How Not to Analyze Data, part 3

April 1, 2008 · 139 Comments

Anthony Watts and Basil Copeland have collaborated on another post claiming to establish a connection between solar activity (as proxied by the sunspot cycle) and global temperature (as indicated by the HadCRUT3v data set). Let’s take a close look.

First, they smooth the temperature time series using a Hodrick-Prescott filter. It has a tuneable parameter which enables one to choose the amount of smoothing which the filter imposes; the parameter is somewhat analagous to the “cutoff frequency” in a low-pass filter, or the “characteristic time scale” in other smoothing methods. Watts/Copeland set the tuneable parameter to 7, which effectively smooths the data on a roughly 6-year time scale.

Hodrick-Prescott filtering is an outstanding smoothing method. It’s especially good near the edges of the time span, where many other methods show undesirable “edge effects.” Here, for example, is a comparison of using the H-P filter (labelled HP-7), to using a “running polynomial” smoothing (with a well-chosen weighting function) also on a roughly 6-year time scale (labelled GSR):

Clearly the two methods give nearly identical results except at the very edges of the time span, where the H-P filter performs better. Of course H-P filtering has its drawbacks too, including the facts that it requires an even time spacing and it’s not as useful as other methods for interpolating between the observation times, but for this analysis those aren’t anything to worry about.

They then take the first differences of the smoothed time series; that’s just the difference between a given value, and the preceding value. It’s an estimate of rate of change (i.e., the first time derivative) of the smoothed underlying signal. That’s fine too, except that one has to bear in mind that the values estimated by any smoothing method have an inherent uncertainty. Hence the difference between two consecutive values also has an inherent uncertainty. Here’s their plot of these estimated rates of change (click the graph for a larger, clearer view):

And here’s what I got using the exact same method:

So far, we’re on the same page. But now things start to go wrong. They take the peaks of these rate estimates, and assert that they tend to happen at the same time as the peaks of the sunspot cycle. But they don’t take all the peaks from the estimated rate-of-change plot; they include only the ones that fall near a peak in the sunspot cycle, which are labelled in their plot with numbers indicating which sunspot cycle they correspond to. It’s certainly suspect to include only the peaks that match one’s theory! Even so, there are only 3 peaks which they exclude, so we’ll note that there’s a problem with their methodology, but that it might not be too severe, and move on.

They compare the times of peak of the sunspot cycle to the times of peak warming rate in this graph (click the graph for a larger, clearer view):

They further note that the correlation between the times of sunspot peak and the times of warming-rate peak is a whopping 0.99846454. Now that is mighty impressive; it certainly deserves some exclamation points!!

But there are two problems with this graph. One is that one of the data points is wrong. Look at the points for cycle 11: they plot both sunspot cycle peak and warming-rate peak right on top of each other, happening in the same year, 1870. That’s the right year for the sunspot cycle peak, but not for the warming-rate peak; that doesn’t happen until 1877. Here’s a corrected graph with the erroneous (now fixed) point circled:

It’s curious that the single data point for which the difference between the time of the sunspot cycle peak and of the warming-rate peak is greatest, is the data point which is in error on their graph.

But there’s a far more serious problem. They’re correlating two data series which are both sorted into ascending order. That means that without even knowing what the numbers are, we can be sure that they’ll correlate strongly; as one series gets bigger so will the other, in quite strict relation because they’re two series in the same order. Let me illustrate: I generated 14 random numbers (one for each solar cycle peak) between 0 and 1 (following a uniform distribution), then sorted them into ascending order, then plotted solar-cycle peak year against the random numbers and computed the squared correlation. Here’s the result:

That’s a mighty impressive squared correlation; it deserves some exclamation points too!! Of course, it’s not really impressive when one realizes that two sorted series will always correlate, and that in this case the “impressive” correlation is between sunspot cycle peak years and random numbers. Consider also that this is the squared correlation; the simple correlation coefficient is 0.9941.

Can we apply a valid test to whether or not the sunspot cycle is synchronized with the peaks in the warming-rate calculation? Let’s take the times of peak of the sunspot cycle and compute the differences; these are estimates of the lengths of the sunspot cycle. We can also take the differences between the times of the warming-rate peaks as selected by Watts and Copeland, as estimates of the lengths of the warming-rate “cycle.” Then let’s compare the sunspot cycle lengths to the warming rate “cycle” lengths. If there’s really a correlation, then longer sunspot cycles should correspond to longer warming-rate “cycles.” Here’s the result:

The correlation between them is not statistically significant, but there are very few data points. More noteworthy is the fact that if there is a correlation, these data indicate that it’s going the wrong way; there’s evidence (but hardly conclusive) that longer sunspot cycles correspond to shorter warming-rate “cycles.”

How do we evaluate the analysis of Watts and Copeland? First, they omit three of the peaks in the warming-rate calculation, because they don’t correspond to their theory. Then they plot the wrong value for the cycle which has the biggest difference between sunspot cycle peak year and warming-rate peak year. Then they compute an impressive-looking correlation for two sorted data series, apparently not even realizing that it’s not much different from what you can get correlating sunspot cycle peak times with random numbers. Finally, a comparison of sunspot cycle lengths with warming-rate “cycle” lengths indicates no significant correlation, although the possible relation is in the wrong direction. All in all, the analysis of Watts and Copeland provides no evidence whatever of any relationship between HadCRUT3v global temperature data, and sunspot data.

In responding to a reader comment, Watts states, “I had a number of qualified people including a published climatologist, solar scientist, a statistician, and a certified consulting meteorologist (among others) look at this beforehand.” Which makes you wonder…

UPDATE UPDATE UPDATE

Readers have wondered, what’s a good test to determine whether or not there’s significant coincidence between the times of sunspot cycle maxima and the times of warming-rate maxima? There are many tests; one I’d like to mention is to compute Rayleigh’s R (see Upton & Fingleton 1989, Spatial Data Analysis by Example, vol. 2, Wiley, Chichester, UK).

We wish to know whether warming-rate maxima tend to occur at some particular time during the sunspot cycle. Each warming-rate maximum will be at some particular phase of the sunspot cycle. If it happens right at sunspot cycle maximum, it’s at phase 0. If it’s halfway from sunspot cycle maximum to the next sunspot cycle maximum, it’s at phase 0.5 for that cycle. If it’s a quarter of the way from one maximum to the next one, it’s at phase 0.25. Etc., etc., you get the idea.

To compute Rayleigh’s R, we first compute the phase $\phi$ for each warming-rate maximum; all phases will fall between 0 and 1. Then we compute $(x,y)$ coordinates for each warming-rate maximum by

$x = \cos(2 \pi \phi),~~~ y = \sin(2 \pi \phi)$ .

We can then plot the $(x,y)$ values for each warming-rate maximum on the $x-y$ plane; all these points will fall on the circle of radius 1 (the unit circle).

If all of the warming-rate maxima coincide exactly with the sunspot cycle maxima, then all of the phases will be 0. In that case, all of the warming-rate maxima will be at coordinates $(1,0)$ ; that’s the point on the unit circle toward the right. If all the warming-rate maxima occur at the midpoint of the sunspot cycle, they’ll all have phase 0.5 and they’ll all have coordinates $(-1,0)$ ; in this case they’re all $180^\circ$ out of phase with the sunspot cycle. The plot of $(x,y)$ positions is like plotting points on a “clock” which marks out the sunspot cycle; toward the right (the “3 o’clock” position) is in phase with the sunspot cycle, toward the left (the “9 o’clock” position) is $180^\circ$ out of phase with the sunspot cycle, etc. etc. you get the idea. And as the sunspot cycle goes forward, the clock goes counter-clockwise.

If warming-rate maxima tend to occur at about the same time in the sunspot cycle, then the points when plotted will aggregate near a particular clock position. If they’re happening at the same time as sunspot cycle maximum, they’ll tend to aggregate near the 3 o’clock position; if they’re happening near the midpoint between sunspot cycle maxima they’ll tend to aggregate near the 9 o’clock position, etc. etc. you get the idea.

To test whether or not they’re aggregating, we compute the average $x$ value and the average $y$ value; call these $\bar x$ and $\bar y$ . We then compute Rayleigh’s R as:

$R = \sqrt{\bar x^2 + \bar y^2}$ .

Suppose all the warming-rate maxima exactly coincide with sunspot cycle maxima. Then all the phases are 0, all the coordinates are $(1,0)$ , and the average coordinates are $(1,0)$ . In this case, Rayleigh’s R is $R=1$ . Suppose they all fall at some other (but the same for all) phase in the sunspot cycle; again Rayleigh’s R will be $R=1$ . But if they’re distributed randomly throughout the sunspot cycle, then the average coordinates will be approximately $(0,0)$ , and Rayleigh’s R will be small.

This is the basis for testing whether warming-rate maxima tend to fall at a particular time during the sunspot cycle using Rayleigh’s R. We compute R, compare it to a critical value, and if it’s greater than that critical value we have evidence that the distribution is not random; if it’s less than the critical value, then the available data are consistent with the hypothesis that they’re occuring at random times throughout the sunspot cycle.

Let’s do it! We’ll use the data according to the method of Watts and Coleman. There are 14 data points (although Watts and Coleman omit 3 of the warming-rate maxima, so we’ll do the same, which is cheating in their favor). Also, they only time the events to the nearest year, so some of the phases turn out to be exactly the same; for instance, two of the warming-rate maxima occur during the same year as sunspot-cycle maxima, so two of the points have phase zero and fall exactly at the 3 o’clock position.

The critical value for Rayleigh’s R, given a false-alarm probability $p$ , applied to $N$ data points, is approximately

$R_{crit} \approx \sqrt{ - \ln(p) / N}$ .

This is only approximate and the sample is small, but as we’ll soon see the result isn’t anywhere near close, so we can ignore the exact calculation (which is generally done by Monte Carlo simulation). We’ll use a false-alarm probability of $p = 0.05$ , which is equivalent to 95% confidence, and $N=14$ data points, so the critical value is approximately $R_{crit} \approx 0.46$ . Here’s a plot of the results:

Three of the black dots represent two data points; they’re indicated by a “(x2)”. There’s also a very short red line, from the origin to the average coordinates $(\bar x, \bar y)$ . And there’s a blue circle indicating the radius corresponding to the approximate 95%-confidence critical value. If the end of the red line extended outside that circle, we’d have evidence that the warming-rate maxima are not randomly distributed, rather that they tend to aggregate at a particular phase of the sunspot cycle. If it were a close call, we’d need to compute the precise critical value for Rayleigh’s R for a sample size of 14 data points.

