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What has global warming done since 1998?

What the science says...

Select a level... Basic Intermediate

Every part of the Earth's climate system has continued warming since 1998, with the ten record temperature years all occurring since 2010.

Climate Myth...

It hasn't warmed since 1998

For the years 1998-2005, temperature did not increase. This period coincides with society's continued pumping of more CO2 into the atmosphere. (Bob Carter)

At a glance

This date-specific talking-point is now something of a historical curiosity, but we'll leave it in the database for now because it's such a good illustration of the simplistic yet reckless mindset of the serial climate change misinformer. And indeed, we could (out of sheer mischief) have revised this myth by replacing "1998" with "2016". In fact, that's what we started to see in the climate change misinformation stream, © the Usual Suspects. But 2023's record temperatures put a stop to that.

Anyway, as first predicted over a century ago, Earth's surface, oceans and atmosphere are all heating up. That's due to our increasing greenhouse gas emissions, but over the years the warming has occurred at varying rates. This should in no way come as a surprise. Other physical phenomena periodically act either to suppress or enhance temperatures.

A prime example of such a phenomenon is the effects of La Nina and El Nino. This natural climatic oscillation features variations in winds and sea surface temperatures over the tropical eastern Pacific Ocean. The cycle can at times strongly influence temperature and rainfall patterns right around the world.

In a La Nina year, temperatures are suppressed, whereas an El Nino year sees them enhanced. This is noise on the long-term upward trend. That's why climatologists work with multiple decades, not just a few years in isolation, in order to get a grasp on what is going on.

The year 1998 featured a massive El Nino. The temperature spike it caused was a huge outlier, like a pinnacle towering over the landscape of the temperature record. In the following years there was a return to more typical conditions, with an erratic but upward warming pattern. That sequence of events gave deniers a brief opportunity to insist that global warming had “paused” or had even stopped.

You only need to remember one thing here. Those who create and spread misinformation about climate change don't care about reality. Public confusion is their aim. In this instance, the misinformation exercise involved deliberately selecting a limited block of years starting with the massive El Nino of 1998 and using that very warm starting-point to insist that global warming had stopped. They knew this would likely work for a few years and that the public would quickly forget why that was the case. Mother Nature had handed them a gift. It was an irresistible bunch of low-hanging fruit to exploit: little wonder the tactic is known as 'cherry-picking'.

Talking about reality, what actually happened? Well, as of 2024, a couple of decades down the line, the top ten warmest years have all been since 2010, whatever observation-based dataset you choose, with eight of them being in the 2015-2023 period. 1998 is nowhere to be seen any more. By modern standards, it simply wasn't warm enough.

Please use this form to provide feedback about this new "At a glance" section, which was updated on May 27, 2023 to improve its readability. Read a more technical version below or dig deeper via the tabs above!

Further details

Even if we ignore long term trends (something deniers often do in order to make a point) and just look at the record-breakers, as of early 2024 the top ten warmest years have all been since 2010, whatever dataset you choose, with eight of them being in the 2015-2023 period. In this top ten grouping, 1998 is nowhere to be seen any more. It was not warm enough.

The myth of no warming since 1998 was largely based on the satellite record estimates of the temperature of the atmosphere.  However, as discussed in the video below by Peter Sinclair, even that argument is no longer accurate.  The satellites show warming since 1998 too.

There's also a tendency for some people just to concentrate on atmospheric or surface air temperatures when there are other, more useful, indicators that can give us a better idea how rapidly the world is warming. More than 90% of global warming heat goes into warming the oceans, while less than 3% goes into increasing the atmospheric and surface air temperature.  Records show that the Earth has been warming at a steady rate before and since 1998 and there is no sign of it slowing any time soon (Figure 1). 

Fig 1

Figure 1:  Global Energy Inventory: observed changes in the global energy inventory for 1971–2018 (shaded time series) with component contributions as indicated in the figure legend. Cross-Chapter Box 9.1 Figure 1 (part a) - From IPCC AR6 WGI Chapter 9.

Even if we focus exclusively on global surface temperatures, Cowtan & Way (2013) shows that when we account for temperatures across the entire globe (including the Arctic, which is the part of the planet warming fastest), the global surface warming trend for 1997–2015 is approximately 0.14°C per decade.

