by Marcia Wyatt
This past summer I was asked to give a presentation on science and ethics. The person who asked me was motivated by the Pope’s encyclical, the comments regarding climate change.
The group to which I was to present – its members most interested and well-informed about climate, yet also confused by the strong opinions of dignitaries and luminaries, such as the Pope – wanted a climate scientist’s perspective. I could not help them with their ethical outlook, but I realized what people really need is not the tit-for-tat, back-and-forth endless debate, with each side being “right”; they needed to understand that we scientists really don’t know what climate is doing or will do! No one does. We only have degrees of uncertainty. Thus, the presentation evolved, with the originally requested topic modified to discuss my perspective on the uncertainties in climate science. After giving the talk, I realized there could be many versions of such a presentation, with different levels of detail and scientific background. I would like this information to be communicated to the public, as well as to college and high-school students. In the past, I could ignore the dissemination of misleading information to the general public. No longer can I. The stakes are too high; the consequences too dire.
Uncertainty in Climate Science
The complete .ppt presentation can be downloaded here [http://www.wyattonearth.net/images/Uncertainty_in_Climate_Science_10_9_2015.ppt]
Introduction:
Word “around town” is that science is truth. Sorry to damp the zeal, but science is NOT truth. By definition, science equates to varying degrees of uncertainty, with hypotheses and theories bookending the uncertainty spectrum – to some, a rather boring outlook. Hypotheses – suggested explanations for how things work, and based upon observed evidence, offering potential prediction of phenomena whose correlative relationships may be causal – must be both testable and falsifiable. A hypothesis cannot be proven to be true; it can only be proved false. For a hypothesis to be elevated to theory – a rare and significant promotion – the hypothesis must survive multiple replications of results with a wide set of data, and it must be tested under a variety of circumstances. Even then, while uncertainty of a theory is minimized; it is never zero. Hence, science is the constant process of trying to figure out how things might work. To a scientist, this is exhilarating. To the non-scientist wanting a solid answer, not so much!
Well, this is all relatively bad news for those of us who study climate. Climate, by nature, does not lend itself well to being tested. We can’t isolate its parts and study them in a lab. We can’t condense decades and millennia into hours and days in order to extract multiple data points and long records. Intertwined and multiple “parts” of the climate system render its evaluation stymied by the endless unknown unknowns! So what do we do? We seek out proxy data – riddled with caveats. We invoke computer climate models – riddled with caveats. No matter which way we turn, we are faced with caveats, but it’s the best we’ve got. Sometimes “we” get so used to working within these constraints imposed upon us, we begin to lose sight of our assumptions, and the attendant biases, caveats, and uncertainties laced throughout our research format. In time, it is not difficult to see how we come to believe the little fantasy world we have made for ourselves in attempt to make sense of nature’s vast stomping grounds. And when it is demanded of us to stop equivocating, to make the discussion short and sweet, packaging into sound bites the complexities of 4.6 billion years’ perspective on climate and how its changing character of today differs from any time past and how we humans and other earthly creatures will survive an onslaught that, by human perception, appears unprecedented and unendurable; “What can we do”!!!! Politics enters the stage, followed closely by celebrities and media. Messages are surgically edited to be woven into stories far more captivating than those told by the equivocating egg-heads; and photographers, accompanied by narrators with scholarly accents and compelling rhetoric, come in to educate the public. And the public find no choice but to believe. Uncertainty is forgotten, actually no, it is abandoned. Uncertainty is not for the impatient. Good intentions pave the path forward. So where does that leave us? How does one make policy decisions based on science, with uncertainty’s role demoted to nuisance status?
It might be of interest to know that historically, skepticism has fueled forward movement of scientific discovery. Uncertainty has always motivated inquiry. Conversely, certainty has squelched it. Certainty entrenches paradigms. Examples dot history of paradigms kept on life support with increasingly complicated constructs to explain phenomena or occurrences inconsistent with hypothesized dynamics and behavior – the 1600-year-long geocentric model being a most vivid example. Upending of faulty paradigms often relies on evolution of technology. New evidence reveals surprises – those “unknown unknowns”. Ironically, those most educated in a field often are not the ones in history to have revolutionized thought. Lay persons and scientists of different specialties often were the ones who “saw” what was hidden from the hardened mental filters of those overly invested in a paradigm’s survival. Skepticism has gotten a bad rap in recent years. Instead, it should be embraced. It is skepticism – not conformity – that provides the checks and balances to humans’ tendency to see the expected.
How does one make good decisions in context of uncertainty? One must gather good evidence – not hearsay, not sound bites, nor “consensus”. Good evidence can be garnered only through understanding how conclusions are reached – the methodology and data used to construct them. This is not easy, but just accepting what others say – their filtered conclusions, even those of “respected” scientists or trusted dignitaries – not investigating the scientific process employed in generating a conclusion, and not exploring alternate possible explanations for observed phenomena, destines its victims to the unintended consequences.
Scientists do agree: Temperatures have increased since 1850; CO2 has too. CO2 is an infrared warmer. With no positive or negative feedback responses, a doubling of it will lead to an approximate 1.1ºC temperature increase. Disagreement erupts over just how much temperature has risen; what part is due to CO2; what part to land-use changes; what part due to natural or intrinsic influences. How well do models represent climate; what is climate’s sensitivity; are the data reliable? Is there really a problem? Is it a problem that can be solved with proposed solutions? And what are potential consequences of proposed solutions? It is said to be certain, to be “settled science”. Really!?!
1.Hypotheses overview: More than one hypothesis can explain observed behavior.
Two general and contrasting views exist on climate behavior. One view is the “consensus” hypothesis, where external forcing – both natural and anthropogenic – dominates climate behavior (“climate change”) — a modification of the former anthropogenic global warming (AGW) hypothesis. The contrasting view allows a greater role for internally generated dynamics, especially on decadal-plus time scales.
According to the external-forcing view, parts of a system operate relatively independently; the system is prone to instability, is not resilient, and, with continued anthropogenic greenhouse-gas-emission increases, is projected to result in catastrophic climatic changes.
In contrast, the intrinsic-dynamics view envisions network-behavior dominating climate behavior, where parts of the ocean, ice, and atmosphere sub-systems self-organize over decadal-plus time scales, interacting with one another, and thereby initiating intra-network communication, conveying resilience and relative stability to the climate system.
The external forcing hypothesis is based on strong understanding of greenhouse-gas forcing, but low-to-very-low levels of understanding of other external forcings – clouds, aerosols, solar influence, for examples. Extreme increases in projected temperatures rely on incomplete understanding of reinforcing consequences of the original CO2-induced warming, i.e. positive feedbacks. Little is understood about potential damping mechanisms – e.g. clouds, aerosols, atmospheric convection, and precipitation. Likewise, little is fully understood about, or attributed to, intrinsic dynamics. None of these weaknesses guarantees this hypothesis is wrong, but the uncertainties involved are striking. More striking is that the hypothesis is not testable. It cannot be falsified. The alternate hypothesis, the network hypothesis, is rooted in observation, among a variety of indices. Mechanisms have been elucidated as possible dynamics underlying climate-signal evolution. Uncertainties underlie this hypothesis, as well. Yet, its strength lies on observations. They are consistent with the hypothesis, and in time – years to decades – this hypothesis is testable and falsifiable.
2. Models: Hypotheses, themselves, models are good tools, yet not “reality”.
Computer climate models – complex, incomplete, and flawed – have failed to capture the temporal and spatial signatures of observed climate behavior. Great tools, they are, but they, themselves, are hypotheses. Each one is an experiment, of sorts. A climate model can be thought of as a script, taking orders from computer programmers in the form of complex mathematical equations. Increased complexity of input is expensive and time-consuming. Hence, simplifying is required. Lost is the ability to capture details of climate phenomena too large or too complex for the model-grid’s scale of resolution. To compensate, some “assumed-to-be unimportant” phenomena are omitted entirely; other phenomena are parameterized, meaning simple empirical formulas are used to represent the collection of phenomena as best as understood, with adjustable coefficients inserted – thermostats, of sorts, “tweakable” to fit observations. This does not mean output is necessarily wrong, but it does mean uncertainty looms in procedure and in results!!! A major problem arises when model outputs are considered to be “reality”.
3. Data: Ah yes, the data…
“But the data!!!” exclaimed the woman, hurriedly removing herself from my presence in undisguised disgust. All I said was, “climate is complex”.
This is an unfortunate tale. Few realize: Data records are a mess. That’s the short version. The long one is filled with justifications and fixes. In short, climate is long-term behavior and we don’t have long-term records. The longest instrument temperature records we have are patchwork compilations of temperature readings gathered from various and evolving technologies and varying degrees of instrumental precision. Confounding consistency are continual changes in measuring distributions; numbers of reporting stations; extent of coverage; and required conditions of the measuring stations; etc. Assumptions rule the temperature record. When we see data that make no sense, we speculate why. If the instrument, technology, conditions, and the like seem sketchy, we “document” such and “assume” what climate conditions likely existed and therefore what temperatures should have been recorded, based on a variety of guidelines, and we change the recorded temperatures to what we think it maybe really was….
