By Ken Gregory, P.Eng. May 26, 2021
Climate policies such as carbon taxes are set by governments using social cost of carbon (SCC) values calculated by a set of economic computer programs called integrated assessment models (IAM). The USA government used modified versions of three IAM, called PAGE, DICE and FUND. Neither PAGE nor DICE includes significant CO2 fertilization benefits. Dr. Pat Michaels wrote “By including the results of IAMs that do not include known processes that have a significant impact on the end product must disqualify them from contributing to the final result” and “The sea level rise module used by the IWG2013/2015 in the DICE model produces future sea level rise values that far exceed mainstream projections and are unsupported by the best available science.” Therefore, this article discusses the FUND model.
FUND is the most complex of the IAMs which links scenarios and simple models of population, technology, economics, emissions, atmospheric chemistry, climate, sea level, and impacts. FUND distinguishes 16 major world regions. It is the only model used by the US Government that includes benefits of warming and CO2 fertilization. Unfortunately, the climate component of FUND that determines temperature is flawed as it assumes that the deep oceans are instantly in temperature equilibrium with the atmosphere, without any time delay, when the equilibrium climate sensitivity (ECS) is 1.5 °C or less. The transient climate response (TCR) is defined as the temperature change starting from equilibrium, of a 1% per year increase of CO2 concentration to the time when it doubles. If CO2 concentrations are then held constant, temperatures would continue to increase to the ECS as the oceans reach temperature equilibrium with the surface, which can take hundreds to more than a thousand years depending on the value of the ECS. The FUND temperature response at an ECS of 1.5 °C shows the TCR is equal to the ECS, also 1.5 °C, which is impossible. Comparing the average of two climate models which each have ESCs equal to 2.1 °C, the FUND model runs 0.43 °C too warm in 2100 using the RCP4.5 emissions scenario.
The FUND model uses a default ESC of 3.0 °C based on the average of climate models that over warm the lower air temperatures by a factor of two compared to global temperature measurements as shown by this graph. This article shows the climate models warm the sea surface at twice the rate of the measured temperatures. The models on average over warm the tropical bulk atmosphere by a factor of 2.7. The models produce too much warming because they attribute natural warming caused by high solar activity and ocean cycles to greenhouse gas warming and they fail to account for the urban heat island effect (UHIE) that contaminate the government temperature datasets.
The ESC can only be estimated using the energy balance method that compares the climate forcings to historical temperature records. The paper Lewis & Curry 2018 presents estimates of ECS with uncertainty analysis. The authors estimated the median ECS at 1.50 °C with a likely (17%-83%) range of 1.20 – 1.95 °C using the HadCRUT4.5 temperature dataset. The probability distribution is shown as the blue curve of figure 1. The analysis was deficient in that the natural climate change from the base to final periods were not considered and no correction was applied to remove the UHIE from the temperature record. There exists a huge body of literature that shows the UHIE is a large part of the warming in government datasets and that the natural millennium cycle of warming from the Little Ice Age affects current temperatures so it is incorrect to ignore these effects. Making these adjustments, the likely range of ECS based on energy balance calculations using actual historical temperatures is 0.76 – 1.39 °C with a best estimate of 1.04 °C. The red line of figure 1 is the corrected ECS probability distribution used to calculate the SCC.
The energy impact components of FUND are very flawed. The energy impacts are for space heating and cooling expenditures. In FUND, the expenditures depend on temperature anomalies relative to 1900, but expenditures actually depend of the actual temperatures where people live. The change of expenditures with temperatures does not correspond to expenditure data published for the USA states. A paper by Peter Lang and me shows that a 3 °C temperature rise would decrease energy expenditures in the USA by 0.07% of gross domestic product (GDP) but FUND projects an increase of expenditures of 0.80% of GDP with non-temperature drivers held constant. The analysis is based on extensive energy consumption surveys in the USA.
The FUND energy cost projections show very bizarre results. For example, when average temperatures in China reach 12.5 °C, China is forecast to spend over 38% of its GDP on space cooling with non-temperature drivers held constant at 2010 values, whereas when the USA reaches the same temperature they are forecast to spend less than 0.5% of its GDP on space cooling. Figure 2 shows the impacts on GDP percent of heating expenditure changes due to temperature change. In China when average temperature are 5 °C, space heating expenditure decrease by 1.8% of GDP per °C of temperature change, again with non-temperature drivers held constant at 2010 values, whereas in Canada with temperatures less than 5 °C, space heating expenditure decrease by 0.006% of GDP per °C of temperature change.
