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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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How sensitive is our climate?

What the science says...

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Net positive feedback is confirmed by many different lines of evidence.

Climate Myth...

Climate sensitivity is low

"His [Dr Spencer's] latest research demonstrates that – in the short term, at any rate – the temperature feedbacks that the IPCC imagines will greatly amplify any initial warming caused by CO2 are net-negative, attenuating the warming they are supposed to enhance. His best estimate is that the warming in response to a doubling of CO2 concentration, which may happen this century unless the usual suspects get away with shutting down the economies of the West, will be a harmless 1 Fahrenheit degree, not the 6 F predicted by the IPCC." (Christopher Monckton)


Climate sensitivity is of the utmost importance. Why? Because it is the factor that determines how much the planet will warm up due to our greenhouse gas emissions. The first calculation of climate sensitivity was done by Swedish scientist Svante Arrhenius in 1896. He worked out that a doubling of the concentration of CO2 in air would cause a warming of 4-6oC. However, CO2 emissions at the time were miniscule compared to today's. Arrhenius could not have foreseen the 44,250,000,000 tons we emitted in 2019 alone, through energy/industry plus land use change, according to the IPCC Sixth Assessment Report (AR6) of 2022.

Our CO2 emissions build up in our atmosphere trapping more heat, but the effect is not instant. Temperatures take some time to fully respond. All natural systems always head towards physical equilibrium but that takes time. The absolute climate sensitivity value is therefore termed 'equilibrium climate sensitivity' to emphasise this.

Climate sensitivity has always been expressed as a range. The latest estimate, according to AR6, has a 'very likely' range of 2-5oC. Narrowing it down even further is difficult for a number of reasons. Let's look at some of them.

To understand the future, we need to look at what has already happened on Earth. For that, we have the observational data going back to just before Arrhenius' time and we also have the geological record, something we understand in ever more detail.

For the future, we also need to take feedbacks into account. Feedbacks are the responses of other parts of the climate system to rising temperatures. For example, as the world warms up. more water vapour enters the atmosphere due to enhanced evaporation. Since water vapour is a potent greenhouse gas, that pushes the system further in the warming direction. We know that happens, not only from basic physics but because we can see it happening. Some other feedbacks happen at a slower pace, such as CO2 and methane release as permafrost melts. We know that's happening, but we've yet to get a full handle on it.

Other factors serve to speed up or slow down the rate of warming from year to year. The El Nino-La Nina Southern Oscillation, an irregular cycle that raises or lowers global temperatures, is one well-known example. Significant volcanic activity occurs on an irregular basis but can sometimes have major impacts. A very large explosive eruption can load the atmosphere with aerosols such as tiny droplets of sulphuric acid and these have a cooling effect, albeit only for a few years.

These examples alone show why climate change is always discussed in multi-decadal terms. When you stand back from all that noise and look at the bigger picture, the trend-line is relentlessly heading upwards. Since 1880, global temperatures have already gone up by more than 1oC - almost 2oF, thus making a mockery of the 2010 Monckton quote in the orange box above.

That amount of temperature rise in just over a century suggests that the climate is highly sensitive to human CO2 emissions. So far, we have increased the atmospheric concentration of CO2 by 50%, from 280 to 420 ppm, since 1880. Furthermore, since 1981, temperature has risen by around 0.18oC per decade. So we're bearing down on the IPCC 'very likely' range of 2-5oC with a vengeance.

Please use this form to provide feedback about this new "At a glance" section. Read a more technical version below or dig deeper via the tabs above!

Further details

Climate sensitivity is the estimate of how much the earth's climate will warm in response to the increased greenhouse effect if we manage, against all the good advice, to double the amount of carbon dioxide in the atmosphere. This includes feedbacks that can either amplify or dampen the warming. If climate sensitivity is low, as some climate 'skeptics' claim (without evidence), then the planet will warm slowly and we will have more time to react and adapt. If sensitivity is high, then we could be in for a very bad time indeed. Feeling lucky? Let's explore.