The motivation for adjusting data is honest; at least we hope it is. A recent increase in the frequency of data adjustments in temperature trends has raised red flags, with findings of undocumented changes, questionable extrapolation practices, and computer-initiated “homogenization” changes made according to assumptions. Some argue that where assumptions might have trumped accuracy, the number of errors is so small as to not present a problem. Yet, it seems yesterday’s data sets showed variability over the years. Now the warm 1930s and 1940s have been erased, relegated to mythology. We shiver as we are told of the “warmest years on record” by hundredths of a degree, and with minor data re-calculations, “pauses” in observed temperature trends disappear overnight, and we are told to accept this, and we do, in light of all the uncertainties. Can this be???
There is more than one way to evaluate temperature. Four categories commonly used include surface thermometers, satellite-retrieved measurements, balloon-mounted instrumentation, and proxy data. None of these temperature trends match the modeled trends. Quantitatively, among the four temperature records, while their trends are analogous to one another, the magnitudes of their trends are not. Surface temperature-trends are steeper than satellite-retrieved and balloon-based temperatures; while satellite and balloon temperatures are similar to one another. Tree-rings buck the trend further, with one of cooling since 1940, most strongly since the 1960s. Tree-rings, depending on tree species and location, capture a variety of information – e.g. moisture content, sun exposure, and also temperatures, generally maximum ones. On the other hand, much of the increase observed in surface instrumental land-temperature increases can be attributed mostly to increases in minimum temperatures, which, when averaged with their daily maximum counterparts, reflect increase. Satellite and balloon instrumentation infers temperature of the lower troposphere, where greenhouse-gas warming is supposed to be greater than surface warming. Thus, all methods differ in where and what they measure. All temperature data are further enhanced by extrapolations of “neighboring” stations, some up to 1200 km away, as in the Arctic – the region known to host the widest extremes in temperature on multidecadal timescales. Sea-surface-temperature measuring methods have their own story. And then we model data – or reanalysis products – to infill “missing” data points. And sometimes we mix modeled data with observational data, subtracting one from the other, in order to evaluate climate. But right or wrong, accurate or inaccurate, this is what we have. Judgment on such is not the point here. The point is uncertainty – bias is potentially injected at every step of “settled science.
4. History: In contrast with the data, history speaks of variability and precedent…
Archival records speak to hot intervals – “The Arctic Ocean is warming up, icebergs are growing scarcer; in some places the seals are finding the water too hot…a radical change in climate conditions and hitherto unheard-of temperatures in the Arctic…well-known glaciers have entirely disappeared” (Washington Post: November 2, 1922). And in 1933, the New York Times: “America in longest warm spell since 1776…a 25-year rise.” And again in 1947, the New York Times: “A mysterious warming of the climate is slowly manifesting itself in the Arctic, engendering a serious international problem…”
And history tells us of cold – July 18, 1970, New York Times: “The United States and the Soviet Union are mounting large-scale investigations to determine why the Arctic climate is becoming more frigid, why parts of the Arctic sea ice have recently become ominously thicker and whether the extent of that ice cover contributes to the onset of ice ages.” Fortune Magazine in February of 1974 warns of a “…very important climate change going on right now… not merely something of academic interest….if it continues, will affect the whole human occupation of the earth…”
A longer view of climate, one supported by thousands of papers pre-dating the 1990s, showed pronounced variability and warm intervals equal to those of today, the most recent of which was about a thousand years ago. Studies in the late 1990s removed that variability. And while the science behind the historical climate revisions has been challenged and shown flawed, the public perception of past uniformity lingers.
5. Consensus: Not a measure of scientific validity.
Science has always been a story of revision. Consensus-based paradigms come and go. The geocentric model endured for 1600 years. But consensus plays no role in scientific validity. Yet, one can understand their evolution. Limitations of technology, egos, hardened mental filters, and the like can contribute to a flawed paradigm’s endurance. Typically paradigms are perpetuated by the best educated. Those not immersed in the field and not financially tied to the discipline were the one who saw through a different filter and revolutionized a science that was not necessarily their area of expertise.
Sometimes scientists find themselves split between being scientists and being useful to society. Most have read the words of scientist Stephen Schneider, now deceased, but once a scientist at NCAR: “We are not just scientists, but human beings…We have to offer up scary scenarios, make simplified, dramatic statements, and make little mention of any doubts we might have…” And then that of an NCAR scientist (to remain unnamed) who spoke to a class of mine in 2007, “We should not talk to the politicians about our doubt or the uncertainties of our model output; we should keep that among ourselves, when we are talking to other scientists. It is our moral duty to express certainty.” Yes, scientists are human…
The diagram that follows traces my view of how today’s consensus evolved.
The left side shows the IPCC* conclusions and goals feed the federal funding for grants given to scientists to study, specifically, the effect of anthropogenic CO2 emissions on climate behavior (AGW: anthropogenic global warming). This is the “external-forcing-dominant” paradigm. Thus, the funding feeds the AGW hypothesis. In turn, the hypothesis inspires the computer-climate-model designs. The modeled output, in turn, has led slowly to the observed data being adjusted, as the observed data records tend to be inconsistent with “theory”. The data, while fed by models and hypothesis, in turn, feed the hypothesis. Studies supporting the consensus hypothesis are easily published, review processes more streamlined and lenient than with studies whose conclusions do not support the hypothesis or are neutral. This all dove tails with media promotion, typically highlighting only AGWsupporting conclusions and not the methodology and data used to derive the conclusion, and not the author’s noted limitations and weaknesses of the study and its conclusions.
The right side shows the fate of a non-AGW hypothesis: The IPCC does not fuel funding for the hypotheses that are not “AGW”, those that tend to argue for a strong role for internally generated dynamics (intrinsic variability). In the case of an alternate hypothesis, the data inspire the hypotheses. The historical data feed the hypothesis. Modeling with the atmosphere–ocean coupled general circulation models (AOGCMs) used for IPCC-related research do not support these hypotheses; it is assumed that critical dynamics are either absent or poorly represented in the AOGCMs.
White asterisks: modified and modeled data. .Red dotted line: no correlation. Blue arrow: arrow points from end member that supports the other. .Red arrow: arrow points to end member being driven by other member. Red dashed double arrow means the two end members are consistent or supportive of one another.
6. Perceptions/Reality: Things aren’t always as they seem.
“Photo-journalism and social media have enhanced our understanding of the world. They bring to our eyes, and our hearts, the enormity of global changes that imperil our future.” This eloquent statement, said to me recently by an acquaintance, was followed by an attempt to boost the credibility of her words – “And I’m a Republican”! Yes, I understand the political framing, much as I rebel against it – as it has no place in science – but that is today’s reality. And she was on to something; indeed, photo-journalism and the power of social networking have scripted our perceptions and redesigned reality for our consumption. But, behind every photograph of a stranded polar bear, of mountain glaciers shrinking, of drought-ravaged landscapes, of tornado-inflicted devastation, of flooded neighborhoods, of pounding seas and calving glaciers, hurricane-pounded surfs and ice-locked shipping ports, our impulse to assign cause to effect confounds our ability to reason, to see the story behind the sensation.
For examples: Polar-bear populations have rebounded, especially since the hunting rules were changed in the 1950s. The bears have redistributed their populations within the Arctic, and for those in regions of greater ice loss, the white giants have been found to exhibit “foraging plasticity” – i.e. they are changing their diets[1]. In the cases of droughts, hurricanes, weather events, etc – many exhibit decadal to multidecadal cyclical behavior, with human population shifts further modifying the trends – not shown to be due to global warming, but through land-use changes, through changes in perception about the events due to where population centers have migrated, and to greater exposure due to 24/7 news and a camera phone in every pocket. Calving glaciers are calving because they are growing; retreating glaciers, especially mountain glaciers, are retreating for a variety of reasons – while rising temperatures certainly play a role in some cases, little evidence supports global warming as the main culprit. In fact, mountain glaciers are really bad thermometers – adjacent glaciers may exhibit opposing trends, with one advancing and the other retreating. Much of the retreat witnessed in glaciers occurred long before carbon-dioxide emissions were prominent. And precipitation patterns, winds, solar-insolation patterns are among factors dominating the behavior of these alpine features. Sea-level-rise is occurring at a rate about 2mm/year, depending on the study cited. A cyclical component underlies a linear one. Complications in measuring and comparing current to historical measurements confound clear assessments. Greenland and Antarctic ice sheets, if melted, would contribute the most severe consequences to rising water, but dynamics are complex and our understanding of them not at all imbued with certainty.
Scientists compound the misperceptions at times. The famous study by Parmesan et al (1999)[2], associating warming with the poleward-migration patterns of butterflies in northern Europe is one such example. A shift has been documented, but a conclusive reason was far from established, a direct link to temperature not forthcoming. But the “conclusion” was promoted anyway. The uncertainties laid in the inconvenient – about third of the 35 species studied moved north with warming temperatures; approximately two-thirds expanded north, not abandoning their southern bounds. A small percentage actually shifted southward with increasing temperatures. The list is long of these ambiguities in study results – none pliable within sound bites, herein muting the message of uncertainty!
