull
You beat me to it. Just like the warmist meme on Atlantic hurricanes. Hurricane severity is enhanced by human caused climate change but a period of decreased hurricane incidence and severity is the result of just plain luck.
Well, of course! If ice is receding, it’s Man’s fault. If it’s growing, it’s natural variability.
This climate change stuff isn’t complicated.
“As the IPO transitions to positive, the increase of Antarctic sea ice extent should slow and perhaps start to show signs of retreat when averaged over the next 10 years or so,” Meehl said.
At least their prediction doesn’t require us to wait 30 years or more for it to be verified or falsified. But if over the next 10 years the Antarctic sea ice extent does begin to retreat while the Arctic extent increases on average, what would that mean for climate change? Wouldn’t it show that natural variability has more to do with current changes in the climate than the models indicate? Right now, If I had to guess, I’d say that climate change is 97% natural and a mere 3% due to increases in greenhouse gases. 🙂
It’s going to take a little longer than 10 years. Based on the average length of 30 years for each phase, it would seem we have at least 5 years of additional cooling before we start to swing towards the warming phase. Assuming, of course, that the IPO has anything at all to do with it.
Prediction isn’t verified or falsified. It is confirmed or disconfirmed.
True, it’s not like the
global warmingclimate weirdingclimate change community has any understanding let alone training in Popper.Semantics at their finest.
Hi from Oz. Methinks the words ‘linked to natural variability’ in the title are intended to have different meanings to non-skeptical and skeptical readers! Misdirection, ambiguity, etc.
“The team discovered 10 simulations that met the criteria, and all of them showed an increase in Antarctic sea ice extent across all seasons.” What??!!, they found ten bulls eyes out of , er, uh some shots? Wow they are good. That’s Texas sharp shooting at it’s best!!!
I object to that fallacy’s informal name.
So it’s _not_ the reduced sea water salinity caused by run off of megatonnes of fresh water melting out of the land ice then?
But NASA _said_ http://www.nasa.gov/topics/earth/features/antarctic_melting.html
/settled
strange thing is Arctic sea melting has also slowed. I guess we’ll just have to admit that natural climate is not perfectly constant after all. I’m glad to see the penny is finally starting to drop with those who have spend 30 years denying that climate changes unless it’s because of man.
https://climategrog.wordpress.com/2013/09/16/on-identifying-inter-decadal-variation-in-nh-sea-ice/
Greg, your first 3 trend lines overlap – the last one doesn’t, and is foreshortned.
Is that just intended as a statement of fact, or a criticism that you are not able to substantiate?
If you want to know how the trends were calculated, I suggest you read the linked article. You will then either understand the features that you pointed out. The analysis was a little more probing that using Excel to fit a trend to arbitrary periods.
If you have any comments or criticisms after having taken the trouble to read how it was calculated, I’d be interested.
Which ever way you look at it, it is pretty clear the ice loss has slowed down since 2007, this is a direct contradiction of all the usual hype about tipping points, death spirals and imminent ice free summers.
Is that just intended as a simple statement of fact, or a criticism that you are not able to substantiate?
If you want to know how the trends were calculated, I suggest you read the linked article. You will then either understand the features that you pointed out. The analysis was a little more probing that using Excel to fit a trend to arbitrary periods.
If you have any comments or criticisms after having taken the trouble to read how it was calculated, I’d be interested.
Which ever way you look at it, it is pretty clear the ice loss has slowed down since 2007, this is a direct contradiction of all the usual hype about tipping points, death spirals and imminent ice free summers.
You will also see in the article that the circa 5 year periodicity I identified will hit the cusp of its minimum this year. Currently 2017 is running quite close to the last min. in 2012.
Once we have full data for 2017 I will be able to fit the next segment to that graph. In view of the last few years of growth, it is likely that will be showing a positive slope. ( Assuming that they manage to keep a consistent record through the technical failures.).
Good experimental design precludes the selection of individual model runs as reflective of anything. It’s only in aggregate that they mean something. Peer review is dead.
If they want to test for the effect of the IPO on sea ice extent they need to design a static model and simulation to answer that question.
But I do note that on my last visit to NCAR that they have their own branded bottled water in the cafeteria. I guess that’s where the monies for continuing maths education went.
“Model experiments”. There they go again, displaying their non-scientific behaviour.
‘When all of those simulations are averaged, the natural variability cancels itself out.’ I’d like to see some sort of proof that averaging has that result. How do they know the ‘simulated natural variability’ is evenly distributed across the models and will be averaged away? How about if there is an actual natural trend or physical process in action that has not been modeled and what we see is not ‘variability’? This does not seem like science.