Sensitivity is expressed as the range of temperature increases that we can expect to find ourselves within, once the system has come to equilibrium with that CO2 doubling: it is therefore often referred to as Equilibrium Climate Sensitivity, hereafter referred to as ECS.

There are two ways of working out the value of climate sensitivity, used in combination. One involves modelling, the other calculates the figure directly from physical evidence, by looking at climate changes in the distant past, as recorded for example in ice-cores, in marine sediments and numerous other data-sources.

The first modern estimates of climate sensitivity came from climate models. In the 1979 Charney report, available here, two models from Suki Manabe and Jim Hansen estimated a sensitivity range between 1.5 to 4.5°C. Not bad, as we will see. Since then further attempts at modelling this value have arrived at broadly similar figures, although the maximum values in some cases have been high outliers compared to modern estimates. For example Knutti et al. 2006 entered different sensitivities into their models and then compared the models with observed seasonal responses to get a climate sensitivity range of 1.5 to 6.5°C - with 3 to 3.5°C most likely.

Studies that calculate climate sensitivity directly from empirical observations, independent of models, began a little more recently. Lorius et al. 1990 examined Vostok ice core data and calculated a range of 3 to 4°C. Hansen et al. 1993 looked at the last 20,000 years when the last ice age ended and empirically calculated a climate sensitivity of 3 ± 1°C. Other studies have resulted in similar values although given the amount of recent warming, some of their lower bounds are probably too low. More recent studies have generated values that are more broadly consistent with modelling and indicative of a high level of understanding of the processes involved.

More recently, and based on multiple lines of evidence, according to the IPCC Sixth Assessment Report (2021), the "best estimate of ECS is 3°C, the likely range is 2.5°C to 4°C, and the very likely range is 2°C to 5°C. It is virtually certain that ECS is larger than 1.5°C". This is unsurprising since just a 50% rise in CO2 concentrations since 1880, mostly in the past few decades, has already produced over 1°C of warming. Substantial advances have been made since the Fifth Assessment Report in quantifying ECS, "based on feedback process understanding, the instrumental record, paleoclimates and emergent constraints". Although all the lines of evidence rule out ECS values below 1.5°C, it is not yet possible to rule out ECS values above 5°C. Therefore, in the strictly-defined IPCC terminology, the 5°C upper end of the very likely range is assessed to have medium confidence and the other bounds have high confidence.

 IPCC AR6 assessments that equilibrium climate sensitivity (ECS) is likely in the range 2.5°C to 4.0°C.

Fig. 1: Left: schematic likelihood distribution consistent with the IPCC AR6 assessments that equilibrium climate sensitivity (ECS) is likely in the range 2.5°C to 4.0°C, and very likely between 2.0°C and 5.0°C. ECS values outside the assessed very likely range are designated low-likelihood outcomes in this example (light grey). Middle and right-hand columns: additional risks due to climate change for 2020 to 2090. Source: IPCC AR6 WGI Chapter 6 Figure 1-16.

It’s all a matter of degree

All the models and evidence confirm a minimum warming close to 2°C for a doubling of atmospheric CO2 with a most likely value of 3°C and the potential to warm 4°C or even more. These are not small rises: they would signal many damaging and highly disruptive changes to the environment (fig. 1). In this light, the arguments against reducing greenhouse gas emissions because of "low" climate sensitivity are a form of gambling. A minority claim the climate is less sensitive than we think, the implication being that as a consequence, we don’t need to do anything much about it. Others suggest that because we can't tell for sure, we should wait and see. Both such stances are nothing short of stupid. Inaction or complacency in the face of the evidence outlined above severely heightens risk. It is gambling with the entire future ecology of the planet and the welfare of everyone on it, on the rapidly diminishing off-chance of being right.

Last updated on 12 November 2023 by John Mason. View Archives

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Further reading

Tamino posts a useful article Uncertain Sensitivity that looks at how positive feedbacks are calculated, explaining why the probability distribution of climate sensitivity has such a long tail.