(“Possible consequences of global warming” – an essay: www.wyattonearth.net “investigations into climate and geology” page)
7. Solutions: Everything is a tradeoff. Beware the fix being worse than the problem.
There is the view point that we should just ‘do something’, just in case… And argument can be made for this opinion. But arguments can be made against too, many laid out in this text and its accompanying Power Point presentation.
Regulation is one approach toward a solution. Will there be unintended impacts? Economic? Environmental? What countries will comply? CO2 knows no boundaries. And most importantly, what “correction’ in the climate-change trend can be effected? Will our best intentions curtail warming significantly? By some estimates, a 40% decrease of CO2 emissions in the United States, alone, will avert a scant 0.016ºC of projected warming by 2050, assuming a climate sensitivity of 2ºC.[3] And if climate sensitivity is assumed larger, at the high end of estimates, say 4.5ºC, then the temperature-increase averted by 2050 will be 0.025ºC, and by 2100, 0.056ºC. Bring all industrialized nations under regulatory control, and if the collective reduction of emissions is 20%, with an assumed climate sensitivity mid-range, at 3ºC, the temperature-increase thwarted is estimated at 0.025ºC; by 2100, 0.045ºC. Is the science settled enough to justify the drastic economic adjustments required for the projected solution realized? What level of uncertainty is acceptable?
And seeking energy resources that provide beneficial alternates is not at all a bad thing, for a variety of reasons, not just environmental. But caution is warranted, as with good intentions, there is always a trade-off, usually hidden behind the good feeling of “doing something”. For example, wind turbines: Just a few months ago, the German medical community requested a halt to further turbine installation until the health impacts of turbine-associated low-frequency noise can be further studied. Perhaps stories of dying sheep and goats due to sleep deprivation and reported human problems of headaches, dizziness, nausea and insomnia associated with noise from the whapping blades hold merit. Birds and bats are casualties – hundreds of thousands each year, with trickle-down consequences on insect populations (increasing mosquitoes, for one). Costs and pollution of associated fossil-fuel use are a dirty secret, a consequence of “on-demand” backup requirements, consequent of wind’s inconsistent presence. Local weather changes result from turbine-altered wind patterns. And solar solutions are not without issue. Manufacturing-related leakage of SF6 and NF3 – greenhouse gases 23,000 and 17,000 times as potent as CO2; reduced albedo (reflectivity) in desert areas due to acreage covered in black panels; and birds vaporizing in flight over hot panels. “Clean” trucks, newer than five-years-old, in Europe, are associated with unexpected increases (34%) in black carbon emissions – soot – a warming agent.
These points are a small sampling of the many documented issues of re-designing our energy use. Not that re-structuring would not be worthwhile to strive toward, but we have talked about this goal for at least forty years and little progress has been made. It must be realized that every source of generating and transmitting energy comes with trade-offs. None are without flaws and detriments.
Deciding on action is difficult, a personal opinion. Understanding the level of scientific certainty of the proposed problem is one step toward that decision. How settled is the science? How much uncertainty hides behind the loud voices and compelling photographs?
[1] Gormezano and Rockwell (2013): What to eat now? Shifts in polar bear diet during the ice-free season in western Hudson Bay; Ecology and Evolution 3(10):3509-3523; doi:10.1002/ece3.740
[2] Parmesan et al. (1999): Poleward shifts in geographical ranges of butterfly species associated with regional warming; Nature 399, 579-583; doi:10.1038/21181
[3] meaning that climate is assumed to behave in such a way, that for a doubling of CO2, temperatures will increase 2ºC
JC comment: Marcia Wyatt’s previous posts at Climate Etc.:
This post reflects several challenges:
- the challenge of a climate scientist wrapping their mind around the ‘whole thing’
- communicating climate science in an effective and ethical manner
- the challenges informed members of the public face in make sense of this
Marcia takes a valuable step forward in meeting these challenges,
As with all guest posts, keep your comments relevant and civil.
Pingback: A perspective on uncertainty and climate science | Enjeux énergies et environnement
Thank you for your continuing efforts. Certainty comes from the Pope. Uncertainty comes from scientific measurements and observations.
We are also trying to resolve this issue on ResearchGate. https://www.researchgate.net/post/Is_a_peaceable_resolution_possible
If you have a clock, you know what time it is. If you have two, you are never sure.
This guy sure sounds sure.
http://www.theregister.co.uk/2015/10/11/freeman_dyson_interview/
He poses good questions too.
Until the next Pope changes his mind.
The issue of UN control over the worldwide internet is now open for discussion on ResearchGate:
https://www.researchgate.net/post/Should_the_UN_control_the_internet_worldwide
Excellent summary of where things stand now. Logical, honest, and straightforward. Now prepare yourself for the personal attacks from the warmists who know the “science is settled” and will accuse you of being a shill for the fossil fuel industry.
For layfolks like myself, this is a thoroughly enjoyable read. I wish some of my college courses had content as clearly written as this. It gives me motivation to do more personal research.
I’ve always found it interesting that the onset of the observed late-20th century warming coincided with the period in which China was completing a million person city every year and the pause coincided with its ending. Probably a coincidence, but…
An exceptionally well written article, it should be spread far and wide.
Test
” CO2 is an infrared warmer. With no positive or negative feedback responses, a doubling of it will lead to an approximate 1.1ºC”
Without accounting for saturation. About half that when saturation is accounted for. Saturation is not a feedback. It must be considered before feedbacks.
Just another challenge in wrapping our heads around the “whole enchilada”
“Saturation” is a myth.
Your personal opinion – or provide a link.
Messieurs Beer and Lambert, as well as the HITRAN measurements beg to differ.
https://geosciencebigpicture.files.wordpress.com/2015/10/280-560-transmittance-annotated.png
The plot demonstrates both the saturated bands in the middle as well as the unsaturated bands at the edges. Both are real and the radiative physics appear to be the best understood part of all of this.
Transmittance from ground to TOA is only a (small) part of the issue. More important is raising the Effective Emission Height (EEH) even for the most absorbed/emitted wavelengths. For concentrations in the current range, this will raise it through the troposphere, thus tending to reduce the effective radiating temperature.
If it rises far enough, the EEH for some wavelengths would pass the tropopause (as it currently sets), so that raising the concentration would have the opposite effect for those wavelengths. Assuming the tropopause hasn’t risen so far that the EEH is still in the troposphere.
The word “saturation” comes from chemistry, where it denotes the amount of solute that can be dissolved in a solvent before it reaches equilibrium with precipitation. Used for the atmosphere, it denotes the amount of precipitating multi-phase gas that can be present at equilibrium with precipitation, such as, with water, the humidity (100% relative) where condensation of water/ice begins as it cools.
Neither of these rigorous meanings applies to CO2, as anybody who’s bothered to actually study the subject knows.
Thus, when the term “saturation” is used for a non-precipitating greenhouse gas, it’s a very loose metaphor with no rigorous referent. Usually used in an attempt to persuade the audience of some factoid that isn’t really true. This makes is a (type of) myth.
Rigorous? You must be joking. Who has ever MEASURED the effective emission height?
So you agree that “saturation” is a myth?
“Saturation” is a terrible descriptor for the phenomenon. Our usual images of saturation do not fit what actually happens. “Radiation depletion” is better, if not perfect. It’s somewhat more complex than that when the atmosphere is the medium.
There is certainly no doubt about the phenomenon (see Beer-Lambert Law). Being one who has done and taught (in my instrumentation course) spectroscopy of almost every kind, I have observed and compensated for it regularly.
Agree it is a terrible descriptor. People want to think of it upside down as if the gas were saturated and adding more light makes no difference. We think of saturation as a “filling” of something.
What is really happening is the existing gas has already exhausted all the available light in the affected bands and adding more gas cannot produce more absorption.
Exhaustion? Semantic overburden there too.
Interesting that at 280 ppmv the central Q branch for CO2 anchored around wn 667 is already “saturated”.
This challenge of ‘ understanding ‘the complexity
of an interacting system’ with the added difficulty of our
‘hardened mental filters’ to boot. Great chart.
https://curryja.files.wordpress.com/2015/10/slide02.png
Marcia a well reasoned, understandable and forthright explanation. A good read. Sometimes people like me need another’s perspective or more criteria to analyze the issues like climate. Fortunately, more “scientists” (RGB, Svalgaard and yourself) are speaking out on the need to acknowledge our limits on knowledge, understanding, instrumentation and paucity of quality data. The “knowledgeable scientist” seems to have little fear acknowledging that they have weaknesses. That is good. There is nothing wrong with being careful about something you may not actually understand. Please keep adding your perspective to the conversation. When is your next research being published? All the best!
Very nice article. The only thing I would add is that it is possible to say with more certainty why climate models do not work, and cannot. Computational constraints on small grid scale phenomena (convection cells) mean these have to be parameterized. Which presents the attribution problem between anthro and natural variability. The pause says the anthro attribution in CMIP5 is at least partly wrong.
Framing is very old school.
Dan 1:4 Children in whom was no blemish, but well favoured, and skilful in all wisdom, and cunning in knowledge, and understanding science, and such as had ability in them to stand in the king’s palace, and whom they might teach the learning and the tongue of the Chaldeans.
1Ti 6:20 O Timothy, keep that which is committed to thy trust, avoiding profane and vain babblings, and oppositions of science falsely so called:
Tried and tied today.
