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All IPCC definitions taken from Climate Change 2007: The Physical Science Basis. Working Group I Contribution to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, Annex I, Glossary, pp. 941-954. Cambridge University Press.

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Is the science settled?

What the science says...

Select a level... Basic Intermediate
That human CO2 is causing global warming is known with high certainty & confirmed by observations.

Climate Myth...

The science isn't settled
"Many people think the science of climate change is settled. It isn't. And the issue is not whether there has been an overall warming during the past century. There has, although it was not uniform and none was observed during the past decade. The geologic record provides us with abundant evidence for such perpetual natural climate variability, from icecaps reaching almost to the equator to none at all, even at the poles.

The climate debate is, in reality, about a 1.6 watts per square metre or 0.5 per cent discrepancy in the poorly known planetary energy balance." (Jan Veizer)

Skeptics often claim that the science of anthropogenic global warming (AGW) is not “settled”. But to the extent that this statement is true it is trivial, and to the extent that it is important it is false. No science is ever “settled”; science deals in probabilities, not certainties. When the probability of something approaches 100%, then we can regard the science, colloquially, as “settled”.

The skeptics say that results must be double-checked and uncertainties must be narrowed before any action should be taken. This sounds reasonable enough – but by the time scientific results are offered up to policymakers, they have already been checked and double-checked and quintuple-checked.

Scientists have been predicting AGW, with increasing confidence, for decades (indeed, the idea was first proposed in 1896). By the 1970s, the scientific community were becoming concerned that human activity was changing the climate, but were divided on whether this would cause a net warming or cooling. As science learned more about the climate system, a consensus gradually emerged. Many different lines of inquiry all converged on the IPCC’s 2007 conclusion that it is more than 90% certain that anthropogenic greenhouse gases are causing most of the observed global warming.

Some aspects of the science of AGW are known with near 100% certainty. The greenhouse effect itself is as established a phenomenon as any: it was discovered in the 1820s and the basic physics was essentially understood by the 1950s. There is no reasonable doubt that the global climate is warming. And there is also a clear trail of evidence leading to the conclusion that it’s caused by our greenhouse gas emissions. Some aspects are less certain; for example, the net effect of aerosol pollution is known to be negative, but the exact value needs to be better constrained.

What about the remaining uncertainties? Shouldn’t we wait for 100% certainty before taking action? Outside of logic and mathematics, we do not live in a world of certainties. Science comes to tentative conclusions based on the balance of evidence. The more independent lines of evidence are found to support a scientific theory, the closer it is likely to be to the truth. Just because some details are still not well understood should not cast into doubt our understanding of the big picture: humans are causing global warming.

In most aspects of our lives, we think it rational to make decisions based on incomplete information. We will take out insurance when there is even a slight probability that we will need it. Why should our planet’s climate be any different?

Last updated on 4 September 2010 by James Wight.

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Comments 51 to 79 out of 79:

  1. Albatross #44: Didn't the NAS say a similar thing about the basics of climate science in their letter to Science as your final suggestion?

    " But when some conclusions have been thoroughly and deeply tested, questioned, and examined, they gain the status of “well-established theories” and are often spoken of as “facts.”

    For instance, there is compelling scientific evidence that our planet is about 4.5 billion years old (the theory of the origin of Earth), that our universe was born from a single event about 14 billion years ago (the Big Bang theory), and that today's organisms evolved from ones living in the past (the theory of evolution). Even as these are overwhelmingly accepted by the scientific community, fame still awaits anyone who could show these theories to be wrong. Climate change now falls into this category: There is compelling, comprehensive, and consistent objective evidence that humans are changing the climate in ways that threaten our societies and the ecosystems on which we depend. "
  2. SkyWatcher @51,

    Thanks, I recall that now. IMHO, you are correct, but much more importantly NAS is probably correct.
  3. There seeme to be a reinvigorated attempt of late to redefine every form of quackery recorded over the last five thousand years as a product of "science", completely ignoring emergence of the scientific method as a product of the modern period.

