And I suspect he’s done so willingly. Well, you know what they say about statistics and liars.
Here’s the story. The Wall Street Journal and the Daily Mail independently published highly misleading and blatantly idiotic pieces on climate change. We’ve covered this extensively already over the last few days. Phil Plait, of the Bad Astronomy Blog on Discovermagazine.com, was one of numerous scientists to respond to those flaming examples of horrific bottom feeding journalism with the post “While temperatures rise, denialists reach lower.” In that post, he presented a still-image from a moving GIF that has been going around, originally from Skeptical Science. I’ve used the GIF myself just recently, but I’ll re-post it here for your convenience:
The graph represents a bunch of data, from various sources, indicating global temperature over time. The data points are linked together with a “line” to show that they represent data over time, though you could leave the line out because the X axis is labeled as time and the data are basically a scatter of points showing the relational between two variables: Time and temperature. But lines like this are traditionally used in climate science and are technically known as “squiggles.” So the line belongs there.
The purpose of the data scatter on this graph is to demonstrate two conceptually distinct approaches to data analysis: Seeking large scale trends by scientists vs. denying the existence of large scale trends by science deniers.
The dynamic graph begins by displaying in sequence chunks of data, one chunk at a time, from left to right, and with each chunk a downward sloping blue line. This represents the denialist perspective … find a series of points that looks like a downward trend, and put a line on it; A downward facing line, of course. Then the graph shows all the data at once with a line representing the trend shown by these data; There is a clear upward slope.
This graphic is a fun and informative way to demonstrate the difference between a series of attempts to lie bout the data vs. an overall simple straightforward presentation of the data. The upward tend line in the final image is actually unnecessary but it serves as a punch line. Personally, I would have preferred different color scheme with the lies in red and the truth in blue, but what the heck.
Phil presented this graph without much comment in his post, and he presented only the part of the image that shows the upward trend. The only context provide for the graph was the short paragraph before it, which read, in reference to the argument that the Earth is cooling and not warming:
The Skeptical Science website destroyed this argument in November 2011, in fact. The OpEd also ignores the fact that nine of the ten hottest years on record all occurred since the year 2000.
Note the link to Skeptical Science that I’ve included here in the block quote. That is a link to the blog post that this nice graph was initially lifted from by everybody else. In that post, Sketpical Science says:
Right now we’re in the midst of a period where most short-term effects are acting in the cooling direction, dampening global warming. Many climate “skeptics” are trying to capitalize on this dampening, trying to argue that this time global warming has stopped, even though it didn’t stop after the global warming “pauses” in 1973 to 1980, 1980 to 1988, 1988 to 1995, 1995 to 2001, or 1998 to 2005 (Figure 1).
And provides this caption for it:
Figure 1: BEST land-only surface temperature data (green) with linear trends applied to the timeframes 1973 to 1980, 1980 to 1988, 1988 to 1995, 1995 to 2001, 1998 to 2005, 2002 to 2010 (blue), and 1973 to 2010 (red). Hat-tip to Skeptical Science contributor Sphaerica for identifying all of these “cooling trends.”
So now you know what the graph is, where it is from, and what Phil said about it and how he used it.
And now, it’s time to play Whack a Mole, because that is what talking about Science Deniers is these days.
William Briggs claims on his blog at wmbriggs.com to be a qualified statistical expert, and he felt moved to criticize Phil’s use of the graph and what the graph shows, but he totally screws that up clearly demonstrating that he needs to rethink his qualifications. Or his honesty.
First, Briggs obnoxiously tells us that he has already blogged about how to cheat or fool yourself with time series, and that Phil had not read this blog post or done his home work, as though anyone on this planet was required to, or interested in, paying much attention to him.
He then tells us that the data “…are not–they most certainly are not–global temperatures.”
Please see the caption above. Thes are BEST land-only surface temperature data.