But it’s clearly not a close call. Rayleigh’s R for this data is $R=0.097$ , the critical value is $\approx 0.46$ . Like I said, not even close.

So in fact there’s no evidence that warming-rate maxima, computed according to the method of Watts and Coleman, tend to fall at any particular phase of the sunspot cycle. Not only do they fail to occur at the same time as sunspot cycle maximum (at phase zero), they don’t tend toward any particular phase of the sunspot cycle.

Categories: Global Warming · climate change

139 responses so far ↓

EliRabett // April 1, 2008 at 3:29 am | Reply

It’s April Fools Day, right? The thing that drives me nuts is that when I look at HadCRUT what I see is a bunch of jiggle jiggle, maybe even 11 year jiggle, on a large rise whose period is ~ 100 years. This “method” differences the rise away. The clowns have thrown the forest away to look at the trees.

[Response: It's not quite April Fool's day yet. But I guess it's close enough.]
kim // April 1, 2008 at 4:03 am | Reply

Longer sunspot cycles correlate with shorter warming cycles. Hmmmm. Very interesting. Maybe longer cycles are weaker? Let’s ask Leif.

Oh yes. April Fools. Laughs hysterically.
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Ian // April 1, 2008 at 4:47 am | Reply

Nicely done – hard to find a more cogent demonstation of a flawed analsis than “significant” correlation with random series.
nanny_govt_sucks // April 1, 2008 at 5:00 am | Reply

Can we apply a valid test to whether or not the sunspot cycle is synchronized with the peaks in the warming-rate calculation? Let’s take the times of peak of the sunspot cycle and compute the differences; these are estimates of the lengths of the sunspot cycle.

Can you run that again with the 22 year sunspot cycle?
Georg Hoffmann // April 1, 2008 at 6:32 am | Reply

Tamino
I dont miss any of your posts. Not that I am particularly interested in Watts “climate analysis” or the question if they are wrong or very wrong, but it’s just a pleasure to read your deconstructions. The best thing that could happen to someone like Watts is that someone like you is taking their studies apart. At least they were worth for something.
Still laughing
Georg
fred // April 1, 2008 at 8:19 am | Reply

Seriously, what is generally thought to have caused the rise the smoothed graph shows from 1900 to 1950, and then the subsequent decline or stabilization until the latest rises?
Onanym // April 1, 2008 at 9:24 am | Reply

I really can’t see the point of their analysis, except trying to fool somebody. And I can’t see many comments that make critical comments to their work (goes for CA as well).

However, what’s the R² for the straight forward correlation of the timeseries for the differentiated temp. curve and the sunspot curve (not just the maxima)?

Else, your site is really nice and educational!

[Response: For sunspot counts vs smoothed temperature 1st differences, the squared correlation R^2 = 0.025.]
mmghosh // April 1, 2008 at 12:14 pm | Reply

Perhaps Mr Watts could get Mr McIntyre to validate his analyses before publishing them.

Mr McIntyre has a good reputation as mathematical analyst, and his imprimatur would carry weight, on this blog as well as others. To do this should be a reasonably straightforward process as well.
blcjr // April 1, 2008 at 12:20 pm | Reply

It is true that 2 out of 16 peaks in the data, during solar cycle 16, are anomalous, and invite further scrutiny. But 14 out of 16 peaks still show Schwabe cycle periodicity. And then there’s the matter of how with higher order HP filtering, we no longer see the even numbered solar cycles, but we still see Hale cycle periodicity in the odd numbered ones.

I’ll look into the data plotted in Figure 5, and if there’s an error, we’ll correct it. Your point about not reading too much, if anything, into a correlation from data that is already ordered in some fashion is well taken.

Would you care to share the weighting you use in your GSR plot? I would like to investigate that further.

[Response: Would you be one of Watts' collaborators? One of his reviewers?

You say you'll "look into" figure 5, and correct it IF there's an error? Are you joking? It took me 15 seconds to realize that graph was garbage analysis. According to reader comments, I'm not the only one. If you do correct it, will you pull a switch and try to pretend the ludicrous mistake never happened, or will you admit on the blog that it was just plain wrong?

As for 14 peaks still showing the Schwabe cycle periodicity -- NO THEY DON'T. Don't you get it?

As for my weighting scheme, I'm preparing to share that -- in the peer-reviewed literature.]
Barton Paul Levenson // April 1, 2008 at 12:26 pm | Reply

I can’t believe they sorted the series before correlating them. Doesn’t that mean they’ve decoupled the individual points?
kim // April 1, 2008 at 12:49 pm | Reply

blcjr is Basil.
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Boris // April 1, 2008 at 12:52 pm | Reply

Perhaps Mr Watts could get Mr McIntyre to validate his analyses before publishing them.

It makes you wonder why Steve M would want to be associated with Watts. Watts is not just a commenter at Climate Audit, he’s a contributer and authors of dozens of threads.
blcjr // April 1, 2008 at 1:09 pm | Reply

I’m “Basil.” I didn’t realize that I was replying under another account (”blcjr”). I still continue to be amazed at how rapidly discourse with you descends into the regions of negative marginal utility. You must be a very angry person, to let things become so personal to you. I would ask you to chill out, but that’s probably not the turn of phrase you want to see or hear in any discussion of climate change.

Basil

[Response: Every time you guys are proved wrong by rigorous application of legitimate analysis, you complain about hostility. I suppose that delusion is the only way you can avoid admitting the truth to yourselves.

You have shown yourself -- repeatedly -- to be the author of not just mistaken, but grossly incompetent data analysis. That's not anger, it's truth. If you really believe in virtue, then you should admit this on Watts' blog and apologize to his readers.]
kim // April 1, 2008 at 1:33 pm | Reply

Shouldn’t the point of figure 5 be how close the x’s and crosses are to each other? Does your analysis show that? Why agonize over the slope at all?
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[Response: It's the "correlation" between the x's and crosses that is reported by Watts and Copeland, and which I reported with the crosses replaced by random numbers. The point of *their* figure 5 plotted in that way (their way), is to give a visual impression of stunning agreement.]
J // April 1, 2008 at 1:40 pm | Reply

BPL writes: “I can’t believe they sorted the series before correlating them. Doesn’t that mean they’ve decoupled the individual points?”

What’s to decouple in this case? It’s just two lists of dates.

:-)
Joel Shore // April 1, 2008 at 1:47 pm | Reply

Excellent post. It is interesting to see how easy it is for people to fool themselves when they know what answer they want to get.

To be fair though, other people (such a Camp and Tung http://www.amath.washington.edu/research/articles/Tung/journals/solar-jgr.pdf ) have found a correlation between the solar cycle and global temperature…so such a correlation may really be out there. However, I agree that this hopelessly flawed method of analysis doesn’t show it.

It is also worth noting that Camp and Tung use the correlation to derive an estimate of climate sensitivity and get good agreement with the estimated range of the IPCC. (This is assuming, presumably, that the same sort of feedbacks apply for warming by changes in total solar irradiance as by changes in greenhouse gases. Of course, the “skeptics” presumably want to believe that the warming is due to some exotic mechanism like cosmic rays so that they can have a high response to the solar changes and still have a low climate sensitivity.)
climatewonk // April 1, 2008 at 1:50 pm | Reply

Need I post this?

“Lies, damned lies and statistics.”

April Fools indeed.
P. Lewis // April 1, 2008 at 2:21 pm | Reply

As well as their (obvious?) detrending of any global warming signal over the 20th century in their lower panel of their Fig 3 to leave the “cyclical” HadCRUT3, wouldn’t one also want to remove any El Nino (and La Nina) signals before proceeding to do their first-difference plot in their Fig 5 and before assigning peaks to sunspot cycle maxima? The 1877-88 (11), 1986-87 (22) and 1997-98 (23) regions would surely look different at the very least.
Ian // April 1, 2008 at 2:24 pm | Reply

kim said:

Shouldn’t the point of figure 5 be how close the x’s and crosses are to each other?

kim, think about the data and look again at how it’s constrained in the graph – how in the world would you get the xs and +s within pairs to be far apart?

Basil, I hope you stay with the thread; we’d like to hear your responses to the criticisms.
kim // April 1, 2008 at 2:37 pm | Reply

Ian, I agree the graph is poor, but the correlation they are seeking is how close the x’s and crosses are to each other. Sure, the format makes it look like they are close to each other, but surely there is a method to measure that and analyze its significance.
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Mike B // April 1, 2008 at 2:56 pm | Reply

kim said:

Ian, I agree the graph is poor, but the correlation they are seeking is how close the x’s and crosses are to each other. Sure, the format makes it look like they are close to each other, but surely there is a method to measure that and analyze its significance.

Did you even read Tamino’s post? There is no significance in an doing correlations between sorted series, even random numbers produce a near perfect result. Tamino did a relevant analysis comparing the correlations between the lengths of the cycles and it wasn’t statistically significant.
P. Lewis // April 1, 2008 at 3:09 pm | Reply

Re my point above. I’ve now got around to reading some of the comments on that thread (Hmm!) over at Watts’house and I see my very point has been sort of raised there (by Pierre Gosselin (aka AGWscoffer)) and is awaiting an answer … although Pierre Gosselin later also says:

I mean just recently a report came out saying the ocean temps have cooled a little over the last 5 years. Could this have led to the current El Nina?

in correcting

(Wikipedia says that the current cooling is caused by the current La Nina. How do we know its not the other way around?)

(Hmm!)
Horatio Algeranon // April 1, 2008 at 3:14 pm | Reply

I have a Theory and it is mine
Hank Roberts // April 1, 2008 at 3:37 pm | Reply

No, that’s not the correlation they’re seeking. That’s not even the hypothesis they’re testing. That’s a picture displaying some of their work graphically.

Mr. Kim, is it fair to assume you have not had a college statistics class? How about a calculus class? Give us some idea what level of math you’ve reached in school so we can start from there.
Chris Colose // April 1, 2008 at 4:43 pm | Reply

Re: fred

[QUOTE]Seriously, what is generally thought to have caused the rise the smoothed graph shows from 1900 to 1950, and then the subsequent decline or stabilization until the latest rises?[/QUOTE]

The earlier warming was mostly solar, some lack of volcanic, a tiny bit of anthropogenic (possibly some black carbon), some internal variations (some El Ninos at the end of the period). Mostly larger fluctuations rather than a trend like today, and more warming is recent decades.

