Significant Arctic Sea Ice Story a Possibility This Year

well done Russians,
“With the current icebreaker fleet, regular through
passages are possible between July and October, and have been made in November. For more
than a decade, the western portion has been kept open year-round as far as the Yenisey River”

Heat transport to the N Atlantic was trending down for the last decade and heat content has been dropping since 2007. I wouldn’t bet money on any individual year since one major storm could change everything but I would bet money that if the heat transport doesn’t pick back up the Arctic will be gaining ice.

The really interesting thing about the first curve is the (unremarked) change in the variance of the sea ice curve in the range of the 21st century where it appears to have flattened out and maybe even be bottoming. The range of natural oscillation goes from roughly 1 million km-sq to 3 million km-sq! One can actually understand the concern that this was a “tipping point” — this is precisely the kind of thing that is observed in the vicinity of a critical point for a second order phase transition — critical slowing down, a divergence in the scale of fluctuations, and eventually a critical fluctuation that pushes the entire system from one bistable or multistable attractor to another.
However, the system is also clearly still stabilized by strong negative feedbacks towards a collectively stable “locally mean” behavior as the width of fluctuations isn’t changing much. Once it hits extremes, it rapidly regresses towards that mean. We still do not understand the motion of the mean — it seems unlikely to be CO_2 driven or driven by the global anomaly, as it has lousy correlation with the latter and a meaningless correlation with the former (generally monotonic functions can always be correlated, but if their pattern of variation and fluctuations don’t correspond it is difficult to even argue that there is a direct causal link between the two).
I personally am curious as to whether or not even these SHORT term predictions for things like ENSO, the AMO, and the arctic sea ice cycle are borne out. I do think that the decadal oscillations are a major factor in climate evolution, but since the decadal oscillations themselves are chaotic and at best quasi-periodic and of highly variable strength and duration, one can see their large effect on climate after the fact easily enough, but predicting that large effect beforehand requires being able to predict them and we can’t. It would be an absolute hoot if — after all of the bated-breath hype concerning a strong ENSO this year (without which the warmist argument collapses under its own weight within a couple more years as the solar cycle starts the long road downhill to a probable extended minimum and a possible very low following cycle, which seems likely to have at least SOME cooling effect) turns out to just be wrong, with the ENSO more or less fizzling out and/or being replaced by a strong La Nina. Perhaps it is “unlikely”, but I still think that our ability to predict large scale things until they are basically already happening is almost nonexistent. In this case, they are “already happening” (or starting to happen) but there are still many, many nonlinear factors that we cannot compute involved, so that we’re basically saying “most of the time when something starts out this way, the following happens” without having any really good understanding of why.
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Phil. says:
May 6, 2014 at 7:43 am
—————–
Even in 1987 the route was all year round for western section.
Year Cargo in Thousands of Tons Length of Season
1935 246 93 days
1940 289 93 days
1950 503 122 days
1960 1013 128 days
1970 2400 140-150 days
1980 4951 year round for western section
1987 6579 year round for western section

cont…
“The first offer to open the Northern Sea Route to international shipping was made
early in 1967, when it was argued that it could save thirteen days between Hamburg and
Yokohama as opposed to the conventional link via Suez. Soviet cargo carriers made three
demonstration voyages from north European ports and Japan. Unforeseen events then
intervened. The Suez Canal was closed later in 1967 by war and the invitation for international
shipping on the sea route was quietly withdrawn. The Soviets apparently did not wish to offend
friendly Arab governments by offering an alternative to the Suez Canal. The Canal was to
remain blocked for eight years and international shipping adjusted smoothly to using the Cape
route”

Phil. says:
May 6, 2014 at 8:30 am
you will note that the route became all year round, 1980, three years after nuclear powered ice breakers came into operation.
Still I never knew the route was offered up in 1967.