Ultimately, every part of the Earth's climate system is warming, and has continued warming since 1998.

Last updated on 8 March 2024 by John Mason. View Archives

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Argument Feedback

Please use this form to let us know about suggested updates to this rebuttal.

Further reading

Tamino further explores the warming trend since 1998 in Garbage is Forever and Wiggles.

I've kept my original treatment of the subject as other websites hotlink to the images. My original treatment uses similar arguments to Fawcett and Jones 2008 although their analysis is much more rigorous (as you'd expect in a peer-reviewed paper).

Further viewing

Fact brief

Click the thumbnail for the concise fact brief version created in collaboration with Gigafact:

fact brief


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Comments 101 to 125 out of 237:

  1. @kdkd - I know what you mean about the IPA but that doesn't count as a valid refutation. Even though the IPA is populated with ideologues who far too frequently see things only through the prism of their free market ideology that doesn't make everything they say wrong. @Riccardo - thanks for that - I was told it HAD been published - that was certainly the claim by the Cox supporter and Cox himself posted a link to it on the Drum (ABC) (as per mine above) to the paper as if it "were" published - typical of his dissembling approach. But you are correct - I can find no reference to it in any of the indexes for this journal. That in itself is telling enough as it is now almost 2 years since it was submitted. In my own days (long past) of publishing in the field of Atomic Physics it could sometimes take 12 months or so from submission to publication. But two years suggests there are some issues with acceptance. I should have checked this before. But I'm not sure your other comment is entirely fair. I agree any physics is absent and I accept Dikran's comments on the poor statistics (as I'm not the expert there) but I'm not sure you can claim that their only conclusion is that local temperatures are sensitive to nearby ocean. Perhaps I've misread it but I gathered they were looking (purportedly) at Australian temperature data and using that as basis to dispute local warming (i.e. saying they can show a statsitically valid trend based on the Chow test that it may be flattening) @Dikran - thanks for your comprehensive statistical refutation - I'm afraid I don't have the statistical expertise that you do - If asked I would have thought sum-of-squares errors was a fair anough approach (which is what you would expect in econometrics). But would you elaborate further? I understand what you mean about physical processes - as climate/temperature outcomes are a function of many different factors each with their own cycles and forcings and ENSO of course being a big one. But given that temperature data (what they are analysing) is ultimately data that is averaged over many sources why isn't it by definition normally distributed? I'm sorry if I'm being a little dense - is it because each of the "drivers" has it's own statistical/natural "noise" and this creates a non-gaussian distribution of noise when the (average) temperature data is considered? Do you know of anyone who has looked at the data after tyrying to remove the effects of ENSO etc? I very much take your point about the "multiple hypothesis testing problem" - some thing I wasn't familiar with before but based on your explanation and a bit of my own secondary research can see how "false positives" might abound in an area like this. Are there any simple tests that can be used to identify the likelihood of this? I do find their comments about breakpoints to be not unreasonable - although I note they make no real statement about what possible physical processes may be causing them. Perhaps the most compelling argument (against this paper) is actually that they offer no fundamental physical reason behind their so called flattening. If I were to have a stab at trying to understand what is going on here based on the statistical arguments you have presented I might have speculated that you can get large maxima and minima in any data that is the physical outcome of many cyclical processes that operate on different periods merely because from time to time the cyclical maxima co-incide in time. The danger is then that you "cherry" pick these points. You have to remove these other cycles to get out any linear drivers underneath the data. I think that is sort of what you are arguing? Regardless - thanks all for your responses. Any more welcome but at least I feel now that we can point out not only that Mr Cox is on shaky ground - but also why. Cheers
  2. Mark #102 Tamino at Open Mind has looked at these issues in these two threads:
  3. @ Sean 103 Thanks - while these links don't explicitly address Cox's paper and the statisticaly validity (or otherwise) of their approach they do remove the effects Dikram was pointing out. The challenge then to Cox and Stockwell would be to analyse again based on this and see if they could still find the break points. On a visual inspection of the graphs in the links I suspect not. Please ignore #101 - I must have hit submit when I meant to hit preview
    Response: [Dikran Marsupial] #101 deleted, done the same myself more than once! ;o)