Well, how about Pseudo-Clement 1 Chapter X. – Cavils of the Philosophers.
Computational constraints on small grid scale phenomena (convection cells) mean these have to be parameterized. Which presents the attribution problem between anthro and natural variability.
1. parameterization does not “present” the attribution problem.
2. the attribution problem exists with or without climate models,
3. the attribution problem is presented in ALL observational science
because we cannot do controllled experiments to isolate attribution.
##################
The pause says the anthro attribution in CMIP5 is at least partly wrong.
1. It ‘Says” no such thing. it doesnt speak for itself.
2. The anthro attribution in “CIMP5” is also a mis nomer. saying it’s partly wrong is either trivially true or wrong itself
At least Steven fleshes out his nitpicking with some assertions. Take a lesson, little willy.
Yep, the “choice of words” fallacy.
Geez Mosh:
“Computational constraints on small grid scale phenomena (convection cells) mean these have to be parameterized.”
why dont you just come out and write that because the resolution of the models is something like 7 orders of magnitude too coarse to even approach the level necessary to actually simulate emergent climatic phenomena, we have to pick numbers, and likely will have to continue to pick values for the next three or so decades.
“parametrization” …..nice word choice Steve; your background in English comes to the fore.
“parameterization” …..nice word choice Steve; it underscores the semiempirical nature of the models. ;o)
“The only thing I would add is that it is possible to say with more certainty why climate models do not work, and cannot.”
Even the IPCC know why climate models do not and cannot work.
“In sum, a strategy must recognise what is possible. In climate research and modelling, we should recognise that we are dealing with a coupled non-linear chaotic system, and therefore that the long-term prediction of future climate states is not possible.”
So stated the IPCC’s Working Group I: The Scientific Basis, Third Assessment Report (TAR), Chapter 14 (final para., 14.2.2.2), p774.
The only people who claim otherwise are computer salesmen and climate “scientists” (or people who are both, of course).
> By definition, science equates to […]
http://www.logicallyfallacious.com/index.php/logical-fallacies/27-appeal-to-definition
Right in front of you willard.
http://www.blbclassic.org/search/translationResults.cfm?Criteria=unbelief&t=KJV
Still yet, you refuse to see. Hope this will help.
“Monkey climb too high, show him tail.”—Jamaican proverb.
That’s trivial nitpicking of the highest order, little willy.
Thank you, Marcia Wyatt. I don’t recall reading a better post here.
Marcia’s kicker is a strawman, Don Don:
Please note that the opposite of uncertainty is certainty, not truth.
You are irrelevant, little willy. Marcia Wyatt is the future. You are the past.
> Marcia Wyatt is the future.
The geological perspective comes from the past, Don Don.
Lamb’s “cartoon” and Bob Tisdale’s research are not exactly new either.
The geological perspective: Marcia is new and you are old.
Who needs science then when you have Judges?
http://www.telegraph.co.uk/comment/11924776/Judges-plan-to-outlaw-climate-change-denial.html
Follows Joshua.
I’m working on a post for this. I’m traveling next week, so not sure when it will be posted
Judith
Have you seen this response by robin Guinier a barrister who has been writing about climate for many years? Max anacker and myself used to correspond with him a few years back
https://ipccreport.files.wordpress.com/2015/10/notes-on-sands-lecture_ty.pdf
Tonyb
yes, post coming soon
Item 5 states:
“I believe it would help to put my Item 4 (above) into perspective if I were to refer to the position of one of the “scientifically qualified, knowledgeable” persons to whom Professor Sands refers (Page 14) – and whose views he suggests “the courts could play a part in finally scotching”. From many distinguished candidates I’ve chosen Dr Judith Curry, Professor and former Chair of the School of Earth and Atmospheric Sciences at the Georgia Institute of Technology. I thought a reference to Dr Curry might be particularly helpful because she has made two presentations this year to US Government committees – presentations that are readily understandable by persons without scientific training.”
Well, I will say that the article employs a very interesting use of quotation marks. I wonder what the statement was without such strategic parsing.
The scents will remained unnamed… why?
Because if the scientist is unnamed, then he cannot defend himself against the gigantic smear she makes.
Gigantic Smear, Wow!
Jch
If gou really think it matters, my money is on Jeff kiehl
http://www.realclimate.org/index.php/archives/2007/05/a-bit-of-philosophy/
Would you like to address the various issues raised in Marcia’s paper rather Than focusing on a tiny part that you seem to think contains a gigantic smear?
Tonyb
gigantic whinging
whatta putz
Agreed.
JCH must have found out about an award for the biggest one. Can’t say he’s not trying.
Marcia, well done. My MS powerpoint (10) couldn’t open the text file. The opening of the intro is a good description of why there is a debate: “Word ‘around town’ is that science is truth. Sorry to damp the zeal, but science is NOT truth. By definition, science equates to varying degrees of uncertainty, with hypotheses and theories bookending the uncertainty spectrum – to some, a rather boring outlook.” The god of the Judeo-Christian religion is known to not prescribe details of “how to” solve knotty complex worldly problems, but leave them to mankind to work them out; however they may, either working together or alone. In this case the Pope, is acting based on his perception of the need to take positive steps for the best interest of mankind based on his perception of the problem (as presented to him, it is not clear that he appreciates the nuances of uncertainties). In doing so this Pope is superseding the wishes of his own god, who might just say to give it the time and let the people sort out the problem and way forward with developing a better understanding of the worldly problem. Robert Burns said this about climate change:
.
But Mousie, thou art no thy-lane,
In proving foresight may be vain:
The best laid schemes o’ Mice an’ Men
Gang aft agley,
An’ lea’e us nought but grief an’ pain,
For promis’d joy!
.
Still, thou art blest, compar’d wi’ me!
The present only toucheth thee:
But Och! I backward cast my e’e,
On prospects drear!
An’ forward tho’ I canna see,
I (can only) guess an’ fear!
Finally: one thing we can all be certain about.
More striking is that the [external forcing] hypothesis is not testable. It cannot be falsified.
…
[The alternate hypothesis, the network hypothesis] is testable and falsifiable.
It seems to me that if this is the clearly case then there is no need for the rest of the post…at least with respect to dismissing the external force hypothesis. But there is nary a further word on that topic. Without this, the rest is then relegated to being a simple restatement of well trodden terrain. For sure it is a well written restatement but still a statement.
Also later text complicates and conflates matters:
Computer climate models – complex, incomplete, and flawed – have failed to capture the temporal and spatial signatures of observed climate behavior. Great tools, they are, but they, themselves, are hypotheses.
Climate models as as expression of external forcing hypothesis? (I would think so.) But also climate models as hypotheses? Huh?
-10 IMO very smooth veneer but untidy underneath. (Here smoothness can be deceptive.)
…and I am a big fan of uncertainty.
…but still a restatement.
What is the difference between being the expression of a hypothesis and being a hypothesis? Perhaps it is that each model adds many specific assumptions, hence many mini-hypotheses, to the general hypothesis being expressed. Then if the model does not work defenders of the general hypothesis (CAGW in this case) can blame the mini-hypotheses. This is one of the ways that the general hypothesis remains untestable and unfalsifiable. Kuhn described this case, which I call “paradigm protection,” very well.
Good point about the additional assumptions as hypotheses attendant in models, David. But can any model, aka ‘hypothesis’ result falsify a hypothesis? It is not an observation. Or better yet can any hypothesis [as a model] falsify a hypothesis? From another perspective a model in a complex system is an approximation to ‘reality’, hence characterization of a model as a hypothesis is would seem to be an intrinsically weak move.
An untidy business.
I would love to see this presentation on Youtube which could gain broader distribution and coverage via links to. A TED talk (although TED talks are usually high level, superficial pontification and short (20 minutes or so).
Marchia said slide 10 – “My studies over the decades reveal to me an earth that exhibits remarkable stability and adaptability.” But another point of the talk is the climate is always changing, all the time so “stability” seems to be contradictory maybe “constrained” or “controlled” and adaptable … or perhaps “resilience and adaptability.”
Karl Popper also realized that the proponents of a theory can protect their pet theory by improper actions:
“it is still impossible, for various reasons, that any theoretical system should ever be conclusively falsified. For it is always possible to find some way of evading falsification, for example by introducing ad hoc an auxiliary hypothesis, or by changing ad hoc a definition. It is even possible without logical inconsistency to adopt the position of simply refusing to acknowledge any falsifying experience whatsoever. Admittedly, scientists do not usually proceed in this way, but logically such procedure is possible”
Consequently he ruled these actions from the hypothetic deductive method.
“For I am going to propose (in sections 20 f.) that the empirical method shall be characterized as a method that excludes precisely those ways of evading falsification”
However, to me it is clarifying to think that definitions can be changed and hypothesis can be added, but such actions means that previous tests are by default nullified. Hence, relevance and results of previous tests will have to be reconsidered. The theory will have to be reestablished. It is like the ladder board game. A minor falsifying experience might bring the idea down a short ladder. A significant falsifying experience might bring back to start.
A significant falsifying experience might bring back to start.
Example: Real data not matching Climate Model Output.
Could you briefly say what makes the exernal hypothesis untestable and the alternative testable?