The correct question to ask is: “How do they know that the ‘simulated natural variability’ accurately reflects actual natural variability?
Answer: They don’t, not in the slightest.
It doesn’t. Models don’t work that way, and we all know it. Any idiot can tell that. If you have 5 models that predict the market will rise exponentially, 3 that predict it will drop precipitously, you can’t say with certainty that it will rise moderately. You can say that “we have no idea”.
“When all of those simulations are averaged, the natural variability cancels itself out.”
This tells me that these scientists are no longer able to draw a line between reality and their imagination – between science and fiction if you like – they are no longer able to critically assess their work.
And the reviewers let this pass – unbelievable – how low can science sink?
And the study is led by The National Center for Atmospheric Research (NCAR): «a federally funded research and development center devoted to service, research and education in the atmospheric and related sciences.»
This would have been funny if it wasn´t funded by tax payers.
So the Natural expansion of Antarctic ice just happens to coincide (roughly) with the beginning of the Pause. How curious……
Yet another explanation paper solicited. One to “explain” the arctic ice.
“The climate we experience during any given decade is some combination of naturally occurring variability and the planet’s response to increasing greenhouse gases,” said NCAR scientist Gerald Meehl, lead author of the study. “It’s never all one or the other, but the combination, that is important to understand.”
Yet Meehl doesn’t have the findings to state such a thing, “It’s never all one or the other, but the combination, that is important to understand.” means there is a bit of “climate change” in everything.
The wording is careful here, it is more Sks logic “Everything that warms is man everything that cools is natural”
Up = man
Down = natural
FFS!
More pseudo science from models and joke scientists like Meehl who claim things about the global climate that he has no evidence for
*Antarctic ice
And he like the others can never say how much is GHG and how much is natural. Just take any weather anomaly and like Seth Borenstein.. say “10% of that was man made” without a shred of evidence to back it up, like the Paris floods
Except Antarctic sea ice is not expanding at present, in fact it is under the 1981-2010 average?
http://nsidc.org/data/seaice_index/images/daily_images/S_stddev_timeseries.png
And Arctic ice at a record = low
http://nsidc.org/arcticseaicenews/
One year is not enough to go on, maybe a positive SAM has something to do with sea ice extent.
?itok=SfM6AroV
Are you looking at the chart you posted? The Antarctic Sea Ice is both expanding and above average. And as we speak it is expanding and tracking the mean well within the deviation.
“Are you looking at the chart you posted? The Antarctic Sea Ice is both expanding and above average. And as we speak it is expanding and tracking the mean well within the deviation.”
Huh? And it is well below where it was this time last year.
Due to WordPress issues you have to click on it to see the updated graph.
seaice1
“Due to WordPress issues you have to click on it to see the updated graph.”
But even when yo do that I’m still left wondering why Scott Wilmot Bennett thinks the graph is saying Antarctic is above average?
Your Antarctic graph is not the latest, but regardless, Antarctic sea ice is currently within measurement error of the 1981-2000 Average. The lower trop. temps have shown no warming in the entire satellite record.
Arctic Sea Ice is not a record low, DMI ice volume is average for the last ten years confirming the stabilization. http://ocean.dmi.dk/arctic/icethickness/thk.uk.php And after the warm winter, the melt season temps have been below normal. http://ocean.dmi.dk/arctic/meant80n.uk.php It’s highly improbable that this year will produce a record low.
There have also been technical problems as well as unrelated chicanery from NSIDC and DMI with inconvenient data/charts being disappeared and replaced, and graphs being rolled back and altered. It is difficult to know how trustworthy/comparable any ice data is any more.
Grim, some confuse area with volume and in general the warmunists dont realize winds can blow sea ice about, they think blown sea ice is melt
Some may confuse area with volume, but only Mr GrimNasty seems to have done so here. The discussion was clearly about extent, but Mr GrimNasty introduced volume. Volume is the output of a model, so I would have thought it less reliable than area, which is closer to a measurement. Granted, the problems with the satellites have introduced uncertainty into this years results, but the volume model uses area as one of the inputs.
Record sea ice will return in the Antarctic and there will be record sea ice both poles.
The true physical explanation of the change in sea ice both poles must explain all of the observations recent and paleo changes. Everything happens and did happen for a physical reason.
The above linked to paper ignores the piles and piles of data that disproves their hypothesis that the Interdecadal Pacific Oscillation (IPO) is the cause of sea ice changes both poles or Antarctic only.
Solar cycle changes caused the changes in sea ice both poles and caused the warming in the last 30 years.
What we have observed has happened before. There are cycles of warming and cooling in the paleo record which correlate with solar cycle changes.