  4. @mark The central limit theorem does indeed suggest that the averaging of temperatures at stations at different location means that a Gaussian noise model is appropriate, but only for a particular time point. To see why this is the case, imagine some AM radios that are affected by mains hum. Each will have a noise component that is due to the electronic components in the radio, these are independent, so the noise for the average signal over many such radios will have a corresponding Gaussian component. However, the mains hum on all the radios will be in phase and will be reinforced in the averaged signal, and will have the same [scaled] distribution as the mains hum measured at any one of the radios. Another way of looking at it, cyclical data is easily confusable with data containing a step change, but how likely is it to see a cyclic pattern in Gaussian white noise? A lot less likely than in data with autocorrelation or cyclical noise. You are not being at all dense, the central limit theorem is hardly stats 101! I checked the archive at the Journal of Forecasting, it hasn't been published yet. For the multiple hypothesis testing issue, there are standard methods to deal with this, but they are generally overly optimistic or pessimistic. What I would do is generate a large number of model runs using a GCM where the only forcing was from CO2 and see how many produced a non-significant trend at some point during a 40 year period via the models internal variability. The forty year period is chosen since worries about global warming began to gain acceptance in the early 70s, the test is "at some point" because we are asking if cherry picking is the issue, so the "skeptics" would make the claim as soon as such a period ocurred. Easterling and Wehner (who Stockwell and Cox claim to refute) did almost that, in that they looked at model output and found that decadal periods of little or no warming were reproduced by the models (although opf course the models can't predict when they will happen). This means that the observed trend since 1995/8 is completely consistent with model output. Easterling and Wehners' result shows that cherry picking is a possibility; it isn't necessarily deliberate cherry picking, but the skeptics have never performed an analysis that shows the ressult is robsut to the multiple hypothesis testing issues. For the removal of ENSO, see the Fawcett and Jones paper mentioned in the intermediate version of this article. If you just look at the data: you can see there isn't much evidence of a step change in 1997 if you account for ENSO. The real problem with the paper is the straw man of a linear centennial trend. AGW theory doesn't suggest a linear centennial trend is reasonable, so showing a model with a break-point is statistically superior to something that AGW theory does not predict is hardly evidence against AGW. I also remember some comment about solar forcing being better correllated with temperatures than are CO2 concentrations, and conclude that CO2 radiative forcing is not significant (or words to that effect). However, that is another straw man, the mainstream position on AGW does not say that co2 radiative forcing is dominant on a centennial scale (and that solar forcing is responsible for much of the warming of the 20th century). This is both a straw man and a false dichotomy, it isn't one thing or the other, but a combination of both. Reviewers at the Journal of Forecasting might not be suifficiently familiar with the climatology to spot that one. What I am basically arguing is that statistics should be used to gain knowledge of the data generating process (in this case climate physics). If you ingore what is already known about the data generating process and adopt a "null hypothesis" (e.g. linear centennial trend) that is known a-priori to be incorrect, then statistical methods are likely to be deeply misleading. It is a really good idea for statisticians to collaborate with climatologists, as together they have a better combination of climate science and statistical expertise than either has on their own. This paper, like McShane and Whyner (sp?) and Fildes and Kourentzes, is an example of what happens when statisticians look at climate data without fully immersing themselves in the climatology or getting their conclusions peer-reviewed by climatologists.
  5. @#104 - Thanks Dikram. Really appreciate your comprehensive reply. I think this just about knocks it on the head - it's good to have such a clear, albeit somewhat arcane and technical, discussion. In summary I would argue this paper can be safely dismissed because #1) After two years it hasn't been published - suggesting a problem with its acceptance #2) It has been submitted to a forecasting journal which, whilst reputable and purports to cover climate forecasting, does so as only as one out of a long list of forecasting topics which are predominantly economic and social in nature (in other words it's light on hard science) - which means there is actually very little climate science expertise within the journal #3) It contains no physics or science arguments what-so-ever as to what may actually be the mechanisms it purports to reveal or forecast. The above 3 really make it clear it is hardly a paper about climate in the first place #4) It's approach is statistically invalid since the test it applies assumes a gaussian noise distribution in the data when that is not the case (due to the multiple impacts of noise from cyclical drivers of climate of different periods and variabilities) #5) It's approach is invalid on the physics of climate because of the above #6) It's invalid on the physics anyway since it is established beyond reasonable doubt that increased atmospheric levels of CO2 produce an increased green house effect #6) It's approach is statistically invalid because of the multiple hypothesis testing problem - i.e. it is highly likely to generate false positives in the statistical analysis of the data - especially when it ignore the underlying physics - in other words the so-called linear trend they