In general the GCM is better than any other tool in predicting long range changes.
Hmm, last week was “agree with Stephen and Nick week”, but today I have to take issue with this. Again, see figures 9.8a and 9.8b of AR5. EMIC’s (Earth System Models of Intermediate Complexity) do substantially better than GCMs in predicting long range changes (up to 2005, where the figure inexplicably ends). Both EMICs and GCMs suck — and I mean really, really suck — at hindcasting the climate. Both of them (unsurprisingly) do decently during the so-called reference period, a.k.a. The training data to those of us who do predictive modeling but this is utterly irrelevant to ability to actually predict. And even in the reference period, EMICs outperform GCMs.
In the post-reference period, EMICs do better BECAUSE they actually made the turn into the current flat temperature regime, where GCMs continue rocketing up. A cynic would conclude that their predictions wasn’t continued or plotted up to e.g. 2011 or 2012 because they do not predict a large climate sensitivity; perhaps they actually worked across the flattening where GCMs fail but then lead to non-alarming rises by 2100, I do not know.
But unless you have actual data that proves your assertion to counter the actual data in AR5 that contradicts it, I think this is incorrect.
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@SAMURAI,
“I realize there are many factors involved in Arctic ice formation/dissipation, but, ceretis paribus, the 56-year record warm Arctic temperatures this winter should have had a negative impact on ice formation in the Arctic region this winter, just as, conversely, the record low temperatures in North America lead to record ice formation of the Great Lakes this winter.”
It is not unusual during severe winters that the polar (arctic) source regions “warm”. I can still remember when I was a weather forecaster during the winter of 1983/84 to see “warm fronts” coming out of north-central Canada! For a period of 6 weeks the upper level jetstream forced the forming polar air masses to advect southward one right after another. Needless to say there appeared to be an arctic “hot spot”, when in reality the surface temps over the arctic and other polar regions didn’t exactly “warm”. At least not in the sense the laymen believed. During other synoptic patterns, the polar and deep arctic air masses remain bottled up in the high latitudes. And during other situations warm waters advected from the tropical regions do in fact melt arctic ice. During the final stretches of the 1983-84 cold shot, it wasn’t unusual to see surface temperatures in the Dakotas and High Plains to be colder than the reporting stations in extreme Northern Canada. And I still remember one of those wicked cold fronts being so strong as to drive into Central Mexico.

@Bob Tisdale,
TRM says: “So PDO is negative, AMO is negative and the sun is quiet….”
Except the PDO has been positive for the first three months this year.
I checked NOAA’s PDO index for the last 30 years and I’ve noticed there were stretches when the PDO was positive that the indicies went negative for a short period of time (3-6 months) and vice versa.
Here’s the link I used:
http://jisao.washington.edu/pdo/
There’s been so much blather about the PDO that I remain agnostic to it all. Maybe I should buy one of your e-books!

evanmjones says:
May 5, 2014 at 9:31 pm
So…how can an anomaly be said to be near or above normal
He’ll be meaning for the average of the 1981 – 2010 time period. “Zero anomaly” would be the average.

I would rather see the anomaly plotted with standard deviation on the Y axis. Statistically it would say more. A great many of the “scary” plots used to show how some metric is behaving relative some arbitrarily chosen “average” period use exaggerated vertical axes to make the behaviour “clear .” The problem is that such exaggeration can also mislead you into thinking the apparent changes are significant. I would like to see an excursion of at least three SD before I started even wondering about “significance” and even that is a fairly high chance of a Type I error (~1:500). That may seem like a small number, but a bit of consideration will lead to the realization that vastly more unlikely events are part of everyday life. If you play some game like Poker, Yahtsee or Risk, you have almost certainly seen far more unlikely events. If you haven’t, then you would be a statistical anomaly yourself