There has been an insignificant secular trend in solar activity from ~1952, no matter how hard the Watts fraud campaign tries to say otherwise. While these deconstructions are nice to see (good work ), it is disappointing that such nonsense is allowed to keep distracting people, which forces people who actually know what they are talking about (e.g., RC, Tamino) to waste time and stray away from the interesting stuff. I refuse to audit poor statistical analysis on my blog because it will never end. Watts is winning the battle, but not because of science, but because he can exploit the ignorance of people who matter– the public. I think it is time to admit this rather than changing the subject to hockey sticks, sunspots, or general counter-arguments I can find on the global warming swindle
luminous beauty // April 1, 2008 at 4:59 pm | Reply

darling kim,

“…but surely there is a method to measure that and analyze its significance.”

Surely there is. But surely not via Basil’s bogosity flux diagrams. Try here:

http://publishing.royalsociety.org/media/proceedings_a/rspa20071880.pdf

I have confidence that you may someday cease being a secondary bogon emitter and eventually become a net cluon absorber.

But I’m not going to hold my breath.
Petro // April 1, 2008 at 5:41 pm | Reply

kim wondered:

“Surely there is a method to measure that and analyze its significance.”

Indeed there is, did you this one: http://tamino.files.wordpress.com/2008/04/periods.jpg
JCH // April 1, 2008 at 7:14 pm | Reply

El Nina?

I don’t even want to speculate.
Dano // April 1, 2008 at 8:04 pm | Reply

Did you even read Tamino’s post? There is no significance in an doing correlations between sorted series, even random numbers produce a near perfect result. Tamino did a relevant analysis comparing the correlations between the lengths of the cycles and it wasn’t statistically significant.

Mike, the confirmation bias programmed into the kim bot does not allow your statement to compute. Same thing as Schrödinger’s cat, only different.

Best,

D
Joel Shore // April 1, 2008 at 9:05 pm | Reply

kim: I’ll give you a slightly different answer than most of the people here. I think the fact that both the sunspot cycle and the smoothed temperature data oscillate on roughly an 11-year time scale does suggest some sort of correlation in the data. What Tamino’s analysis shows is, however, that the fantastic correlation that Watts and Copeland pulled out was largely an artifact of their method…and he has also shown that any correlation is weak enough that you can’t see it if you look to try to see if variations in the time between the peaks in the first-differenced-smoothed-temperatures are correlated with variations in the solar cycle length.

I would also caution that, to the extent that the smoothed temperature data do have in them an oscillation on roughly an 11-year timescale, one might wonder if it is partly or even largely an artifact of the smoothing process, which Tamino noted is basically smoothing over roughly a 6-year period and thus an 11-year oscillation may be about the shortest that can show up. So, I would want to see the smoothing done for different values of that tunable parameter.

At any rate, there are other papers in the literature, like the one that I referenced above, that do claim to detect the solar cycle in the temperature data…And, in fact, this is not unexpected on the basis of the change in total solar irradiance and the estimated climate sensitivity (although there is some debate about how much this should be suppressed because of the relatively fast nature of these oscillations compared to some slower timescales in the climate system). In fact, that paper by Camp and Tung actually uses the oscillation that they find to show that the IPCC estimate of climate sensitivity seems to be right on.

I’m not sure how the field as a whole feels about the Camp and Tung work. Detecting these sorts of correlations in noisy data is not trivial to do correctly (and is very easy to do wildly incorrectly, as Watts and Copeland have demonstrated).

However, it is important to keep in mind that the AGW theory is not dependent on there being no response of the climate to the sun. Rather, the problem with the idea that the sun is responsible for the warming in the last 30 years or so is that there doesn’t seem to be the necessary secular trend in the solar data to produce the warming. And, of course, in order to make the solar hypothesis negate AGW, one would also have to explain why solar effects (that, as I noted, don’t seem to have the right trend anyway) get amplified and CO2 effects that should be causing warming get de-amplified.
Hansen's Bulldog // April 1, 2008 at 9:09 pm | Reply

Readers have wondered what test might give a *correct* estimate of whether or not there’s correspondence between the times of sunspot cycle maxima, and the times of “warming-rate” maxima. So I’ve updated the post, to illustrate the application of a good method.

In case you’re wondering — the hypothesis of correlation fails. Miserably.
Joel Shore // April 1, 2008 at 9:25 pm | Reply

Hmmm…My last post was made before Tamino’s update that throws cold water on the idea that there is any phase relationship between the solar cycle oscillations and the smoothed-difference-temperature ones. That seems to make it look even more damning for the hypothesis tying the temperature to the solar cycle.

As a question to Tamino: What do you think of the work of Camp and Tung ( http://www.amath.washington.edu/research/articles/Tung/journals/solar-jgr.pdf ), or other papers in the literature that do claim a relationship between the solar cycle and global temperatures?

[Response: There are lots of papers claiming a connection between global temperature and the solar cycle, but most of them fail statistical significance. Camp & Tung claim both significance, and a larger amplitude of solar-cycle induced temperature variation than most (if I recall correctly, 0.18 deg.C). I suspect there might be a problem with their analysis, which artificially inflates the estimated amplitude of the response. But I'm not sure.

I'd be very surprised if there's *not* some connection; more solar energy in should lead to higher temperature. But the effect is slight, and doesn't seem to rise above the noise level sufficiently to be detected -- unless Camp & Tung are correct, in which case they've managed to identify it. As I say, I'm skeptical but uncertain.]
David B. Benson // April 1, 2008 at 9:39 pm | Reply

Tamino aka “Hansen’s Bulldog” — I especially appreciated the update. Exquisitely clear.

Random indeed…
kim // April 1, 2008 at 10:52 pm | Reply

Thanks, HB and JS; that is helpful. No thanks, D and HR, but bowling about par. Smooches, lum; that was funny.

Still, solar minima and climate minima coincide. How come?
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Andrew W // April 1, 2008 at 11:22 pm | Reply

I tried to make the following comment over on Watt’s blog but he’s not posting it:

I see that Tamino has done an analysis of your post here:
http://tamino.wordpress.com/2008/04/01/how-not-to-analyze-data-part-3/#more-673

Care to comment on the merit or otherwise of his post?”

I guess your work has allowed him to understand just how embarassingly bad his analysis is.
Hank Roberts // April 1, 2008 at 11:26 pm | Reply

> Still …

cite, please? Why do you believe this is true? “How come?” following a statement of belief asks the readers here to find evidence to support what you believe.

Can’t you?
Hank Roberts // April 1, 2008 at 11:27 pm | Reply

One thing you might want to do is find the terms used, because yours don’t find anything in Google Scholar:

search – “solar minimum” “climate minimum” – did not match any articles.

search – “solar minima” “climate minima” – did not match any articles.
Lee // April 1, 2008 at 11:40 pm | Reply

Andrew,

Watts seems to be blocking quite a number of people. He blocks me too. Even better, he has gone back several weeks and systematically removed my old posts questioning his analyses – posts he previously allowed and even commented on in some cases . Sweet!
kim // April 2, 2008 at 12:04 am | Reply

Hank, sunspots during the Maunder Minimum were sparse, inordinately large, and all in the Sun’s Southern Hemisphere. During the Dalton Minimum they were virtually absent. How do I know? Leif Svalgaard says so.

There is meaning there. What is it?
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Heretic // April 2, 2008 at 12:07 am | Reply

Kudos to HB for exposing Watts for what he is, altough it seems Watts is doing a pretty good job or revealing himself!
That kind of individual gives a bad name to skepticism in general, a time honored virtue indispensable to any scientific undertaking.

The behavior of the individual, deleting posts, responses or the incompetence showed by the “analyses” he posts, which is more telling? What do you think, Kim?
kim // April 2, 2008 at 12:11 am | Reply

What do I think, Heretic. I think he’s a soul similar to mine, seeking understanding in a wondrous world, not someone certain and content in his faith. If the shoe fits; wear it.
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David B. Benson // April 2, 2008 at 12:43 am | Reply

kim // April 2, 2008 at 12:11 am — You would do a lot better to take the time to read S. Weart’s “The Discovery of Global Warming”.

Stick with the physics (and the statistics performed by the competent).
Hank Roberts // April 2, 2008 at 12:55 am | Reply

Kim, Leif’s answered your question.
Pointer for you in the relevant thread:
http://tamino.wordpress.com/2007/10/13/solar-cycle-24/#comment-16131
Hansen's Bulldog // April 2, 2008 at 1:10 am | Reply

Anthony Watts has posted this comment on the post in question.

We’ll see what happens.
kim // April 2, 2008 at 1:15 am | Reply

What do you think of the three independent confirmations of Watts’ and Copeland’s thesis?

Hank, see response on thread titled Solar Cycle #24. I don’t think the question is answered satisfactorily, yet.

Thanks, David, for the pointer to Weart’s work. I’ll peruse it. I may be too skeptical about carbon dioxide and clouds to absorb it though. I’ll try to be critical.
============================

[Response: They're not independent confirmations. They appear to be simply application of filters other than Hodrick-Prescott to estimate the times of warming-rate maxima.

None of them address the real problem: that the method used by Watts and Copeland to show correlation between the two series of timings (sunspot cycle maxima and warming-rate maxima) is completely invalid. They claim correlation of 0.99846454 between those two series, but I managed to get 0.9941 replacing their warming-rate maxima series with random numbers. Application of a proper test shows that the evidence for genuine correlation isn't even close.]
nanny_govt_sucks // April 2, 2008 at 2:29 am | Reply

So in fact there’s no evidence that warming-rate maxima, computed according to the method of Watts and Coleman, tend to fall at any particular phase of the sunspot cycle.

Can you run this test taking into account a 22 year sunspot cycle? Can you test odd vs even sunspot cycles? It is well know that the reversal of the sun’s polarity relative to Earth’s magnetic poles every 11 years can have dramatic effects. Just looking at 11 year cycles ignores this aspect of solar effects on Earth’s climate.
climatewonk // April 2, 2008 at 3:03 am | Reply

Reading over at Watts’ blog is telling. So many of his readers admit to not understanding the maths/statistics well enough to follow or judge, but still feel confident enough to take him at his word and marvel at the amazingly significant correlation he’s uncovered with his novel approach to statistical analysis!!!

They reject the whole of climate science for the past few decades, not trusting published climate scientists or their work but accept at face value one paper using a methodology they do not understand.

This is what it has come to — rejecting the preponderance of evidence for half-baked and erroneous “papers” published on internet blogs — what a sorry state of affairs.
Jeff C. // April 2, 2008 at 5:25 am | Reply

As Tamino mentions, Anthony Watts has posted a comment admitting that the correlation plot has problems. Okay, they screwed up. Let’s see where it goes from here.