    The Denialview is not only anti-scientific, it is also ahistorical.
  4. AGW is settled by physics and observations. However, CAGW is posited by models which say AO will go more positive as part of a positive feedback of less ice, more positive AO, more warming. See http://www.cccma.ec.gc.ca/papers/jfyfe/PDF/FyfeBoerFlato1999a.pdf and http://www.cccma.ec.gc.ca/papers/ngillett/PDFS/gcm_aochange.pdf (2002). But by about 2002 we started seeing the "paradox" http://www.atmos.colostate.edu/ao/other_papers/GRL2005-Arctic-Paradox.pdf: "We are left with an apparent paradox of more linear Arctic climate change beginning in the late 1970's and the more episodic AO." The authors don't provide an answer to the paradox. But all the authors above acknowledged that natural factors like volcanoes can have a large effect.

    At the same time models were being used to predict secular increases in AO (and the positive AO of the early to mid 1990's minus Pinatubo was being touted as part of that increase) other researchers were positing natural cycles (e.g. Polyakov and Johnson http://denali.frontier.iarc.uaf.edu:8080/~igor/research/pdf/50yr_web.pdf described here http://www2.gi.alaska.edu/ScienceForum/ASF15/1582.html) to help explain why ice decreased more than expected (than from AGW alone). P&J used a coupled ocean-atmosphere model of the Arctic driven by historical measurements to plot the cycles. Their implicit prediction of the current negative AO turned out to be accurate. Now negative AO is being misconstrued as a consequence of ice loss, but it is not since the models have considered ice loss and Arctic temperature anomalies all along and have predicted positive AO. So nobody misunderstands, I am not saying that the bulk of the GAT increases are from these natural cycles, they are not, they are AGW.
  5. #54: "help explain why ice decreased more than expected (than from AGW alone)"

    Eric, the Polyakov and Johnson paper is from 2000; the alaska scienceforum paper from 2002. Since that time, a lot more ice has gone.

    Serreze 2009 speaks of arctic amplification as just emerging in the late '90s, a signal that would not be evident to the papers you cite.

    As the climate warms, the summer melt season lengthens and intensifies, leading to less sea ice at summer’s end. Summertime absorption of solar energy in open water areas increases the sensible heat content of the ocean. Ice formation in autumn and winter, important for insulating the warm ocean from the cooling atmosphere, is delayed. This promotes enhanced upward heat fluxes, seen as strong warming at the surface and in the lower troposphere.

    And of course, continued sea ice discussion should go on the appropriate thread.
  6. It appears to me that CAGW originated with the Oregon Petition. The distinction is an ideological argument ranging in form from "it's not bad" to "climate sensitivity is low". What is catastrophic is a subjective quality, unless an objective definition is developed; such as with "likely" in the IPCC reports.
  7. #55 muoncounter, Serreze et al doesn't explain why the models predict higher AO when AO is going lower. The paper references this 1998 paper with the same model-predicts-positive-AO theme http://tinyurl.com/6gy9zl9 in the context that these other factors like AO might have something to do with some of the ice loss. Then they drop the subject. The specific paper that I would be delighted to read is the one that explains why AO is not going positive like the models predict.

    #56 Bibliovermis, the term CAGW is disliked by some here, but what I am trying to do is distinguish between the settled science of AGW and the extreme Arctic warming predicted in the models due to positive AO feedback loop and the amplification that the Serreze describes.
  8. #57: Eric,
    Look at this AO time series, which has AO going positive very soon and respond here.

    Between Serreze (autumn warmth), Flanner (decreased albedo in the Arctic Ocean) and Tedesco (decreased albedo in Greenland), what part of arctic amplification do you object to?
  9. I am asking what happened to the old theory of amplification by positive AO. New theories are nice, but not a sign of "Settled Science".
    Response: Thank you for parsing this comment and the previous one into the relevant threads!
  10. #59: "New theories are nice, but not a sign of "Settled Science"."

