First some background for our readers that may not be familiar with the term “random walk”
See: http://en.wikipedia.org/wiki/Random_walk
New Paper “Random Walk Lengths Of About 30 Years In Global Climate” By Bye Et Al 2011
There is a new paper [h/t to Ryan Maue and Anthony Watts] titled
Bye, J., K. Fraedrich, E. Kirk, S. Schubert, and X. Zhu (2011), Random walk lengths of about 30 years in global climate, Geophys. Res. Lett., doi:10.1029/2010GL046333, in press. (accepted 7 February 2011)
The abstract reads [highlight added]
“We have applied the relation for the mean of the expected values of the maximum excursion in a bounded random walk to estimate the random walk length from time series of eight independent global mean quantities (temperature maximum, summer lag, temperature minimum and winter lag over the land and in the ocean) derived from the NCEP twentieth century reanalysis (V2) (1871-2008) and the ECHAM5 IPCC AR4 twentieth century run for 1860-2100, and also the Millenium 3100 yr control run mil01, which was segmented into records of specified period. The results for NCEP, ECHAM5 and mil01 (mean of thirty 100 yr segments) are very similar and indicate a random walk length on land of 24 yr and over the ocean of 20 yr. Using three 1000 yr segments from mil01, the random walk lengths increased to 37 yr on land and 33 yr over the ocean. This result indicates that the shorter records may not totally capture the random variability of climate relevant on the time scale of civilizations, for which the random walk length is likely to be about 30 years. For this random walk length, the observed standard deviations of maximum temperature and minimum temperature yield respective expected maximum excursions on land of 1.4 and 0.5 C and over the ocean of 2.3 and 0.7 C, which are substantial fractions of the global warming signal.”
The text starts with
“The annual cycle is the largest climate signal, however its variability has often been overlooked as a climate diagnostic, even though global climate has received intensive study in recent times, e.g. IPCC (2007), with a primary aim of accurate prediction under global warming.”
We agree with the authors of the paper on this statement. This is one of the reasons we completed the paper
Herman, B.M. M.A. Brunke, R.A. Pielke Sr., J.R. Christy, and R.T. McNider, 2010: Global and hemispheric lower tropospheric temperature trends. Remote Sensing, 2, 2561-2570; doi:10.3390/rs2112561
where our abstract reads
“Previous analyses of the Earth’s annual cycle and its trends have utilized surface temperature data sets. Here we introduce a new analysis of the global and hemispheric annual cycle using a satellite remote sensing derived data set during the period 1979–2009, as determined from the lower tropospheric (LT) channel of the MSU satellite. While the surface annual cycle is tied directly to the heating and cooling of the land areas, the tropospheric annual cycle involves additionally the gain or loss of heat between the surface and atmosphere. The peak in the global tropospheric temperature in the 30 year period occurs on 10 July and the minimum on 9 February in response to the larger land mass in the Northern Hemisphere. The actual dates of the hemispheric maxima and minima are a complex function of many variables which can change from year to year thereby altering these dates.
Here we examine the time of occurrence of the global and hemispheric maxima and minima lower tropospheric temperatures, the values of the annual maxima and minima, and the slopes and significance of the changes in these metrics. The statistically significant trends are all relatively small. The values of the global annual maximum and minimum showed a small, but significant trend. Northern and Southern Hemisphere maxima and minima show a slight trend toward occurring later in the year. Most recent analyses of trends in the global annual cycle using observed surface data have indicated a trend toward earlier maxima and minima.”
The 2011 Bye et al GRL paper conclusion reads
“In 1935, the International Meteorological Organisation confirmed that ‘climate is the average weather’ and adopted the years 1901-1930 as the ‘climate normal period’. Subsequently a period of thirty years has been retained as the classical period of averaging (IPCC 2007). Our analysis suggests that this administrative decision was an inspired guess. Random walks of length about 30 years within natural variability are an ‘inconvenient truth’ which must be taken into account in the global warming debate. This is particularly true when the causes of trends in the temperature record are under consideration.”
This paper is yet another significant contribution that raises further issues on the use of multi-decadal linear surface temperature trends to diagnose climate change.
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How is “random walk length” defined in the paper?
KR: You could have replied simply, “No. I have not plotted and analyzed them for their full term,” in your February 14, 2011 at 2:45 pm reply to my earlier question. It would have saved you some time.
You replied, “You are correct, Bob, bad terminology on my part, my apologies. They are components of expected variations in temperatures based upon seasonal and oceanic cycles. And accounting for (correcting for) these cyclic variations reduces the underlying variability of the observed temperature data.”
But you are overlooking the fact that these seasonal and ENSO-induced variations are parts of the instrument temperature record and, for ENSO, are responses to internal coupled ocean-atmosphere processes that have multiyear aftereffects. They are not noise, and for the paper presented in this post, they would need to remain in the data.