As a first time visitor, I was reasonably impressed with your site, write-up and analysis. After wading through your moderated comments, it passed. Probably a third stated in one way or another – you really took that clown Watts down a few notches. Classy. Red meat for the believers won’t bring converts.

[Response: If only it were just a case of "Okay, they screwed up."

I've examined a number of the posts on Watts' site which attempt data analysis. Every one of them is plagued with "screw ups" at least as blatant as that described here; Watts has a pattern of promoting incompetent analysis in an attempt to contradict global warming. These aren't cases of rival methodology, or close calls, or failure to comprehend the subtleties of new and intricate analysis methods. They're blatant, even grotesque examples of incompetence, from Watts himself, Joe D'Aleo, Jim Goodridge, Basil Copeland, and I'd venture to guess, many others. I certainly haven't reviewed Watts' site with any thoroughness, but I have seen a fair number of his posts and I haven't yet seen one data analysis on Watts' site which is correct -- or even close.

This time, perhaps as a result of my previous critiques, he had his and Copeland's post reviewed by "a number of qualified people including a published climatologist, solar scientist, a statistician, and a certified consulting meteorologist (among others)..." Yet none of them caught a glaring problem which it took me about 15 seconds to see (and according to one reader's comment, I'm not the only one to notice it that quickly). There's no getting around the fact that Watts and his collaborators and reviewers simply are not competent to undertake data analysis. Yet he persists in obstinate promotion of falsehoods.

But this is the first time I'm aware of that he's admitted there even *might* be a problem. His response to previous critiques has been suggestive of evasiveness, even to the point of removing an entire post, which was later restored but without any correction or statement that it "has problems." As I said in commentary to an earlier post, if he had simply said "Oops -- my bad" then we would have gained respect for his character. Instead he has let his posts continue to mislead readers, in spite of having been fully informed of the problems. And in commentary here, he has always used polite language but has nonetheless engaged in ad hominem attacks against me personally, his favorite of which seems to be the implication that my choice to blog anonymously is cowardice.

In light of the pattern of grossly incompetent analysis which gives the false impression of discrediting climate science, the lack of corrections and admissions of error, the questionable reaction to criticism, it's no surprise that I and my readers are frustrated to the point that yes, we vent our frustration on Watts.

We'll see how he handles the current situation. He can go a long way toward redeeming himself with a clear and highly visible admission of the error of his ways.]
Charles // April 2, 2008 at 7:12 am | Reply

I have to agree with climatewonk and others expressing concern about those not knowing the science being suckered in by seemingly sound analyses like the ones of Watts and Basil. The public will reject the preponderance of scientific evidence available in the peer reviewed literature, largely because the public doesn’t know the the details and depths of the evidence, not being familiar with the literature. So they are easily influenced by blogs–and it looks as though those skeptical about AGW are seizing on this phenomenon. What concerns me are the illiteracies in the public around science and the workings of science.
fred // April 2, 2008 at 7:41 am | Reply

Joel Shore: thanks, exactly the right tone.

Lee: he blocks your comments because you have lost him due to their tone. Think about how much more effective Joel’s is – not in terms of releasing feeling, but in terms of getting agreement.

Chris: the tags are “blockquote” and “/blockquote” as in

this is a quote

at least I hope they are since we can’t preview here!
Heretic // April 2, 2008 at 8:30 am | Reply

Kim, that is truly funny. I know now how much attention you deserve, and that is how much Watts does, i.e. close to zero. The self righteous faith thing was the icing on the cake.
kim // April 2, 2008 at 11:40 am | Reply

Hank, comment #365 in the Svalgaard #4 thread has Leif’s answer. He’s agnostic about the question.
======================
Harold Ramsey // April 2, 2008 at 12:36 pm | Reply

1. Random number graph
Your random numbers seem a little too evenly spread to be random. You also choose to use 14 random numbers – why not 10 or 20? It is not random to choose an equal number of random numbers as solar cycles. The fact that there are 14 peaks in warming rate (excluding a couple of minor events) to match with 14 solar cycles over the same time period indicates a pattern in itself.

2. Warming cycle length vs solar cycle length

As you point out, there are not enough data points for this type of graph to be statistically significant – therefore the graph is pointless. It cannot show a correlation or non correlation. Why show it in the first place?
That said, I can clearly see a pattern. For the sunspot cycle lengths of 9, 12 &13 years there are only 1 or 2 data points so there is inadequate information and they can be ignored.
There are 5 data points for the sunspot cycle length of ten years. So if you take an average of these 5 data points you get an average of 10.4 years warming cycle length for solar cycle lengths of 10 years.
There are 4 data points for the sunspot cycle length of 11 years. The average of these 4 data points gives an average of 10.5 years solar cycle length for solar cycle lengths of 11 years.
For a small data set this seams a reasonable correlation. The average is only half a year different between solar cycle length and warming cycle length.!

I believe you are using statistical trickery to discredit some fairly obvious patterns.

[Response: Your criticisms, and your analysis, are so bogus that I'll leave it to others to tear you limb from limb.]
J.Hansford. // April 2, 2008 at 12:42 pm | Reply

Tamino… In your response to JeffC… You are a bit like the pot calling the kettle black….

If you were to use your own critique against yourself, you would have, time and again compromised your own integrity by defending Mann’s indefensible hockey stick graph…

… When really you would say that you were only exploring possibilities and interesting areas of significance…. Why is Mr Watts and Co suddenly beasts eating children, when they explore their interesting ideas and areas of significance…? ‘eh?

I suggest you look into the idea that there may be a strong correlation between Solar influences and Temperature…. Why not?

Instead of being scathing of mistakes you could be helpful in exploring other avenues of enquiry…. Considering how no empirical data supports AGW… It remains a Hypothesis based entirely on computer models…

Be less harsh in your criticism and more constructive… After all, as far as you are concerned, you are correct in your own mind…. So why should it be any skin of your nose….?

[Response: Clearly I don't agree with your assessment of Mann's hockey stick. But -- just for the sake of argument -- suppose you're completely right about that and I'm completely wrong. Then, to paraphrase Jeff C., "Okay, I screwed up." How does that compare to Watts & co. who have been wrong about every data analysis I've examined from his blog? How does being wrong about a complex issue involving application of a new and intricate technique, which is still in dispute by many experts and which renowned (perhaps the world's foremost) expert on PCA Jolliffe himself confessed not to understand in sufficient detail to evaluate, compare to repeated blatant and grotesque incompetence?

Answer: it doesn't. Mistakes are inevitable, many issues remain in dispute, but Watts' analytical incompetence is beyond dispute, and in his case mistakes aren't just inevitable, they're the norm. If a physician makes a mistake which leads to the death of a patient, he's likely to be held accountable in a court of law. But if he doesn't know a kidney from a kneecap, and he kills every patient he treats, he's deprived of his license to practice.]
EliRabett // April 2, 2008 at 1:21 pm | Reply

Just eyeballing Watt’s #5 I would have thought that the distribution of points in your update would not have been so evenly distributed. Of course, one of the issues to be avoided is which maxima in the temperature you assign to which in the solar output.

[Response: It's not quite as even as it looks, because three of the black dots represent two data points. Also bear in mind that Watts' #5 contains an error, plotting the maxima assigned to cycle 11 as exactly coincident when in fact that's the cycle for which the disagreement between sunspot and warming-rate maxima is greatest.]
climatewonk // April 2, 2008 at 2:01 pm | Reply

Considering how no empirical data supports AGW… It remains a Hypothesis based entirely on computer models…

Wrong.

AGW is based on theory and observation and computer model projections.

We have a theory of the greenhouse effect in which CO2 acts to trap heat from the sun that would otherwise escape, leading to a warming of the atmosphere, oceans etc.

We have observations of both CO2 increase and warming over the past thirty years in particular but over the period of the instrumental record and paleoclimate research that informs us about past climate. For observation, think Arctic melting, West Antarctic warming, permafrost melting, glacier retreat, temperature increases, sea level rise, changes in habitat and a host of other observational evidence.

We take the two and create computer models that project what might happen given certain increases in CO2.
fred // April 2, 2008 at 2:23 pm | Reply

“I’ll leave it to others to tear you limb from limb.”

No, please do not let us go around doing this. A more constructive suggestion would be that he verify using Excel Tamino’s statement that

two sorted series will always correlate

Try it. Generate two columns of random numbers in Excel, plot them, then sort them, and plot them again. And, everybody, if he comes back with questions, do not sneer. Just answer calmly and factually and constructively.

[Response: I understand the virtue in your approach. But I'm only human, and when someone slings feces at me I have an instinct to respond in the same way as most of my species.

There's also the fact that I get *so much* stuff like this, that it's impossible to keep up with it. Which makes me suspect there's also virtue in another of your suggestions, to be much more ruthless in moderation. That runs the risk, of course, of accusations of censorship, and of the actual fact of censorship.]
Barton Paul Levenson // April 2, 2008 at 2:23 pm | Reply

J. Hansford writes:

Considering how no empirical data supports AGW… It remains a Hypothesis based entirely on computer models…

It is based on radiation physics, and the theory was first published by Svante Arrhenius in 1896, some fifty years before the existence of computer models.
dhogaza // April 2, 2008 at 2:28 pm | Reply

Considering how no empirical data supports AGW… It remains a Hypothesis based entirely on computer models…

When denialists continue to repeatedly make flat-out incorrect statements like this, they have absolutely no reason to complain about scathing rebuttals.
Eli Rabett // April 2, 2008 at 2:34 pm | Reply

You realize that you have just shown Svalgaard is close to right. If the solar insolation difference between max and min is appreciable, there should be a strong forward bias in the Rayleigh chart, once you filter out the dominant greenhouse gas warming.
Lee // April 2, 2008 at 2:49 pm | Reply

fred,

Wrong. He blocked me when I asked him when he is going to get to part three of the histogram series, and reminded him that he had open statements that he had promised to support, and that he had made mild attacks on people for not having teh patience to wait..

Its been a month now.

And then, he went back through the old threads, and systematically removed old comments he had approved and often responded to.

He is blocking me because I was not not letting him get away with ignoring his promises to deal with his embarrassing mistakes. Before he removed the posts, he was on record as sayign, in response to one of my comments, that he was not going to let me mention those old promises. He SAID that, in public, and then removed it along with the response that asked him aobut those old promises.

I’ll give you tone now – he’s a dishonest twit, and his rewriting of the history on his own blog demonstrates that.
Hansen's Bulldog // April 2, 2008 at 3:01 pm | Reply

On a less contentious note:

I stated that after this post I was taking a hiatus from critiquing the analysis of others, and would post about real science. And so I shall. The very next post will be on a topic fred is eager to learn more about: feedback in the climate system.