forecast is likely to be plain wrong #7) It fails to remove the effects of things like ENSO and volcanos from the data in order to analyse the temperature effects of increasing CO2 in the atmosphere - particularly egregious when the ENSO of 1997/98 was known to be one of the largest ever #8) It actually fundamentally fails to address the central tenet of AGW - that increasing levels of human generated atmospheric CO2 are contributing to a warming of the planet independent of other (natural) factors sufficient to cause substantial climate change that will most likely be deleterious. have I missed any? If they want to come back on any of that all they have to do is re-analyse the data accounting for ENSO etc (as per your graph) and then show that a linear trend is still valid and is not a false positive - and of course get that accepted in peer review. If they were honest scientists that's what they'd do. I hope I get the chance to put that to them :)
  6. Oops - for "show that a linear trend is still valid" I should have said - "show that a FLAT trend is still valid". I wish they could show such a thing - I'd love to discover AGW isn't a real problem! I wish it wasn't! But wishing doesn't make it so and good scientists don't fall for the "is/ought" fallacy. So I am betting they won't and can't.
  7. Mark, note that some arguments are stronger than others, for instance the test used to detect the step change may still be reasonable, even if the noise is non-Gaussian, but in such circumstances it is up to the authors to convincingly demonstrate that it is O.K. (for instance by testing it using synthetic data where the noise is statistically similar to the real data). They would have to do more than just remove ENSO, even after that is done, a linear trend model over a complete century still isn't a reasonable model, given what we know about climate of the 20th century, so it would still be a straw man. If they wanted to demonstrate that there really was a step change in 1997 that was evidence against AGW, they would have to limit the analysis to the period where mainstream science actually says CO2 radiative forcing was dominant (e.g. approximately 1970 onwards). For any test, the null hypothesis ought not to be known to be false apriori. If they wanted to show it wasn't just ENSO they would also have to use data that had been adjusted for ENSO. As it is well known that ENSO affecte climate (especially Australian climate), showing ENSO is responsible is nothing new. If the want to say it is PDO, this is more of an oscillation that modulates ENSO, so a step change model isn't really appropriate anyway. I don't think there is evidence that the analysis isn't honest, just naive (from the climatology perspective) and lacking in self-skepticism.
  8. Thanks Dikram for those points. I think your point about 1970 onwards is the most compelling since this is indeed the relevant AGW period. As for your comment about "honesty" - I agree the paper shows no dishonesty. But I don't think it is "naive". If you had been following Mr Cox's tactics on the ABC and other blogs you might question whether he is always entirely forthright in his approach. He is actually a lawyer - not a trained scientist. He wrote an article once on Drum ( about how there had been a challenge to the Australia/New Zealand tempetarure data, implying some sort of conspiracy on the part of BOM people in New Zealand. He made it out as if this was independent challenge from credible sources. What he failed to disclose directly in the article was that he was actually one of the prime architects of the challenge (in his capacity as secretary of the Climate Sceptics)- which didn't come from reputable client scientists at all. He also published the link to his "paper" on Drum in response to a challenge to submit a piece of peer reviewed science that invalidated AGW. Somehow he conveniently neglected to mention that it hadn't actually been published. In other words he has an avowed political agenda - it not simply a naive approach or lack of self-scepticism
  9. Hmm, If it is not warming, it is because of natural causes. If it is warming it is because of dangerous carbon dioxide. Way to go!
    Response: [Dikran Marsupial] No, for example the rapid warming suggested by the decadal trend ending in the 1998/9 El-Nino was largely due to natural causes. The point is that short term trends are unstable because of natural variability, which has a tendency to average out over longer timescales.
  10. Dikran Marsupial: What evidence can you present for your claim that natural variability 'has a tendency to average out over longer timescales'? Given that we have geophyiscal evidence of massive natural shifts over millions of years, your claim sounds spurious and without merit.
  11. Interesting. Over the past week, I've noticed a pattern developing in 'denialist' language. It's some form of "AGW is falling apart." I've also seen "coming unraveled," "disintegrate," and something like "becoming full of holes." I wonder if this can be traced to a single mass media event. The regular causes of short-term variability (ENSO) do not cause long-term swings. The changes you're talking about "over millions of years" are not caused by short-term (11y or 25-50y) solar cycles.
  12. DSL#111: There's an echo 'faster than they can repackage and rebrand' that seems to start in an editorial in Investor's Business Daily on July 28. Based, of all things, on the Monnett investigation charade. I get all my climate science news from investment tip sheets, don't you? But FauxNews sure picked it right up. It was less than a week after the Monnett story broke that permits for drilling the Arctic started moving forward. Beneficiaries - Shell Oil. Here's one environmental blogger that sees this as more than a 'coincidence.'