    According to Serreze and Francis 2005,

    Recognition of the ice-albedo feedback as an important climatic process can be traced to the early work of Croll (1875). That hardly makes it a 'new theory.'

    Further,
    Our synthesis of the available evidence points to the Arctic as in a state of preconditioning, less advanced than that shown in the ACIA simulations for 2010–2029, but setting the stage for larger changes in future decades. This preconditioning is characterized by general warming in all seasons, a lengthened melt season, and an initial retreat and thinning of sea ice, all accompanied by strong expressions of decadal-scale climate variability.

    What is becoming apparent is that prior predictions of these 'larger changes' were conservative. That suggests the natural cycles aren't so natural any more.
  11. I take that this sentence

    "anthropogenic greenhouse gases are causing most of the observed global warming"

    is an essential part of AGW theory.

    Can someone please offer a practical method of how to disprove it?

    Unfortunately so far I failed to find one.

  12. h-j-m @61, each of the following methods states a condition which has been experimentally tested and is known to be false, but which would falsify the theory if true.

    Method 1:  Warming of land surfaces equal warming of oceans, showing the change in temperature is caused by changes of SST rather than forcing.

    Method 2:  Stratosphere warming as troposphere warm showing the warming to be dominated by changes in solar radiance.

    Method 3:  Meso-sphere and thermosphere increasing in volume (showing that they are warming) as troposphere warms.

    Method 4:  Warming exists even though anthropogenic forcing factors remain constant.

    Method 5:  Known natural forcings are larger than known anthropogenic forcings.

    Method 6:  Width of anthropogenic GHG absorption spectra in outgoing LW radiation  unchanged over time.

    I am sure the list can be extended substantially, particularly once we start applying statistical tests rather than the crude method of simple falsification.  It should be noted that if there were reasonable doubt about the theory, competing natural explanations would not have been falsified (they all have been).

    Now, here is the real challenge.  Find a theory that contradicts the claim that is both falsifiable and has not already been falsified.  It is a challenge "skeptics" seem to avoid like the plague.

  13. Further to 6 - measure the change in surface radiation or OLR and then find that is inconsistent with calculated change due to increased GHG.

    You could also add - models based on AGW forcing would not reproduce past climate within the errors of model and forcing. You might think from arguments about paleo that this isnt a strong argument, but note that you can use this method to disprove alternative hypotheses like "the sun explains it all". "GHG changes have no effect".

    I think that the easy practical ways to disprove AGW were all tried long ago and failed with explains your problem with find them.

  14. Thinking on this further - that statement is not "an essential part of AGW theory". It is an outcome of the current theory of climate. Falsifying climate theory is same as for any other theory - the theory must change if predictions derived from the theory do not match observation with both the limits of prediction and limits on observation. One of the problems with claims to  falsify climate theory is that they falsify predictions that climate theory does not make.

  15. I have some questions related to this that have been bothering me for a while.

    This article isn't about equilibrium climate sensitivity from double co2, but I'll use that for my point. the IPCC report gives a value of 2 to 4.5 C with a likely value of 3C and confidence level of greater than 66%. Less than 1.5C has a confidence level of less than 10%.

    This is where I'm confused, for very well understood fields, such as heat transfer, equilibrium values can be calculated with a high degree of accuracy. For example, we can calculate the equilibrium temperature that a mixture of 1lb of 80F water and 1lb of 60F water would reach. Or in vibrations, how much a spring would stretch when it reaches rest from a hanging mass.

    Obviously these are simple examples, but the point is that equilibrium values can be calculated with a high degree of accuracy in well understood fields certainly. The 5% not understood in climate looks like it has a pretty significant impact on the calculation of an equilibrium value. So why is the topic of climate considered well understood? Thanks

  16. engineer,

    I think that the problem is that you are trying to compare climate science with the hardest of hard sciences -- engineering sciences, like classical physics.  Many other sciences are not nearly so precise, including quantum physics, biology, neuroscience, medicine and more difficult chemistry (especially the state of chemistry before the development of the electron microscope).