It’ll take several days to prepare, perhaps even longer with a heavy work schedule, so please be patient.
Hank Roberts // April 2, 2008 at 3:17 pm | Reply

For reference:
http://math.ucr.edu/home/baez/crackpot.html
steven mosher // April 2, 2008 at 3:27 pm | Reply

Lee.

If I published that Paris France was located at 42.5N 72.5W and you pointed out my error, would you expect me to correct it?

If I refused what you you say?

If 4 years later, I repeated this same data error what would you think of me?
J // April 2, 2008 at 3:29 pm | Reply

Thanks, Tamino. I really, really like the update.

For fun, I duplicated your analysis … then repeated it using a simulated data set, where the temperature peaks were forced to be “correlated” with the solar peaks (plus or minus some random fraction of one year, for “noise”).

The difference between the two was obvious, visually. For the fake data, R was about 0.9, versus R for the real data (approx. 0.1).

I’m convinced — if you convert the dates of Anthony & Basil’s smoothed-temperature-first-difference-peaks to phases of the solar cycle, they’re actually close to random.

Insofar as there is anything useful to be learned from this method (filtering, first-differencing, and identifying local maxima in the temperature data) … it seems to show that there isn’t any significant imprint of solar cycles on climate. Logically, Watts should probably admit either that his method or his conclusions are completely wrong, though I won’t hold my breath.

[Response: There are other issues with the analysis as well, particularly the accuracy with which rates of change can be determined by filtering and 1st-differencing.]
steven mosher // April 2, 2008 at 3:35 pm | Reply

HB.

Looking forward to the feedback stuff. Actually what would be nice ( and gentlemanly) would be a comparison of Schwartz and Lucia on lumped parameter models. Lucia has some issues with schwartz, different from yours, and she had some issues with your analysis of schwartz.

Best of all would be a three way discussion between yourself, annan and lucia. Not a war.
I dont think james’ blog gets the attention it deserves, like atmoz.

So. I think a three way discussion between you, lucia and Annan would be a good treat for the math inclined. Not sure how to organize such a discussion/interaction blog wise.

Maybe guest posting. could be more fun than mud wrestling. everyone takes a turn guest posting at the other site. sumthin like that.
J // April 2, 2008 at 3:38 pm | Reply

kim writes: “Hank, comment #365 in the Svalgaard #4 thread has Leif’s answer. He’s agnostic about the question.”

Actually, that’s not quite correct. Leif’s answer to your question is in comment #342: “as this is spurious it is hard to make sense of, but I would say that the longer a cycle is, the more it warms. Here I assume that at solar minimum we get a certain base amount and that within each cycle we get a little bit extra due to solar activity, so the longer the cycle the more extra we get. But this is just hand waving, there are people that say we get cooling, warming, nothing, whatever. We are past logic here.”

I agree. The claimed correlations are spurious, hard to make sense of, and mostly just hand-waving. The people who obsessively try to pin down relatively minor connections between solar cycles and climate are “past logic here”.
kim // April 2, 2008 at 4:07 pm | Reply

J, different questions. The answer in #365 is about sparsity of sunspots at climate minima.

But, back to the other question. Aren’t longer solar cycles weaker? Leif dodged that one, hiding behind his agnosticism.

There is too much evidence linking the sun’s output to climate changes. There is too little evidence of the causative mechanism.
=================================
JCH // April 2, 2008 at 5:14 pm | Reply

“If 4 years later, I repeated this same data error what would you think of me? …” – SM

Is the mistaken location of Paris mentioned in both abstracts?
Hank Roberts // April 2, 2008 at 5:20 pm | Reply

Yep. See the thread there for that discussion, it’s off topic here.
Search that thread for “astrology” …
Barton Paul Levenson // April 2, 2008 at 5:32 pm | Reply

I don’t think some folks understand why what Watts and Copeland did is wrong. Let me give an example using non-climate data.

Here are the inflation rate (GDP deflator) and money growth rate (new M2) for the 1970s:

YeardPdM
19705.296.57
19715.0013.38
19724.3412.95
19735.586.63
19749.035.45
19759.4312.65
19765.7813.36
19776.3510.27
19787.037.53
19798.297.88

If you take a Pearson’s product-moment correlation coefficient between the two columns of data, you get r = 0.2978. Since variance accounted for goes as the square of r, we can say 9% of the variance of inflation was accounted for by changes in the money supply.

Now, here is the same table sorted in ascending order by dP — from the smallest value of dP to the largest:

YeardPdM
19724.3412.95
19715.0013.38
19705.296.57
19735.586.63
19765.7813.36
19776.3510.27
19787.037.53
19798.297.88
19749.035.45
19759.4312.65

The order of the points doesn’t matter. The correlation is still r = 0.2978.

But now, let’s say you sort dP from smallest to largest, AND sort dM from smallest to largest, independently — matching the lowest dP with the lowest dM, the second-lowest dP to the second-lowest dM, etc. Here’s the data, with the years sorted along with dP but dM sorted independently:

YeardPdM
19724.345.45
19715.006.57
19705.296.63
19735.587.53
19765.787.88
19776.3510.27
19787.0312.65
19798.2912.95
19749.0313.36
19759.4313.38

Now, if you figure the correlation, r = 0.9501, and 90% of variance is accounted for rather than 9%. An astoundingly high correlation!

Except that it isn’t. By sorting the columns independently, you’ve decoupled all the points! The smallest dP occured in 1972, but the smallest dM occured in 1974! It’s no longer a fair comparison because you’re not comparing like with like any more. You’ve spuriously enhanced the fit by pre-matching the orders of the points. In statistical science you’re simply not allowed to do this. It’s bad, it’s wrong, it’s incorrect, and most importantly, it’s meaningless. That’s what Watts and Copeland did in their solar article.
luminous beauty // April 2, 2008 at 5:34 pm | Reply

“If 4 years later, I repeated this same data error what would you think of me?

If this ‘data error’ is nothing more than an insignificant typo, I would suspect you might be repeating it just to tick me off.

I’d let it go. Why can’t you?
Barton Paul Levenson // April 2, 2008 at 5:39 pm | Reply

Well, that looked awful. Apparently this blog doesn’t take HTML tables, though it does take many other HTML tags. Here are tables 1, 2 and 3 again:

Year   dP   dM
1970   5.29   6.57
1971   5.00   13.38
1972   4.34   12.95
1973   5.58   6.63
1974   9.03   5.45
1975   9.43   12.65
1976   5.78   13.36
1977   6.35   10.27
1978   7.03   7.53
1979   8.29   7.88

Year   dP   dM
1972   4.34   12.95
1971   5.00   13.38
1970   5.29   6.57
1973   5.58   6.63
1976   5.78   13.36
1977   6.35   10.27
1978   7.03   7.53
1979   8.29   7.88
1974   9.03   5.45
1975   9.43   12.65

Year   dP   dM
1972   4.34   5.45
1971   5.00   6.57
1970   5.29   6.63
1973   5.58   7.53
1976   5.78   7.88
1977   6.35   10.27
1978   7.03   12.65
1979   8.29   12.95
1974   9.03   13.36
1975   9.43   13.38
Hansen's Bulldog // April 2, 2008 at 6:03 pm | Reply

I received a very conciliatory email from Anthony Watts — an olive branch, if you will. It argues well for his character, especially considering the scathing criticism I’ve had for his posts.

So I urge everyone to set passions aside, and for the time being confine discussion to the facts, dispassionately.

Tamino, aka Hansen’s Bulldog
climatewonk // April 2, 2008 at 6:43 pm | Reply

So I urge everyone to set passions aside, and for the time being confine discussion to the facts, dispassionately.

Civility and generosity should be employed in debates, however, where warranted. Sometimes, civility is not warranted and generosity dangerous. I am willing to give Watts the benefit of the doubt if he is willing to amend his post to show that he has made some critical errors in analysis. Otherwise his erroneous analysis will be incorporated into the denialist database of “evidence” against AGHG as a cause of warming and for solar causes of warming.

If he made an honest mistake and the analysis is flawed, he should just come right out and state as much. He should revise his post and acknowledge that his initial findings were premature. He owes it to his readers.

If he is not willing to do so, he should expect critics to be merciless and if that is deemed unacceptable to him and his supporters, he should just give up engaging in public analysis that is apparently beyond his skills .

[Response: I agree with you. But overtures of peace are rare and should be treasured, so please let's set this discussion aside for now. If Watts fails to address important issues to your (or anyone's) satisfaction, there'll be plenty of time to criticize him for that -- but at least let's wait until we find out.]
Brian D // April 2, 2008 at 7:08 pm | Reply

Setting aside passions, I should mention that a private “olive branch” (which I sincerely believe he sent) that is kept secret, while leaving the offending analysis public, serves no purpose except to placate those most critical of it while still spreading disinformation.

Watts needs to make his apology public and correct the mistake before I’d be willing to accept his apology as sincere and restore some of his credibility — but then again, I’m just a commenter on a different blog.

Still, out of respect for our host, I’ll silence my criticism for now, giving Watts time to make the necessary move.

[Response: I would think the opposite: that a public olive branch (say, a comment here) might just be a show for readers, while a private one (which Watts could not have expected me to mention) indicates sincerity.]
nanny_govt_sucks // April 2, 2008 at 7:14 pm | Reply

So I urge everyone to set passions aside, and for the time being confine discussion to the facts, dispassionately.

Who are you, and what have you done with Tamino?

I wonder if you can run some of your sunspot cycle correlations with some of the other known sunspot cycles, including looking at odd and even 11 year cycles vs temperature. This seems to be where some of the Watts/Basil analysis is going.
steven mosher // April 2, 2008 at 8:18 pm | Reply

JCH. is the mistake in the abstracts? Weird question. funny distinction.

But anyway, no the mistake I ask you consider and render an honest opinion about is a mistake in the data used by the study published in the SI.
If Fred Singer published a paper and supplied data supporting his study. AND IF that data showed he thought paris france was located at 42.5N 72.5W, AND IF he were notified of this error, and IF he repeated this same error 4 years later, what would your opinion of Fred Singer be?

What if Tamino made such an error? I suspect he would fix it. What if Anythony Watts made such an error? would he correct it? if he didnt what would you say? What if you made such an error?