This is what must be explained not one year, one decade, or three decades of temperature change.
http://arctic.atmos.uiuc.edu/cryosphere/IMAGES/seaice.anomaly.antarctic.png
http://wattsupwiththat.files.wordpress.com/2012/09/davis-and-taylor-wuwt-submission.pdf
Greenland ice temperature, last 11,000 years determined from ice core analysis, Richard Alley’s paper. William: As this graph indicates the Greenland Ice data shows that have been 9 warming and cooling periods in the last 11,000 years.
http://www.climate4you.com/images/GISP2%20TemperatureSince10700%20BP%20with%20CO2%20from%20EPICA%20DomeC.gif
The sudden reduction in Antarctic sea ice is due to an increase in solar wind bursts. The solar wind bursts create a space charge differential in the ionosphere which causes there to be current flow from the high latitude regions (40 to 60 degree latitude) to the equator. The electric current flow causes a change in cloud properties and cloud lifetime at both locations which causes warming.
The solar wind bursts were cause by the sudden appearance of extraordinarily large and numerous coronal holes on the sun. The coronal holes are now starting to dissipate and Ap (a measurement of the change in the geomagnetic field by solar wind bursts) is now dropping month by month.
Natural Variability (to some of us known as the solar variability)
For or five years ago I looked in another natural variability (change in the intensity of the Earth’s magnetic field) observed in the Antarctic.
And guess what? It is closely follows what sun is doing.
http://www.vukcevic.talktalk.net/TSI-dBz.png
Association between two does not necessarily mean A causing B or C is causing A & B.
Let’s listen to Juno , nudge nudge, wink wink.
It’s obvious why the Arctic is melting and the Antarctic is expanding , Co2 is rising to the top of the world .
Got to go now and make my tinfoil hat .
Robert from oz
July 5, 2016 at 1:33 am :
Showing that SH is really the top of the World, CO2 being heavier…..(grin0
No, cold air sinks!
Robert,
Funny, sounds like government science.
all changes in nature are explained by natural variability except for those we can use in our war against fossil fuels.
This level of stupid is really starting to tick me off!
And the clothing experienced by the Emperor is a combination of natural cloth woven using supernatural thread; FFS!
“The climate we experience” is called weather and even if we could “experience” the mean (Noun) of it, a decade won’t cut it. Twenty odd years of growth, followed by fourteen of even faster expansion followed by… speculation, does not a theory make! “Combination of natural..” What, no UHI and no anthropogenic portion of those greenhouse gases!
“The Planet’s response..” Global aint global if one pole* didn’t get the memo! The glaring contradiction that local and global are mutually exclusive in their own arguments eludes them.
*Let alone hemisphere or anything less such as the Southern Ocean.
“The recent trend of increasing Antarctic sea ice extent — seemingly at odds with climate model projections — can largely be explained by a natural climate fluctuation …”.
==============================
That explanation is very disappointing, their ad hoc excuses usually show more creative flair than mundane old “natural climate fluctuation”.
Man, it’s all the extra radiation 1.3472 watts per meter squared (at the top of the atmosphere) held there by CO2…it’s like…reflecting back solar incoming black body radiation in the form of Ultra violet rays which disturb the Auroras. These Auroras then trap the rising coldness off the Antarctic Ocean (as it heats the atmosphere and before it plummets into the depth of the oceans) and lift it by aurora convection over the South Pole. This results in a drop in temperature in that region. It’s the CFC’S man…
I mean duh!
“Natural variability is linked to natural variability!”
Wow – that’s sure to set off rumours of a Nobel prize.
Dizzy wizzy climate scientists find Mother Nature’s fingerprint on Antarctic sea ice expansion and model it for us using government funding. It is a red letter day, surely, when climate scientists discover something that common sense would have told them initially, if they had had any.
I’m just a dumb wally, but this paper doesn’t seem to be telling me anything i didn’t know, if not actually, at least intuitively.
So it’s not that the ‘ice extent increases because of “fresh” water as a result of the ice melting’ anymore. Who’d have thought that?
With a headline like that you know statistical perversion has gone full circle – circumnavigation of the indeterminate. We have entered the age of post normal invariant variability: The Anthropobolloxene.
Any minute now a carbuncle encrusted galleon with a Black Swan figurehead will appear out of the fog. Captain Bayes at the helm, with an overwhelming sense of déjà vu, still modelling anchor chain inclination adjusted for ocean acidification. It’s surreal, where’s Master Jack with his compass when you need him?
“Expanding Antarctic sea ice linked to natural variability”
Or the fact it’s winter in the southern hemisphere.