Janne says:
May 6, 2014 at 11:00 am
“The SS Manhattan did it in 1969.”
Accompanied by four ice breakers apparently. Nordic Orion did it by itself
——————–
although the Nordic Orion was accompanied by the Louis S. St. Laurent, a Coast Guard icebreaker.
I am sure satellite navigation helps compared to 1969.
The ship MV Nordic Orion weighs 13,000 tons, of which about 3,000 tonnes are pure ice strengthening. The engine has 18,500 horsepower at an ordinary ship in the class 11,000 to 12,000 horsepower. All this has meant that the vessel has ice class 1A, which is the highest commercial grade of ice-strengthened ships.
Still good news for the ice breaking industry,in the 2010-2011 seas they rescued over 10,000 ships.
http://www.arctic-info.com/ExpertOpinion/Page/-the-need-for-icebreakers-will-increase-after-the-year-2016-
“For this reason, especially in the summer, there has been an increase in the need for icebreakers on the Northern Sea Route”

Janne says:
May 6, 2014 at 11:00 am
Like it or not the passage is becoming a viable option for shipping.
——————-
nothing new.
The russians offered the route up for shipping in 1967.

Janne says:
May 6, 2014 at 11:00 am
“The SS Manhattan did it in 1969.”
——————————
“The most important satellite we use is equipped with an active radar instrument that sends out a signal obliquely to the Earth’s surface and measures the signal reflected back to the satellite. If the signal meets a calm sea surface, little is reflected, but when the satellite passes over ice, the surface is normally more uneven, and the reflected signal is stronger. In this way we obtain valuable knowledge of where and when it is safe for ships in the area to travel,” says Dinessen.

