Guest post by Dr. David Stockwell
I suspect that the only really convincing evidence against global warming is a sustained period of no global warming or cooling — climate sensitivity and feedbacks are too esoteric.
I have followed the recent global temperature with some excitement, and started to prepare a follow up to a previous article I wrote on the failure of global temperature to meet AGW expectations.
The Nature publication “Recent Climate Observations Compared to Projections” by Rahmstorf, Hansen and others in 2007 claimed an up-tick in a graph showed that “global temperatures were increasing faster than expected”, and consequently climate change would be worse than expected. In “Recent Climate Observations: Disagreement with Projections”, using their methodology and two additional year’s data, the up-tick was shown to be an artefact of inadequate smoothing of the effects of a strong El Nino. Perhaps this rebuttal played some part in subsequent revisions of Rahmstorf’s graph with longer smoothing, which had the unfortunate effect (for him) of removing the up-tick, so they could no longer claim, “global temperatures were increasing faster than expected”.
Can we answer the question “Is the Atmosphere still warming” in a reasonable way?
From the field of econometrics comes empirical fluctuation processes (EFP), available to programmers in an R package called strucchange – developed to analyse such things as changes in exchange rates by the brilliant Achim Zeileis. The idea is to find a test of the null hypothesis that the slope parameter m for a section of a series has not changed over time:
H0: m1 = m2 versus the alternative H1: m1 not equal to m2
The idea is to move a window of constant width over the whole sample period, and compare local trends with the overall distribution of trends. The resulting process should not fluctuate (deviate from zero) too much under the null hypothesis and—as the asymptotic distributions of these processes are well-known—boundaries can be computed, which are only crossed with certain probability. If, on the other hand, the empirical process shows large fluctuations and crosses the boundary, there is evidence that the data contains a structural change in the parameter. The peaks can be dated and segmented regression lines fit between the breaks in slope.
I applied the strucchange function EFP to the five official global temperature data sets (CRU, GISS, NOAA, UAH and RSS) from 1978 using the latest values in 2011, and to mean global sea level. The results for the global temperature are below:
The fluctuation process (top panel) crosses the upper significance boundary a number of times, indicating that the trend parameter is unstable. For example, it crosses in 1998, coincident with the strong El Nino, and then relaxes. Most recently, three of the five data sets are at the lower boundary, indicating that at least the CRU, NOAA and RSS datasets have shifted away from the overall warming trend since 1978.
The middle panel shows the structural break model for the CRU data, with the optimal number of breaks given by the minimum of the Bayesian Information Criterion (BIC) (bottom panel). The locations of the breaks are coincident (with a lag) with major events: the ultra-Plinian (stratosphere reaching) eruptions of Mt Chichon and Mt Pinatubo, the Super El Nino and the Pacific Decadal Oscillation (PDO) phase change in 2005.
Sometimes these types of models are sensitive to the start and end point, so I re-ran the analysis with data from 1950. Figure 2 is the resulting structural break model for CRU. While the fluctuation process did not show the same degree of recent downtrend, the structural break model is similar to the shorter series in Figure 1, except the temperatures since 1998 are fit with a single flat segment.
The temperature is plotted over random multiple AR(1) simulations, showing the temperature has ranged between the extremes of an AR(1) model over the period.
Another indication of global temperature is the mean global sea level, both barometric and non-barometric adjusted. Global sea levels tell the same story as atmospheric temperature, with a significant deceleration in sea level rise around the PDO shift in 2005.
By these objective criteria, there does appear to be a structural change away from the medium-term warming trend. Does this mean global warming has stopped?
What are the arguments that warming continues unabated?
Easterling and Wehner in their article “Is the climate warming or cooling?” lambasted “Numerous websites, blogs and articles in the media [that] have claimed that the climate is no longer warming, and is now cooling” for “cherry picking” the recent data. They examined the distribution of 10 year slopes of both the realized and modelled global temperature. They argued that because there were a small number of periods of flat 10 year temperatures that the long-term warming trend is intact.
Both E&W and EFP agree that there is a small chance of flat temperatures for 10 years (EFP says around 5%) during a longer-term warming trend. What E&W’s are saying is that given a small chance at one time, the chance of flat temperatures at any time, over the last 50 years say, is much higher. This doesn’t alter the fact that to an observer during any of those decades when temperature was flat (as now) there would still be a 5% chance of a break in the long-term trend.
Breusch and Vahid (2008 updated in 2011) chimed in with “Global Temperature Trends”, stating “there is no significant evidence for a break in trend in the late 1990s”, and “There is nothing to suggest that anything remarkable has happened around 1998.” As hard as I looked I could not find any estimates of significance to back up their claim of significant evidence.
The statement is even more puzzling as the last 15% at the ends of the series are typically not tested for breaks due to low power of the test on the diminishing numbers of data. The 1990’s fall in the outside 15%. Breaks the size of the break in 1976 would not have been detected on their data.
