The title of this post might seem like a truism, but for about a decade some people have claimed the opposite, and many people have spent much time and effort trying to understand why. Much of that effort was wasted.
A decade ago, Nature Geoscience published Cohen et al (2014), a review paper on potential connections between the Arctic warming and extreme events (which has been cited an impressive 1449 times), which quite sensibly concluded that:
…improved process understanding, sustained and additional Arctic observations, and better coordinated modelling studies will be needed to advance our understanding of the influences on mid-latitude weather and extreme events.
However, within the paper were a couple of graphs that attracted a lot of attention. These were the following, showing northern mid-latitude extreme events from 1950-2013:
The change of trend from the late 1990s onward in the minimum daily average temperature in each winter is striking, and leads Cohen et al to discuss possible mechanisms for these unanticipated results (related to planetary waves, the jet stream etc.).
The data plotted are derivable from the GHCNDEX data available from Climdex. The description paper (Donat et al, 2013) for that data, has the following text:
… spatial coverage is one of the major sources of uncertainty when calculating global trends… Therefore, we recommend that appropriate masks for data completeness should be applied when analyzing time series of area averages.
A new paper, Blackport et al (2024) makes it extremely clear that this masking step is essential for the regions looked at by Cohen et al, and without it, the trends are compromised. The demonstration of this is shown on the right. First, Panel A shows that the GHCNDEX data has a very large coverage change – particularly in the 20-40ºN band (an over 50% drop). Applying a common mask over the period allows one to produce a consistent record, and that is done in Panel B. It is clear that the data drop out impacts the 1995-2012 trend, turning a slight positive trend into a large (and spurious) downward trend in line with the results shown by Cohen et al. The addition of ten more years of data confirms the overall story.
As a further confirmation, the masked GHCNDEX changes are an excellent match to the quasi-independent (and spatially complete) data from ERA5. It thus seems indisputable that the implications of the Cohen et al analysis were not valid.
Blackport et al also do a clear analysis of how well models match the (properly handled) observational data. With the corrected data, a multi-model ensemble does a very creditable job at tracking the trends in minimum temperature:
This is nonetheless a quite noisy system, and with short time periods one can find small regions where the trends go the other way (e.g. Cohen et al., 2024), but no recent analyses (that I’ve seen) support the large claims made in the original paper (see also Blackport and Screen (2020)).
It is therefore very likely that there is no mystery to be solved, no huge model-data discrepancy to puzzle over, and no counterintuitive result to set the scientists’ hearts racing.
Unmasking the problem
So what happened here, and why has it taken a decade for clarity to emerge about a result that was spurious at the time? This ties in to one of my frequent themes here related to the replication and reproduction of results. To be clear, scientists sometimes make mistakes, or more often, make assumptions about data that aren’t valid (and I have made my fair share). However, this was an analysis of publicly available data, using a methodology that the originators of the data had already flagged as problematic. Someone should have been able to point out the problems with the original data immediately.
Why didn’t that happen? I can’t say. I do know that the Blackport et al paper was desk-rejected by Nature Geoscience (the original publishers of the Cohen paper) in keeping with the known reluctance of journals to deal with comments and post-publication criticism (even if implicit) of their editorial choices.
Perhaps we still need to do work to build a scientific culture where routine replication and robustness tests are done by many people without the expectation that there is something wrong, but just as a basic check that conclusions are sound, and that discordances between models and observations are real, before we spend a decade looking for solutions to problems that don’t exist.
References
- J. Cohen, J.A. Screen, J.C. Furtado, M. Barlow, D. Whittleston, D. Coumou, J. Francis, K. Dethloff, D. Entekhabi, J. Overland, and J. Jones, "Recent Arctic amplification and extreme mid-latitude weather", Nature Geoscience, vol. 7, pp. 627-637, 2014. http://dx.doi.org/10.1038/ngeo2234
- M. Donat, L. Alexander, H. Yang, I. Durre, R. Vose, and J. Caesar, "Global Land-Based Datasets for Monitoring Climatic Extremes", Bulletin of the American Meteorological Society, vol. 94, pp. 997-1006, 2013. http://dx.doi.org/10.1175/BAMS-D-12-00109.1
- R. Blackport, M. Sigmond, and J.A. Screen, "Models and observations agree on fewer and milder midlatitude cold extremes even over recent decades of rapid Arctic warming", Science Advances, vol. 10, 2024. http://dx.doi.org/10.1126/sciadv.adp1346
- J. Cohen, J.A. Francis, and K. Pfeiffer, "Anomalous Arctic warming linked with severe winter weather in Northern Hemisphere continents", Communications Earth & Environment, vol. 5, 2024. http://dx.doi.org/10.1038/s43247-024-01720-0
- R. Blackport, and J.A. Screen, "Weakened evidence for mid-latitude impacts of Arctic warming", Nature Climate Change, vol. 10, pp. 1065-1066, 2020. http://dx.doi.org/10.1038/s41558-020-00954-y
I get it that with extremes data, e.g. lowest minimum temperature, if the area of coverage is reduced then it will miss more of the extreme events, do the data needs to be corrected upwards. However the data used by Cohen et al (2014) ends in about 2013 and the anomaly cited by Blackport et al (2024) occurs after this time. How does this affect the trends reported by Cohen et al?
Chris,
You ask of the “anomaly cited by Blackport et al … how does this affect the trends reported by Cohen et al?”
In the OP above, the graphics Cohen et al (2014) figs. 3d, 3f & 3h show the trends reversing from about 2000 and as you say the data used runs only to 2013.
Blackport et al (2024) show the levels of GHCNDEX data coverage including post-2013 in their fig 3 (shown in the OP above) and also in maps presented in their fig S5 in the supplementary materials. The maps show 2015 data is missing for pretty-much all of China and 2020 data missing pretty-much all of Asia except China. These are of course missing data which post-dates Cohen et al (2014). These are indeed big sets of missing data and would obviously make a total nonsense of the Cohen et al analysis if it didn’t account for their absence.