Could you briefly say what makes the exernal hypothesis untestable and the alternative testable?
I can not. It is an assertion by Dr. Wyatt–an assertion which if true makes the rest of the post of no consequence. So indeed it merits further discussion.
well, I only gradiated 15th grade
but
one problem with the ‘external forcing’ thing is the external part
it is impossible to parse the parts
the version of reality with one of the ‘forcings’ removed is impossible
there is no external
seems a basic logic flaw
are any of the other forcings ‘external’?
only the bad ones
a collective model could be falsified
a model that parses an inseparable component can not
Jeez, the parts can’t possibly behave independently
dependence is intrinsic
the CO2 ‘forcing’ paradigm was conceived in a cultural and political environment that doomed it right from the start
good minds like Marcia Wyatt weren’t able to stop it
weather is the perfect device for controlling a society in which sin has become an anachronism
genius, this ‘climate change’ thing
ronin, I’ve read that the external forcing was untestable, I was curious what makes the alternative testable. What you’ve said seems applicable to both.
Very interesting that mwgrant can dismiss most of this post as being of no consequence, yet it seems of great consequence to others. mwgrant, can you explain why you think this, even though it seems obvious to you?
Nick. Read again.
human1ty1st
“Could you briefly say what makes the exernal hypothesis untestable and the alternative testable?”
I will try:
The external hypothesis proposes that temperature changes are the result of external forcings, but obviously the hypothesis is not falsifiable because there is no way to run an experiment in which all the possible forcings are controlled.
The intrinsic-dynamics hypothesis envisions network-behavior dominating climate behavior. It is a hypothesis of the entire system and it’s testability does not require control of individual parts, merely observations of the entire system. It is therefore falsifiable. I believe she is talking about the stadium wave theory, that it is falsifiable.
Richard
mwgrant
‘Could you briefly say what makes the exernal hypothesis untestable and the alternative testable?’
“I can not. It is an assertion by Dr. Wyatt–an assertion which if true makes the rest of the post of no consequence. So indeed it merits further discussion.”
After some thought, I may have answer. AFIK a model can be used to test a hypothesis, provided that the model has been validated by observation.
The external-forcing models cannot be validated because they apply only to the earth’s climate which cannot be duplicated in an observed validation experiment. The intrinsic-dynamics model is a general model and has been already used and validated in fields of science other than climate science.
I agree that this should be explained in Dr Wyatt’s post.
Richard
Richard,
I appreciate your taking up the question of the falsifiability of the external hypothesis and moving that forward in a clear manner. I declined because I did not make the original assertions of Wyatt’s hypotheses and felt it would entail too much speculation on my part. Leaving something so fundamental to the realm of ‘obvious’ interpretation is a red flag for me–particularly when less important aspects are discussion with more detail.
BTW I do wonder whether the intrinsic-dynamics is likely subject to the pains of equifinality limbo. (Multiple model hypotheses leading to the same endpoint, e.g. see Bevens)
regards mwg
mwgrant
Thank you for the response. I agree with you and explored it only because the question interested me. As you might have suspected, my answer was conjecture, based on knowledge that she used an existing network model.
Richard
richardswarthout,
I still dont see it. Future observations are going to test the validity of both hypotheses. We have seen that the hiatus has so far come close to testing model ensemble predictions. While a gap has openned up between the model mean and obs the obs remain within the model spread. If obs where to fall outside the model mean this would raise questions about the validity of the concensus hypothesis. Its also possible if Judith’s expectation for the Arctic pan out over the next few years then this too would challenge the hypothesis just as much as it might strengthen the Stadium Wave (and visa-versa). Equally a better understanding of forcing and feedbacks would test it, reducing uncertainty around aerosols, solar, clouds etc. A decade more of ocean heat content is going to addfurther clarification.
There are many ways that climate science can develop and observations can pan out that would seem to strengthen or weaken the concensus hypothesis, just in the same way that obs would strengthen or weaken the stadium wave.
Scientific Realism at it’s best, nice one Marcia Wyatt.
The network hypothesis is pretty much summed up by the belief that increasing the amount in ppm of atmospheric CO2 has about as much effect on global warming as barbequing hot dogs in the backyard has on a thermostat in the house and what effect it arguably does have is counteracted by nature turning on the a/c.
Excellent read! A real luxury.
I would point to a minor detail. It is not only a question of IPCC and the money. There has been some effort to understand the “internally generated dynamics” — as yours. But, internal variability is still the big bag of what we don’t know. And so is perceived by the public. The not so minor detail is humans expect a cause (a culprit) for a problem. So, as far as the media photos -and the “warmest year ever” and so on- are able to “show” a problem (and they always will), you don’t have two competing hypothesis. You have a powerful narrative … against nothing. Or, if you like, a powerful narrative against rational thinking. And that’s not a fair duel. Not in the short-term. Decades, at least.
This kind of post makes me uncomfortable. Of course all science has uncertainties. The question is – always – how much real information can you extract despite the uncertainties? The answer to that is the job of the scientists/experts. Here there seems to be a claim: Whatever you suggest, the answer is No, because the uncertainties are too great. I can imagine that this may be true in particular cases (tree-rings…) I really don’t see any reason to think that the whole field is like that.
Maybe one might suggest that Curry et al are fighting an uphill battle against a political cabal that is so anxious to present a “rosy” picture of disaster that they constantly ignore uncertainty in every aspect of the field. And there’s nowhere you can point that isn’t rotted through. Is that the claim? Or are some parts of the field competently done and others not?
Greater uncertainties do not lead to a ‘no’ or a ‘yes’. They just make a decision more difficult potentially playing to risk aversion on the part of decision-makers.
And yes, your discomfort is shared.
Compare the esoteric quantum physics with climate science. Some of the concepts in quantum physics are counter-intuitive, and some are out and out mind blowing. Yet, many of those hypotheses can be tested and proved false or true.
As Dr. Wyatt points out, you can’t run an experiment on climate.
I think her points are spot on.
If you include superstring theory then apparently the comparison of climate science with quantum theory gets more interesting. Woit do you think?
Also if it is correct that you can not run an experiment on the climate then would that not also apply to the alternative hypothesis?
Many of her points are well written and that serves to draw attention to the lack of discussion on the testing and falsifability of the two hypotheses here.
Just IMO people here are rejoicing in the chorus and not paying attention to all of the verses. :O)
Sure, the more speculative physics hypotheses are more difficult to test. Dark matter/energy also.
With more high quality climate data, we should be able to use that to begin to weed hypotheses. But that’s the problem right now, we don’t have several hundred years of high quality data that would allow us to say for certain there is no natural cycle that can account for the current warming trend.
It sucks, but that’s the way it is.
But that’s the problem right now, we don’t have several hundred years of high quality data that would allow us to say for certain there is no natural cycle that can account for the current warming trend.
It sucks, but that’s the way it is.
Jim2: Good summary, indeed. Decision-makers get paid big bucks. They should earn them.Uncertainty is what makes a decision a decision and not a script.
“Decision-makers get paid big bucks.”
Pity, that.
Pity that.
It sucks, but that’s the way it is.
Lets just hope that we get a new set of decision makers that consider the societal/economic impacts of decarbonization before taking action to eliminate reliable, affordable, and abundant energy sources in favor of expensive and unreliable sources. Frankly, I am a bit cynical that this will happen.
Are you saying that the science is not settled? And that anybody who dares to differ should be prosecuted to the full extent of RICO?
Michael Aarrh,
This kind of post makes me uncomfortable too. It gives the appearance of being to certain about the others side’s uncertainties while downplaying their own is a preaching to the choir kind of way.
However, in the end the scientific method should be allowed to play out. Their hypothesis suggests certain behaviors. They model these behaviors. The models are tested against reality. No mid-tropospheric hot spot… no continuous warming… not continuous loss of ice.
While it is an up hill climb, the slope becomes gentler over time.
One demonstrable certainty is that the field of climate science has been corrupted. The cabal has manipulated and misrepresented data to achieve a desired result, lied about there being a consensus, worked to suppress papers that do not support their view and worked in other ways to silence skeptical voices – most recently suggesting that legal action is warranted against skeptics. And the msm has helped turn the lies into perceived truths to the point where the general public believes that co2 caused AGW is a real problem despite the fact that the evidence is anything but certain.
Pingback: Una perspectiva sobre incertidumbre y ciencia del clima, y dos hipótesis contrarias | PlazaMoyua.com
Biggest source of uncertainty? An enormous percentage of studies are flawed. No one ever replicates the work of others. No possible way to assess the quality of the science or correct all the garbage. And there’s lots and lots of garbage.
I think all aspects for why/how the climate may change have been put forth over the last 50 years now it is wait and see time for me,
I wonder if this equally applies to the “stadium wave” hypothesis which you describe here:
Whenever I get a little skeptical about my skepticism I will pull out this terrific post to remind me of all the reasons I became that way. Are there any serious challenges to the essence of what the author has laid out? If they are required to use reason and logic, I doubt it very much.
