What spurious rubbish you write. Did you not read the letter from Smith?

“This letter raises serous concerns because IGES appears to be almost fully funded by taxpayer money while simultaneously participating in partisan poltical activity by requesting a RICO investigation of companies and organizations that disagree with the Obama Administration on climate change.”

This is not Smith applying RICO to Shulka, but an inquiry into what they have been doing in possible violation of their receiving government money. And no one went hunting for this…Shulka and his troop of a** clowns shouted it out. Smith would be remiss in his duties if he didn’t follow up with an investigation. There is no equivalency here, moral or otherwise, except in the warped mind of a Progressive.

More egregious nonsense from the Left. Did you not read the letter from Smith?

“This letter raises serious concerns because IGES appears to be almost fully funded by taxpayer money while simultaneously participating in partisan political activity by requesting a RICO investigation of companies and organizations that disagree with the Obama Administration on climate change.”

This is not Smith applying RICO to Shulka, but an inquiry into what they have been doing in possible violation of their receiving government money. And no one went hunting for this…Shulka and his troop of a** clowns shouted it out. Smith would be remiss in his duties if he didn’t follow up with an investigation. There is no equivalency here, moral or otherwise, except in the warped mind of a Progressive.

Jim D,

I suggest you are reading but not understanding what you are reading. The claims that the benefits of GHG emissions abatement exceed the cost are based on a whole host of assumptions that are highly favourable to the catastrophists’ argument. For example:

1. They project abatement costs and benefits out 300 years and sum them for the 300 years and claim a benefit by spending enormous amounts now with benefits to accrue in hundreds of years. This is ridiculous. Only the gullible would swallow that nonsense. If, instead, you use their highly favourable (to their case) assumptions but show the net cost and benefit each period (e.g. each 5 years to 2100, then the costs greatly exceed the benefits for all this century.

2. If you want to see some of the assumptions see here:

Nordhaus explains that the assumptions used for the cost-benefit analyses, which are used to justify global carbon pricing, are theoretical; arguably, they are unrealistic for the real world. He says, p68:

“We should provide a word of caution about the optimal case. It is not presented in the belief that an environmental czar will suddenly appear to promulgate infallible canons of policy that will be religiously followed by all. Rather, the optimal policy is a benchmark to determine how efficient or inefficient alternative approaches may be. This is the best possible policy path for emissions reductions, given the economic, technological, and geophysical constraints that we have estimated.”

In other words, the assumptions that underpin the economic analyses used to justify carbon pricing are appropriate for a theoretical modelling exercise but unrealistic, impracticable and highly unlikely to be achieved in the real world. Some key assumptions that underpin the analyses are:

There will be negligible leakage (of emissions between countries, between industries and between emissions sources)
All GHG emission sources are included (all countries and all GHG emissions in each country)
There will be negligible compliance cost and negligible fraud
There will be an optimal carbon price and it is implemented globally in unison
All countries act in unison to increase the optimal carbon price periodically and continue to maintain the carbon price at the optimal level for all of this century (and beyond).
If these conditions are not met, the projected benefits of carbon pricing would not be achieved.

http://catallaxyfiles.com/2014/10/26/cross-post-peter-lang-why-carbon-pricing-will-not-succeed-part-i/

Other assumptions:
– unrealistically low discount rate
– ECS = 3.2
– RCP8.5
– unrealistically optimistic participation rates
– others

Nic,

Observational estimates of ECS and TCR are virtually unaffected by the hiatus, despite propaganda to the contrary:

But, if the hiatus is an internally-driven slowdown (as some seem to think) then the observed change in temperature could be slightly lower than the externally-forced response (by maybe 10% since 1950). So, your statement that it is virtually unaffected is – I think – only true under the assumption that the observed warming is externally forced only (i.e., no internally-forced influence).