The pre-2013 missing data is not so obvious. Blackport et al show in their fig 3a an increasing level of missing data from a little before 2000 and the 2000, 2005 & 2015 maps in figS5 show increasing areas of the Middle East have data missing.
I would suggest it is failing-to-account for this less obvious missing-data that results in the trends reversing 2000-13 in Cohen et al (2013) fig 3, Had post-2013 data also been used without accounting for the missing data, the downward trend would have been precipitous, as shown in Blackport et al (2024) fig 3b above.
I don’t understand the term of the art “data masking” and why it is important in this study.
[Response: The data are on a grid, but the points with data on the grid change over time. Having a fixed (spatial) mask allows you to have the average over the same points for the entire time series. If you don’t do that, the average is over a very different spatial at each point and that can introduce artifacts. – gavin]
JD asks Gavin Schmidt:
“I don’t understand the term of the art ‘data masking’ and why it is important in this study.”
Gavin’s Response:
“The data are on a grid, but the points with data on the grid change over time. Having a fixed (spatial) mask allows you to have the average over the same points for the entire time series. If you don’t do that, the average is over a very different spatial area at each point, and that can introduce artifacts.”
In plain English, here’s what Gavin is saying:
When scientists analyze temperature data, they look at it on a grid (like a map divided into squares). However, the spots on this grid where they have actual data can change over time. Some areas might have data for certain years but not others.
To get a more accurate comparison of temperatures over time, scientists use something called a “fixed mask.” This means they only look at the places where they have data for the entire time period. If they didn’t do this, they would be comparing temperatures from different areas each time, which could create misleading results or “artifacts.” The mask helps maintain consistency and reliability in the analysis over time.
However, even this explanation is not completely clear.
The mention of grids is significant because temperature data is collected from different locations (temperature recording stations, satellites, etc.), and scientists divide the world into grid cells to organize and analyze that data. Each grid cell represents a specific fixed area on Earth, similar to dividing a map into a checkerboard.
When comparing temperature trends over time, using the same grid cells ensures that scientists are consistently analyzing data from the same locations. If data for a particular grid cell is missing in some years but present in others, that could skew the results. So, the “grid” provides the framework for organizing the data, and the “fixed mask” ensures they consistently use the same grid cells with data for the entire time period to avoid inaccuracies.
Without this grid structure, it would be hard to determine whether changes in temperature over time reflect real global trends or merely differences in data collection locations. Thus, the use of grids is crucial for making sure that comparisons are valid over time.
However, problems and concerns about potential errors or inconsistencies remain. Even within the same grid cell, the temperature data could come from different recording stations each year, and those locations might have varying local conditions due to geography, elevation, or weather patterns. While the system ensures data from the same grid cell is included each year, it doesn’t necessarily guarantee the data comes from the exact same locations within that grid cell.
In fact, discrepancies like these may affect every grid cell being compared globally in a specific analysis. Scientists do not check for this issue; they only monitor whether temperature data is reported in each grid cell for every year. If data is missing, those grid cells are discarded, leaving the rest in the dataset.
This approach could lead to inconsistencies, especially when different recording locations within a grid cell experience varying temperatures due to their specific surroundings. The concern about comparing “apples to apples” still stands—there could be variation within the same grid cell that isn’t fully accounted for, potentially affecting the analysis.
In summary, the correct understanding of “data masking” is that the data might not always reflect the same precise recording locations, even within the same grid cell. This could lead to variations or inaccuracies in the reported trends—variations that are never checked nor subjected to proper scrutiny.
Reflection and Implications
Reflecting on this issue, I find an important underlying discrepancy in the climate data comparison process that isn’t often discussed openly. While climate scientists emphasize the consistency of data within grid cells over time, they don’t always make it clear that data from different years may come from entirely different spatial locations within those same grid cells. Given variations in geography and local weather patterns, this could introduce inconsistencies that impact the reported trends.
My concern is that such assumptions remain hidden unless specifically asked about, making it difficult for the public to fully grasp the nuances of the data. Far too often, when intelligent, thoughtful questions are posed to climate scientists in public forums, these inquiries are dismissed, or worse, the person asking is blocked. This automatic resistance to scrutiny, possibly due to genuine fears of denier memes and personal attacks on scientists online, raises serious questions about transparency. Open and honest communication is vital, especially when the public is trying to engage constructively with such an important issue. The opposite can trigger more doubt and distrust in the public domain.
I believe raising this point is not only fair but necessary to improve climate science communication. Full transparency and proactive openness about the limitations and assumptions in data analyses would foster a more informed and engaged public discourse.
I hope this perspective will be considered in a spirit of cooperation rather than seen as an attack, as it is driven by a genuine desire for clarity. I am trying hard to avoid sounding confrontational while making my points clear—firm but polite.
Unfortunately, I suspect my comments here will attract unjustified criticisms, ad hominem attacks, and possibly lead to being blocked by users on social media like X or being banned from online forums run by climate scientists and activists.
I have often seen others offer well-reasoned, respectful critiques only to find themselves blocked or banned in certain circles. Climate discussions can be highly polarized, and some scientists or activists may view any challenge or questions as confrontational, even when they are not intended that way.
That said, remaining composed and continuing to raise important points, as I have here, will likely resonate with others who value open dialogue. This approach could encourage more productive conversations in the long run. Regardless, I will persist in sticking to facts, sound logic, and thoughtful questions, even if the response isn’t always what I’d hope for.
In Re to D(h)arma, 8 Oct 2024 at 11:47 PM,
https://www.realclimate.org/index.php/archives/2024/10/cold-extremes-do-in-fact-decrease-under-global-warming/#comment-825232
Dear Sir or Madam,
In the flood of your posts, I noted following paragraphs:
“Reflecting on this issue, I find an important underlying discrepancy in the climate data comparison process that isn’t often discussed openly. While climate scientists emphasize the consistency of data within grid cells over time, they don’t always make it clear that data from different years may come from entirely different spatial locations within those same grid cells. Given variations in geography and local weather patterns, this could introduce inconsistencies that impact the reported trends.