A study by Dayaratna, McKitrick and Michaels (D, M & M 2020) of the CO2 fertilization effect and the FUND agricultural component shows that the FUND CO2 fertilization effect should be increased by 30%. The study says “New compilations of satellite and experimental evidence suggest larger agricultural productivity gains due to CO2 growth are being experienced than are reflected in FUND parameterization. … For numerous crop types around the world, CO2 fertilization more than offsets negative effects of climate change on crop water productivity, with some of the largest gains likely in arid and tropical regions”.
I have created a modified version of FUND which incorporates a 2-box ocean climate model that is tuned to closely match the temperature profile of climate models. A 2-box ocean energy balance model can very well replicate the temperature rise of climate models. A blog post by Dr. Isaac Held provides a set of equations and information about this model. The top 70 m of the oceans are well mixed and in near temperature equilibrium with the surface. Heat flow from this layer to the deeper ocean acts as a negative feedback, inhibiting the surface temperature rise. The results are shown figure 3. The global temperature profile of two climate models that each have an ECS of 2.1 °C are shown. The blue line is their average. The purple line is the FUND temperature profile with ESC set at 2.1 °C. The 2-box energy balance model is the orange line which well matches the model average blue line. All models use the RCP4.5 emissions scenario. Nic Lewis published an article that shows both the FUND and DICE climate modules are mis-specified. He calls DICE module a “trillion dollar error”.
I have replaced the flawed space heating and cooling components with new components to match the empirical heating and cooling USA data. The model assumes that when other regions reach the wealth per person of the USA in 2010, adjusted for the same energy efficiency and temperature, they will have similar space heating and cooling costs per capita as that in the USA. I also increased the FUND CO2 fertilization effect by 30% as recommended by D, M & M 2020. This allows me to calculate the realistic social net benefit of CO2 emissions using all impact sectors, weighted by the energy balance based ECS probability distribution.
The table below shows the SCC (negative means CO2 emissions are net beneficial) for emissions in 2020 in US and Canadian 2020 dollars, using 3% and 5% discount rates, with and without the CO2 fertilization update using the modified FUND. The Can$ to US$ exchange rate of 0.83 was used. The results show the net benefits of CO2 emissions range from 8 to 12 US$/tCO2 (10 to 14 Can$/tCO2) depending on the discount rate used.
The data show that climate change with CO2 fertilization effect is quite beneficial, so policies costing trillions of dollars to reduce CO2 emissions are misguided. Bjorn Lomborg estimates reducing global temperatures by 0.35 °C in 2100 would cost US$18 trillion. At the 3% discount rate, the 30% increase of the CO2 fertilization effect increases the benefits of emissions by US$3.32/tCO2.
The social cost (benefit) of CO2 is a marginal concept. It represents the difference of a base case of a forecast global wealth changes with CO2 emissions without any emissions control policies and the case with a pulse of CO2 emissions added in the year 2020, discounted to the year of the pulse, divided by the pulse size, giving the wealth impact in dollars per tonne of CO2. In FUND, the pulse size is 10 megatonnes (Mt) of CO2. If the SCC is positive, a tax may be imposed on CO2 emission equal or less than the SCC only after all other non-tax policies designed to reduce fossil fuel use are removed and all other taxes which are greater than that imposed on other factors of production are removed. Since this study shows that the SCC is negative, the optimum policy would be to subsidize CO2 emissions equal to the calculated net benefits.
Figure 4 compares the temperature forecasts by FUND and the 2-box climate model, both using FUND’s default emissions scenario with ECS = 1.1 °C. FUND’s climate component causes too much warming.
The figures 5, 6 and 7 below show the empirical space heating and cooling impacts for 7 selected regions versus the regional temperatures, from 2000 to 2200, with non-temperature drivers held constant at 2010 values. I do this to show only the impacts of the temperature change. The regions are Canada, USA, Australia & New Zealand, North Africa, South America, China & near countries and Small Island States. The ECS probabilistic distribution gives a mean SCC equal to that calculated using ECS of 1.13 °C, so the ECS is set to 1.1 °C for the following graphs and discussion.