If there has been internally-driven cooling then your estimate for TCR could be too low by a few percent. Of course, technically one might expect this internal variability to not influence the ECS, since any change in temperature should be associated with a corresponding change in system heat uptake rate. However, even this isn’t strictly the case (see Palmer & McNeall for example) and if it was, you would then have a result where the ratio of your best estimate for TCR to your best estimate for ECS is much greater than seems reasonable given the inertia in the system.

Also, given that actually reducing atmospheric concentrations is likely to be extremely difficult, this statement seems somewhat misguided

Having said all that, it is transient climate response (TCR) that is most relevant for warming this centrury, not ECS.

Nic,
Actually, here’s a specific question for you. Given your best estimates for TCR, I’ve seen Matt Ridley argue that we could follow an RCP6 pathway and still keep warming by 2100 below 2C (i.e., roughly 5.5/3.7*1.4). Do you agree with this? If you do, how do you explain that today our cumulative emissions are about one-third that of RCP6’s cumulative emissions by 2100 and yet we’ve already warmed by almost 1C? Doesn’t seem consistent to me. Do you think that we can follow an RCP6 pathway and only warm by around 2C by 2100 and, if so, how do you explain this?

+1000

I am sick and tired of people blathering on about ECS, which has absolutely nothing to do with the likely climate in 2100.

Jim D, having trouble seeing the difference between a case where there is evidence of specific wrong doing vs a case where there are a bunch of vague accusations by a group of conspiracists?

“A) observational? Yes
B) Paleo ? No
C) Models ? No”

Models? Yes if you use lower aerosol forcing estimates and include things like the Iris effect. Models are also subject to confirmation bias due to the large number of parameters that need to be chosen and of course have numeric approximation issues.

Paleo? Yes! With respect to the Pleistocene, you just need to take Milankovitch cycles into account and also take into account that changes in radiative forcing in polar regions results in a larger change in global average temperature than changes in equatorial regions (due to the Stefan-Boltzman law) so many estimates overestimate climate sensitivity due to underestimating the relative strength between albedo feedbacks and GHG feedbacks.

I wrong a post a while back on this:

For climate sensitivity estimates that look at temperature changes prior to the Pleistocene, there are a number of issues with these estimates, including:

– Lack of a globally representative set of temperature reconstructions, large uncertainty in temperature reconstructions, and large uncertainty in atmospheric CO2 reconstructions result in estimates having so much uncertainty that not much confidence can be gained from these estimates. The estimates from Pleistocene + Holocene ice core data have far more confidence than the estimates of all the remaining Paleo data put together.

– Often these estimates do not properly take into account the effects of changes in the positions of the continents (which becomes significant at this timescale). Such changes can significantly affect the global distribution of albedo and the global pattern of heat transfer. Hansen et al. completely ignore the effect of changes in the position of continents, which means that they are overestimating climate sensitivity since the changes in the position of continents has led to a gradual cooling over the Cenozoic. The PALEOSENS 2012 paper does appear to try to address this issue by taking into account long term albedo changes though.

– When looking at temperature changes over large timescales such as the Cenozoic, it makes sense to take into account changes in solar irradiance. However, since solar irradiance and GHG forcing are negatively correlated in the Cenozoic, not taking into account the fact that solar irradiance is not distributed evenly across the surface of the planet can lead to an overestimation of the strength of changes in solar irradiance and therefore an overestimation in climate sensitivity estimates (I describe this effect in more detail further down).

– Most of these non-Pleistocene paleoclimate estimates are not taking into account changes in CH4 and N2O. Since CH4 and N2O are strongly correlated with temperature and were likely higher in the past when temperatures were higher, not taking CH4 and N2O into account results in an overestimation of climate sensitivity. Not only that, since radiative forcing is an approximately logarithmic function of CO2, but an approximately square root function of CH4 and N2O, as temperatures rise the relative importance of CH4 and N2O may rise relative to CO2.