My concern is that such assumptions remain hidden unless specifically asked about, making it difficult for the public to fully grasp the nuances of the data. Far too often, when intelligent, thoughtful questions are posed to climate scientists in public forums, these inquiries are dismissed, or worse, the person asking is blocked. This automatic resistance to scrutiny, possibly due to genuine fears of denier memes and personal attacks on scientists online, raises serious questions about transparency. Open and honest communication is vital, especially when the public is trying to engage constructively with such an important issue. The opposite can trigger more doubt and distrust in the public domain.
I believe raising this point is not only fair but necessary to improve climate science communication. Full transparency and proactive openness about the limitations and assumptions in data analyses would foster a more informed and engaged public discourse.”
Personally, I somewhat doubt that you have discovered a mistake that can change the view on the topics discussed by Dr. Schmidt in his present article substantially. If you, however, think so, please try to be as specific as possible and strive to describe your observations and explain your objections in sufficient detail, so that experts like Dr. Schmidt or informed readers of this website like MA Rodger can grasp your point and assess its relevance.
In other words, if you have a substance which in your opinion may be valuable and useful for others, please be so kind and present it clearly and directly, without lot of unnecessary rhetoric around.
Best regards
Tomáš
While your opinion and rhetoric are noted, I’m curious about your own qualifications to judge either myself, Gavin, or climate science in general. Given your track record here, your position on this is, at best, questionable.
That being said, your question is valid. In response, I’ve revised my original “shoot from the hip” comment and published it on Substack. You’re welcome to follow up with any further inquiries there, where the conversation can be more productive.
I don’t wish to clutter this thread with endless back-and-forth. For the record, this is my sixth response to queries directed at me. Clearly, the topic has sparked interest, considering the pushback from so many commenters.
https://substack.com/home/post/p-149992528
In re to Dharma, 12 Oct 2024 at 2:07 AM,
https://www.realclimate.org/index.php/archives/2024/10/cold-extremes-do-in-fact-decrease-under-global-warming/#comment-825354
Dear Dharma,
Thank you for revision of your objections and the link to your publication thereof on Substack.
As a layman in climate science (I am chemist and patent engineer by education), I cannot assess if your interpretation of the masking process is correct or not, and similarly incapable am I as regards an assessment in which extent could e.g. the assumed changes in data reporting stations within cells influence the overall results.
Good luck on Substack, perhaps you find therein some experts who will help you.
Greetings
Tomáš
“Dharma” to Tomas: “ While your opinion and rhetoric are noted, I’m curious about your own qualifications to judge either myself, Gavin, or climate science in general. Given your track record here, your position on this is, at best, questionable.”
Strong claims for somebody who …. appeared here 2 weeks ago. You wouldn’t be by any chance a rebrand of the “Escobar” troll, who first tried to endear himself to Tomas with his pretend compassion:
Escobar: To Tomáš Kalisz. You have zero chance of any success at being heard accurately (in context, in kind) or being treated with respect here by anyone.
and when Tomas spurned his advances, has shown how much “respect” he has for Tomas:
“ I have not seen any improvement in your knowledge or gaining anything since arriving and focusing on your minutia issue. Comments by others indicate the very same observation.
What I see here daily is a frog in a blender on high speed. But again, if you enjoy this, I will butt out. I wish there was a block sender function so I did not need to see this depressing display. ”
And this is how you “treat others with respect”, the Escobar style …
Darma: “ For the record, this is my sixth response to queries directed at me. Clearly, the topic has sparked interest,”
What could have said a troll, who had defecated in the middle of a family picnic, to prove how fiercely iconoclastic he is ?
in Re to Piotr, 20 Oct 2024 at 10:25 AM,
Dear Piotr,
Thank you for your observation.
I am not sure about Dharma’s identity with Escobar, however, I am pretty sure that (s)he is present pretty long herein on Real Climate. His or her agenda, supported by references to sources like Jason Hickel who calls himself “marxistic ecologist” strongly resembles entities that previously appeared herein as “Ned Kelly”, “cj” or “Complicius”.
I very appreciate Kevin McKinney’s observation regarding eco-fascists. Eco-marxists or eco-fascists, they seem to be remarkable similar in my opinion.
Greetings
Tom
For Darma: https://www.realclimate.org/index.php/archives/2007/07/no-man-is-an-urban-heat-island/
A little addendum:
The semantics of these explanations are using different words for the same thing. When they say: “only look at the places”, and “from different areas each time”, and “these specific locations”, and “Each cell represents a specific area” – the words places, areas, locations and cells all mean and refer to the very same thing—“grid cells.” Using multiple words like “places,” “areas,” “locations,” and “cells” for the same concept (grid cells) is confusing.
Consistency in terminology would help make the explanation clearer. Here is an updated version of the explanation without using different words for the same concept:
The mention of grid cells is important because temperature data is collected from different locations (such as temperature stations or satellites), and scientists divide the world into these area grid cells to organize and analyze the data. Each grid cell covers a specific fixed part of the Earth, similar to how a map is divided into grid sections by latitude and longitude.
When scientists compare temperature trends over time, using the same grid cells ensures they are consistently analyzing data from the same grid cells. If data for a particular grid cell is missing in some years but available in others, it could distort the results, and so that grid cell is discarded from the analysis completely. This “fixed mask” process ensures that scientists only use the grid cells that have data for the entire time period being studied, preventing inaccuracies.
Without organizing the data into these grid cells, it would be difficult to tell whether changes in temperature over time reflect real global trends or just differences in where the data was collected. So, the use of grid cells is crucial for ensuring that the analysis is consistent and meaningful over time.