There have been a number of critiques of Schwartz' paper:

Denial101x videos

Here is a related lecture-video from Denial101x - Making Sense of Climate Science Denial

Additional video from the MOOC

Expert interview with Steve Sherwood


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Comments 151 to 175 out of 389:

  1. Actually the Archer model you reference seems to be consistent with White's numbers: 385 W/m^2 x .566 (% absorbed clear sky) = 217.9; 217.9 W/m^2 x 0.333 (% clear sky) = 72.6 W/m^2 385 x .857 (% absorbed cloudy sky) = 329.9; 329.9 W/m^2 x 0.666 (% cloudy sky) = 219.7 W/m^2 219.7 W/m^2 + 72.6 W/m^2 = 292.3 W/m^2; Archer = 287.8 W/m^2, which is awfully close.
  2. First hit: Start around slide 31.
  3. RW1 @150, if you care to look at the settings, Modtran is run for specific typical locations, with the default being the tropics. It does not produce a globally averaged result. Because the tropics is warmer than the global average, OLR at the tropics is warmer than the global average of approx 240 w/m^2. As set for default, it also does not include the effect of clouds. Further, and for the umpteenth time (as this is just your same question in a different guise) the OLR from the atmospheric window is included in the calculation. This can clearly be seen in the graph of the emissions for each model run. It can also be seen with line by line detailed data by viewing the whole output file. If you want a closer approximation to the global average, use the 1976 US Standard atmosphere (effective brightness temperature = 259 K). Alternatively, use the ground temperature offset to either set the surface temperature at 288 K (effective brightness temperature = 257 K), or adjust it to match an output of 240 w/m^2, and then run the doubling of CO2 experiment. As previously indicated, this is an obsolete model. And as implemented on the net, it does not even allow us to control all parameters so that you cannot set up a globally averaged surface temperature plus cloud cover. It's use is to show you quite clearly that the 3.7 w/m^2 is the difference in total OLR from doubling CO2. If you want a more up to date model, you'll have to pay the licensing fees.
  4. RW1 @151, it is no surprise that the figures are close to George White's in that GW used a hi-tran model to get his figures. He then misinterpreted the Outgoing Long-wave Radiation as being the the total energy emitted from the top most layer of the atmosphere, and divided it by two to get what he believes to be the OLR. Looking at the Modtran model you can clearly see that that is a mistake. That model calculates the IR radiance at a given location that is either out going, or incoming. You can set the altitude to 0 and Look Up to calculate the back radiation. Or you can use the default to set the altitude to 70 km and look down to model what a satelite at 70 km altitude would detect. Clearly that satellite is not going to detect the radiation that is returning to the Earth, it will only detect the OLR. So, the I(out) of the model with that setting is the OLR. There is no need to divide it by two, and doing so shows complete incompetence on this subject. (Not a problem in somebody who is trying to learn, but a huge problem in someone like George White who purports to lecture.)
  5. "Looking at the Modtran model you can clearly see that that is a mistake." I've spent the last hour or more looking at the detailed line by line output and don't see the 'mistake' you're referring to. I do see that the atmospheric window is included in the data though (more on that in my next post). Also, I know this model is out of date, but for the purposes of understanding what these numbers mean, let's break them down as they are. Here are the inputs I'm using: CO2 (ppm) 375 & 750 CH4 (ppm) 1.7 Trop. Ozone (ppb) 28 Strat. Ozone scale 1 Ground T offset, C -1 hold water vapor pressure Water Vapor Scale 1 Locality 1976 US Standard Atmosphere No clouds or rain Sensor Altitude km 70 Looking Down This is the data output I'm looking at.