Hansen made an error in GISTEMP. Others found it, he fixed it. And he wrote it up.
Here is my error. Here is my fix. here is the impact. It’s simple. we all respect that and the issues goes away, eventually. It would have been nice to credit the people who found the error, but never mind. thats manners not truth.

So. simple question. no one wants to answer.

If I told you that people were evacuating their homeland due to global warming, and that was not true. Would you expect me to correct that mistake? And if I wouldnt, what would you think of me?

Pardon me, I have to duck some sniper fire here in Bosnia.
L Miller // April 2, 2008 at 8:19 pm | Reply

I don’t think some folks understand why what Watts and Copeland did is wrong.

I think it’s the fact that there is no clear “sorting” step in his analysis that is confusing people. His final result is basically identical to a sorted random series, he just doesn’t get there using a sort.

Another way you can look at it is that he is comparing a series against itself, and adding a small random variation to one of the terms. Since there are a couple leftover peaks it’s pretty easy to choose the ones that line up with what he wants to see and any temperature change peak can’t be more then a few years from a sunspot peak. This will be a basically random but ultimately small distance from the solar cycle peak assigned to it.

I.E. say x(1), x(2), … are random number between -5 and 5 then he is plotting:
Year Vs Solar Cycle
And
Year + x(n) vs Solar cycle

Which is really no different then comparing a series to itself as far as R^2 correlation is concerned. That’s a little simplified because the range for x won’t necessarily be exactly the same each time.
L Miller // April 2, 2008 at 8:22 pm | Reply

bah. I didn’t close the blockquote tag properly

[Response: Fixed]
cohenite // April 3, 2008 at 1:47 am | Reply

Before you dismiss the link between Schwabe and Hale solar cycles and global temperature fluctuations completely, may I suggest a peak at this paper which seems to address your complaint about Watt’s susceptibility to randomness:
http://www.fel.duke.edu/~scafetta/pdf/opinion0308.pdf

[Response: Please pay better attention. I did not dismiss the link between solar cycles and global temperature changes, I refuted the analysis of Watts and Copeland. In fact, as I already said quite unambiguously in response to another comment, I'd be surprised if there's *no* connection, but the failure of so many legitimate analyses to establish it argues for its very low level, and I have doubts about even the most plausible detection (due to Camp & Tung).

And as I said before, when someone linked to the exact same opinion piece on another thread, there are serious problems with the work of Scafetta & West, many of which have been addressed on RealClimate (see also the links within that link). Even in the opinion piece you link to their graph already indicates problems, particularly the phrase "smoothed to stress the 11-year modulation."

It's no surprise tha blog posts are vulnerable to substandard data analysis. But what most non-scientists are not aware of, is the journal publications are too. The quality of work is certainly a lot better than blogs, but it still amazes me what sometimes makes it past peer review into the literature.]
Dano // April 3, 2008 at 2:28 am | Reply

kim // April 2, 2008 at 12:04 am

There is meaning there. What is it?

The kim bot sows the D portion of FUD. It doesn’t work here. At wingnut sites, surely. Redstate, definitely.

kim bot programmer: new search algorithm and response parameters please! This routine grew stale and tedious about 1999.

Best,

D
EliRabett // April 3, 2008 at 2:45 am | Reply

Nanny, I don’t think this sort of analysis is good for what you want. Better some sort of Fourier transform to see if there are significant 11 year/22/60 year cycles in the global temperature and the 60 only would allow for ~3 cycles in the instrumental record, in other words, chancy to dig out.

Another thing to try would be to look at the temperature north of 60 degrees latitude where the swings might be larger.
fred // April 3, 2008 at 7:53 am | Reply

Looking forward to the feedback discussion. This is really the central part of the question. If you have space, it would be nice to have some consideration of Spencer’s remarks about sampling and correlation and causation.
Adam // April 3, 2008 at 9:43 am | Reply

This is vaguely related so I’ve posted it here:
http://news.bbc.co.uk/1/hi/sci/tech/7327393.stm

See “related links” on the RHS for more information.
steven mosher // April 3, 2008 at 12:45 pm | Reply

luminous, if it were an insignificant typo, you’d thank me, fix it and not repeat the error.

what if I got all the locations in my data set wrong?
climatewonk // April 3, 2008 at 1:49 pm | Reply

Steven Mosher, can you explain the repeated references to coordinates and Paris? I do not know the background to this and it appears to me to be nothing more than rude behavior on your part to keep repeating it.
fred // April 3, 2008 at 2:28 pm | Reply

climatewonk

Mosher is referring to the fact that in one of his datasets, Mann made an error about the location of Paris. A couple other places too if I recall correctly. It was probably a typo, a line feed in the wrong place or something. Obviously he knows where Paris is. I don’t recall anyone saying it made any material difference to the results. Mosher is saying that not only did he do it once, he continued to use the same erroneous data set after it was pointed out, which was a little silly.

This is what the remarks are about. They are not very pertinent to the present discussion, but perhaps Mosher is arguing that standards should be applied to Mann if they are to be applied to Watts. Probably so, but it doesn’t make the Watts charts any more correct.
luminous beauty // April 3, 2008 at 2:47 pm | Reply

mosh,

“luminous, if it were an insignificant typo, you’d thank me, fix it and not repeat the error.”

If you were a persistent jackass, ranting excessively about meaningless gobbledygook, I would ignore you, and not make an insignificant correction, just to point out that I am ignoring you.
steven mosher // April 3, 2008 at 4:55 pm | Reply

Thanks Fred.

The point is this. We all make mistakes. I made one about what Tamino wrote. I corrected it.
Tamino made one about what lucia wrote. He corrected it. Lucia made a an error about log versus ln She corrected it. Christy and Spencer made and error. they corrected it. GISS made a mistake in GISS temp. They fixed it. Hadcru made a mistake. They fixed it. And the theory of AGW still stands as the best explanation of the warming we see. And now I see people asking AW and Basil to correct what tamino documents as an error. Fair enough.

Then we have this:

Mann not only got Paris wrong, he got EVERY location wrong ( except one) . It was pointed out in 2003, and in 2007 he published another paper using the same mistaken locations. Now,
it’s a simple matter for everyone to say. “He made a mistake, AGW is still the best explanation. ” But nobody, seems able to say that.

I find that odd. I find it odd and noteworthy that you cant even get some people to say simply
” ya Gore made mistakes in AIT” there is always a caveat, always a disclaimer, always a shading..
“err he got the tense of verb wrong ” that was a precious one from RC.

It’s odd.

For the record. I was wrong to compare the hockey stick to the Piltdown man.
Ken // April 3, 2008 at 5:51 pm | Reply

HB, sadly I don’t make it to your site daily. When I do, it seems like I’ve already missed out on all the discussion. But I wanted to commend you for these 3 excellent posts, nonetheless. This whole series reminds me of the quote:

“A little knowledge is a dangerous thing”

While I commend anyone that enjoys working with data, making plots, and trying to understand phenomena, I must say that Watts and his blog are an example of the Dunning-Kruger effect.
Mike B // April 3, 2008 at 6:19 pm | Reply

It’s not just “a little knowledge is a dangerous thing” although that is certainly part of it. It begins with the fact that they KNOW something other than CO2 must be causing the current warming and therefore their results no matter how contorted and in many cases ridiculous in nature, show that something else is the culprit.
climatewonk // April 3, 2008 at 6:39 pm | Reply

Mann not only got Paris wrong, he got EVERY location wrong ( except one) . It was pointed out in 2003, and in 2007 he published another paper using the same mistaken locations. Now, it’s a simple matter for everyone to say. “He made a mistake, AGW is still the best explanation. ” But nobody, seems able to say that.

Ahh, this is the case of the transposition of one line of data that occurred and led to some strange results and interesting speculation, IIRC. It made no difference to the ultimate conclusions, I seem to remember.

I wonder why you keep bringing this up except to flog a favorite dead horse? It has no bearing on whether Watts’ analysis is valid or mistaken and appears rather juvenile.
Boris // April 3, 2008 at 6:44 pm | Reply

what if I got all the locations in my data set wrong?

Getting one location wrong seems kind of minor to me. I don’t know exactly what your “gotcha” point is here, mosh. I’d probably, say, “boy, that’s dumb.” and move on.

It’s not like someone is going around the internet using this mistake to argue that Paris is where it is not, right? Not the way the words of Fred Singer, Patrick Michaels, Tim Ball and Roy Spencer are used to support similar misconceptions, right?
Hank Roberts // April 3, 2008 at 6:53 pm | Reply

> It was pointed out in 2003, and in 2007
Which journal? Was the criticism published as a letter, comment, or correction in the same science journal? If not was it submitted to the journal?

What’s important is whether there’s a difference in the result section. This isn’t religion where a minor flaw in something attributed to a founder can topple all subsequent work.
TCO // April 4, 2008 at 1:51 am | Reply

Agreed. All the more reasons for people on either side to ALWAYS concede true points…because they’re TRUE.
climatewonk // April 4, 2008 at 1:31 pm | Reply

TCO, it would be important to always concede true points if this was just another academic debate over methodology or data selection or interpretation of results, etc. It’s not. It’s now a huge political issue.

Politics is war carried on with other means.

This has become a war, in other words, and as such, it’s now become a question of strategy and tactics rather than a quaint scholarly debate. Giving aid and comfort to the enemy and all that. Treason.

And frankly, after reading all the endless flogging of the “hockey stick is broken” meme by the “skeptics”, torture. :)

It shouldn’t be a war. It became one when those with vested interests in the outcome, aka fossil fuel interests, started politiczing it in order to influence the public and policy.

[Response: This particular discussion belongs on the open thread.]
climatewonk // April 4, 2008 at 1:52 pm | Reply

I want to add that I think scientists should strive to keep out of the politics as much as is possible. Leave the “battles” to the rest of us because we need your best work to help make the best decisions.
TCO // April 5, 2008 at 4:49 pm | Reply

It looks like I am banned from comments. This despite basil addressing a post to me.
TCO // April 5, 2008 at 4:49 pm | Reply

I mean banned from Watts Up blog.
Lee // April 5, 2008 at 5:36 pm | Reply

So ti seems I’m still blocked over at WattsUp. I’ll note here – Anthony Watts has still not retracted or corrected his figure 5, it is still in the original post with no correctin or addition, and only if yo read well down int o the comments do you see Anthony acknowledge a problem with Figure 5. He seems to be ignoring this, hoping it will go away.