  13. RichyRoo - changes in climate over such long timescales tend to be forced change, rather than unforced variability. To see that natural variability tends to even out, all you have to do is look at ENSO, which is the strongest source of naturl variability - it is quasi cyclical, and hence averages out to near zero for periods long enough to contain several cycles. That is why climatologists use windows of around 30 year mark.
  14. DSL#111: That noted climatologist James Taylor had a July 27 editorial in Forbes touting Spencer's paper. Here's the system works: - Do bad science, get good press. Repeat. Ignore rebuttals. - Do good science, nobody pays attention.
  15. I have always wondered whether average temperature is the best measure of what is happening. If the theory is correct then, with more carbon dioxide in the atmosphere every year, the earth should retain more heat every year. Of course there are other factors--solar variation, dirt in the atmosphere, and I don't know what else. But there can't be that many of these. In addition, heat doesn't all go to raise the temperature. There is the heat of fusion and vaporization. Perhaps heat is used in some other ways in ocean acidification. But again there can't be that many other places for heat to go. Would it be possible to quantify all these effects? Surely there can't be that many really significant ones. If so, a new number might be generated that would reveal the increased retained heat.
  16. michaeld - average temperature possibly isnt the best because oceans introduce a lot of internal variability- but its what we have. The Argo network should eventually provide a better measure (see Von Schuckmann and La Traon 2011). See the Ocean Cooling corrected again for more discussion.
  17. michaeld#115: "Would it be possible to quantify all these effects?" Done. See Tracking Earths Energy and any of the many sensitivity threads, for example here. But average temperature (actually temperature anomaly, in comparison to a standard base period) is important because it is a directly observable change. But more important than the year-to-year, month-to-month anomalies is the temperature trend. Since the mid-70's that trend is up.
  18. From Roy Spencers blog, here are the most recent UAH lower trophosperic temperatures Spencer describes the 3rd order polynomial fit to the data as being "for entertainment purposes only, and should not be construed as having any predictive value whatsoever.". It may not have any predictive value, but it does show in hindsight that it has warmed since 1998. Many thanks for debunking this one for us Roy! ;o)
  19. 118, Dikran,
    ...but it does show in hindsight that it has warmed since 1998.
    It also shows that his choice of 3rd order polynomial fit doesn't fit, unless that brief foray into La Nina land continues non-stop for about a half a decade.
  20. Infrequent poster but I've been reading about the Muller's BEST data set and then saw some counter arguments and critique supposedly from one of the co-authors of the report. I am not making any argument from expertise about the data, but there are a number of quotes from Professor Judith Curry, supposedly the second author on all of the papers, she's a climatologist out of Georgia Institute of Technology. I checked around and all of the skeptic websites have their rehashing of an article that seems to have originated in the daily mail. From what I understand, that's a pretty cruddy source, but using a link below, I went to Curry's own website and it sounds like this is what she's saying: This quote is from the daily mail article: In fact, Prof Curry said, the project’s research data show there has been no increase in world temperatures since the end of the Nineties – a fact confirmed by a new analysis that The Mail on Sunday has obtained. ‘There is no scientific basis for saying that warming hasn’t stopped,’ she said. ‘To say that there is detracts from the credibility of the data, which is very unfortunate.’ Read more: Here is a blog from Judith Curry, climate etc. I don't know much about it, but the most recent post goes into detail about a conversation she had with Muller and a second post clarifying her comments and what happened in the daily mail interview. I went and re-checked the article linked on the home page about the skeptic myth that it hasn't warmed since 1998. It says it hasn't been updated for a while. I get that Muller released his data and leaked his summaries before the data had been peer reviewed and Curry makes a number of comments saying she wished he hadn't done that and that he did it on his own. I get her critique hasn't been peer-reviewed either. A number of the articles referenced a site called wood for trees that has a simple app that lets you access the BEST data and make simple plots. I know nothing about its accuracy or validity, but you can use it to check various date ranges. I'm curious if anyone has any better info on this argument and if there is any agreement or counter argument related to Curry's declaration that the BEST data set shows that warming has stopped over the last 10-12 years? Also, please don't hear me saying that in and of itself proves anything about anything. I'm not "going anywhere" with this quote and from reading Curry's blog, she says it doesn't prove or disprove global warming. But it does call into question many of the models and most specifically, it makes Muller look like a bit of a dodo for the way he presented his data and his initial denial of the data then later retractment and admission supposedly of what the data says. Thanks for any thoughts, Rick