You are spot on with your assessment of ECIMs/GCMs. Unfortunately, those who believe in their ability to predict future climate really don’t want to talk about the differential equations, numerical methods or initial/boundary conditions which comprise these codes. That’s where the real problems are…
Well, let’s be careful how you state this. Those who believe in their ability to predict future climate who aren’t in the business don’t want to talk about all of this, and those who aren’t expert in predictive modeling and statistics in general in the business would prefer in many cases not to have a detailed discussion of the difficulty of properly validating a predictive model — a process which basically never ends as new data comes in.
However, most of the GCMs and ECIMs are well, and reasonably publicly, documented. It’s just that unless you have a Ph.D. in (say) physics, a knowledge of general mathematics and statistics and computer science and numerical computing that would suffice to earn you at least masters degree in each of those subjects if acquired in the context of an academic program, plus substantial subspecialization knowledge in the general fields of computational fluid dynamics and climate science, you don’t know enough to intelligently comment on the code itself. You can only comment on it as a black box, or comment on one tiny fragment of the code, or physics, or initialization, or methods, or the ode solvers, or the dynamical engines, or the averaging, or the spatiotemporal resolution, or…
Look, I actually have a Ph.D in theoretical physics. I’ve completed something like six graduate level math classes (mostly as an undergraduate, but a couple as a physics grad student). I’ve taught (and written a textbook on) graduate level electrodynamics, which is basically a thinly disguised course in elliptical and hyperbolic PDEs. I’ve written a book on large scale cluster computing that people still use when setting up compute clusters, and have several gigabytes worth of code in my personal subversion tree and cannot keep count of how many languages I either know well or have written at least one program in dating back to code written on paper tape. I’ve co-founded two companies on advanced predictive modelling on the basis of code I’ve written and a process for doing indirect Bayesian inference across privacy or other data boundaries that was for a long time patent pending before trying to defend a method patent grew too expensive and cumbersome to continue; the second company is still extant and making substantial progress towards perhaps one day making me rich. I’ve did advanced importance-sampling Monte Carlo simulation as my primary research for around 15 years before quitting that as well. I’ve learned a fair bit of climate science. I basically lack a detailed knowledge and experience of only computational fluid dynamics in the list above (and understand the concepts there pretty well, but that isn’t the same thing as direct experience) and I still have a hard time working through e.g. the CAM 3.1 documentation, and an even harder time working through the open source code, partly because the code is terribly organized and poorly internally documented to the point where just getting it to build correctly requires dedication and a week or two of effort.
Oh, and did I mention that I’m also an experienced systems/network programmer and administrator? So I actually understand the underlying tools REQUIRED for it to build pretty well…
If I have a hard time getting to where I can — for example — simply build an openly published code base and run it on a personal multicore system to watch the whole thing actually run through to a conclusion, let alone start to reorganize the code, replace underlying components such as its absurd lat/long gridding on the surface of a sphere with rescalable symmetric tesselations to make the code adaptive, isolate the various contributing physics subsystems so that they can be easily modified or replaced without affecting other parts of the computation, and so on, you can bet that there aren’t but a handful of people worldwide who are going to be able to do this and willing to do this without a paycheck and substantial support. How does one get the paycheck, the support, the access to supercomputing-scale resources to enable the process? By writing grants (and having enough time to do the work, in an environment capable of providing the required support in exchange for indirect cost money at fixed rates, with the implicit support of the department you work for) and getting grant money to do so.
And who controls who, of the tiny handful of people broadly enough competent in the list above to have a good chance of being able to manage the whole project on the basis of their own directly implemented knowledge and skills AND who has the time and indirect support etc, gets funded? Who reviews the grants?
Why, the very people you would be competing with, who all have a number of vested interests in there being an emergency, because without an emergency the US government might fund two or even three distinct efforts to write a functioning climate model, but they’d never fund forty or fifty such efforts. It is in nobody’s best interests in this group to admit outsiders — all of those groups have grad students they need to place, jobs they need to have materialize for the ones that won’t continue in research, and themselves depend on not antagonizing their friends and colleagues. As AR5 directly remarks — of the 36 or so named components of CMIP5, there aren’t anything LIKE 36 independent models — the models, data, methods, code are all variants of a mere handful of “memetic” code lines, split off on precisely the basis of grad student X starting his or her own version of the code they used in school as part of newly funded program at a new school or institution.
IMO, solving the problem the GCMs are trying to solve is a grand challenge problem in computer science. It isn’t at all surprising that the solutions so far don’t work very well. It would rather be surprising if they did. We don’t even have the data needed to intelligently initialize the models we have got, and those models almost certainly have a completely inadequate spatiotemporal resolution on an insanely stupid, non-rescalable gridding of a sphere. So the programs literally cannot be made to run at a finer resolution without basically rewriting the whole thing, and any such rewrite would only make the problem at the poles worse — quadrature on a spherical surface using a rectilinear lat/long grid is long known to be enormously difficult and to give rise to artifacts and nearly uncontrollable error estimates.
But until the people doing “statistics” on the output of the GCMs come to their senses and stop treating each GCM as if it is an independent and identically distributed sample drawn from a distribution of perfectly written GCM codes plus unknown but unbiased internal errors — which is precisely what AR5 does, as is explicitly acknowledged in section 9.2 in precisely two paragraphs hidden neatly in the middle that more or less add up to “all of the `confidence’ given the estimates listed at the beginning of chapter 9 is basically human opinion bullshit, not something that can be backed up by any sort of axiomatically correct statistical analysis” — the public will be safely protected from any “dangerous” knowledge of the ongoing failure of the GCMs to actually predict or hindcast anything at all particularly accurately outside of the reference interval.
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Thank yewww! shout-outs to Mike Jonas , RACookPE1978 and everyone else who set me straight on my “anomaly” question.

If I happened to be a squawking Chicken Little I would say: you guys are making a big deal about “normal” amounts of Arctic ice? Like normal is a “significant story.” Like it signifies plummeting temperatures and the onset of a new ice age? Seriously, normal? We’ve had very low levels of Arctic ice and once this little bit of normal blows over we will go back to being ice free again like we predicted for 2013. And if not, so what, we look elsewhere, like to Antarctica, or well then to U.S. temperatures, or to skyrocketing global temperatures over the last 20 years, or er to our climate models, or er um, uhm, to whatever it is, the media will report our story, and the little people will believe. Like you guys think that the people are going to be all freaked out about “normal” levels of ice. Not! That won’t scare anyone! (/s)

Or is he suggesting that the ice will be much thicker, despite volume?