[Response: I haven't seen any acknowledgement that it's mistaken, the closest I've seen is "we need to do a better job."]
TCO // April 5, 2008 at 6:55 pm | Reply

He’s a simpleton crackpot. A disgrace to the name of good skeptics. And SM is a slippery snake. Who wiggles like a girl who needs to go when he gets pinned down on a point.
steven mosher // April 6, 2008 at 1:08 pm | Reply

climatewonk,

yes I think we are talking about the same mistake. Lets stipulate that it was immaterial. Let’s stipulate that it says nothing about the truth of AGW. that makes it all the MORE ODD, that the correction was not made or acknowledged and all the more odd that no one can say the simple words. he made a mistake. fix it. thank the guy who found it, move on.

Thanks TCO
TCO // April 6, 2008 at 7:02 pm | Reply

Mosh:

Agreed. This whole lawyerly thing that I find both SM and MM doing is a drag. Concede valid points. If you think the opponent will twist it or use it for something else, then deal with that (and when it happens). But CONCEDE valid points. Otherwise, there’s no way to have a math discussion.

Oh and above, I mean the other SM (not you).
TCO // April 6, 2008 at 10:22 pm | Reply

my post got through on watts up. guess i was wrong.
steven mosher // April 7, 2008 at 12:09 am | Reply

TCO,

Yes lawyerly is the frame I would put it in. It’s like people see it as a court of law ” false in one, false in all!” rather than just fixing the problem and moving on.

Ah hell, look how long it took me to say I was wrong about the piltdown thing, i should talk.
How’s them bloody marys?
Hansen's Bulldog // April 7, 2008 at 12:43 am | Reply

I posted this nearly a week ago. Watts and Copeland both noted my analysis, Watts conceding that “we need to do a better job with figure 5″ and Copeland stating that “I’ll look into the data plotted in Figure 5, and if there’s an error, we’ll correct it.”

But there’s been no admission of error, the closest they’ve come is “we need to do a better job.” There’s been no correction. The post still stands, unchanged, including their figure 5 unchanged which not only illustrates one of the most foolish analyses I’ve seen on Watts’ site (which is saying a lot), it also has a data point plotted wrong so that it shows exact agreement with their thesis, when in fact it’s the cycle with the strongest disagreement. Of the five bogus analyses about which I’ve posted, none has been corrected, none disavowed.

Watts has yet to admit that any of them are in error; I have yet to see an analysis on Watts’ blog which is not in error.

Anthony Watts: shame on you.
steven mosher // April 7, 2008 at 1:16 pm | Reply

I found this

UPDATE: We have had about half a dozen people replicate from HadCRUT data the signal shown in figure 4 using FFT and traditional filters, and we thank everyone for doing that. We are currently working on a new approach to the correlations shown in figure 5, which can yield different results using alternate statistical methods. A central issue is how to correctly identify the peak of the solar cycle, and we are looking at that more closely. As it stands now, while the Hodrick-Prescott filtering works well and those results in figures 2,3, and 4 have been replicated by others, but the correlation shown in figure 5 is in question when a Rayleigh method is applied, and thus figure 5 is likely incorrect since it does not hold up under that and other statistical tests. There is also an error in the data point for cycle 11. I thank Tamino for pointing these issues out to us.
We are continuing to look at different methods of demonstrating a correlation. Please watch for future posts on the subject.

[Response: Yesterday, when I posted this, the admission that figure 5 is "likely incorrect" wasn't there -- I archived a copy of his page. Of course it's not just "likely" incorrect, it's certainly incorrect. And replicating the results using other filters doesn't mean anything; it's still the same signal and the same *noise* so the result is still not precise enough even to do their analysis.

I think an admission of "likely incorrect" is the best I can hope for.]
Hank Roberts // April 7, 2008 at 3:14 pm | Reply

And an explicit statement:

> We are continuing to look at
> different methods of demonstrating
> a correlation

Perhaps a topic about falsification and its uses in science is needed?

Watts thinks this is religion or math, and is looking to present a proof, eh?
Rainman // April 7, 2008 at 7:15 pm | Reply

I’m someone who believes the climate is changing, but is uncertain as to ALL the causes.

CO2 is thrown around as the undoer of mankind, and we do need to get a handle on what we do with it. However, it would seem CO2 can’t be the sole source of our climate changes.

I recognize the difficulty in achieving true understanding of the climate all of it’s interactions, but it seems that large numbers of individuals on both sides are unwilling to even acknowledge the possibility of ‘other’ factors.

Thus far, I’ve not seen or heard of a single model that can reproduce the temperature patterns of the past 2000 years (at least as we understand them).

We also don’t have a model that can tell us when/why the ice ages occur, or when the next one will start. (It would seem likely to start in around 3000 years given past interglacial averages.)

Hank Roberts mentions religion, and I think that’s what a lot of this has become. Differing ideologies unwilling to give or concede the possibilities that lay outside their perspective dogma. Just because a presentation has issues (large or small) doesn’t mean the idea is without merit.

Let’s get back to science, leave the bashing to politicians.

[Response: Climate scientists acknowledge, and account for, a large number of influences on climate -- including solar changes, orbital variations, volcanic eruptions, albedo change, ozone, anthropogenic aerosols, and yes greenhouse gases too. I myself, in this post argue for the extremely high likelihood of a solar cycle influence, but we just haven't pinned down its size yet, in this post I discuss some of the other influences on climate which lead to feedbacks in the climate system, and this post is all about emphasizing that there are many influences on climate even over the last few decades. The temperature pattern of the last 1,000 years is reasonably well modelled in Crowley 2000, Science, 289, 270, and that's probably been superseded (both in reliability and length of time) since then. We know quite a lot about the causes and timing of glaciations and deglaciations, and although our understanding is far from perfect, it's even further from the abysmal ignorance suggested by your comment.

It seems to me that your objections are rooted in ignorance and misunderstanding of the state of climate science. Perhaps you should leave science to the scientists.]
Rainman // April 7, 2008 at 9:06 pm | Reply

Was I objecting, or was I looking for everyone to keep an open mind and be constructive?

Climate change affects us all, and I would much rather all the possibilities be thoroughly considered and tested. Jumping to conclusions based on incomplete data or a flawed analysis is something that happens far too often. We don’t need a knee-jerk reaction to this problem.

I have read your most recent post on solar influence and appreciate the openness to it (and your responses in the comments).

In reading community responses in this thread, most of your readers are dismissive to the point of rudeness (data 3).

Now, your own conclusion about me is true. My knowledge and understanding of the current state of climate science is incomplete. This is why I’m educating myself by reading the various blogs to see what is being done/theorized/etc. Is it inappropriate to want to know more?

I’ll not say I’m a scientist in another field, but I could have been. If that had been the case I would find your last statement quite insulting. As it is, I still find it insulting.

[Response: Perhaps you didn't mean to imply that climate science is poorly understood and deeply flawed, but that's the distinct impression from your previous comment. In this comment you warn against "Jumping to conclusions based on incomplete data or a flawed analysis," which pretty clearly implies you think that's the state of climate science. And you directly indicated that climate scientists fail to consider factors other that CO2, which is patently false. I find *that* insulting.

If that's your opinion of blog readers but not climate scientists, then say so. If that's your opinion of climate scientists, then I think you're completely mistaken.]
Rainman // April 7, 2008 at 10:33 pm | Reply

I may have been infected by the vitriol that seems to pervade the internet…

With regards to climate scientists, no insult was intended. Thing is, the layman only hears about CO2, therefore it would appear that is the only ‘real’ consideration.

I see climate science as still being in it’s infancy. There is such complexity… The closest metaphore I can come up with is biological. We know more about human physiology than the climate, but we don’t know all of it. Attempting to diagnose and fix a problem is tricky. You run tests and hope those tests give you a diagnosis and course of action. The diagnosis can be erroneous, or just be part of the onion…

My view may not give credit where it is due. That is not meant to be insulting, it is meant to convey an appreciation of situation at hand.
David B. Benson // April 7, 2008 at 10:54 pm | Reply

Rainman // April 7, 2008 at 9:06 pm — Understanding the climate can be quite daunting. It certainly helps to first acquire a background in the subject of climatology. Here are two suggested starting links

http://www.realclimate.org/index.php/archives/2007/05/start-here/

http://www.aip.org/history/climate/index.html

and I also encourage early reading of W.F. Ruddiman’s excellent “Earth’s Climate: Past and Future”.
TCO // April 7, 2008 at 11:19 pm | Reply

I echo Rainman.
Hank Roberts // April 7, 2008 at 11:36 pm | Reply

> I’m educating myself by reading the
> various blogs

Chuckle. No wonder. Starting with the links David provides will be far more like education.
steven mosher // April 8, 2008 at 12:52 pm | Reply

well speaking of errors here’s one that james annan
found. note how the authors responded

http://groups.google.com/group/sci.geo.oceanography/browse_thread/thread/a59a3509ecef9344/34d38d81f1734eaf?#34d38d81f1734eaf
Adam // April 8, 2008 at 2:28 pm | Reply

I would also recommend reading “Global Warming, Understanding The Forecast” by David Archer.
chriscolose // April 8, 2008 at 4:52 pm | Reply

tamino, I apologize, a bit off topic…

I was wondering if you could tell me how to adjust GISS and Hadley temperature data on excel to a similar baseline (i.e., say I wanted to move HadCRUT over to a 1951-80 reference period) so that I could plot them. I know you did a post on this, bu I’d like to know how you bring them together.

Thanks

[Response: First, compute the average value for each data set during your chosen baseline time frame. Be sure the chosen baseline time frame is the same for both data sets, and it's a good idea if it's at least 30 years long.

Then subtract the baseline-average value from each data set. You can check for correctness by making sure that after the subtraction, both datasets have average value zero during the chosen baseline.]
chriscolose // April 8, 2008 at 5:06 pm | Reply

Thanks…I take it I’ll need absolute values for HadCRUT if I am to find the average over the new baseline? If so, where I can I find those, the data sites generally just give anomalies? Sorry, I’m not good at this.

[Response: No, you just need the anomalies.]
steven mosher // April 9, 2008 at 2:15 am | Reply

Chrisclose,

tamino is right you just need the anomalies, but Hadcrut and Noaa ( maybe GISS now) ALSO supply the absolute figures . Its a little HARD to find, and a bit annoying, but U can find them.
steven mosher // April 9, 2008 at 12:47 pm | Reply

here tamino.

Last week, when Basil and I posted Part 2 of our series on seeing a solar imprint in the HadCRUT temperature record, it spawned a lot of interest, debate, replication, and criticisms. One of the criticisms from Tamino surrounding the concluding results presented in figure 5 showed how using a different statistical test nullified the results. Thats good, falsification of results by alternate methods is what science is about, and we are now reworking our approach using some different data and methods to see if we can create a robust conclusion that stands up to many different statistical tests.
Lee // April 9, 2008 at 2:17 pm | Reply

mosher,
Translation: we’re still hunting desperately for a statistical method that gives us the result we want, but in the meantime we’ll keep pushing the pattern that was shown not to mean what we’re claiming it means.