Thank you Gavin for yet another fascinating illumination that correctly (imo) ends by asking questions and making observations that encourages thinking about improvements needed. Particularly with the recent “Pluralism” post in mind.
Perhaps we still need to do work to build a scientific culture where routine replication and robustness tests are done by many people without the expectation that there is something wrong, but just as a basic check that conclusions are sound, and that discordances between models and observations are real, before we spend a decade looking for solutions to problems that don’t exist.?
Perhaps we still need to do work to build a scientific culture where a basic check on conclusions that show agreement between models and observations are also real?
Darma: Perhaps we still need to do work to build a scientific culture where a basic check on conclusions that show agreement between models and observations are also real?”
Perhaps you can speed up the process by YOU proving that “ the agreement between models and observations is NOT real“. Because that’s what you are implying, right?
So don’t wait for “the scientific culture” to do YOUR job – do it yourself – the onus of the proof is on the insinuator, not on their target. And how hard could it be – you didn’t take out your words out of thin air – so you MUST HAVE already some plausible information there agreement is NOT real, right?
Then put them up – for everybody to see.
Piotr, thanks for the reply, though I feel you may have misunderstood the intent behind my rhetorical question.
I was not implying that the agreement between models and observations is not real. My point, rather, is about ensuring that scientific conclusions—whether they show agreement or discordance—are consistently and rigorously tested. The spirit of scientific inquiry demands that both concordant and discordant results be equally scrutinized.
Your suggestion that I need to “prove” something misunderstands the process of scientific investigation. The strength of science rests not on proving preconceived notions, but on ongoing validation. Replication and robustness tests are essential to ensure confidence in both agreements and disagreements between models and observations. It’s not about burdening individual contributors with personal “proofs” but about building a culture where checking all conclusions—favorable or unfavorable—is a routine and expected part of the process.
This isn’t a matter of proving or disproving a singular point but about ensuring scientific integrity by applying the same rigorous standards across the board. After all, confidence in a model’s reliability grows not just from agreement with observations but from the consistency of that agreement across diverse studies and real-world data.
In short, my original comment highlights the need for us to avoid confirmation bias—both for agreements and disagreements. Ensuring that all conclusions, even those that align with current models, and the expectations of the scientific community, undergo proper testing and scrutiny strengthens the scientific foundation on which future decisions are made.
Best,
Darma
Darma, saying that rigourous testing and checking of all things scientific is desirable and that confirmation bias is bad is stating the obvious. You provide no evidence that testing and checking is not already rigorous. Remember scientists are taught to test and check things carefully and have many motivations to do this well, and theres a peer review process to check things, and this also gives people the opportunity to publish their own criticisms of scientific findings and models. The point is the testing process is already quite rigourous. You provide no evidence of confirmation bias.
I’m mystified why you state the obvious, unless you are a denialist trying to undermine the integrity of the present scientific processes and generally spread doubts. Your wording that “…before we spend a decade looking for solutions to problems that don’t exist.?” certainly makes me suspicious that you are sceptical about the climate problem. I could be wrong about you, but perhaps you could clarify your position on anthropogenic warming?
Nigelj, thanks for your reply. I’d like to first clarify that the phrase you’re suspicious of, “…before we spend a decade looking for solutions to problems that don’t exist,” is actually a direct quote from the author of the article I was originally commenting on. Ironically, if you’re skeptical of that statement, it’s the author’s position, not mine, that you’re critiquing.
It seems like you might have misunderstood the source of that line. Or have not read Gavin’s article in full.
Now, regarding your broader concerns: Yes, it’s obvious that rigorous testing, peer review, and the scientific method are cornerstones of modern science. My point wasn’t to deny or undermine that. I fully recognize that scientists are motivated to test and check their work carefully. But acknowledging that scientific processes are generally rigorous doesn’t preclude the need for constant vigilance against potential biases—including confirmation bias. No system is flawless, and no field is immune to human error or unintentional bias.
You ask for evidence of confirmation bias, but my point wasn’t to suggest that it is rampant or unique to climate science. Rather, it was to emphasize that confirmation bias, as a potential issue in any field of inquiry, deserves attention. Ensuring that rigorous scrutiny is consistently applied—especially in a field with such far-reaching consequences as climate science—only strengthens the integrity of the research.
Surely this was the driving point of Gavin’s entire article above.
As for my stance on anthropogenic warming, let me be clear: I am not a climate skeptic. I fully acknowledge the reality of human-driven climate change and its critical importance. My comment was intended to advocate for scientific rigor across the board, not to question the existence of the climate problem itself. It’s unfortunate that my call for thorough testing and scrutiny was interpreted as a denialist tactic. Ensuring strong science is key to addressing the climate crisis effectively, and that’s a goal we should all share.
My apologies overlooking to put quotation marks on that part of the text I used from Gavin’s article.
Dharma, I accept your explanation. However I still thiink you are stating the obvious, and unless you have a novel suggestion on how to improve things, you aren’t saying very much.
Mal: “By implying that there is unexamined confirmation bias in published climate science, you are abetting self-interested denialists, who never let up trying to undermine the scientific consensus for anthropogenic climate”
Darma/Dharma: I’m not abetting anyone,”
By their fruits, not by their self-interested declarations about themselves, you shall know them.
And we just have had the very same discussion with your fellow “sceptic” about the credibility of the climate science, Tomas Kalisz, who also declared that he is not abetting Russia and Saudi Arabia, the countries that stand to lose most if” the agreement between model sand observations IS real” and if based on it, the world moves off their oil and gas.
So I’ll just recycle it, after all – what’s good for a Tomas is also good for a Darma:
Piotr: “the very definition of Lenin’s phrase “useful idiots of Russia ” is that they either have NO IDEA that they play straight into Russia’s hands, OR they don’t allow a thought of this, when others point it to them.”