    [DB] Thanks for taking the time to voice your concerns.  Tom Curtis has already addressed most of them below, but let me focus on Wood For Trees. is a website run by Paul Clark, a British software developer.  Paul has loaded into the website all the publicly-available temperature datasets, including BEST.  As such, it is an invaluable tool for quickly comparing temperature trends over varying timeframes.  Many climate scientists use Wood For Trees for quick comparisons for the public to turn to for answers to questions.

    It's not a panacea for research, as the pros still work directly with the datasets directly, but it is a valuable tool.

    As for the rest, I'll close by saying that anyone who agrees that a time series of only a decade isn't scientifically significant AND who also says that over the same time a scientifically significant long-term trend has stopped is speaking out of both sides of their mouths.  The two positions are mutually exclusive.

  21. Rick @120, the best currently available discussion of Judith Curry's comments can be found at Tamino's Open Mind. He does a series of analyses of the data showing that: 1) The trend over the chosen period is positive; 2) That the last two data points are almost certainly flawed - so much so that the real scandal here is why where they included? (See below); 3) That if you exclude the flawed data, the trend rises to a level comparable to the trend in various satellite products; 4) That if you do not cherry pick the start point and use a full decades data (rather than artificially truncating it at less than a decade, as Curry did), the trend matches the trend since 1975 at a hefty 0.27 degrees C per decade: Finally, Tamino shows that the minimum time period with a statistically significant slope terminating in early 2010 (the end of the BEST data excluding the two faulty values) is approximately 16 years. That is the minimum period over which the level of statistical significance is sufficient to determine the sign of the slope. And over that period, the trend is positive, and very much the same as the trend since 1975: Finally, I referred to the last two data points being flawed. Tamino shows the huge rise in uncertainty for those two points, but it was Nick Stokes that discovered why. It turns out the data for those last two months comes from just 47 stations, compared to the 14,488 stations for the preceding months. What is worse, all of those stations are in Antarctica. Given the low number of samples, and biased distribution, there is no scientific justification for including the last two samples in their finished product. This is one genuine issue with the BEST product, but as the faulty data points bias the end points low, don't expect to here it raised by so called "climate change skeptics", for whom the predetermined outcome has always been more important than scientific integrity.
  22. Thanks a ton for the response and great info. I was hoping wood for trees was a useful site, but, I get the danger of cherry picking beginning and ending dates to find what you want to find. When I entered 1998 as the start date at wood for trees and used the same settings as for their example data, there was a clear positive slope. You have to hunt around to find a cluster that doesn't slope. I also get [DB]'s comment about a very short period of time not indicating anything about the longer term trend, and Curry makes that exact comment as well. But Tamino sure goes off on her and presents some pretty compelling analysis saying she was way off base in her critique of Muller. It is pretty odd, however, that Muller was wrong about his own data. I don't know Tamino, but when two of the folks who did the data set both say the same thing, it seems odd that they're both wrong. My last thought, I read through Tamino's post and all the comments. A number of folks offered that what she said was "technically accurate" (i.e. there's no scientific evidence than global warming hasn't stopped", but that her statement is meaningless. But at least from what I read, she said she made that comment to shut up Muller who she said made some comments saying the BEST data set proved AGW was true and that skeptics were totally wrong. I get reminded occasionally by my advisors about the limits