In an attempt to quantify the magnitude of ignoring the effect of CH4 and N2O, look at Pleistocene ice core data. The 95% confidence interval for the change in global temperature from Holocene to LGM is 4.0 +/- 0.8 C (Annan and Hargreaves 2013). The difference in CH4 concentrations is approximately ~347 ppb and the difference in N2O concentrations is ~44 ppb. The early Eocene (55 mya) had global temperatures ~13C higher than current temperatures. If one were to treat N2O and CH4 concentrations as roughly linear functions of temperature, then this would suggest that there was ~1850 ppb of CH4 and ~413 ppb of N2O. If one uses the IPCC’s GHG radiative forcing formulas (http://www.esrl.noaa.gov/gmd/aggi/aggi.html) then this suggests that the CH4 and N2O levels would have caused ~0.95 W/m^2 more radiative forcing than pre-industrial levels. Alternatively, if the early Eocene had approximately 4 times current levels of CO2 then by http://www.pnas.org/content/108/24/9770.full.pdf, there would be ~3614 ppb of CH4 and 323 ppb of N2O, which gives a change in radiative forcing of ~1.22 W/m^2 relative to pre-industrial levels. In comparison, a quadrupling of CO2 causes a change in radiative forcing of ~7.42 W/m^2, so excluding changes in CH4 and N2O mean that climate sensitivity is being overestimated by ~16% (obviously there is a lot of uncertainty here, but the point remains).

– – – – –

Paleoclimate estimates that use Pleistocene + Holocene ice core data are far more reliable and give better estimates than other Paleoclimate estimates. However, many of the studies that try to estimate climate sensitivity have flaws that cause an upward bias in estimates and an underestimation of uncertainty. These flaws include:

– Overestimation of temperature changes over the Pleistocene can cause overestimation of climate sensitivity and not taking into account uncertainty in temperatures changes over the Pleistocene can cause an underestimation of uncertainty of climate sensitivity. Some studies (such as those by Hansen et al.) use outdated estimates of temperature changes since the LGM (such as Shakun and Carlson 2010) to infer global temperature changes over the Pleistocene. My understanding is that the current best estimate for LGM-Holocene temperature difference is 4.0 +/- 0.8 C (Annan and Hargreaves 2013). This means that estimates that used higher LGM-Holocene temperature differences of ~5C are overestimating climate sensitivity by ~25%. The PALEOSENS 2012 paper you refer to though has a reasonable polar amplification factor + uncertainty, so avoids this issue.

– Milankovitch Cycles. This is my biggest gripe with Pleistocene estimates. What causes the ice ages? Milankovitch Cycles. What do most Pleistocene estimates ignore when estimating climate sensitivity? Milankovitch Cycles. It’s insanity!

The ‘argument’ that is consistently given to dismiss the effect of Milankovitch Cycles is something along the lines of “because changes in global annual solar irradiance are small due to Milankovitch Cycles, they can be neglected”.

This is complete nonsense. For one, global annual solar irradiance is proportional to 1/sqrt(1 – e^2), where e is the eccentricity of the Earth’s orbit. So the above claim basically suggests that obliquity and precession do not matter as they don’t affect global annual solar irradiance. Perform a simple linear regression where global temperature over the Pleistocene is the dependant variable and eccentricity, obliquity and the precession index are the independent variables (add other explanatory factors if you want). You will find that obliquity is by far the most important Milankovitch Cycle, not eccentricity.