Excellent post. I think the following is especially interesting:
“Thus, the funding feeds the AGW hypothesis. In turn, the hypothesis inspires the computer-climate-model designs. The modeled output, in turn, has led slowly to the observed data being adjusted, as the observed data records tend to be inconsistent with “theory”. The data, while fed by models and hypothesis, in turn, feed the hypothesis. Studies supporting the consensus hypothesis are easily published, review processes more streamlined and lenient than with studies whose conclusions do not support the hypothesis or are neutral. This all dove tails with media promotion…”
Nice try Mosher, your defensiveness is showing through your petticoat clouding your cognitive functions.
Crunch their numbers first and then chew or spew them out.
http://www.latimes.com/science/sciencenow/la-sci-sn-predicting-violent-crime-by-army-soldiers-20151006-story.html
The boys and girls will never be in the same, Utopia.
Wow, its funny when a piece about recognizing uncertainty is so certain about topics OUTSIDE the author area of expertise.
Lets Fisk this
“Assumptions rule the temperature record. When we see data that make no sense, we speculate why. If the instrument, technology, conditions, and the like seem sketchy, we “document” such and “assume” what climate conditions likely existed and therefore what temperatures should have been recorded, based on a variety of guidelines, and we change the recorded temperatures to what we think it maybe really was…”
1. This doesnt come CLOSE to what we do.
2. We dont SPECULATE when we find data that makes no sense. WE
a) form a hypothesis and TEST IT. for example TOB
b) we run field experiments to test, side by side, different instruments.
3. Variety of GUIDELINES? where? I know of no such guidelines. Every
group has its own unique approach to correcting bad data. There are
no guidelines except this. Do your best and document your work.
4. ‘we change recorded temperatures’ The hell we do. raw data
remains forever untouched. We create a NEW DATASET.
that new dataset is derived from the raw data. It is labeled as
ADJUSTED. if you disagree with the adjustments, use the raw data.
if you can do better or different, please go ahead.
“The motivation for adjusting data is honest; at least we hope it is. A recent increase in the frequency of data adjustments in temperature trends has raised red flags, with findings of undocumented changes, questionable extrapolation practices, and computer-initiated “homogenization” changes made according to assumptions.”
1. Increase in the frequency of data adjustments? really? tell me
what was the rate of adjustments in GHCN from 1995 to 2010?
how did you measure the increase in the frequency? Did you really
just mean to say that you dont like karl’s paper?
2. raised red flags?.. Where? who raised these red flags? Saying that ‘red flags were raised” hides the actors who raised them. Skeptics are always raising red flags.. its not relevant
3. Questionable extrapolation? really? show me the tests you did.
every thing I have seen says extrapolation approaches are improving and they are vindicating even the simple approaches of the past.
4. “computer inititiated’ changes made according to assumptions?
a) IF you do NOT homogenize you are ASSUMING that raw data is better. Check that assumption.
b) IF we did “human adjusted” you would complain that biased humans touched the data.
c) Guess what? The human approach matches pretty well with
the statitistical approach. Maybe our code is a closet liberal.
d) of course there are assumptions. That is why we TEST the assumptions.
########################
Some argue that where assumptions might have trumped accuracy, the number of errors is so small as to not present a problem. Yet, it seems yesterday’s data sets showed variability over the years. Now the warm 1930s and 1940s have been erased, relegated to mythology. We shiver as we are told of the “warmest years on record” by hundredths of a degree, and with minor data re-calculations, “pauses” in observed temperature trends disappear overnight, and we are told to accept this, and we do, in light of all the uncertainties. Can this be???
1. Who argues that assumptions trump accuracy? strawman
2. Its seems yesterdays datasets showed variability?
a) citations please
b) in some cases where this appears to be the case, the reasons
are simple. We have more data and better methods.
here is a clue. Look at Berkeley earth before 1850.
See all that variability?? wow. guess what? its not real.
3. we Shiver? who is shivering? We told people CORRECTLY that
the past years are likely the warmest years in the record. NASA, CRU, NCDC, BE.. we all annouced probabilities.. not certainties. But
in your narrative.. “somebody” said it with certainty. who?
Also who exactly is shivering and what does THAT have to do with data
uncertainty. Your subjective reports of ‘shivering’ are the LAST thing
we want to consider in addressing uncertainity.
4. Pauses disappear? Depending on the assumptions YOU make
you can make a stronger pause or weaker pause.
5. No one is Telling you to accept this. And further who cares if someone told you to accept it? That has nothing to do with uncertainties.
####################################
#########################
There is more than one way to evaluate temperature. Four categories commonly used include surface thermometers, satellite-retrieved measurements, balloon-mounted instrumentation, and proxy data. None of these temperature trends match the modeled trends.
1. Notice how you you remove the probabilities?
2. The trends DO MATCH with a low Likelihood.
3. The surface matches pretty well, once you do the math right
“Quantitatively, among the four temperature records, while their trends are analogous to one another, the magnitudes of their trends are not. Surface temperature-trends are steeper than satellite-retrieved and balloon-based temperatures; while satellite and balloon temperatures are similar to one another. ”
1. Notice YOUR ASSUMPTION that they have to match
“Tree-rings buck the trend further, with one of cooling since 1940, most strongly since the 1960s. Tree-rings capture maximum temperatures. On the other hand, much of the increase observed in surface instrumental land-temperature increases can be attributed mostly to increases in minimum temperatures, which, when averaged with their daily maximum counterparts, reflect increase. ”
1. HUH? are you talking about the divergence? if so you have it WRONG.
2. Tree rings capture max temperature? Really? Are you certain you
got that right?
“Satellite and balloon instrumentation infers temperature of the lower troposphere, where greenhouse-gas warming is supposed to be greater than surface warming. Thus, all methods differ in where and what they measure. All temperature data are further enhanced by extrapolations of “neighboring” stations, some up to 1200 km away, as in the Arctic – the region known to host the widest extremes in temperature on multidecadal timescales.”
1. weird, with no measurements in the arctic you somehow know with
certainty that it hosts the widest extremes? nevermind.
2. last I looked I think Siberia was more more extreme.
http://berkeleyearth.org/graphics/physical-effects-of-warming/#section-0-0
Mosher, that’s not a fisking. Fisking is when you demolish the written arguments para by para. You’ve just outed yourself as a believer in the hockey stick – no variability – and a real hater of raw temp data.
You fisked yourself!
You can’t fight newspapers, horse races, cricket games, farmers almanacs, literature, art. It was hotter in the 30s and 40s or at least as hot as now and BEST, BOM, NOAA and all the others have homogenised krigged algorithmed and reanalysed that heat away.
Now, who is more likely to have correctly recorded the weather in the 1930s and 1940s? The horse race marshals and cricket umpires and farmers et al of the day? Or people like you in the 21st C?
Steven – please tell me (other that “the algorithm is the proof”) why temperatures before 1950 are “adjusted” mostly downwards and temperatures after 1950 mostly upwards. Please realize that I am not a genius, merely a curious being.
I forget who it was, but recently someone concluded the temperature adjustments had to be bogus because they always cause more warming. Something about flipping a fair coin, half the time should be heads, half the time, tails. That’s a persuasive argument. The coin obviously isn’t fair.
Except it’s false. Giss changes in 2010 cooled the record. Even Karls adjustments cooled the long term trends
Karl 87? You have a point WRT Giss 2010.
Well, at any rate, a fair coin will come up 50:50 Heads:Tails. A totally unfair coin will be 100:0 or 0:100. And you seem to be saying the global temperature adjustment coin is 90:10 or thereabouts.
No Karl’s Most recent work ACTUALLY COOLS the Long term trend.
it raises thr trend during the pause, but the LONGEST TREND is cooled.
so steve…what do you make of Robert G Brown’s analysis of the adjustments?
have you looked over his post at wuwt?
I think we are all curious about your take on his thoughts.
The real point is this – are all the adjustments, homgenizations, assumptions, etc, etc, sufficiently accurate to determine that co2 is THE evil gas causing unimaginable catastrophic climate change that requires a dramatic and urgent decarbinizatiion response thrusting us all into some form of energy poverty?
Of course not. The adjustments notwithstanding, I believe there has been a warming trend for some hundreds of years. Even though one must take proxies with a grain of salt, there are enough of them pointing in that direction that I believe it.
It’s attribution that hasn’t been well established. Doesn’t matter to governments, though. They apparently will declare global warming to be a legal fact, CO2 to be a catastrophic gas, and screw the rest of us in the process. They’ll back it up with guns, to. The EPA has about 200 militarized agents. Note the government doesn’t want to give up its guns, it wants only us to give up ours.
What a nice bunch a people.
You don’t need temperature data to understand the problems with co2. We knew this 100 years ago
The only problem with CO2 is there isn’t enough of it. It’s plant food.
…we all announced probabilities, not certainties, but in you narrative, “somebody” said it with certainty. Who?
Apparently, mosher pays no attention to every msm outlet, npr, and virtually every liberal and left leaning politician, which includes some republicans. The question for mosher, has he or anyone from BEST, NASA, or the others made any serious attempt to correct the obvious misinterpretation of the estimates by letting the leftist cabal know that the estimates are at least a little uncertain and not something reliable enough to justify anti co2 policies, especially since temp estimates have nothing to do with causation?
Yes we have.
Read harder
Steven Mosher
I can think of several possible definitions of “raw data”.