He then tells us “Each dot instead is an estimate of global temperature: worse, most dots are also different kinds of estimates from each other. That is, the first dot was estimated using data X and method A, and the second dot was estimated using data Y and method B, and so forth. Well, maybe the first and second dot were the same, but older dots are different than the newer ones.”
The data are from here. Yes, they are from a variety of sources, and have been combined systematically to make a useful source of analysis for climate studies. Here’s what Berkeley Earth says about them:
The Berkeley Earth Surface Temperature Study has created a preliminary merged data set by combining 1.6 billion temperature reports from 15 preexisting data archives. Whenever possible, we have used raw data rather than previously homogenized or edited data. After eliminating duplicate records, the current archive contains 39,390 unique stations. This is more than five times the 7,280 stations found in the Global Historical Climatology Network Monthly data set (GHCN-M) that has served as the focus of many climate studies. The GHCN-M is limited by strict requirements for record length, completeness, and the need for nearly complete reference intervals used to define baselines. We have developed new algorithms that reduce the need to impose these requirements (see methodology), and as such we have intentionally created a more expansive data set.
We performed a series of tests to identify dubious data and merge identical data coming from multiple archives. In general, our process was to flag dubious data rather than simply eliminating it. Flagged values were generally excluded from further analysis, but their content is preserved for future consideration.
There’s more, but that should give you an idea of what we see here. Briggs is trying to make you think that this is a horrid data set that can’t be trusted with huge internal error, but in fact, this is one of the best data sets ever put together for anything.
Then Briggs says:
All you have to remember is these dots are estimates, results from statistical models. The dots are not raw data. That means the dots are uncertain. At the least, Plait should have shown us some “error bars” around those dots; some kind of measure of uncertainty.
This is wrong at three levels. First, the graph was not used by Phil or Skeptical Science in a way that requires error bars. Second, Briggs is inappropriately emphasizing the degree to which the data are estimates or derived or otherwise iffy. Third, one thing we know about these data is that at the global scale (remember,we are measuring global temperature here) the variation is relatively low. Most large scale variation in temperatures is regional or inter-regional, not global. This is a case of Briggs making a huge mistake in his evaluation: He has lost control of the source and nature of variation. Variation must be understood on a situational basis. For example, if I said that I’ve measured the number of heads per person in a classroom of living humans, and I gave you the estimate of “1” you would not say “Hang on a sec.. variation in opinion polling data tends to be about 5% at two sigmas, so you really should say that the number of head per person ranges from .95 to 1.05” If you added error bars to the dots on that graph you would still have the same graph, and if you added error zones to the line itself the line would still be there. Briggs is trying to make you think there is huge error that simply is not there. (More about estimates below.)
He then blathers on further about confusing estimates and predictions which is totally irrelevant to the graph as well as to Phil’s point. In any event, we do have confidence limits for these data, from Berkeley, shown in this graph:
Another point Briggs makes is that the starting point for a line determines the overall position of the line. That is not true. If you determine the Y-intercept of a line as fixed then the rest of the line will be different than if you let the Y-intercept go where it ends up, but that is not what has happened here. He points out that the starting point for this graph is 1973, “a point which is lower than the years preceding this date.” That’s interesting because it indicates that he’s seen the original raw data, but all of his other comments suggest he does not really know where the data are from. In any event, note that the line is not fixed at any starting point on the left side of the graph. He’s just making this up. If we need to look to the left, to time periods earlier than 1973, to see if 1972 and earlier were warm and that the Sketpical Science graph is thus made up, there are plenty of sources of information and pretty pictures to examine the longer term trends. Like this one:
Which is from here.
The earth is warming, folks. And Briggs is not making it any easier by pulling wool hats over our eyes.
I’d like to make another point about Brigg’s blathering on about “estimates.” Everything is an estimate. Say you want to know the temperature outside before you head off for work. You can look outside and make an estimate. You see snow, but around the edges it is wet. Someone is walking down the street with a heavy coat, but it is unzipped, yet they are wearing a hat. Someone is jogging and not wearing shorts, and their breath is just a little steamy. Someone else is wearing a medium size coat and it is zipped up.