Also they are not “expected variations”. If they were, climate modelers would be able to duplicate ENSO and its aftereffects since 1880s, but, of course, they cannot.
You wrote, “I believe he’s finding the transient response to solar variations, not any long-term response – just the upper 100 meters of well-mixed ocean.”
The key word in that sentence is “believe”. The other studies (much discussed and debated a few years ago) with the multiyear and multidecadal lags were also investigations of the surface temperature record, not the upper 100 meters of ocean.
You wrote, “I will note that he’s [Tamino’s] perhaps one of the most skilled time series analysts I know of…”
Anyone [Tamino included] who claims to account for the process of ENSO with linear regression and further claims the trend of the volcano- and ENSO-adjusted global temperature anomalies is caused by anthropogenic global warming [as Tamino did in the two posts you linked earlier] is not a “skilled time series analyst”. ENSO is a process and cannot be accounted for (as Tamino attempted) with linear regression. They are [he is] simply attempting to prolong a myth.
I have long regarded that icon of the 60’s, the lava lamp, as a particularly interesting, though simple, example of “climate in a bottle”. You have a closed system with an external energy source which in general, functions within fixed boundaries and in a rather predictable fashion, in that the wax will melt, rise to the top, then fall down again. But the detail is very different – there appears to be no real pattern to how the motion unfolds, a little like a log fire, you can watch the seemingly random activity of either of these for ages (if you have nothing else to do). I have often wondered if anybody had bothered to accurately model what goes on in the lava lamp’s environment, my bet would be that it is possible to simulate the behaviour on a computer, but if you ran it on a monitor next to a real lamp, it would fail to predict the actual sequence of events. And this is my problem with models, they simulate and in broad terms describe outcome scenarios, but rarely, if ever, maintain any direct connection with reality.
So if the normal climate variations can be ascribed to a ‘random walk’ can the glacials and inter-glacials be ascribed to ‘Levy Flight’ variances?
I notice no one is incorporating the 3 year GCR lag. Based on 100 AU it takes 1.5 years for the heliopause to adjust to current sun conditions and then a further 1.5 years for the GCR to reach earth from the heliopause.
Bob Tisdale – “It would have saved you some time.”
So – you are simply ignoring causal relationships between minimum and maximum temperatures? And the relationship of the beginning and ending of seasons as botanical zones move towards the poles? Ignoring cause and effect? If you had just stated that, well, that would have also saved me some time.
Actual statistical analysis of the random walk components of the climate (Gordon and Bye 1993 http://www.sciencedirect.com/science?_ob=ArticleURL&_udi=B6VF0-487DN15-1&_user=10&_coverDate=11%2F30%2F1993&_rdoc=1&_fmt=high&_orig=search&_origin=search&_sort=d&_docanchor=&view=c&_searchStrId=1641686257&_rerunOrigin=google&_acct=C000050221&_version=1&_urlVersion=0&_userid=10&md5=333426af25a2723dce790818c565ceb9&searchtype=a) indicate that maximum excursions of random walks are indeed seen on the scale of ~5 years, matching the ENSO and QBO variations. However, “…the projected temperature rise due to the enhanced Greenhouse effect possibly cannot be supported as a random walk…”.
Unless these papers have disproven Gordon and Bye, their argument about random walks are not valid.
A better link for the paper I noted in my previous post, Gordon and Bye 1993, should be http://linkinghub.elsevier.com/retrieve/pii/092181819390007B
Sorry for the overly long URL.
Eric the halibut,
Many years ago I read an article in the Economist [before it caught the CAGW virus] that reported on the use of lava lamps as random number generators. IIRC, a half-dozen lamps were placed in a mirrored room, with a value assigned to the amount of reflection from the moving wax, which was picked up by a CCTV camera.
Since true random number generators don’t exist and would be very much in demand, I’ve often wondered why this idea never caught on.
…We now return you to your regularly scheduled programming.☺
RE: Gary Pearse
February 14, 2011 at 9:55 am
Comment on expected number of maximums or minimums in a record. I looked at the Mean monthly and yearly data from CET. I recalculated monthly anomalies based on the average of all the months present.
4224 months Ln(4224)=8.3 Counting year one, 12 new maximum and 11 new minimum anomalies.
352 years Ln(352)=5.9 Counting year one, 9 new maximums and 9 new minimums
Looks like the number of max and mins is a little higher than predicted, but the number of both is very even.
The slope of the monthly anomalies is 0.25°C/100yrs
Ian W mentions ‘Levy Flight’ a couple of posts above.
I’ll have to add that to the growing list of various statistical distributions and descriptions I need to further study.
Levy Flight, Hurst Exponent, rescaled range, fractional gaussian, fractional brownian, long range dependence, Hurst-Kolmogorov distribution …… they all show much more low frequency variation than expected from a gaussian or normal distribution.