Obliquity has an effect on global temperatures beyond GHG or albedo feedbacks. This is due to the Stefan-Boltzman law. The earth’s surface does not have a uniform temperature; polar regions are colder than equatorial regions. Because of this, a change in the incoming radiation in a polar region will have a larger effect on global temperatures than a change in the incoming radiation in an equatorial region as the marginal change in emitted black body radiation due to a change in surface temperature is higher in the equator than in the poles. I’ll demonstrate the magnitude of this effect below:

– – – – –

Not taking into account the unevenness of changes in the distribution of solar insolation can cause significant bias and underestimation of uncertainty in estimates of climate sensitivity. For example, Van Hateren 2012 assumes that a change in solar irradiance will have approximately 0.7/4 (1 – albedo of earth divided by the ratio of the surface area of a sphere to the area of a circle of comparable radius) times the effect of an equivalent change in W/m^2 in GHG forcing. This arguably overestimates the strength of the sun relative to GHG forcing because it doesn’t take into account the fact that extra sunlight in the tropics has less affect on global temperatures than an equivalent amount of extra sunlight in the poles due to the Stefan-Boltzman law.

To illustrate the magnitude of this effect, consider a grey model of earth where in equilibrium:
(1-α)*S(φ) + B = G*σ*T4(φ) + k*(d2T(φ)/dφ2 – tan(φ)*dT(φ)/dφ)

Where α is the Albedo of Earth, S(φ) is the annual solar insolation at latitude φ, B = 0.087 W/m^2 is the heat flux due to the Earth’s internal energy, G is a factor due to greenhouse gasses, σ is the Stefan-Boltzmann constant, k is the constant that determines the rate of heat transfer across the surface of the Earth and S(φ) is the temperature at latitude φ.

If I impose a restriction that the average temperature of this grey earth is 288 K and that the temperature at the equator is 300 K (which gives a temperature profile that is similar to that of Earth), then I get G = 0.1967 and k = -0.0452. If I use this model and vary solar irradiance by 1 W/m^2 then I get an equilibrium global average temperature change that is 5.44% the temperature change I get if I change greenhouse gas forcing by 1 W/m^2 (if you wish to see my matlab code that gives me this I am happy to share it).

Now if the assumption by Van Hateren were valid then the above value should be 0.7/4 = 17.5%, not 5.44%. So not taking the unevenness in the distribution of global insolation and temperature can cause one to overestimate the strength of the sun relative to GHG forcing by a factor of 3; which suggests that Van Hateren’s estimate is an underestimate of climate sensitivity. More realistically, one should take into account the unevenness of albedo distribution and the effect of cosmic rays; if I try to estimate a Van Hateren impulse response function from instrumental data and allow the effect of the sun to vary as a free parameter relative to the effect of GHG forcing, then I find that a change in solar irradiance has about 8% the effect of an equivalent change in W/m^2 in GHG forcing; so the assumption by Van Hateren overestimates the relative strength of Solar Irradiance to changes in GHG forcing by a factor of two.

– – – – –

So clearly, changes in the distribution of incoming solar radiation causes global temperature changes beyond those caused by GHG or albedo feedbacks due to the Stefan-Boltzman law. In addition, the precession index is very relevant because the albedo distribution of the Northern Hemisphere is different from the albedo distribution of the Southern Hemisphere. So to have a decent climate sensitivity estimate using Pleistocene data, Milankovitch Cycles need to be taken into account.

Let’s say I take Dome C data of dO18, CO2, CH4 and N2O. I use Annan and Hargreaves 2013 to convert the dO18 into a proxy for global average temperatures and I convert the CO2 + CH4 + N2O data into GHG forcing. For albedo forcing, let’s assume for the sake of argument that the claim by Hansen et al. 2013 that the radiative forcing due to albedo changes from Holocene to LGM is 3.4 W/m^2 +/- 20%. I can then use a sea level reconstruction/dataset (say de Boer’s ANICE output) and an assumption of linearity to get a proxy for the albedo forcing.

For the effect of Milankovitch cycles, let’s use 3 variables: the change in solar irradiance (which is proportional to 1/sqrt(1 – e^2)), the sine of the obliquity, and the precession index (e*sin(precession). I can then perform a linear regression to estimate the model T = β0 + β1*(GHG + Albedo + 0.05*Solar) + β2*sin(obliquity) + β3*precession_index + model error. If I take into account all my sources of error (model error, temperature error and albedo error) and propagate error correctly my 95% confidence interval for ECS is (2.48 +/- 0.49) C.