Obviously it is about 35 degrees F, minus 3 and plus 6. That is an estimae.
Or, you can look at the thermometer you nailed to your fence last year. It says 34 degrees. Hey, that’s close to our estimate! But the thermometer reading is still an estimate. The thermometer works on the physics of a bimetalic strip inside it. How carefully was it calibrated, and it is accurate a all ranges of temperature? The angle of viewing adds variation of about a half a degree. In any event, the temperature indicated by the dial is not a temperature, but rather, a response to the physics of two metals contracting and expanding deferentially in a spring, and how this positions a pointer on a big dial of numbers. That’s not temperature, it is an indirect effect of temperature. And what temperature are you measuring? You want to know the ambient temperature of the air you will be walking around in, but the air by thermometer is the air in your snow covered yard, not the cleared off sidewalk next to the road. And the thermometer is measuring the temperature of the fence it is attached to and it’s own corpus on which the sun is shining, along with the air.
And so on and so forth. Don’t let this “it’s an estimate” thing of Briggs fool you. All measurements are estimates, and one of the things scientists do is deal with that reality by understanding where the numbers come from, what the sources of variation are, and what the tolerances of the system are. Briggs does not seem to understand that.
There is a word on estimates and Brigg’s misunderstanding of the term (and his misunderstanding of what an “average” is) over at Open Mind as well.
And now we come to the final and most important point. Briggs appears to be critiquing the points Phil Plait is making in his post, but he is not. He does not really talk about the points Phil makes. He has created straw arguments and then attacked them. He is trying to distract from the central point that the Wall Street Journal and the Daily Mail totally botched their reporting and are essentially engaged in a disinformation campaign, in which Briggs is willfully engaged as well. Briggs is playing the Watch the Monkey strategy.
Pay no attention to the monkey. Pay attention to the Planet.
By the way, if you’ve gotten this far, you probably would like to know about Mike Mann’s brand new book: The Hockey Stick and the Climate Wars I’ve not read it yet, but after writing this blog post I feel like I’m in it!
Have you read the breakthrough novel of the year? When you are done with that, try:
or Paperback
*Please note:
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Muller et all, originators of the dataset, do in fact display their uncertainty range here:
http://berkeleyearth.org/faq/#stopped
Michael, thanks, I’ve added that graph to my post.
Oh dear and oh my. You, too, have forgotten the error bars. If it’s any consolation, it’s a common mistake. You add to it by making the second frequent error: confusing the fitted line for the data itself.
You’ll note (if you do your homework) that I’ve extensively critiqued the Berkeley results.
Everything is not an estimate, as you claim: a silly thing to say.
And I don’t own any wool, so I can’t pull it over anybody’s eyes.
Still complaining about the data, I see? That was the impetus for the BEST team’s work. They complained about, didn’t trust, the data so they redid it all, and surprise, surprise, came up with the same answers that Mann et al and many other teams had come up with during the preceding 15 years or so.
So Briggs is saying that every team, including the ‘skeptic’ BEST team, is incompetent because they all did their stats wrong despite the fact that statistical scientists David Brillinger (Professor of Statistics at UCB, whose work includes a contribution to the theory of time series analysis), and Charlotte Wickham were on the team.
Perhaps Briggs would like to send Brillinger and Wickham the link to his (Briggs’) article on how to cheat or fool yourself with time series. I’m sure they’d slap themselves on the forehead and say, “D’oh! How’d I miss that?”.
Or better yet, perhaps Briggs aka Galileo would like to do his own work and also redo the series to show how everyone but him has got it wrong.
William, thanks for commenting.
I’m sorry you missed my point about estimates. It’s pretty fundamental. Also sorry that you missed the confidence intervals on the graph. Click the link to get the details.
Your comment does not make any sense at all. You took Phil Plait to task for not showing the huge errors on the data that would unravel the entire global warming hypothesis, you claim to have seen the original BEST study and to have even critiqued it, yet you’ve demonstrated that you have no clue what the data look like or how it has been reported.