So it is very foolish to expect climate variations to follow a sqrt(n) sort of random walk.
Mike Haseler says:
“A drunk still has some goal in their walk … the randomness has a general direction … given time it will become obvious they are heading somewhere.”
Perhaps you haven’t been as drunk as I have been. When you figure out what my goal was could you write me and let me know?
DeWitt Payne beat me to the punch in making the point that global climate cannot be a random walk because it is bounded. At least since the Hadean the presence of liquid water shows that.
It is arguable that within those ranges and timescales a ‘random walk’ behavoir could dominate variations.
But the obvious correlation with orbital cycles and major volcanic activity indicates that the climate is not causally independent of radiative transfer effects.
I think I remember an article about casinos/gambling devices that sheds light on this. They monitor the wheels etc because although these devices are carefully designed to exhibit ‘random walk’ behavior to prevent prediction and biasing the odds, that random walk may look like a consistent trend over some timescales/magnitudes.
It is actually quite difficult to exclude the possibility that a sequence is a random walk robustly. But the Casino’s take the opposite approach. Given the possibility that small physical effects can cause a trend or bias in the outcomes, and knowing that others doing analysis could make money from them if their wheels etc were NOT random, they remove any device that shows a trend long before it is possible to establish it ISN’T a random walk.
Because the consequences of there being a physical cause of the bias/trend is too great to risk.
Perhaps climate policy need not be as cautious as Las Vegas….
>>that global climate cannot be a random walk because it is bounded<<
Short term it can certainly appear to be a random walk. Longer term climate for most of the past 600 million years has swung between an average of 12C and 22C, with little time spent in the middle.
This resembles a drunken walk down a hallway, where the drunk leans against one wall or the other for stability, and occassionally veers from one wall to the other for no apparent reason.
Why the climate appears stable long term at 12C and 22C and unstable elsewhere is an interesting question.
February 14, 2011 at 11:00 am
Ross McKittick provides a clear and concise summary of the misdirection in enconometrics that prevailed on the basis of blind academic faith in the random walk model. In the physical world, apart from diffusion processes, it’s unlikely that a strict random walk (Wiener-Einstein process) is encountered anywhere on geophysical scales. A pervasive problem with many empirical statistical analyses is the employment of weak tests for stochastic independence (e.g., Durban-Watson statistic) on increments in arbitrarily discretized (and often aliased) time-histories of physical signals.
Proper power spectrum analyses almost invariably reveal significant oscillatory components quite apart from the periodic diurnal and seasonal cylces. In climatic series, some oscillations are quite wide-band (ENSO) and unpredictable, whereas others are narrow-band enough (multi-decadal oscillations) to provide some useful predictability. There’s a intrinsic difference between the well-studied noise models that academics appeal to theoretically and the signal behavior that is encountered in practice. Sadly, climate science has not produced its own Granger to tell the difference. Consequently, all sorts of baseless statistical speculation tries to fly in a vacuum of analytic grasp of real-world signals.
Bill Hunter says: at 5:27 pm
“When you figure out what my goal . . .”
Agreed. And we are in good company.
Life’s Been Good / Joe Walsh
“I go to parties, sometimes until four
It’s hard to leave when you can’t find the door”
Smokey – Random number generation from lava lamps:
That sounds fantastic – and great fun too. Until the statisticians chill out too much to work while watching the lamps, of course! 🙂
We can navel gaze all we like. We can create a theory its all about socialism. However we can bleat all we like about dying ideologies – yes there will death of both if we continue to these work the theory of papers and “play the fiddle whilst Rome burns”.
I know we know about it. You have heard time and time again that the signs globally are coming out since 2005 ever stronger. More and more we are seeing the delays of increased greenhouse gas effects come through loud and clear as a distinct impact.
Latest reading indicate we nearing are 400ppm of CO2. Please do play on the ppm game of concentration. Anyone who has a decent high school education knows about its radiative forcing properties. Anyone also knows that a globally warming world sets in motion the water vapor cycle and speeds it up. That is water -> Water vapor -> upper atmosphere – a potent greenhouse gas effect then interplays on our climate.
DID IT EVER OCCUR to anyone when water vapor goes into the upper atmosphere – it STORES the energy that put it up there in the first place! Did it it ever occur to anyone that this stored energy then rebounds back to the earth and is not lost to space.
And lets be clear on this this – heat returns to earth’s surface when it rains.
Water vapor is a potent greenhouse gas along with other gases such as carbon dioxide and methane. Wikipedia.
The water molecule brings heat energy with it. In turn, the temperature of the atmosphere drops slightly. In the atmosphere, condensation produces clouds, fog and precipitation (usually only when facilitated by cloud condensation nuclei). The dew point of an air parcel is the temperature to which it must cool before water vapor in the air begins to condense.