And this is an overestimate of ECS since I am using a low value (0.05) of the strength of the sun relative to GHGs (my regressions using the instrumental data suggest this should be closer to 0.08) and I’m not taking into account the fact that the albedo changes are not uniform. As the albedo changes are higher in polar regions than equatorial regions the strength of albedo changes relative to GHG changes should be stronger than what is assumed in the model (due to the Stefan-Boltzman law).

In any case, I think I can conclude that a proper evaluation of the Pleistocene + Holocene ice-core data yields a 95% confidence interval of climate sensitivity that excludes ECS greater than 3 C. So an ECS greater than 3C is excluded at the 2.5% confidence level by Paleoclimate data!

Well said, Michael.

Looniness on a scale of 1 to 10 is just as well represented on the right as on the left. Those least equipped to see this are the loons.

Your opponents raise excellent points, David. In case a shorter argument would help, anyone who has not explored the feasibility of distinguishing the peak of a bell curve from the peak of a sine wave is likely to be unqualified to deny the proportionality of a given function to a logarithmic dependence.

ATTP, I’m replying here since the sub-thread is rather long. You wrote:

“Nic,
Observational estimates of ECS and TCR are virtually unaffected by the hiatus, despite propaganda to the contrary:

But, if the hiatus is an internally-driven slowdown (as some seem to think) then the observed change in temperature could be slightly lower than the externally-forced response (by maybe 10% since 1950). So, your statement that it is virtually unaffected is – I think – only true under the assumption that the observed warming is externally forced only (i.e., no internally-forced influence).

If there has been internally-driven cooling then your estimate for TCR could be too low by a few percent. Of course, technically one might expect this internal variability to not influence the ECS, since any change in temperature should be associated with a corresponding change in system heat uptake rate. However, even this isn’t strictly the case (see Palmer & McNeall for example) and if it was, you would then have a result where the ratio of your best estimate for TCR to your best estimate for ECS is much greater than seems reasonable given the inertia in the system.”

I think it reasonable to assume that both the hiatus and the preceding faster than trend warming were due primarily to internal variability, but with multidecadal variability as well as interannual (mainly ENSO) and decadal variability. The AMO and related multidecadal variability probably depressed GMST during the grand hiatus (~3rd quarter of the 20th century), boosted it from the late 1970s to the start of this century and has since turned down again.

What you seem to forget is that, despite the hiatus, decadal temperature changes have been almost constant. Look at Fig. SPM.1 of AR5 WG1, which shows decadal average GMST over 1850-2012. The last four decadal values are all evenly spaced. Although the GMST trend was low over, e.g, 2002-2012, the average value (which is what counts for estimating TCR and ECS from long term warming) was much higher than in the preceding 10 years, due to a big jump in the second half of the 1990s/ start of this century.

You also suggested that my statement that transient climate response (TCR) was most relevant for warming this century, not ECS, was somewhat misguided “given that actually reducing atmospheric concentrations is likely to be extremely difficult”.

I don’t disagree about the importance of ECS (although effective climate sensitivity is more relevant out for the next 300 years, at least). But warming over this century, which is what the paper being discussed was about, is far more closely related to TCR than to ECS. TCR is a measure of warming after a 70 year forcing ramp – that takes us into the last bidecade of the century. There seems to be little “warming in the pipeline”, with the Earth’s energy imbalance only 0.5 to 0.6 W/m2 – which would be expected to produce a warming over rest of the next century of only ~0.1 x ECS, probably less.

I have posted a response to ATTP here: http://judithcurry.com/2015/09/30/the-uncertainty-of-climate-sensitivity-and-its-implication-for-the-paris-negotiations/#comment-734324, as this sub-thread had got very long.

you should also know that La Nina and a cold AMO will make continental interiors wetter and cool them too.