    Would you consider all of these fields to be "not well understood?"

  17. Understanding the feedback processes well does not necessarily mean that crucial numbers can be extracted easily. Things like - amount of aerosol, full thermal description of ocean, cloud vapour response etc. The Argo network, better satellite measurement, GRACE and so on eventually allow for more precision.

  18. engineer:

    I will answer the question with more questions.

    1) you are selecting some very simple examples from heat transfer (mixing two different quantities, at two temperatures, of the same fluid) and the properties of materials (a single Hookian spring). They are high-school "engineering", not engineering school engineering. How simple is it to calculate the peak spark plug tip temperature in an F-1 racing engine at the end of a straight-away on the 72nd lap of the race at [pick a course] on a hot summer afternoon - from first principles? Would you consider the design of racing engines to be an area that is not well understood?

    2) I would think that brige-building, slope stability calculations, etc. would be considered well understood engineering areas. Why does standard design practice often  use relatively large (e.g. 2 or greater) factors of safety? Surely any factor of safety greater than one will do? (For those not familar with the term, a design factor of safety of 2 means that the design strength is twice the needed strength.)

    3) a standard physics example of things that are difficult to calculate is the n-body problem. Does this difficulty in calcuating an exact answer mean that our understanding of gravity is not well understood?

    4) If you wish to continue the discussion, would it be better if we did so without rhetorical questions?

  19. so is the uncertainty mainly the result of the lack of theoretical understanding or the lack of more sophisticated technology (e.g. better satellites)? How much of the uncertainty in equilibrium climate sensitivity is from a lack of theoretical understanding?

  20. @ bob, relax man. I'm not sure why you're so defensive.

  21. Good question. As far as know, for ECS you need to know where feedbacks will stabilize. Ie if you perturb CO2, where does T settle when all feedbacks are in equilibrium. Now I think you could say there is a lot of confidence about what the feedbacks are, a lot of confidence about how the feedbacks work, but a lot less confidence about quantifying some of those processes accurately. (eg the complex dance of aerosol, water vapour, temperature and clouds).

  22. thank you. that explained a lot.

  23. scaddenp, last question. when you say "a lot less confidence quantifying some of those processes accurately" is that due to technology limitations (computing power) or theory? thanks

  24. engineer:

    ...it is odd that you interpret my somewhat-rhetorical questions as "defensive", when you yourself began with somewhat-rhetorical questions. Granted, it can be difficult to read tone into a written comment, but you started off with what semed like a "gee, this should be so simple if it is well-understood" sort of comment. It reminded me of the following XKCD comic:

    Physicist encountering a new subject

     

    Perhaps a better start would have been to pose the question something like "What part are understood, and where does uncertainty in this value come from?" (as you are beginning to ask now) rather than implying it can't be "well understood" because it can't be predicted as easily or accurately as the simple examples you gave. The question relates to the How reliable are climate models? discussion, where you can find out much more about how the reliability is examined.

    In a system as complex as global climate, you can have uncertainty in predictions due to uncertainty in the measurement of input variables, even if the physics of those portions of the system are well understood at a theoretical level. For example, consider the effect of aerosols. The radiative effect of a specific aerosol can be modelled quite well, given sufficient data about the size distribution, physical, and optical properties of the aerosol, etc., but getting detailed measurements of those physical properties over huge swaths of the atmosphere over sufficient time can be extremely difficult. Even if the technology exists (e.g AERONET), budgets aren't infinite and measured data is incomplete.

    Then take that difficulty into the future, and try to predict exactly what the future aerosol state will be. It's not that it's hard to predict what a particular aerosol will do - it's hard to predict exactly what will be up there.

  25. There can be quite a gap between a qualitiive description of a process (eg think ENSO) and a computer model able to capture it, but a big factor is limitations on the measurement system and time length of good data. (eg for Argo we have only 10 years so far). If you want quantitive models, you need accurate measurements. As far as I know, aerosol measurements are still short of modellers hopes.

