Arguments
Is the science settled?
What the science says...
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Basic
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Intermediate
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That human CO2 is causing global warming is known with high certainty & confirmed by observations. |
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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?
Basic rebuttal written by James Wight
Update July 2015:
Here is a related lecture-video from Denial101x - Making Sense of Climate Science Denial
Last updated on 7 July 2015 by James Wight. View Archives
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.
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.
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.
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.
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
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?"
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.
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?
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?
@ bob, relax man. I'm not sure why you're so defensive.
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).
thank you. that explained a lot.
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
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:
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.
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.