– Data exactly as recorded by the observer without any changes what so ever.
– Data records which might have been through some preprocessing by national or international metrological organizations or authorities
From your web site:
“Source data consists of the raw temperature reports that form the foundation of our averaging system.”
“Does Berkeley Earth use adjusted data?
Berkeley Earth collects data from 16 different sources. Wherever a source has an unadjusted version, that version is used. If multiple data sources have records for the same location, unadjusted values are given priority over adjusted values.”
Your web site also opens up for the following possible definitions of raw data:
If a source has an unadjusted version, that version is the raw data. If the source does not have an unadjusted version, the adjusted version is the raw data.
Can you please shed some more light on this by providing your definition of “raw data” so we know exactly what is meant by the term “raw data”?
1. Data is data that is publically available for download.
2. Adjusted data is data that is marked by the provider as adjusted.
3. Raw data is not marked as adjusted.
The vast majority of data comes from ghcn d.
Daily data marked as raw. To my knowledge noaa doesn’t adjust daily data..
The raw adjusted distinction matters only in how we prioritize station source data.
Could data marked as raw actually be adjusted???
Yes. For many stations in the US observers round their reports to whole degrees.
Steve: with your degree in english, and a fairly sparse publishing history, and no experience at all, for example, in teaching any applied mathematics at a college level…just what do you consider your area of expertise to be?
as for this gem:
1)”Guess what? The human approach matches pretty well with
the statitistical approach. Maybe our code is a closet liberal.”
maybe your code reflects the presuppositions of the authors of the code…ya think?
Like “our code” is anything but the product of your assumptions and world view? like it could be anything else?
Does Mosh think that code has a “soul” an independent identity? its own motives?
No, of course not.
And then there is this:
“Pauses disappear? Depending on the assumptions YOU make
you can make a stronger pause or weaker pause.”
eh…no…the data show what it shows…now, if you choose to massage the data, I suppose you could make it do things it wouldn’t normally do, but thats you, not the data.
Let me give you some insight given to me by the guys who started Wharton econometrics back in the day, when I was learning macro modeling.
Every time you transform or filter or eff with your data set, you lose something…resolution, whatever…theres no free lunch…
So go on and krig and smooth and adjust away…
You still have chicken crap…youve just covered it with mayonnaise.
Really Mosh: as the public face of BEST, we expect….more from you.
If you’re not going to publish or teach, you could at least provide something more than the hand waving you’ve been reduced to producing….
If from the tones here I can tell who has been exposed to the dismal science. (Dismal because of track records, maybe ;o) )
English majors (and physics) are a hell of lot more fun—and informative.
“Well, this is all relatively bad news for those of us who study climate. Climate, by nature, does not lend itself well to being tested. We can’t isolate its parts and study them in a lab. We can’t condense decades and millennia into hours and days in order to extract multiple data points and long records.”
I have, and I have been testing and improving it in forecasts for solar forcing of NAO/AO variability at the scale of weather type changes since 2008. I have enough hindcasts employing the particularly suitable CET series, and further back with written records for NAO/AO variability, to demonstrate a planetary ordered solar theory at a number of scales including the sunspot cycle and solar grand minima. And I believe that aspects of it will eventually be seen as laws.
The forcing hypothesis is falsifiable, since we have raised the CO2 concentration to 400 ppm, if we saw cooling due to this it would be falsified.
But we have not. so the current data could have falsified it but no deal.
Anyway as some posters here would point out, the adjustments do not cool the past and warm the present, it’s the other way round.
No, no, no. The obvious response to cooler temperatures would be that it would have been even cooler without the CO2. Ya gotta learn how to play the game.
bobdroege
Respectfully, you are wrong. The forcing hypothesis says that atmospheric temperatures are mainly attributed to forcing. Watching the temperature rise or fall cannot be a means of falsifying this hypothesis; there are many possible causes for temperature changes. Also, IMO, the well documented MWP proves that preindustrial levels of CO2 emissions do not result in lower temperatures.
Richard
Respectfully Richard,
You have no evidence that the MWP was warmer than today. The best paper on the MWP says that temperatures then were statistically no different than the last three decades of the 20th century. And it is currently a bit warmer than then, no matter which data source you choose.
You are wrong about the forcing hypothesis, that stated that a change in temperature is due to a change in temperature. The actual temperatures are due to the energy balance.
Still the forcing hypothesis that the warming is due to CO2 would be falsified by temperatures cooling or remaining the same with all other external forcings remaining constant.
bobdroege
On the MWP I stated that lower CO2 did not result in lower temperatures, a statement you seem to agree with.
“Still the forcing hypothesis that the warming is due to CO2 would be falsified by temperatures cooling or remaining the same with all other external forcings remaining constant.”
“With all other external forcings remaining the same”. AFAIK that can be done only with validated models and no validated models exist. Because, AFAIK, the only way to validate a model is by having controlled observed experiments; increasing real world CO2 and holding all other real world external forcings the same. Not possible and therefore not falsifiable.
Regards,
Richard
Bob
In the real world we have practical evidence that the mwp was warmer! at least in Britain. On dartmoor and other uplands crops can not now be grown at the same altitudes that were possible up till the 15th century.
There are reams of literature on this and the evidence of the habitation, crop drying barns, medieval strip fields can be seen to this day. Indeed I can verify their existence as of 3 pm this very afternoon as I was there.
In the national park visitor centre, funded by the government, it says of the bronze age and the mwp that it was warmer and drier than today.
Tonyb
Tony,
That’s not reliable evidence for temperature, especially on a global scale.
But there is even now wine grapes grown farther north in your home country than during the MWP.
England may have been as warm as now, but globally no reconstructions have the MWP as warm as now.
Richard,
We don’t have to use models, we can use the actual data for the forcings in question.
Bob
This wine business is a bit of a red herring as with greatly improved viticulture skills, ability to improve soils,Better equipment, more time, scientific selection of the best sites it is hardly surprising that vineyards can be grown in places that weren’t possible previously. Anyway, a large part of the geographic restriction of vineyards in the mwp was the British ownership of fine vineyards in their French processions.
Tonyb
Don’t forget more CO2.
My point of falsifiability is the Wyatt makes an important assertion without discussion–even minimal discussion. If that assertion holds most everything else in the post does not matter. One does not let the reader fill-in such details, and in particular when more detail is provided on lesser items. At best it is poor practice.
“My point on falsifiability is that Wyatt… [ugh wordfill…]
A couple of things are reasonably certain.
The first is that the Earth has cooled over the last 4.6 billion years or so, in spite of much higher historical levels of CO2.
According to real scientists – such as geophysicists – it continues to do so, at some millionths of a degree per year.
The second certainty is that removing CO2 from the atmosphere would result in the death of all the plant life necessary to sustain us. Shortly thereafter, humanity, and all other mammals would cease to be.
More CO2 and H2O from burning Nature’s bounty is a Good Thing. Who believes that wiping all sentient life from the face of the Earth is an admirable aim? Who is against more food? Who opposes the greening of the deserts? Have we all surrendered our common sense, and become mindless slaves of the deluded Climate Cultists?
Maybe I’m wrong. Maybe we do have a collective death wish! I hope not.
My first impression – this is one of the best posts I have read to date. Now I will read the comments of others who will undoubtedly offer more indepth insights than mine.
Great article. Thanks!
“…Tree-rings capture maximum temperatures. On the other hand, much of the increase observed in surface instrumental land-temperature increases can be attributed mostly to increases in minimum temperatures, which, when averaged with their daily maximum counterparts, reflect increase.”
Surely tree-rings indicate growth. Often they indicate rainfall. Sometimes temps+rain. If you know lots more about particular species and situations you might be able to guess clumsily at temps and very clumsily at max temps…but should one bother about max temps, when min/max readings tell you so little anyway?
While I’m happy enough with a bit of general warming post 1850 and a recent spike since about 1980 (with a plateau or pause since the turn of the century?) I really can’t see a reason to care. It too shall pass, I know not when. What staggers me is that min/max records in areas of population – and hence of adequate rainfall and cloud cover – are treated seriously as records of “temperature”. What can I say? It should be laughed out of court.
I’m sure a wise head with a nose for weather could work out a vague story of what actually happened climate-wise by using min/max along with other records and “anecdotes”. As for putting a number on things – good luck.
I see a lot of evidence to suggest that the period between 1910 and 1919 was especially warm in my region. Plenty of high readings in 1914 along with plenty of cloud cover would indicate 1914 was a stinker. But please don’t extrapolate. For a long time we’ve had quite a few weather stations and conscientious postmasters up and down the coastal fringe of NSW. If there hadn’t been records taken in similar regions to the north and south of here, maybe a modern scientist would feel entitled to use my region to guess about others. And those guesses would be wrong. Yamba Pilot station, to the north, had its run of hottest years by mean max before 1900. Taree, to the south, actually had its highest annual max readings (95th percentile) post 2000.
But does any of this matter? If I don’t know what cloud movements occurred at the potential hottest part of the day, do I know much at all from knowing max? As for minima…around here they are mostly indicators of wind direction and cloud cover while we slept.
Prissing about Stevenson screens, UHI and station movements seems a bit frivolous when one is neglecting the wildest of all wild cards. That’s cloud!