Would you happen to have any compelling statistical or other evidence for a cold AMO, ulriclyons?

Reason I ask is that I don’t, so evidence of that sort would make a big difference to how I model future climate.

Nic,

I think it reasonable to assume that both the hiatus and the preceding faster than trend warming were due primarily to internal variability

Maybe for you, but there are other analyses that suggest that the forced response since 1950 is maybe 10% greater than what is observed. That you can construct an argument as to why internal variability has averaged out over some time interval, does not make that true. What I was getting at, though, was that your claim (a rather strong one) that the estimates are virtually unaffected by the “hiatus” is based on the assumption that the observed temperature change is a good representation of the forced response. There is evidence to suggest that this may not be the case.

What you seem to forget

I don’t think I’ve forgotten any such thing.

I don’t disagree about the importance of ECS (although effective climate sensitivity is more relevant out for the next 300 years, at least). But warming over this century, which is what the paper being discussed was about, is far more closely related to TCR than to ECS.

I realise, which I why I phrased it as I did. TCR is certainly relevant, but appearing to dismiss ECS (which you did appear to do) is – in my view – misguided. I would actually argue that TCR and ECS are really just model metrics and are not necessarily good indicators of what will happen. They can certainly guide us, but what is more interesting is what will happen given various emission pathways, not simply what will happen if we double CO2 at 1% per year.

I was hoping you might also answer my other question about Matt Ridley’s claim that RCP6 would only lead to around 2C by 2100. Do you agree with this and can you explain how we can only warm by around another degree while emitting 1.5 to 2 times as much as we have already? (Actually, this may still be in moderation, but I would be interested in your answer)

Also, you appear to be promoting the idea that climate sensitivity could be (probably is, in fact) lower than the IPCC suggests. What if you’re wrong? Even your own analyses do not rule out a TCR of 2K and an ECS of 3K with high confidence. Be wonderful if climate sensitivity is as low as you seem to be suggesting, but what will we do if we do follow what seems to be your, at least, implicit advice and we discover in 20-30 years time that your estimates are low? I realise that there are risks associated with whatever we may decide to do, but by promoting low CS values, you appear to be minimising the risk associated with climate change and, consequently, strengthening the argument that the risks associated with acting outweigh the risks associated with climate change itself. What if you’re wrong? Also, that you may disagree with some of the other evidence isn’t necessarily a good reason for effectively dismissing it.

@ AK – “All represent risks that can’t be quantified.”

The possibility that climate change will cause the flying spaghetti monster to get angry, appear out of nowhere and rain meatballs on the Earth causing mass genocide represents a catastrophic risk of climate change that cannot be quantified.

On the other hand, the possibility that extreme mitigation measures will cause the flying spaghetti monster to get angry, appear out of nowhere and rain meatballs on the Earth causing mass genocide represents a catastrophic risk that cannot be quantified.

Appeals to the strong precautionary principle and unquantifiable risks with no empirical evidence to back them up gets us nowhere. And personally, I think the well being of 7 billion people is worth thinking things through and making decisions using risks that can be quantified. If these risks are not completely absurd like the flying spaghetti monster, then I think they can be quantified; you just need to put the evidence in. Claiming they can’t be quantified and giving up to me seems like laziness.

“you just need to put the evidence in”

This should read: you just need to put the effort in.

Isoprene they put it on the test just to be mean,
But Google told me it was butadiene.
Oh I believe in isoprene.

Suddenly I got half the grades they gave that nerd
Now my applications won’t get heard
Oh isoprene is so absurd.

Why they drag it out, I don’t know, they just won’t say.
I wrote something wrong in my wonderful essay.

Chemistry—you gotta have it to be green,
It’s not physics, math, it’s in between.
Dear god I must have isoprene.

Typo.

“I wrong a post a while back on this:”

Should have read
I wrote a post a while back on this.

Darn post-concussion syndrome.