NIgel: “< Dharma, I accept your explanation.
Nigel, this may be a bit … premature. Dharma’s “ apologies [for] overlooking to put quotation marks” is sacrificing a nail to save a hand
D(h)arma’s main problem with his/her posts using problems affecting apples to attack …. oranges.
Gavin’s post is about a very specific case – 2014 Cohen et al . on mid-latitude weather events, which WRONGLY claimed the discrepancy between their observations and the model predictions of that rather narrow aspect of AGW.
Further – Cohen et al used erroneous methods DESPITE a clear warning from the data providers who explicitly warned in 2013 to NOT do what Cohen did a year later.
And this error opened their work to be used by the deniers to question the validity of the climate science
D(h)arma takes _that_ narrow in scope (weather events in mid-latitudes) and one that has ignored obvious red flags
and EXTRAPOLATES it onto “climate models” which
– by their nature already include extensive comparisons of the models with observations,
– since the results of these models have incomparably large societal consequences every aspect of modelling is subject to stricter verification
– while independent reproduction of the paper by Cohen should be relatively simple. To reproduce the results of massively complicated climate global circulation models one would need access to supercomputers and UNDERSTANDING how such a model works.
Thus D(h)arma proposes something that s/he knows or should have known, is NOT feasible
– D(h)arma IGNORES the fact the effective irreproducibility of a given model is compensated by running an entire group of independent models by various groups – so if one model got something spectacularly wrong – then it would be sticking out like a sore thumb from the rest of the models.
If it does not stick out – then either it is not wrong and the model predicts AGW well, or all models are wrong (and by the same amount), which in turn would require a … worldwide conspiracy of the climate modelers.
Now, by the Occam’s razor – which of these two possibilities is more likely?
You’ve never gotten to meet Dr. G. B. L. Warmer under his extinct hollowed out volcano???I have and he guided all my stats.
Your argument sounds reasonable only to someone who isn’t well acquainted with modern global scientific culture. Peer review of model skill at hind- and forecasting is continuous and unsparing at all times. As models become more sophisticated, errors are always being found, and fixed in the next release. Verification of the CMIP ensemble included in IPCC Assessment Reports is exhaustive. If you are here in good faith, the expectation that scientists will take still more time to replicate results they’re already confident of, suggests you think their spare time is copious, and you don’t grasp the importance of peer consensus. You are free to take the initiative, however. If you want to launch a replication project in the peer-reviewed climate-science literature, I await your first publication. If OTOH you’re not here in good faith, eff off.
Mal Adapted, I appreciate your response, but it seems like my point may have been misunderstood. I’m well aware that peer review of climate models is continuous, and I agree that errors are identified and fixed as part of that process. In fact, I wholeheartedly agree with Gavin Schmidt and other leading scientists on these matters and their efforts to ensure model accuracy. However, the issue involves a two-way street: the rigor in testing isn’t just about identifying errors; it’s also about maintaining a mindset that avoids confirmation bias.
The scientific method thrives on constant scrutiny from all sides, and while I understand that peer review is exhaustive, the barrier of confirmation bias is still a challenge that exists in any scientific discipline. I’m not asking for every model to be replicated from scratch but rather for there to be an openness to re-evaluating results when new data or perspectives emerge. Peer consensus is critical, but so is ensuring that consensus doesn’t prevent valid counterpoints from being considered.
As for taking the initiative myself—climate scientists like Gavin already do great work in ensuring that scientific rigor is applied. My role, like any casual observer committed to the principles of science, is merely that the importance of scrutiny is emphasized, whether or not it aligns with what’s currently accepted.
To dismiss a call for ongoing scrutiny as bad faith seems like an overreaction. Scrutiny is the foundation of science, not an attack on it. After all, robust models and consensus become even more credible when tested under the harshest critiques. Something which you yourself seem to savour applying at every opportunity.
Again, Dharma, your response sounds superficially reasonable, but identification of confirmation bias is among the basic functions of intersubjective verification in science, i.e. “peer review” broadly defined. By implying that there is unexamined confirmation bias in published climate science, you are abetting self-interested denialists, who never let up trying to undermine the scientific consensus for anthropogenic climate change any way they can! When you say:
Peer consensus is critical, but so is ensuring that consensus doesn’t prevent valid counterpoints from being considered.
You are implying there are “valid counterpoints” that aren’t being considered by anyone in the peer group of published international climate specialists, who all know what any of them does. Surely you’re aware that all manner of invalid counterpoints have been iteratively considered and rejected by peer consensus all along, yet repeatedly rise from the dead demanding brains to eat. From the perspective of the the members of the international specialist peer community, it’s on you to demonstrate there’s actually a need for trained, disciplined scientists to invest effort in more formal scrutiny of their process. Good luck getting their buy-in.
As for my savoring every opportunity to criticize harshly, blame that on the commenters who keep providing opportunities. You’d think newcomers would be at pains to avoid tone trolling or “Red Team” throwdowns, as if climate modeling is a cage match. At the least, you’re over-pluralizing your position. Why do you think your proposal has met with so much push-back? What makes you think your “counterpoint” is valid?
Mal Adapted, thanks for your thoughtful response. I appreciate your point about the role of intersubjective verification and peer review in addressing confirmation bias within the scientific community.
My original query was aimed at exploring whether the scientific community is as rigorous in confirming agreements between models and observations as they are in identifying discordances. To clarify, this discussion began with Gavin’s remark about building a scientific culture where routine checks on model/observation discordances are conducted to avoid wasting time on non-issues.
My question focused on the opposite side—whether there is an equally consistent effort to ensure that conclusions showing agreement between models and observations are real and robust.
The goal here is to promote transparency and enhance public understanding of the processes at work in climate science. It’s unfortunate that reasonable queries are often met with hostility and accusations. In public discourse, isn’t it more productive to welcome questions and seek clarity rather than consistently responding with accusations of denialism or partisanship?