Of course, there are a variety of other observations of the Earth’s radiative balance and ocean heat content, supporting of the “no warming” claim, by top researchers such as Douglass and Loehle. There does not appear to be any credible empirical evidence from the AGW camp that the atmosphere is still warming.
I suspect that as in “Recent Climate Observations” where climate scientists were fooled into thinking that “climate change will be worse than expected” by the steep up-tick in global temperatures during a strong El Nino, they have also been fooled by a steep but longer-term up-tick in global temperatures associated with a positive phase of the PDO.
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David Stockwell, how are you defining PDO?
None are so “easily fooled” as those who desperately want to be!
But I think Anthropogenic Global Foolishness is definitely receding.
There is nothing to prevent a big La Nina from stepping down the global temps.
A lot of folks who have been stressing out over natural changes will find thier hot air baloons gone cold, and the dizzying heights that they soar, with thier wild predictions, will mean a rapid descent to a hard and unforgiving surface.
Why does Figure 3, for global sea level, have an axis labelled “Temperature (C)”?
REPLY: It is segmented, top and bottom two different graphs, with the top graph sub-segmented for comparison. – Anthony
The AGW projections are so vague that their practicality is near meaningless. The projections are so well mixed in with the climate noise that it is impossible to separate any anthropogenic signal from variability.
You showed the rate of warming regressions for time periods, but a moving rate warming provides some interesting results.
http://theinconvenientskeptic.com/2011/04/2000-years-of-rate-of-temperature-change/
The current warming period is normal in both the magnitude and duration. What is most interesting is that there have been weaker periods of cooling over the past 400 years, well before any anthropogenic signal could have been impacting the climate.
Trying to focus on a 30 year period to predict climate is exactly why the warmists are so far off base. Their entire science is based on the current warming being caused by CO2. All of their efforts are for naught if the warming is 100% natural.
Murray, Oops – that should be sea level. I used the same routine on both sets of data.
Bob, I got the PDO dates from wikipedia. I don’t actually use the values anywhere, as only interested in it as an ‘event’ modifying the slope.
Your analysis of the data is based on some amount of trust in the data being correct. My biggest skepticism of Alarmist Global Warming AGW (not natural global warming) is that the data is too messy and inaccurate to draw any meaningful conclusion from it.
I suspect strongly that the urban heat island effect is underestimated. I suspect strongly that the closing of temperature stations has a larger effect than estimated. I find it curious that global warming has seemed to slow down or even stop about the time skeptics started really paying attention to how data is gathered – so I suspect the data since around 2000 is more accurate than the previous data. I am very suspicious of how the raw data is handled and bias accounted for.
Scientists studying global warming should be addressing all of these factors – instead some seem intent on avoiding a sensible discussion of these factors.
So while I find your analysis interesting, without some confidence in the data your conclusions about THIS data is not convincing, or even meaningful. You can’t analyze bad data and get meaningful results.
I do not mean any of this to be disrespectful of you and your work. I just need to trust the data first.
So, the middle graph of Figure 3 says the temperature has risen from -30C in 1995 to +30C in 2010? I don’t remember it being that cold in 1995. 60C sounds like a HUGE amount of gorebull warming,or am I totally missing something here?
Not being a statistician — or even very good at the stats courses I took as a geology major — whenever I read an article like this that talks about a new statistical tool, I wonder “What did they test this against for correctness”?
So: what DO these stats wallahs run their brilliant new schemes against to see if they make sense at all? What are the sanity checks? Do they take a known curve or linear function and run it against them to see if the slope of the slope, or whatever they’re analyzing, stays constant over the range?
When I read these articles that basically say scientist X used a new tool to determine thus about so, my first thought isn’t about the results — it’s more along the lines of “Is that new-fangled meter stick really a meter long?”, or thoughts to that effect.
How DO we know these new tools are useful, and not just telling us things we want to see?
Thanks David, ignore my second post, timing issues.
the only option is to move the temp recorders closer to the air conditioner units .why JUST do it, I am not going to get off the gravey train just do what you are told
Interesting analysis but why is there no legend on fig.1 and fig.3 ?
You present 5 data sets in fig.1 but there is no legend , no indication in the caption , not even an explanation in the accompanying text to say which is which.
Same in fig.3 , I’m interested to see how the barometric adjustments affect the data but which is which?
Also in fig.3 the middle segment y axis is labelled “temperature (C)” from -30 to +30 . Clearly this is supposed to be a plot of mean sea level not temperature.
The ‘click to enlarge’ images are nice and clear but then fig.3 loses it’s caption, it has no title .
This is incredibly sloppy work from a PhD (unless the doctorate was in sociology or something, I have not checked.).
Robert of Texas: While you could be right, a definite structural change down would be incontrovertable that something is wrong with the theory of AGW, nomatter what the deficiencies in the data, wouldn’t it.