If you want to be taken seriously you should start taking the work itself seriously.
“a response to the physics of two metals contracting and expanding deferentially (sic) in a spring”
I suppose these springs can be differentiated from rude and impolite ones.
Ironically, had you read Dr. Briggs original article about time series you could have saved yourself most of your rebuttal. The first six paragraphs of your post rehash his points and your GIF simply demonstrates the exact point he makes in his post that by choosing when you start your graph you can manipulate the conclusion. IMHO the failure in Philâ??s article is that he fails to make this point. Instead he blusters on and claims that the stated facts are false when they are demonstrably not so. What he should have said (but you do) was that the multi-decadal data demonstrates that the shorter term trends may be inconsistent with the underlying longer term trend. Sadly Phil appears to have allowed his annoyance to get the better of him and the result is a very unsatisfactory post.
Well, I think a major issue is how the temperature data has been arrived at. The University of East Anglia folks were constantly rounding up temperatures and taking out data that they felt were too cold, saying they must be in error. Heck, they even took out the data from the “Little Ice Age” at one point saying it didn’t happen. Many people have taken pictures of NOAH temperature reporting stations that are located near heat vents, buildings, asphalt parking lots, etc. Data from Siberia was conveniently taken out during record cold waves there, or replaced with warmer data from the previous month. A lot of grants (money) depended on scientists to find evidence of global warming because there were no grants given to study global cooling. And then, of course, you have the insistence that all of this is caused by CO2 while not taking into account what the sun was doing (oh, we don’t study the sun, was a common comment). The field is full of shoddy research and quite possibly out-and-out charlatans. Their work is roughly equivalent to those promoting creationism or intelligent design.
You missed the error bars, you fool. Thus rendering what you say erroneous and invalid. Not the sort of thing William Briggs, (proper statistician), would do. Except when he does. Not that it would really affect the slope of the graph.
Perhaps a simple way to demonstrate one of Briggs’ points is to track down another well worn animated gif doing the interwebbie rounds. That one shows how the GISS land temperature series has transmorphed over time from one apparent times series to another one ( specifically one that gas increased it’s simple linear trend ). Now, if it was data that sort of revisions
would be impossible no? It would also mean we would have only one measure of “global temperature” instead of the 4,5 or 6 or whatever we have expanded to now.
I know people make typos in posts, but you’ll have to excuse me if I don’t take you very seriously after that one.
dealing with all of these supposed issues were the stated purpose of the BEST team. Which is the data set being used here. Did you miss that?
seriously? Here:
http://www.ipcc.ch/publications_and_data/publications_ipcc_fourth_assessment_report_wg1_report_the_physical_science_basis.htm
IPCC AR7, WG1. Read, for instance, chapter 9. Descriptions of the effect of solar variability are found throughout the chapter, with more references than I can easily count.
DanZee’s comment is a paragon of confusion.
Excellent post, Greg. FWIW, I chose blue for the ‘skeptic’ version and red for the ‘realist’ version simply because blue is a cool color and red is a warm color. I thought it made sense.
Coincidentally, John Cook predicted, the day before it happened, that the deniers would attack The Escalator the way they attacked the Hockey Stick. Considering that I first created the graphic several months ago, I think the man may be psychic.
Blair– except I do make that point, more than once, in that article and many others. I show that graph as an illustration, but the links right above it talk about how we know the Earth’s warming up. AND the plot shown can be traced further back in time, and surprise, the upward trend is still there.
That’s kinda the whole point of all this: the Earth is warming up, and loads of evidence supports it. But that point is consistently obfuscated by the deniers, who generally amplify some small thing to make it seem big. Rather like Briggs’ use of the word “estimate”.
Perhaps I can help you here.
As you rightly point out the basic measurement of the temperature is an estimate. When you combine a number of these measurements across the globe you are making a further estimate (with an assumed model of how temperatures behave spatially and throughout the year); then you are comparing these with other estimates of how this estimate compares with estimates (from different models) at different times (years).