Also, a net condensation of water vapor occurs on surfaces when the temperature of the surface is at or below the dew point temperature of the atmosphere. Deposition, the direct formation of ice from water vapor, is a type of condensation. Frost and snow are examples of deposition. Wikipedia
The link is obvious – the climate feedbacks of late indicate that what has been said time and time again are 100% correct.
You do need not the parroting of climategate/new papers assertions of just theory -we just need to co-operate together and not politic this debate.
Science papers that attempt to theorize our past century whilst there are obvious signs of definitive global warming highlights that not enough people really get it.
This is not about politics – this will be a brave new world that we will all face together.
Ross Brisbane says: “We can navel gaze all we like…”
Which is exactly what your comment consists of. You’ve not put forth proof that any of what you say is correct, meaningful, or applicable.
I love this. The paper is called “Random Walk Lengths Of About 30 Years In Global Climate”. But as near as I can tell, they never look at the global climate at all. It’s kinda like a Hollywood movie that the filmmakers say is “based on a true story” but changes the plotline entirely, this study is “based on a true climate” but doesn’t use a scrap of climate data.
Instead they take their so-called “data” from the “NCEP twentieth century reanalysis (V2) (1871-2008) and the ECHAM5 IPCC AR4 twentieth century run for 1860-2100, and also the Millenium 3100 yr control run mil01, which was segmented into records of specified period.” Note that none of those are data, they are all the results of climate model runs. Every one of them.
Nor are their “eight independent global mean quantities” independent in any sense, they are all related to each other.
So instead of using eight independent climate variables as they claim, they have used eight closely related climate model outputs … isn’t there some kind of “Truth in Scientific Advertising” law that prevents this kind of misrepresentation? Because if they tried this kind of “bait and switch” tactic while selling soap flakes, they’d be put in jail …
To me, the length of random walks in climate model outputs is one of the most meaningless statistics I can imagine. Why would anyone possibly care? Random walks in real data are interesting, but it has to be real data.
w.
You know, scanning down this thread I just couldn’t help think of my Dad laying out his facts and figures, explaining why his next business scheme would be a hit.
But the thing is, just like him, you folks seem to forget that your map is not the territory.
You can make all your learned arguments – but the Earth Observation Data; along with the considerable uptick in extreme weather phenomena; supported by the consensus scientific understanding for why this is happening – really ought to rattle you folks out of your ivory towers.
[snip]
jorge;
you were far too kind to Ross.
Not worth replying to, actually; he’s way too whacked to even represent the average Believer.
citizenschallenge says:
February 14, 2011 at 11:46 pm
Could you provide some reference of this “considerable uptick in extreme weather phenomena”? All other source seem to indicate none.
From your own blog:
May I paraphrase:
Climate is big, huge, beyond anything anyone of us can imagine. Won’t we recognize that when reading, absorbing, witnessing the IPCC reports (or any Holy Book) we interpret it through our individual eyes while weaving our own observations into our understanding and further telling? This isn’t denying the truths within sacred texts: it is admitting that the the Climate’s mysteries are beyond our laymen’s ability to grasp.
Ross McKitrick says:
February 14, 2011 at 11:00 am
‘’’’’’’’’’Nonetheless, the model getting the most support in the data indicates RW behavior and yields a contemporary trend component well below GCM forecasts.’’’’’’’’’’
‘’’’’’’’’’The email traffic pertaining to the AR4 Ch 3 review process (not in the Climategate archive, but public nonetheless, if you know where to look) shows that the Ch 3 lead authors knew they were in over their heads.’’’’’’’’’’
——————-
Ross McKitrick,
Your comment was very clear and enlightening. Thank you.
Can you kindly answer two questions?
QUESTION #1: Can you please tell us the name of the statistical model getting the most support in the data.
QUESTION #2: Where do I look for the emails pertaining to the AR4 Ch 3 review process?
John
DeWitt Payne,
I think the logic is fundamental in support of the existence of a random component(s) to natural processes on this planet. First logical step is to develop and verify some tests for the presence of a random component in the behavior of nature. Next do the tests on some real data (for example GST time series data). Evaluate and cross reference various test results. If they show a random component is involved then, until the tests can be shown to be in error, the treatment of data must include analytical processes that account for random component behavior; analytical processes that do not account for a random component behavior cannot be logically justified.
DeWitt, do you find errors in the statistical tests or their application?
John
Ross Brisbane says:
February 14, 2011 at 7:23 pm
This is not about politics – this will be a brave new world that we will all face together.
You don’t have an idea what Brave New World means, do you? Read it, then report back, please.
At least Bokanovsky’s process is definitely about politics, not science. The issues at stake used to be called “freedom“ in Oldspeak.