  6. You did not show the data output. However, with settings as indicated and 375 ppm CO2, the base output is: I, W / m2 = 255.565 Ground T, K = 287.20 For 750 ppm, the output is: I, W / m2 = 252.801 Ground T, K = 287.20 The difference in I is 2.764 w/m^2. That is the difference, according to this model, between the IR leaving the atmosphere with 350 ppm and with 750 ppm. Plainly, if that is the IR leaving the atmosphere, it is incorrect to divide it by two to determine the difference in the IR energy leaving the planet in the two cases. But that is exactly what George White does with his equivalent calculation.
  7. "he then misinterpreted ... that is a mistake." The misinterpretation.
  8. The first thing I notice in the data is that at 375 ppm, the average transmittance is 0.2526, and the average transmittance at 750 ppm is 0.2465 (a reduction of 0.0061 or about 2.4%). At temperature of 287.2K, the earth's surface emits about 385 W/m^2. 385 W/m^2 x .2526 = 97.251 W/m^2 passing through the atmospheric window at 375 ppm, and 385 W/m^2 x .2465 = 94.903 passing through at 750 ppm for (a reduction of 2.348 W/m^2). 385 W/m^2 - 97.251 W/m^2 = 287.749 W/m^2 absorbed by the atmosphere at 375 ppm. 385 W/m^2 - 94.903 W/m^2 = 290.907 W/m^2 absorbed at 750 ppm. Here is what I can't figure out: The output of the data is showing 255.565 W/m^2 leaving at 375 ppm and 252.801 W/m^2 leaving at 750 ppm (a reduction of 2.764 W/m^2). If I divide 287.749 W/m^2 (375 ppm) by 2, I get 143.8745 W/m^2. 143.8745 + 97.251 = 241.1255 W/m^2 leaving (255.565 W/m^2 needed to match the data?). If I divide 290.907 W/m^2 (750 ppm) by 2, I get 145.0485 W/m^2. 145.0485 W/m^2 + 94.903 = 239.9515 W/m^2 leaving (252.801 W/m^2 needed to match the data?). 145.0485 W/m^2 - 143.8745 W/m^2 = 1.174 W/m^2, which is exactly half of the 2.348 W/m^2 reduction in the atmospheric window. To match output of the data exactly, at 375 ppm there needs to be 158.314 W/m^2 from the atmosphere (158.314 + 97.251 = 255.565 W/m^2). For 750 ppm there needs to be 157.898 W/m^2 from the atmosphere (157.898 + 94.903 = 252.801 W/m^2). The difference between 158.314 W/m^2 and 157.898 W/m^2 is 0.416 W/m^2, which is the exact difference between 2.348 W/m^2 reduction in the window and the reduction in the data output of 2.764 W/m^2). What accounts for the missing 0.416 W/m^2???
  9. RW1 - Why are you dividing by 2? Seriously, why? What Modtrans outputs is the total outgoing IR, and hence the 2.764 change on doubling CO2 is the entire, whole, complete difference between outgoing IR. Not half the amount, not twice the amount, but the whole amount. Dividing by 2 is wholly unphysical and wrong. This is the basic mistake that GW makes, and that you have repeated. It is wrong.
  10. KR, Then why does the 2.764 W/m^2 difference outputed NOT match up to the difference in the transmittance data outputed? Are you saying it shouldn't? Explain why. What accounts for the difference? All I've done is run some calculations showing what the numbers would be dividing by 2. Those calculations using the exact transmittance data provided at least yield about 240 W/m^2 (255K) leaving.
  11. RW1 @158: 1) You did not account for the emissivity of 0.98 for the Earth's surface. That means Surface Radiation (SR) = 385.8 * 0.98 = approx 378 w/m^2 2) The average transmittance, ie, the sum of each line's transmittance divided by the number of lines, cannot be used as you have done it. The energy emitted at each line is not constant, so the distribution in variation in transmittance relative to the distribution in emitted energy can make very large differences in the net transmission. Therefore using a simple average of transmission will give invalid results. 3) Total radiance obviously includes values for emissions by the atmosphere, as for example at line 400: Surface Transmission: 3.18E-29 Total Radiance: 1.42E-03 Transmittance: 0.00000 Clearly with a transmittance of 0, Total Radiance would be 0 if radiation emitted from the atmosphere was excluded. To conduct the analysis you wish to make, you need to go through line by line, and sum the total of surface radiation * transmittance to get the amount of radiation from the surface that escapes to space unabsorbed. You then need to go through line by line and sum (total radiance - (surface radiation * transmittance)) to get the amount of radiation emitted from the atmosphere to space. You will then be in a position to do what you are trying to do in 158. Have fun.