Then you get into the issue of fitting linear models to this dataset in order to make claims about the significance of any trends. this raises issues such as autocorrelation in the data and the ability to pick a number of different time periods to make ones point (this is the point Skeptical Science makes, but fails to go on to realise that this feature in the time series increases the uncertainty associated with any model selected to be fitted to it).
Further at each stage you not just have to estimate the mean but the variability in the measurements.
So you perhaps understand why the error bars get wide, and claims of trends being of significance need careful assessment. Maybe the errors in spatial temporal estimates are well behaved and tend to reduce on aggregation, maybe they don’t.
Anyway your rather extravagant comments do seem to suggest a lack of appreciation of statistical methods, perhaps more appropriate to a social anthropologist?
HAS, thank you for your primer on statistics. Next time I teach a graduate seminar on multivariable stats, can I use your comment?
I agree with you about social anthropologists. They are totally annoying. I had to interact with them sometimes while working on my dual PhD is in Biological Anthropology and Archaeology.
Anyway, regarding what you call “Error Bars” (confidence limits would be a better word, “Error Bars” are a thing you put on a graph, confidence limits are what you base them on) please see the post where there are indeed confidence limits on the graph.
I know what you meant to say but what you actually wrote was: â??Itâ??s laden to bursting with factual errors, but the one that stood out to me most was this whopper: “Perhaps the most inconvenient fact is the lack of global warming for well over 10 years now.” What the what? .That statement, to put it bluntly, is dead wrong. It relies on blatantly misinterpreting long term trends, instead wearing blinders and only looking at year-to-year variations in temperature.â?
Certainly at the end you qualify yourself but the words you use to describe the data are â??errorâ?¦whopperâ?¦bluntly is dead wrongâ?¦â? (yes I know that is poor use of ellipses) my point being the statement is not in error, nor a whopper nor dead wrong. The authors conflate short-term trends with multi-decadal trends but do so directly and in a forthright manner and are not lying. Your reply should have consisted of the last sentence only. The sentences above it completely undermine your credibility by making statements of fact that are demonstrably incorrect.
You do the same thing later in the story when you challenge the 15 year trend. The Met data does show a lack of increase for the last 15 years but you deny that fact and then provide a citation that says (and I paraphrase) that 2012 will continue the short-term trend.
Clearly we donâ??t see eye to eye on this but you can understand that for the reader seeing you make factual claims that are demonstrably false in the process of making an otherwise sound argument is not very satisfying.
Greg Laden @ February 1, 2012 5:31 PM
How many sources of uncertainty can you count underlying the original issue under debate, and how many are taken into account in the Berkley piece you quote? That is of course the point of the difference you are having with Briggs (and are trivializing by referring to “a high school data graph”).
If you do indeed teach a graduate level multivariate stats course then I hope for your students’ sake you do use this as an example of some of the pitfalls in glossing over uncertainty.
[BTW I referred to “error bars” because that is what you used in your post and I thought you would be more comfortable with that term.]
That is not my difference with Briggs. Briggs does not have any valid statistical points to make. My difference with him is that he is trying to distract people with made up critiques that don’e even address the original posting.
Regarding uncertainty in the data, I’ve provided links to extensive and intensive descriptions of the entire process of making this data set. Please do your own homework.
Did you see the graph with the confidence limits? Start there, work your way backwards (the link is provided) and come back later with your critique of where the Berkeley group, who are climate change skeptics, by the way, got it all wrong.
Actually I didn’t start the day by trivializing issues of uncertainty when making inferences about whether trends were significant or not.
It is therefore sort of incumbent on you to demonstrate the home work you have done. Just a list of the sources of uncertainty quantified and unquantified would be a good start, and yes you can refer to those that Berkley identified in both categories as part of that list (although in this case that is just a small part of it).
http://www.pbfcomics.com/216
I did not trivialize uncertainty. I made the claim that the uncertainty is low compared to what Briggs was claiming. I provided a graphic based on analysis of the data, and a link to the source which has full documentation.