For example, the comment “If OTOH you’re not here in good faith, eff off” seems unhelpful and detracts from meaningful dialogue.
I’m not abetting anyone, nor am I implying anything beyond the question at hand. I posed a straightforward rhetorical question aligned with Gavin’s stated principles and goals. It seems, however, that instead of addressing that specific question, the discussion has veered into hypothetical scenarios involving bad actors and conspiracy. I neither live in that kind of world nor wish to. But I thank you for your time anyway.
Darma:7 Oct 7″Your suggestion that I need to “prove” something misunderstands the process of scientific investigation.”
Yours is a subjective OPINION, expressing innuendoes NOT SUPPORTED by anything is NOT a part “the process of scientific investigation.“, hence the onus to prove YOUR insinuations about the lack of integrity of climate modellers is still on the insinuator.
Darma: “ I was not implying that the agreement between models and observations is not real.
By their fruits, not their declarations about themselves, you shall know them:
1. you implied that climate modellers are either stupid or dishonest – since they don’t do even “ a basic check whether the agreement between models and observations are real” or not.
2. you presume that models OVERESTIMATE the future climate change (if they didn’t – there would be no point for your opinion piece here)
Thus your reasoning and methods – straight from the denier’s handbook:
– “the science is not settled”,
– “the model predictions are not trustworthy”,
– “the climate scientists are either stupid or corrupt ”
– “the uncertainty will be our friend” – presumption that the real future would be LESS BAD than the models imply”
Nicely wrapped up with a classic deniers conclusion:
Darma: “before we spend a decade looking for solutions to problems that DON’T EXIST”
If it walks like a denier and quacks like a denier, then it is a denier.
P.S. Out of your 7 posts (almost HALF of all the post by all authors in this thread…) – 4 by “Darma”, and 3 by “Dharma”. Nobody to build a scientific culture for a basic check what your name is?
Piotr, while I appreciate that you’re passionate about your perspective, your personal attacks and mischaracterizations here are unnecessary, and they misrepresent my original points.
First, I never implied that climate modellers are “stupid or dishonest.” It’s quite a leap into fantasy domains to assume that any critique of modelling approaches automatically equates to questioning the integrity of scientists. What I did imply is that the methodologies used in climate models should be rigorously tested against observable reality—that’s a basic principle in scientific investigation. If you interpret that as an attack on the entire scientific field, that’s your projection, not my intention, and it’s certainly not what I said.
Let’s also clarify another distortion: suggesting a process should be improved or critically examined does not mean the science is “not trustworthy” or that it’s “all wrong.” There’s a vast difference between being skeptical of methodology and being a climate change denier. Constructive criticism is a normal and necessary part of scientific progress, as well as in public discourse. I hope you’ll learn to engage in that manner as you gain more experience.
Finally, your insults and attempts to discredit me by calling me a denier are not only unprofessional but reflect poorly on the open discourse we should be striving for in discussions of this nature. Personal jabs and assigning motives to others without evidence weaken your argument while undermining your own credibility, not mine.
As for the number of posts or a typo in the spelling of my name—it’s irrelevant to the substance of the discussion. The real issue here is your unwillingness to engage with my points fairly. Four of my comments were replies to people responding to me; this now makes five replies. I’m using the site as it was designed to be used, so your criticism on this point is again groundless.
If you’d like to have a productive discussion, I suggest focusing on the actual content and leaving the insults aside. Rational debate doesn’t need to devolve into labeling or personal attacks.
Dharma, you claim Piotr is misrepresenting what you said. I dont agree with that. I will take one key example, Piotr said : :”1. you implied that climate modellers are either stupid or dishonest – since they don’t do even “ a basic check whether the agreement between models and observations are real” or not.” I dont believe this misrepresents you. He is quoting your own words, and his interpretation that you are implying modellers are either stupid or dishonest is exactly what I thought from the start.. Its the only rational conclusion I could make..
Maybe you let your frustrations with the state of the science turn into being condescending to scientists. You could have admitted this and defused the isssue, or otherwise clarified what you meant..
You also claim you are being personally attacked. It people act badly they are going to get personally attacked sometimes, – as in criticised personally, and sometimes its quite justified. You have left yourself open to this. Of course it needs to be done without name calling (idiots etc,etc) and insults. Piotr was blunter than I would be, but he didnt resort to name calling or insults.
Dharma, primo voto Darma , 3 Oct. Piotr, while I appreciate that you’re passionate about your perspective
Spare me your duplicitous “appreciation” – a backhanded compliment, “praising” me on my “passion”, thus, while PRETENDING to be a compliment, in reality IMPLYING that my critique of your words is emotional, that is: not rational and that my arguments which I ground in universal logic that CAN BE falsified by anybody … you portray as entirely subjective, i.e., NOT OPEN to falsification (D: “ you’re passionate about YOUR PERSPECTIVE “).
D(h)arma: “ your personal attacks and mischaracterizations here are unnecessary”
That’s called “calling spade a spade”, which I BASE on presenting a FALSIFIABLE analysis of YOUR WORDS, proving you to be one.
Contrast this with your approach – your backhanded “compliments” to your opponents, and your innuendos NOT supported by any falsifiable proof., which when challenged, and unable to defend, you try to discredit by posing as a victim of “mischaracterization”. E.g.:
D(h)arma: “ First, I never implied that climate modellers are “stupid or dishonest. ”
WHAT ELSE did you imply by accusing modelers that they don’t know, or don’t want, to carry out SUCH a BASIC thing in science as checking whether:“the agreement between [their models and reality] is REAL” and therefore whether ” the conclusions [from these models] are sound “. And they that do so DESPITE the potentially massive social costs: “ we [could] spend a decade looking for solutions to problems that DON’T EXIST
And no, you CAN’T avoid explaining “what ELSE did you imply by that” – with an empty DECLARATION that my falsifiable analysis of the implications of your words – is a “ quite a leap into fantasy domains .