  12. Tom, The average transmittance for '100 TO 1500 CM-1' is given at the bottom. Also, I tried using an emissivity of .98 and it didn't make much difference (2.3058 W/m^2 instead of 2.348 W/m^2).
  13. Addendum to 161: Looking at the values, it appears quite probable that "Surface transmittance" is the surface radiation that escapes to space at each line, with transmittance rounded to five significant figures, thus showing 0 in this case. In that case, to get the transmittance you would have to calculate independently the surface radiance at the surface for each line. However, it would save you a step in integrating determining the total emissions from the atmosphere. You may need to find a manual to clarify this. Of course, the sensible thing to do would probably be to assume that no fundamental errors slipped into the programing based on the fact that a large number of independently programed models yield essentially the same result.
  14. @162, I know the average is given at the bottom. That does not mean you can use it as you are doing.
  15. Tom, 'INTEGRATED ABSORPTION FROM 100 TO 1500 CM-1 = 1054.84 CM-1 AVERAGE TRANSMITTANCE =0.2465' You're saying this doesn't account for the differences in energy emitted at each line? How do you know this?
  16. Tom, "I know the average is given at the bottom. That does not mean you can use it as you are doing." How do you know? Have you added all the lines up and divided?
  17. Tom Curtis, RW1 - do you have a link to the Modtran model you are using? I'm not seeing the same freedom of parameters you seem to have discussed at the model here.
  18. Tom, Most of the radiance is in the window, so if anything that would seem like it would make the number much higher than only about 0.25?
  19. Tom, Should I add up all individual transmittance lines and divide?
  20. RE: my 168 Actually most of the energy is not really in the window.
  21. KR @167, that is the model. If you run it there will be a link to "View the whole output file" which shows a large number of additional values. RW1 @168, as can be seen in this image, the peak of the surface transmission is in the 400 to 800 wavenumber band, ie, in the band with a deep trough due to CO2 and a number of troughs due to H2O. The peak radiance is at wavenumber 592, inside the left hand side of the CO2 trough. Therefore if the average transmittance is the mean, it would definitely underestimate the reduction in outgoing IR from the surface. @164 and 165, I don't know, but that seems the most natural reading to me. You should always take average to mean "mean", not "weighted mean" (or median or mode) unless there are clear contextual reasons to think otherwise. There are no such contextual reasons here; and furthermore, your discreprancy gives weight to that interpretation. Which is more likely, that a program developed by the air force for research and which has been used in various incarnations since 1988 with good correspondence to observational results has an error that produces up to 20% errors in its output? Or that you are simply mistaken in your interpretation of average? Regardless, if you disagree with me, you do the LBL integration. I am not the one chasing windmills here. @169, no, you just add up the individual lines. Any divisions (if necessary, see 163) shoud be done for each line only.
    Response: Fixed image width.
  22. I'm downloading the manual.
  23. wrong version.
  24. Tom, Do we agree that the reduction in the window should be twice the 2.764 w/m^ outputed (or about 5.528 W/m^2)? If not, why not? You don't think that all the infrared the atmosphere absorbs is directed toward the surface? Clearly it's not.
  25. RW1 - "Do we agree that the reduction in the window should be twice the 2.764 w/m^ outputed" Ummm, absolutely not. It's both a reduction in the atmospheric window and a deepening in the GHG emission bands. As we have said repeatedly. Not just a single effect, but two different ones that make up the total reduction in emissions.

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