Cloud. Got it?
Great post. Heck, I’ll even give it an exclamation point … Great post!
Devastating for the settled science crowd, this should be mandatory reading for anyone remotely interested in the topic. Bravo!
You may have heard of the City of Flint Michigan and its drinking water lead contamination. Today’s Detroit Free Press (10/11/2015) has an article on how the increased lead in drinking water and children’s elevated lead levels came to be identified:
“…getting the state to concede the probability that Flint’s water is poisoning its children with lead —after months of assurances from both city and state officials that the water is safe — was far from easy.
It required Dr. Mona Hanna-Attisha, 38, to side-step bureaucracy. It meant awkward conversations and putting her hospital —city-owned Hurley Medical Center — smack-dab in a political minefield”
It seem to be a similar issue as with climate change: commingling of irrelevant data with pertinent data. The State of Michigan homogenate the data of children not exposed (not receiving the Flint River Water System) with children who were exposed to the recently configured Flint River water system. The recently configured Flint River source water was substantively different than the previous source (Detroit water system) and was leaching lead out of water pipes.
So Marcia Wyatt suggests that the data has inherent uncertainties. Further we should be careful in applying meaningfulness to data that is incomplete or has been altered, adjusted, homogenized.
” Studies in the late 1990s removed that variability (speaking to warming of the late 19th Century and early 20th Century along with cooling mid-20th Century). And while the science behind the historical climate revisions has been challenged and shown flawed, the public perception of past uniformity lingers.”
My question: whose responsibility is it to undue the errors in public perception once it has been molded by falsehoods and issues fraught with uncertainty? Currently, the correction of false perceptions appears to me to be squarely on the shoulders of the 5th Estate. This correction of course would work not for the complicity of the naive and/or un-interested journalism major seeking sound bites, currying the un-imaginative narrative, to the hard slogs of investigative journalism. Those in the past who may have had credibility with a broad audience, now reiterates a consensus meme like the NY Times climate blogger….ahhh, whats his name?
Are there no main stream journalists who has not had their opinions jostled by the skeptic retorts? If so,are they willing and able to try on a different concept, one of uncertainty, before they type another article?
When last I checked the state of play for lead poisoning, I could not find a definite rebuttal of the reverse causation approach from the link below. One of its authors, Dr Alan Christophers, was a world leader on the toxicity of lead, with 40 years experience. He noted that severe cases of lead poisoning do exist and that they have definite manifestation; but not so for low levels. Establishment low level literature is, like climate science, beset with unknown unknowns and obfuscations in the prose.
http://dnacih.com/SILVA.htm
Geoff.
Marcia mischaracterises the hypotheses. The AGW hypothesis doesn’t think all systems act separately or that there are no linkages between them. It is also testable, through models, hindcasting and checking projections. It is also certainly based on observations. She gives the impression that there is only one alternative hypothesis but there are almost as many as there are contrarians.
In regard to uncertainties, many here seem to think that uncertainties will resolve to our benefit but it could also be the other way. If that were the case, then the dire projections would become catastrophic indeed. But no-one here seems to consider that angle.
To me her characterizations are too minimal to be useful and probably even to critique.
Regarding the second paragraph: Funny how uncertainties may play out. I guess people read what they want to read. That is easy to do.
+1
The benefit of cheap energy from fossil fuels is incalculable. Civilization would collapse and billions would perish without it. The benefits of CO2 in the atmosphere appear to clearly outweigh any adverse consequences. The planet is getting greener through both CO2 fertilization and modest warming in higher latitudes where growing seasons are extended and crops previously excluded by short growing seasons are now viable. Increased CO2 makes plants require less fresh water for the same amount of growth which provides relief from agricultural losses due to drought and relief to aquifers and ground water sources in irrigated fields.
Then someone comes along like Chicken Little saying the sky is falling. Over and over like the Boy Who Cried Wolf. Predictions from this crowd of Nervous Nellies fail again and again. Yet I’m expected to heed these nattering nabobs of negativity running around like Evangelical Baptists predicting the Apocalypse is looming near with about as much evidence and deceitful means of communication as the religious fanatics.
Spare me. Get some solid information or go home.
Maybe, maybe not. On all counts. Such is the charm of uncertainty.
“It is also testable, through models”
You mean testable in the imaginary sense, then.
Andrew
“Testable, through models.” Who are you kidding? Can anybody provide a list of three models which correctly predicted .. excuse me, projected .. 2010-2014 climate prior to 2010?
Again to point here is Wyatt did not discuss the topic beyond the assertion. This leaves too much open to interpretation by the readers–who are reasonable in not accepting the assertions at face value.
Excellent work, Dr. Wyatt!
“Most have read the words of scientist Stephen Schneider, now deceased, but once a scientist at NCAR: “We are not just scientists, but human beings…We have to offer up scary scenarios, make simplified, dramatic statements, and make little mention of any doubts we might have…” – MW.
Can’t say I have much faith in people lecturing on ethics when they conveniently quote a fragment of Schnieders statement about the difficulty of communicating science in the media.
Dr.Wyatt’s essay is an interesting complement to Kerry Emanuel’s booklet What We Know About Climate Change, published several years ago. I expect that few here will agree with Prof. Emanuel, but the differences in perspective are noteworthy.
Dr. Wyatt’s essay does bring to mind a personal incident that occurred early in my career, which I subsequently recalled with embarrassment. Having done some astronomical research, I was asked by a few of my colleagues to review for them the evidence of the widely held view that the so-called T Tauri stars represented the earliest stage of stellar evolution. I dutifully read the pertinent literature and concluded that, although there was evidence to support this view, it was subject to so many caveats, assumptions, approximations and uncertainties, that considerable skepticism was justified. Of course I was quite wrong; those who had actually conducted the research had a much broader and deeper perspective than myself; they knew what they were talking about and were correct in their evaluation of the evidence, circumstantial as it was at that time.
I hope that Dr. Wyatt will not look back on the judgments expressed here with regret.
And if the trend of warming for the last 18 years continues 30 more years I wonder
if Emanuel will look back on his judgments with regret.
Hi Marcia. Judith has my email address. If you would, please email me. I’d like your permission to reproduce this post.
Cheers.
Bob, the post can be reproduced under open commons. Please reference Marcia’s web site http://www.wyattonearth.net
Marcia Wyatt,
This is an excellent post. Thank you.
This was an exceptionally good post. Thank you.
Indeed, an exceptional, compelling post which was shared, receiving a curious FB comment:
“…Not all is known but inaction based on her delay and distract tactics is not the answer.”
(Included a Yale Environment 360 “report”: http://e360.yale.edu/feature/the_rapid_and_startling_decline_of_worlds_vast_boreal_forests/2919/ in which the “environmental journalist” and author used a doctor-patient analogy…)
After thanking my “friend” for his always thought-provoking comments, the physician in me replied:
“Uncertainty is not for the impatient”… or for the emotionally or otherwise invested in entrenched paradigms… “Scientists know the ultimate answer…” – Really? How does focusing on a single variable, to the exclusion of all others, on CO2 and “rapid reduction in global CO2 emissions” address historical forest/wildfire mismanagement and future impacts of land management on local/global climate?… The doctor-patient analogy is an interesting one… A physician can’t “treat” a patient using force, coercion, or manipulation. Patients and good physicians know: 1.) Doctors, multiple doctors, even a “consensus” of doctors can be wrong; 2.) Medical problems can be complex, affected by multiple factors and other disease processes; 3.) “Treatment” or a prescription has to be not only evidence-based but realistic, considering human nature and personal circumstances, or it won’t be followed; 4.) Trust and “do no harm” oath: A physician motivated by anything other than the well-being of the patient has no place in this relationship… Finally, if one has followed Judith Curry’s career, analysis, and message, how can one make the assumption that her motivation is for “delaying urgent action”? How exactly is she doing that? By following her conscience and voicing her professional judgement? Only government scientists, environmental activists and so-called journalists are considered infallible and allowed to do that?… What is her message/concern (which anyone with common sense and a basic understanding about what is/is not science can appreciate)?: The concern is about abandonment not only of skepticism but of basic scientific principles, history, logic, ethics, and particularly, humility… Btw, taking a look at who the authors of these “reports” are, as well as the selected studies cited, is always useful. Also noteworthy are all the caveats, qualifications, and disclaimers (like the one Yale made regarding the “report” posted and its publication.)… What if the “urgent action needed” is the opposite, or at least something different from what many scientists, governments and society is doing now?
Great Post! To inject some scientific reasonableness into the consideration of our current political discussion is very useful. Maybe it’s just refreshing to see something other than a re run of those famous Goya prints in which a Jackass replete with mortar board hat in instructing a classroom full of jackasses.
“With four parameters I can fit an elephant, and with five I can make him wiggle his trunk.”
Attributed to von Neumann by Enrico Fermi, as quoted by Freeman Dyson in “A meeting with Enrico Fermi” in Nature 427 (22 January 2004) p. 297
We will never develop a national consensus to act unless we both acknowledge the uncertainty in the consensus view and allow differing views to be heard. If we keep on our current course of action, knowledgeable people will destroy us with our failed predictions and rightfully ignore us for stifling debate.
Excellent point. I agree 100%