D(h)arma: “ Let’s also clarify another distortion: suggesting a process should be improved or critically examined does not mean the science is “not trustworthy” ”
WHAT ELSE did you imply when you claimed that the authors of that science … DON’T DO such a BASIC thing as: checking whether “the agreement between [models and reality] is REAL or not)” and therefore whether the conclusions [from their models] are sound“, AND as a result of which: “ we [could] spend a decade looking for solutions to problems that DON’T EXIST ???
D(h)arma: “ There’s a vast difference between being skeptical of methodology and being a climate change denier. ”
Yes – there’s a vast difference between being “ skeptical of methodology. AND INSINUATING, without any proof, that the climate scientist DON’T DO even the “basic check” that “their results are sound“, and based on that – ask the society to “spend a decade looking for solutions to problems that [may not] exist. .
.D(h)arma: “ Constructive criticism is a normal and necessary part of scientific progress”
“Constructive criticism” – yes. Insinuations based on one’s ignorance and ideological/ psychological confirmation bias (see above) by an anonymous Internet denier …. not so much.
As for you assuring us that you are not a denier (reminding me Nixon’s famous: “I am not a crook!”) see the characteristics of a denier I listed in the post to which you “reply”, which, if you want, I can append with those you have exhibited since.
If it walks like a denier and quacks like a denier then it is a denier.
Piotr says
15 Oct 2024 at 9:11 AM
Thanks for sharing Piotr, but I am going to stick to discussing the facts and logic of the issue. Making assumptions about personal matters and being all emotional helps no one. I am saddened that life has been such a struggle for you. May you eventually find peace and some acceptance of your life circumstances.
Try – https://www.youtube.com/watch?v=JRMOMjCoR58&list=PL2WtaJs6FmoOARZ66BqFgDt6dlCHOKUz7
Darma 16 Oct Thanks for sharing Piotr, but I am going to stick to discussing the facts and logic of the issue.
Put your money where your mouth is – here is my FALSIFIABLE analysis of your words –
so do you best with your “facts and logic”:
Darma: 3 Oct. “ Piotr, while I appreciate that you’re passionate about your perspective ”
Me: “Spare me your duplicitous “appreciation” – a backhanded compliment, “praising” me on my “passion”, thus, while PRETENDING to be a compliment, in reality IMPLYING that my critique of your words is emotional, that is: not rational and that my arguments which I ground in universal logic that CAN BE falsified by anybody … you portray as entirely subjective, i.e., NOT OPEN to falsification (D: “ you’re passionate about YOUR PERSPECTIVE “).”
So show off your “facts and logic” by PROVING that you appreciation WAS sincere, and not a backhanded compliment IMPLYING that my critique of your words was emotional, that is: not rational.
D(h)arma: “ your personal attacks and mischaracterizations here are unnecessary”
P: That’s called “calling spade a spade”, which I BASE on presenting a FALSIFIABLE analysis of YOUR WORDS, proving you to be one.
Contrast this with your approach – your backhanded “compliments” to your opponents, and your innuendos NOT supported by any falsifiable proof., which when challenged, and unable to defend, you try to discredit by posing as a victim of “mischaracterization”.
What, no witty comeback ?
D(h)arma: “ First, I never implied that climate modellers are “stupid or dishonest. ”
P: WHAT ELSE did you imply by accusing modelers that they don’t know, or don’t want, to carry out SUCH a BASIC thing in science as checking whether:“the agreement between [their models and reality] is REAL” and therefore whether ” the conclusions [from these models] are sound “. And they that do so DESPITE the potentially massive social costs: “ we [could] spend a decade looking for solutions to problems that DON’T EXIST
So – “WHAT ELSE did you imply” here? Feel free to impress us with your “facts and logic”..
D(h)arma: “ Let’s also clarify another distortion: suggesting a process should be improved or critically examined does not mean the science is “not trustworthy” ”
P: WHAT ELSE did you imply when you claimed that the authors of that science … DON’T DO such a BASIC thing as: checking whether “the agreement between [models and reality] is REAL or not)” and therefore whether the conclusions [from their models] are sound“, AND as a result of which: “ we [could] spend a decade looking for solutions to problems that DON’T EXIST ???
Again, WHAT ELSE did you imply here? Give an ALTERNATIVE explanation and one that is
more PROBABLE than mine. After all – you must know what you imply in your own posts, so how hard could this be ?
So?
Darma: You’re suggesting that scientists should do science? What an idea!
You’re several decades behind on climate science. Because they’ve been under constant attack by people who think they’ve just found something new to attack, and are intelligent and skilled, they’ve done exactly this in every possible way, again and again and again.
Throughout centuries, science has studied ways to observe objectively and check their conclusions. They don’t always succeed, but the hypocrisy and stupidity you imply belongs to the field of ‘alternate facts’ and lies trying to substitute for real facts, the truth, and reality.
For some checking on the sources (if you have any) of your counterfactual claims, try DeSmogBlog, Skeptical Science, Open Secrets (for the vast funding from wealthy and powerful interests), and many other honest sources.
Real scientists are skeptics. What you suggest is not skepticism but denial.
Susan, I appreciate your passion, but it seems like your interpretation of my comment was unnecessarily hostile and missed the actual point I was raising. Nowhere did I imply that scientists are not already doing their jobs or that they lack intelligence or skill. Suggesting that my call for ongoing scrutiny of scientific conclusions equates to hypocrisy or stupidity is both unfounded and unfair.
If you took the time to read my comment carefully, you’d see that I’m reinforcing the idea that science thrives on constant evaluation—something that has always been a hallmark of the scientific method. I wholeheartedly agree with Gavin on these matters, and I am supportive of his calls for better scrutiny and ensuring that scientific models are as robust as possible. Waiting a decade for solutions to problems that might not exist is far too long a wait. We must act based on the best evidence available while continually scrutinizing and improving that evidence.