JamesS: If you read some of the background material from the links I provide, these methods have been known to statistics for a long time and well researched. Contrast that with the ‘novel’ statistical approaches that demonstrate the so-called climate breakthroughs. Its chalk and cheese. Steve McIntyre has always been on about this. They need to use methods that have been around the stats literature that are well understood — what I have tried to do here — not roll their own for every new breakthrough.
Also what is the gray scribble on fig.2 ? Anybody’s guess.
Well I am not much of a statistician; so I don’t play the lotteries. I figure that if I buy a ticket, I might win, and I might not; so its a 50:50 shot. If I don’t buy a ticket its a 0:100 shot that I don’t win.
I figure if I played the next million lotteries, that I am going to not win the vast majority of them; but I could win the next one; but only if I buy a ticket. It’s like I bought one ticket, and somebody else bought every other ticket, and he didn’t win; I did !
So much for the statistics.
So back to your premise “is the ATMOSPHERE still warming?” (my emphasis).
It would seem to me that the answer to that question is predicated on the assumption that we even know, or can know the Temperature of the atmosphere. We certainly can’t say if it is still warming until we know that we can even measure it.
I’m not aware that we have the means to measure it. Well I know for sure that Mother Gaia, knows exactly what the Temperature of the atmosphere is; she has a thermometer in each and every atmospheric atom/molecule, so for sure she knows what the (average) Temperature is; and at any instant of time too, so ergo, the average over any interval of time one could wish for.
But then she has no means of telling us what the Temperature is. And it’s for darn sure, that we don’t have nearly enough thermometers in the atmosphere to measure the Temperature. Well there’s that little problem of sampled data system theory, called the Nyquist Sampling Theorem. And we are sampling a field of two variables; time and space. And we don’t take enough observations often enough to satisfy the Nyquist criterion for either one of those two variables; let alone for both of them simultaneously.
And remember that, one only has to fall short of the Nyquist prescribed sampling rate by a factor of two to have the reconstruction of the sampled continuous function produce aliassing noise at zero frequency; which means that not only can we not reconstruct the continuous two variable function, but we can’t even obtain the correct average, without aliassing noise.
Other than that; it is an interesting question that you ask. In the long run, the properties of the H2O molecule will ensure that the answer to your question is NO !
David Stockwell says: “Bob, I got the PDO dates from wikipedia. I don’t actually use the values anywhere, as only interested in it as an ‘event’ modifying the slope.”
In looking at you Figure 1, the PDO switch that you’ve highlighted is the only event that lags the structural break.
Regardless, since the PDO is an abstract form of the North Pacific SST anomalies and does not represent them, there’s no mechanism for it modify the slope. The North Pacific SST anomalies peaked in 2005 and have been dropping since then.
“Both E&W and EFP agree that there is a small chance of flat temperatures for 10 years (EFP says around 5%)”
I believe it was once stated that the IPCC was 90% confident that CO2 was to blame for global warming. And even if we assume for argument sake that the temperatures were flat for only 10 years, does that mean the IPCC is now only 5% certain CO2 is to blame for global warming?
P. Solar: Tough crowd. I have sent in a new Fig 3 to replace the old one.
Great job, Dr. Stockwell! I thank you for post this! You saved me a ton of work and I don’t think my approach would have been as comprehensive as yours.
For those that wish a simpler view, similar to what I’m taking from the information,
go here, http://suyts.wordpress.com/2011/04/12/rss-going-negative/
No, it isn’t a blog per se, just some informative graphs that shows all of the recent “warming”. Hopefully, some people can come to an understanding that when a “scientist” speaks of “recent” warming on a global scale, they will know they are being entirely disingenuous. (Think about the explanation for the recent snowy years.)
The third segment of fig 1 and fig 3 have no label on the vertical axis. What does this represent?
Just for informational purposes , since axis ticks are usually marked with dimensionless quantities like 0,1,2… so the axis label should also be dimensionless, eg. temperature/C or MSL/mm .
As always when showing climate related data, no indication of the uncertainty of the data is given.
Perhaps that’s all we can expect form environmental “science”.
P Solar, the gray scribbles are: “The temperature is plotted over random multiple AR(1) simulations, showing the temperature has ranged between the extremes of an AR(1) model over the period.”
The uncertainty of the breaks are indicated by the red bars over the x axis of the middle panels.
No, S for brains. the atmosphere isn’t still warming.
Murray, did you ever get an answer to your -30C question? It’s a good on. Its probably in hundredths of a degree Celcius.
I’m sorry but could we stop “analyzing” the temperatures within such a narrow time frame window?… rising, or falling, or flat over a month, a year, or even a decade? It’s silly, populist, non scientific to me. In this planet’s history of climate and geology, anything less than a couple of centuries is just noise. Or weather. Are you bullish or bearish on stocks for this year, based on an analysis of the S&P 500 index yesterday between 2:30 p.m and 2:32 p.m?