  26. @ Bob, It's just a miscommunication on my part. I couldn't think of how to word my question that's why I ended up asking that subjective question in the beginning.

    I'm not questioning the reliability of models...models are used all the time like CFD. The limitations in CFD is due to budget and computer power. I was wondering where the uncertainty in climate was mainly coming from like the uncertainty in equilibrium climate sensitivity from double co2. was it because of theory or tech? but you guys already answered my questions that the it's due to limits on current tech. thanks.

  27. engineer

    There are a range of potential feedbacks that are hard to quantify because each one of them is an entire field of study in its own right. For example:

    Vegetation response. Will the Amazon for example remain a rainforest? Become a drier forest? Grassland? Each has different implications for carbon cycle sinks and sources, surface albedo and evapotranspiratioin patterns.

    Ice sheet retreat. What are the dynamics of any decline in Greenland ice sheet cover, WAIS, EAIS? Timing and extent of this for any particular level of GHG forcing again has significant impacts on albedo.

    Ocean Circulation. Major ice sheet melt might impact on the Thermo-Haline circulation that drives ocean currents - there is some evidence this was a part of what happened during the warming from the last Glacial Maximum. If ocean currents change, this can alter the distribution of where heat is transported to. Thus cloud patterns, climate zones, all sorts of things.

    Methane release from Permafrost. How fast will permafrost melt and where? Will this produce more aerobic or anaerobic decomposition of the defrosted organic matter, influencing whether carbon outgasses as Methane or CO2. Higher rates of methane release will have a greater short term warming effect than if it is released as CO2 even though the longer term impact will be the same as ultimately the methane is oxidised to CO2

    This stuff is too hard to do at a theoretical level and even modelling involves stacking models on models. Thats why paleo climate studies are an important reference point. That is what climate has actually done in other circumstances.

  28. @engineer

    Here's a concise descpriton of how global climate models evolved and function.

    By the mid-1990s, it was possible to investigate the causal mechanisms behind changes in Earth's climate using relatively sophisticated mathematical models of Earth's climate. These models solved the same complex equations of atmospheric physics that numerical weather prediction models did. But they also took into account components of the climate system other than the atmosphere, including the oceans, the continental ice sheets, and even life on Earth (collectively known as the "biosphere"), and they attempted to account for the physical, chemical, and biological interactions among these components. Of course, no theoretical model is ever perfect; even the best model is only an idealization of the actual world. There are always real-world processes that cannot be captured—for example, in the case of a numerical climate model, individual clouds or small-scale air currents like dust devils—that are simply too small for the model to resolve. The key question is, can the model be shown to be useful? Can it make successful predictions?

    Source: How Do We Know Humans are Responsible for Global Warming? by Michael Mann, WeatherUnderground, April 22, 2013

  29. engineer:

    I don't think it is correct to just call it a technical problem. To follow on Glenn's comment, when you are trying to model today's climate, you can get away with saying "this is what the vegetation is", or "this is where the ice sheets are", etc., and simply measure the required input parameter for the climate models. You can even do that to a certain extent for past climates, as there are proxies that will give you an indication of vegetation cover, ice cover, etc. Understanding why the vegetation, ice, etc. are the way they are is a help, but not an absolute necessity to be able to develop a good understanding and a reliable model of current climate.

    Contrast that with the future: we can't measure the vegetation cover or ice sheet distributions - we have to model them. But uncertainties in how vegetation responds to a changing climate is not a problem that necessarily requires increased understanding of climate dynamics - it is a problem of understanding vegetation dynamics. Predicting something like future aerosols not only requires estimating future levels of existing emission sources (which requires economic modelling), it also requires assumptions of what future combustion technology might produce, and what social policy choices might be made. You can start by assuming they won't change, but proper policy decisions require that you also evaluate what might happen if they do change (using realistic ranges of possibiliites).

    It's a classic multi-disciplinary issue.

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