The fact that climate science has faced criticism from bad-faith actors does not negate the importance of maintaining high standards of review, especially in a field that’s so crucial to global decision-making. If anything, this scrutiny should be welcomed rather than dismissed as ‘denial.’ Is this not precisely what Gavin has done here? I believe it is.
As for your recommendation to check sources, I am well aware of the influence of misinformation in this space, and that’s exactly why my comment emphasized the importance of rigorous scientific practice. I do not traffic in ‘alternate facts’ or misinformation—my concern is for the ongoing integrity of the scientific process. Real scientists are indeed skeptics, and it’s through that skepticism that the best science emerges.
What I’m advocating for is ensuring that, in the face of both agreement and dissent, conclusions are always rigorously tested and re-evaluated. This only strengthens the trust we place in science, rather than undermines it. Thank you for listening.
Thanks Dharma. I’m glad you are paying attention. I did read your comment, and my reply may have been a mite snarky, but I stand by my claim that in this space, and other climate science areas, special rigor has been observed and practice for the reasons I presented.
I am not myself a scientist, only scientist adjacent, but have spent major time in multiple roles (student, colleague, teacher, friend) with some top people, including PW Anderson (and a passel of physics Nobelists, including Hopfield who was a family friend) and Richard Feynman. In my own field of expertise, I found scientists who took up drawing were the best students, because they were ready to accept what they didn’t know, willing to cast aside their preconceptions, and eager to take the chance/risk of trying without fear or bias.
Susan, funny thing… I’ve found artists who took up science to be the best students, for exactly the same reason.
Zebra, thanks. [fwiw, I will be taking a break for several days because I am busy opening my studio for (Boston) Fort Point Open Studios this weekend. If anyone is in the area:
https://www.fortpointarts.org/programs/open-studios/
Susan-san, best luck with your opening, Hope it goes very well.
You’ll have to get more specific. Who exactly is doing the bad science?
“Perhaps we still need to do work to build a scientific culture where routine replication and robustness tests are done by many people without the expectation that there is something wrong, but just as a basic check that conclusions are sound, and that discordances between models and observations are real, before we spend a decade looking for solutions to problems that don’t exist.”
Some recent echos from the field of water sciences:
https://doi.org/10.5194/hess-28-4127-2024
https://www.nature.com/articles/sdata201930
How about a new journal, “Nature Replication” — specifically for grad students to replicate recent results? Grad students get published, research gets replicated — seems like a win-win.
I think that would be a great idea! Can some professionals approach something like Elsevier and try to get this started? I’d be willing to sign onto a petition.
Wonderful idea tamino!
That said, I’m reminded of a Masters student at my institution who decades back discovered world class Ediacaran fossils on bedding planes at Mistaken Point while on a picnic! This included many previously undescribed forms and seem to be deep sea vent organisms. They got their quite deserved Nature pub along with their completed theses! But a dedicated journal geared towards replications is a very creative idea.
Thanks for this post, Gavin.
Together with colleagues, I have a paper in press in Science Advances that presents a global picture of record-hot and record-cold years, as well as the fraction of the earth’s surface area with extreme hot and cold daily temperature. Our conclusions are in line with the title of your post: we are seeing fewer cold extremes.
This is fantastic. I recently completed a tree-ring study which shows the same thing and had it published here:
https://www.hyzercreek.com/Manns_Law.html
Thank you!
Interesting post. Also had a recent paper desk rejected from Nature Communication that strongly qualified findings previously published in Nature Communication. This is not how this is supposed to work in my opinion. Journals should embrace updates, replications and different interpretations as part of the normal scientific discourse. Interesting twist with Blackport and al. 2024 is that there is overlap in authorship of Cohen et al. 2014. Scientists are apparently ahead of journals in their ability to update their views given additional data and analysis.
I don’t have the patience to go through all of Darma’s ramblings, but I wonder if they’re aware that temperatures are referenced as anomalies relative to a baseline, not as absolute temperatures?
Yes one station in a grid cell may be 1000 feet higher than another and therefore colder, but if all the stations within a cell warm by 2C, it doesn’t matter which cells are present or absent from year to year – they all say 2C warming. Whereas it does matter if huge swathes of land 1000km from the sea and prone to cold winters are present or absent year on year.
Yes there are exceptions – for example I grew up on moorland 600 feet above the nearest city, and there’s a panoramic video on YouTube shot from a nearby hill. One commenter noted a temperature inversion in the valley, i.e. on that winter’s day the valley was cooler than the hilltop. However that was only interesting and worthy of attention because it’s a rare event, and not something that would contaminate a result based on hundreds or thousands of cells, day after day or averaged over weeks. It’s a nit not even the keenest picker could successfully pick up.
You also have to consider the correlation length. For longer-term climate records I recall from kriged studies that the correlation length is more like thousands than hundreds of kilometres, i.e. many grid cells, in any modern model other than a geological one which is stepping through millions of years. Weather events are shorter, but Atlantic storms and fronts are BIG. Anyone looking at the weather maps if the British Isles last week will have seen that while there were days when half the map was a lot colder than the other half, either side of a front, we were still talking about near-uniformity of pattern on the 500-1000km length scale.
The reason scientists don’t waste time sweating non-issues is implicit in the “non” part of the name.
The article written by Gavin states that cold extremes will decrease in a warming climate, however there’s a convincing argument for more extreme cold snaps due to increased disturbance of the polar vortex.
In addition to that article, there are more arguments for a slowing AMOC to cause a Little Ice Age – which will cause increase in cold snaps and more extreme cold snaps
How can both arguments be valid – less extreme cold extremes and more extreme cold extremes?
Does one argument invalidate the other – if so – which result is wrong?
https://theconversation.com/extreme-cold-still-happens-in-a-warming-world-in-fact-climate-instability-may-be-disrupting-the-polar-vortex-221276