of what the data I'm analyzing says and what I can and can't claim about it. If one takes her comment as chastising Muller for over-speaking, it doesn't have the connotation Tamino goes after and then, all of Tamino's analysis ends up demonstrating her exact point which is that small of a period cannot be used to prove anything. It was late when I read through her blog so I don't remember what she said she was responding to from Muller, but that's what I remember her saying started this whole thing, some statement from him she said was way overblown, so she wanted to restate it technically accurately and say let the data speak for itself.
  23. Rickoxo#122: "It is pretty odd, however, that Muller was wrong about his own data." Odd because that is incorrect. Read the BEST FAQ under 'has global warming stopped?' the decadal fluctuations are too large to allow us to make decisive conclusions about long term trends based on close examination of periods as short as 13 to 15 years. There is no evidence of a change in trend on that long a time scale. Muller said it correctly; it's Curry and others who are deliberately spreading disinformation. #120: "a fact confirmed by a new analysis" There is no 'new analysis'; there is just a deliberately cherrypicked graph. Based on that kind of science, consider this: It was cooler today than it was in July; is that evidence that global warming stopped?
  24. Murry made this comment publically, when asked about the question of recent temperature data: ‘We see no evidence of it [global warming] having slowed down,’ he told BBC Radio 4’s Today programme. There was, he added, ‘no levelling off’. Read more: Curry's argument was much like Tamino's argument against her, that the statement from Muller was a stupid statement and meaningless. He could have simply said that short term trends don't matter due to decadal fluctuations, but he didn't. It seems like she called him on a statement of his that was not careful and that she saw as misleading. Help me with this if you can Tom or Muon, if Tamino said Curry screwed up bad for making her statement that there is no evidence global warming hasn't stopped, wouldn't the exact same argument apply to Muller's statement? And since he made it first, isn't it more logical to see her statement as a correction of his? The second thing Muller said that seemed pretty crazy stupid was the comment in the WSJ article, ‘there were good reasons for doubt until now’. Read more: Curry said she critiqued him in part because of this comment. The site you referenced Muon makes the following statement at the end of the FAQ: Our study addressed only one area of the concerns: was the temperature rise on land improperly affected by the four key biases (station quality, homogenization, urban heat island, and station selection)? The answer turned out to be no – but they were questions worthy of investigation. Berkeley Earth has not addressed issues of the tree ring and proxy data, climate model accuracy, or human attribution. Why would answering this one question mean that there was no longer any basis for skepticism? The insinuation that there used to be a basis for skepticism but the only possible reason was potential inaccuracy in the temperature data is pretty silly and Curry called him on it. It seems like he has backed way off his strong interpretational statements of what the data means and is going back to what Curry said earlier, let the data speak for itself and let the project be simply about trying to make the cleanest and most accurate, publically available set of temperature data available.
  25. Rickoxo - the short answer is that what Muller said was correct, and what Curry said isn't. See our new post on the subject. The "good reasons for doubt" comment is a different issue. Reasons for doubting what? AGW? The surface temperature record? Frankly Muller is exaggerating the importance of the BEST results regardless of what specifically he was talking about, but exaggerating the importance of BEST is nothing new for Muller. BEST shouldn't have been necessary to accept the accuracy of the surface temp record to begin with. Regardless, Curry's statements were ill-conceived and inaccurate, as the new post discusses.

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