And not even in the post where he made the error. Watts has not altered his post where he claims correlation with the sunspot cycle Figure 5 in that post is unaltered, and has not been withdrawn. And note Watts wording here – that was ‘nullified.’ No hint that his original correlation was simply wrong. And he does not allow comments criticizing his work.
luminous beauty // April 9, 2008 at 2:50 pm | Reply

mosh,

You might want to look at Frölich and Lockwood 2007

It might not give the conclusion you are looking for, but, robust, it is.

[Response: I posted about that paper here, and about the response to it by Svensmark and Friis-Christensen here.]
Mike B // April 9, 2008 at 2:51 pm | Reply

Sure Steven, but I think the telling sign is at the end of Watt’s update on the post:

We are continuing to look at different methods of demonstrating a correlation. Please watch for future posts on the subject.

That doesn’t sound very scientific to me, he is assuming there is a correlation and if this try didn’t find it then he’ll try to find another method that will.

Maybe, just maybe, there ISN’T a significant correlation between the solar cycle and the recent warming.
Hank Roberts // April 9, 2008 at 3:20 pm | Reply

Does the phrase “must be a pony here someplace” come to mind?
Rainman // April 9, 2008 at 3:46 pm | Reply

Lee:

I saw some of your posts on Watts’ site before the ’scrubbing’. My posts here about not bashing are partially about you posting there and some posters here. Constructive arguments seem to be welcome, bashing not.

He has a job/life, and running his site along with responding to posts and doing more work in the areas he believes need to be explored will preclude some avenues… (addressing your concerns were a victim of time constraints and your tone it would appear)

As to him continuing on the path of validating his hypothesis… why not? Just because your initial proof has holes in it doesn’t mean the idea is wrong. As long as we have people willing to explore alternate theories, we won’t stagnate. Science is about looking outside the box. Who would have thought quantum theory would prove out 50 years ago?

Let them explore, somebody has to.

[Response: Your timeline is off; 50 years ago quantum theory was a well-established fact.]
Rainman // April 9, 2008 at 4:03 pm | Reply

My apologies on the timeline, it was a WAG as to when it was proposed…

The point was some serious out of the box thinking came up with it, then that person(s) had to run a gauntlet of proofs to become accepted.
Hank Roberts // April 9, 2008 at 4:18 pm | Reply

> validating his hypothesis

You’ve got science backwards. Science works by finding ways to disprove, not validate.

This is a common “alternative” notion. I recall J. Baldwin of the old Whole Earth Catalog pronounced “newage” to rhyme with “sewage.”
pough // April 9, 2008 at 4:23 pm | Reply

I see climate science as still being in it’s infancy.

“Hello, experts, I just want to let you know that – based on only a tiny amount of information – I feel like I can judge your field of expertise and I judge it to be lacking, so you should shut up until I’m satisfied that you know what you’re doing. Thank you and best wishes.”
L Miller // April 9, 2008 at 5:36 pm | Reply

That doesn’t sound very scientific to me, he is assuming there is a correlation and if this try didn’t find it then he’ll try to find another method that will.

They should work out how much more energy the earth receives in the high half and low half of the solar cycle and see how much effect it would have on temperature. (How much would it warm the top 100m of the ocean, since that is where most of the heat will go) This would give them a rough idea of the +/- swing in temperatures you could expect over a sunspot cycle. If it were below the range of weather noise (which I suspect it is) it’s going to be pretty hard to find a clear solar cycle signal.
Rainman // April 9, 2008 at 6:19 pm | Reply

pough:

While my statement is not meant to convey the words you have attributed, I can see that view being taken.

My view is due to there being a new paper on the effects of one variable or another just about every other day.

At some point, there will be one climate model that accepts input and can reproduce the appropriate climate for a given timespan (with the ability to add in spike events like volcanic eruption, large fire or even meteor strikes).

Technically, we have such a model… we live on it. But computing capability is getting to the point where we should be able to model all the inputs/outputs/feedbacks and be able to reproduce what has happened.

But back at you… do you consider climate science to be mature? Adolescence? Perfected?
Why?
P. Lewis // April 9, 2008 at 6:55 pm | Reply

Rainman said

But back at you… do you consider climate science to be mature? Adolescence? Perfected?
Why?

I hope this is not the beginning of a descent into sophistry. It could very well be.

But why ask pough those questions, or me or most people here?

Why not ask a climate scientist for an answer on Real Climate, for example, or even RP Snr?

FWIW, I daresay climate science is as mature as any other science that’s been going for 100 years or more. Wouldn’t you?

If not, why not?

Science at the coal face is always in its infancy. Science away from the coal face is mature. And science away from the coal face is always ripe for a fresh look. And science at the coal face is always immature and ripe for going down blind alleys. That’s science in a nutshell, whatever the subject.
pough // April 9, 2008 at 7:06 pm | Reply

I’d say in the 50s and 60s it was in its infancy. In the 70s and 80s it was getting pubes. Now’s it’s rather nubile and old enough to pose nude.

No, I don’t know. It’s not my place to judge, especially not on the blog of someone who is in a far better position than me to make a call. HB? Care to give an approximate age of climate science?

My view is due to there being a new paper on the effects of one variable or another just about every other day.

Maybe pay attention to the other sciences and you’ll see the same thing.

At some point, there will be one climate model that accepts input and can reproduce the appropriate climate for a given timespan…

I doubt that. I get the impression that’s not really how things work. As much as science uses math, it doesn’t have the same absolutes, as far as I can tell. But I, too, am no expert, so it doesn’t really matter what I think.

As for perfected… that’s just silly. Is biology perfected? Physics? Chemistry? Geology? I think of science as being like a relationship. You can never perfectly know another person, but you can continually get closer and your lack of initial knowledge is in no way a sign that you know nothing and should give up. That’s the impression I get from some people about climate science: it should either be perfect or it’s fatally flawed.

[Response: I'd say climate science is reasonably mature. The basic physical processes are very well known: thermodynamics, hydrodynamics, and atmospheric chemistry. The overall behavior of planetary atmospheres is sufficiently well understood for us to have at least a handle on the climate of other planets. And we're modelling earth's climate in sufficient detail to make quantitative projections, some good some more uncertain. I guess I'd say "young adult."]
Hank Roberts // April 9, 2008 at 7:10 pm | Reply

> computing capability is getting to the
> point where we should be able to model
> all the inputs/outputs/feedbacks and be
> able to reproduce what has happened.

What basis do you have for this belief?
Why do you trust your source for this?
Do you realize it’s a cartoon?
http://imgs.xkcd.com/comics/morning.png
Rainman // April 9, 2008 at 8:39 pm | Reply

P. Lewis:

At the end of the post he was ‘fixing’, I acknowledged credit may not have been given where due. That means he didn’t give me credit where due. I was stating my view with the caveat I could be wrong, he twisted it to an absolute.

As to the ‘coal face’, that is a perspective I had forgotten to consider. Thanks for the reminder.

pough:

Thank you for responding. I do believe what I think matters. We are all in this together, and if something needs to be fixed, we all need to be on board to fix it. Something this important and impacting can’t be decided by a ’select few’ and pushed on the masses.

Belief by the public in climate science is suffering due to perceived ‘failures’. The media isn’t helping either… The over reporting of any GW issue is just reducing the signifigant events to noise. While the collapse of the ice shelf last week is an event, doubt/panic/? is introduced when it is mentioned it collapsed in half the time projected prior, and the atypical cold snap this year in North America/Asia. So people (myself included) wonder just how much climatologists really know.

Tamino:
Thanks for your perception of things. Do you see climate science merging with bioscience (assuming it hasn’t already) to form biosphere science? Life appears to have it’s affects on the climate (plants-> co2) and would need to be taken into account in the climate models. Like the difference in albedo from a plains area compared to conifer forest or broadleaf forest…

Hank Roberts:
Amusing, but no. My belief stems from an article I read a few years back about one of the major labs (I think it was JPL) was in the process of constructing a clustered super computer to model fission reactions in real time. I know from my time in the Naval Nuclear Power Program that is no small feat.

Can we model every molecule/interaction? No. Can we macro model the interactions? Yes. The trick is getting all the inputs/feedbacks set right.

I’ve been thinking of writing up a model (but don’t have a chance of getting it close to right at this stage) that divided up the globe based on lat/long squares or a hex system. Each square would have various objects that would represent different sections of that ‘pie piece’. Troposphere, stratosphere, albedo of the terrain/ocean underneath, wind pattern effects from terrain and the albedo, ocean currents, etc… I figure each pie piece could be subdivided as the model gains precision (and computing power is available, I only have a single dual core system right now).

This seems a lot like a weather predictor, and I keep hearing weather and climate are not the same, but the climate does drive weather. So if we can model the climate, weather should follow.

Out of curiousity, has a model like this been attempted or been developed already?
Hank Roberts // April 9, 2008 at 10:50 pm | Reply

How many variables in one single fission system being modeled? How many in climate?

So far so good (not realtime, of course):
http://tamino.wordpress.com/2008/04/02/open-thread-4/#comment-16766
TCO // April 9, 2008 at 11:44 pm | Reply

HR:

Short answer: I don’t know.

Long answer: I think there are a lot of interesting analogies of reactor performance and climate systems ( I said it before, I said it before). There may be lessons to learn from RD for CS. In RD, you have issues with different time scales, etc. The physics itself is well known but it gets more complicated when you look at the actual geometries, effects over core life, performance during transients, etc. (Philosophy: It is not unusual for different fields to have insights for each other.)
steven mosher // April 10, 2008 at 12:48 pm | Reply

teleconnections.
TCO // April 22, 2008 at 11:14 pm | Reply

xenon

	Timothy Chase on Breaking Records
	Timothy Chase on Breaking Records
	jyyh on Vapor Lock
	Hank Roberts on Vapor Lock
	Hank Roberts on Vapor Lock
	Hank Roberts on Vapor Lock
	Timothy Chase on Vapor Lock
	Ian Forrester on Vapor Lock
	Ray Ladbury on Vapor Lock
	suricat on Vapor Lock
	suricat on Vapor Lock
	David B. Benson on Open Thread #14
	MikeN on Open Thread #14
	freemike on Open Thread #14
	chriscolose on Vapor Lock

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