Why do you keep asking for what I’ve already provided? Is that all you’ve got?
As usual, the deniers posting here are liars, ignorant, and/or incompetent. DanZee is the worst of the bunch, but the others aren’t much better. Tragically, because of how widespread such traits are, this experiment in primate evolution is heading toward failure. (I just watched Surviving Progress … I highly recommend it, but few of the people who most need to see it will.)
Greg Laden @ February 1, 2012 7:34 PM
In summary you feel that all the uncertainty when making inferences about whether trends were significant or not is covered by the Berkley graph.
I think you’ll find that Briggs suggests (with justice IMHO) that this isn’t the case. And the problems aren’t just confined to BEST.
Perhaps a case for a little discussion? Who knows who might learn something – even the lovable Marcel Kincaid perhaps?
There are multiple lines of evidence that the climate system is warming (http://www2.sunysuffolk.edu/mandias/global_warming/modern_day_climate_change.html) and that humans are responsible (pattern of warming and well-understood physics prove this).
Let us not get distracted from that point. We need to rapidly reduce our carbon emissions if we wish to keep enjoying the world in which we evolved.
Ack! URLs are not automatically resolved. Link below.
Modern Day Climate Change
It’s pretty obvious that people here are failing to apply common-sense to the problem of straight temperature trendlines: as these graphs all go to demonstrate, they’re an inappropriate fitting technique for this kind of data.
Imagine an L-shaped graph – that is one in which the data points all initially fall in a straight vertical line, before making a right-angled turn and continuing horizontally. It is obvious that a straight-line fit of this data from any starting point will not be representative of the whole.
This isn’t about understanding statistical techniques – it’s about looking at whether your statistical techniques are appropriate to the nature of the data, whether they make sense considered in terms of the real world.
Anyone, whichever side of the argument they’re on, who fits straight lines to temperature data, thereby demonstrates that they’re not competent to hold a meaningful opinion.
“Anyone, whichever side of the argument they’re on, who fits straight lines to temperature data”
Except it’s the deniers fitting the straight line.
Then some realists coming along and showing how their straight line feature shows warming still.
And rather than imagine an L plot, imagine a wavy graph with an increasing trend. Just like the one in the graph above.
And then imagine that the IPCC actually don’t fit a straight line to it, but a curve because the science says that, if it IS CO2, then the curve should be logarithmic with CO2 concentrations. And then find that their supposition is supported by the date.
Then imagine that deniers keep fitting straight lines.
Then imagine that YOU come along and whine about how everyone (other than you) are incompetent.
Oh, goody, a graph that dishonestly starts in 1973 — you know, about the same time Hansen’s model was being used to predict an Ice Age, because that was the trendy enviro-scare at the time.
A better graphic would be one that extends every trend to infinity, labelled “How Alarmists See Temperatures” and maybe a second Y-axis labelled “$$$$$$”.
” predict an Ice Age, because that was the trendy enviro-scare at the time”
Er, no, you can repeat that lie all you want (and having looked through the site to which your name links, I’m guessing you tell quite a few lies), there was no big “prediction of a coming ice age”. A couple popular articles in Time (Newsweek? I forget which) but nothing else. There were, however, concerns about warming.
TallDave, rather bold of you to sue me for several hundred thousand pounds then come over to my blog and make nasty comments, and violate my blog policy.
HAS, Briggs, TalDave, et. al.,
Hey, keep comforting youselves with quibbling over estimates if you want. It’s not like there’s any evidence of any actual changes in the environment, right?
(from:http://www.guardian.co.uk/environment/2010/jan/20/climate-change-glaciers-melting)
“Lonnie Thompson, a glaciologist at Ohio State University, said there is strong evidence from a variety of sources of significant melting of glaciers – from the area around Kilimanjaro in Africa to the Alps, the Andes, and the icefields of Antarctica because of a warming climate. Ice is also disappearing at a faster rate in recent decades, he said….
It is not any single glacier,” he said. “It is very clear that these glaciers are behaving in a similar fashion…
Scientists now had evidence collected over a long period of that decline from samples of the ice core and even collections of plants from mountains that were left ice-free for the first time in more than 5,000 years, Thompson said.
The World Glacier Monitoring Service shows a similar picture. In a 2005 survey of 442 glaciers, 398 – or 90% – were retreating, 18 were stationary and 26 were advancing.
Thompson, who has been studying glaciers in the Andes for more than 30 years, said he had watched the loss in his own lifetime. A number of the region’s glaciers have disappeared. Venezuela, which had six glaciers when he first began as a graduate student in the early 1970s, now has only two small ice masses which Thompson thought would be gone within ten years. An Andean glacier that had been melting at a pace of six metres a year 40 years ago is now disappearing at a rate of 60 metres a year, he said.”
Greg: Do you happen to know if the confidence interval on the BEST data (from the “Has Global Warming Stopped?” FAQ) incorporates the correction for spatial autocorrelation? I can’t find a specific discussion on the BEST site about this point. I’m sure they discuss it somewhere….
My understanding about how these estimates are generated is that a large number of station data are averaged, and the variance computed. The 95% confidence band is then assumed to be +/-1.96 sigma according to the assumption of normality. Spatial autocorrelation increases the uncertainty. Is that correct? Or does the 95% confidence band on the BEST dataset actually correspond to the real order statistics?
Thanks
BBB
Great article Greg laden. Thankyou.
@14.dana1981 | February 1, 2012 4:27 PM
Makes sense to me too. Good graph there. Cheers.
Scott A Mandia
No, you broke the link by attaching parentheses to it. If you want an active hyperlink in parentheses, leave spaces.
(Decent primer, that page.)
More fun tips: Don’t put a period directly at the end of a URL, either.
Trivia, but part of my missionary work:
“So the line belongs there.” (the connect-the-dots lines)
Because it’s traditional.
As the number of points gets larger, connecting them gets worse. To hell with tradition – rather ask if it is good.
Allot of what’s traditional in my work (biology) is popular precisely because it is bad (misleading, hiding detail, dumbed-down).
@ Greg Laden | February 2, 2012 3:18 PM
TallDave, rather bold of you to sue me for several hundred thousand pounds then come over to my blog and make nasty comments, and violate my blog policy.
Did you ensure that TallDave was indeed TallBloke? It seems to me to be unlikely, given that TallBloke’s name, as you were once aware, is Roger.
Fred, no I didn’t, but that was my mistake You’re probably right that Dave is not the same bloke as Bloke. Is there some meme in which one calls oneself “tallX” that I’m missing?
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Greg Laden has made a mistake here because as the graph shows the temp has risen just 1C which is the agreed margin of natural variability therefore the graph shows no Global Warming.
Sorry to be a late comer to this discussion. I am always amazed that the main focus of talk in Climate Change discussion is climate change. There is absolutely no “estimate” or argument against data that show the Earth’s atmosphere is being filled with carbon molecules at an alarming and disastrous rate. Nor is there any real counter to the data that shows the seas are becoming more and more acidic. Climate change, including Global Dimming, are but symptoms of the increased carbon and acidification. Science tells us that the Earth has had previous periods wherein the Earth’s atmosphere was probably unsuitable for human life. Now humans are living in a way that will push the atmosphere and the environment (including the waters) to a point where humans can no longer exist.
“If you want to be taken seriously you should start taking the work itself seriously.”
No normal, sane, thinking person can take a climitard seriously… come on.
Dr. William M. Briggs
He talks about God.
However, he is a hypocrite.
And he is a married person.
He tempted me who was skeptics same as him.
I was not able to have a meal for the shock for a while.
Please be careful about him when you are a woman.
Because he did not reflect at all, I posted this.
https://douleurblog.wordpress.com/
Briggs is a rightwing nut. Hell he gave an interview in amerika. And thats just the,tip of the iceberg of his rightwing bullshit.