Figure 5 shows the energy impacts which are the sum of the space heating and cooling impacts. A decrease in space heating cost due to a temperature rise results in an increase in GDP as people are left with more cash to spend on other things.
The impacts are positive for cold countries and negative for warm regions. Canada’s temperature in 2000 is much warmer than that shown in the FUND graph, figure 2, because I use the temperature at the population centroid latitude, not the geographical center of the country as used by FUND. Figure 6 shows the heating impacts. Small Island States (SIS) have no impact because their average temperature is above 26 °C so no heating is required.
Figure 7 shows the cooling impacts. An increase of cooling costs with temperatures decreases wealth.
Figure 8 shows the global energy, heating and cooling impact, again with non-temperature drivers held constant at 2010 values. Note that the temperature impacts on space energy (heating plus cooling) reduce expenditures and increase global wealth. The blue line shows that 2 °C of global warming would increase global wealth by 0.029%. By contrast, the default FUND parameters forecast that 2 °C of global warming would decrease global wealth by 0.37%.
Figure 9 show the global impacts per GDP of seven impact sectors and the total impacts, with non-temperature drivers changing with time.
The non-temperature drivers of energy, including population and GDP per capita growth, have a large effect on the forecast. The large income growth caused the forecast of energy (mostly heating) expenditure to increase from 2000 to 2040 despite increasing temperatures resulting in a reduction of wealth per GDP. Figure 8 by contrast shows that global energy impacts are always positive with non-temperature drivers held constant.
To get a better understanding how temperatures affect the seven impact sectors, the calculated SCC values can be parsed by impact sector. Figures 10 and 11 show the percent contribution of each impact sector at 3% and 5% discount rates, respectively. Agriculture dominates the SCC values. At 3% discount rate, agriculture represents 115.3% of the US$11.74/tCO2 net benefit. Water resources is the next largest at -6.0%. The mainstream media is fixated on storms and sea level rise which are insignificant. Sea level rise damages are kept in check by protection expenditures which are included by cost-benefit optimization. At 5% discount rate, agriculture increases to 123.0% and ecosystems is the next largest at -11.2% of the US$8.41/tCO2.
An Excel file with all the data and calculations is here. [2,853 KB]
The FUND model can be downloaded and installed from here.
The IJulia notebook used to modify and run the FUND model in the html format is here. [1,754 KB]
Further reading: https://www.rossmckitrick.com/uploads/4/8/0/8/4808045/empirical_scc_cce_preprint.pdf
Joe, I criticized the paper you link to by Dayaratna, McKitrick and Kreutzer for not taking into account the urban heat island effect(UHIE) and the natural warming from the Little Ice Age. McKitrick is the lead author of the key UHIE paper http://icecap.us/images/uploads/MM.JGR07-background.pdf
He is also the author of several papers debunking the Mann hockey stick, thereby restoring the millennium cycle and the Little Ice Age to history. Did McKitrick forget about these two issues?
Thanks for the input. I haven’t dug deeply enough into this subject to be entitled to an opinion on that detail; I’m still gathering sources, of which this piece will be one, alongside Dayaratna et al.
For the time being I take the view exemplified by the “Apocalypses That Ain’t” chapter in Steven Koonin’s new book. Specifically, let’s accept Fig. 29.3 of the 2018 National Climate Assessment for the sake of argument. Even a whopping 5°C global-average-surface-temperature increase by 2100 would reduce year-2100 gross world product by only about 6%—i.e., would delay total growth by only about three years.
Why should we forgo fossil fuel’s benefits and suffer higher prices of nearly everything to make people who will be four or five times richer than we are 6% richer still? To me a lot of the arguments about ECS, discount rate, etc. seem secondary to that question.
Climate policy is faced with two huge problems. The first is that the IPCC has created a consensus that climate sensitivity to CO2 is likely 1.5 to 4.5 C based on climate models that over warm the surface and lower atmosphere by a factor of 2 by assuming that there is no natural climate change, no urban heat island effect (UHIE) and positive cloud and water vapour feedbacks. The don’t match the observations so they are wrong. The second is that economic models, IAM, used to estimate the social cost of CO2 depend on these climate models and but forecast warming much faster than the models. Most IAM fail to include benefits of warming and CO2 fertilization. A cost benefit analysis should include benefits, not just costs!
Judith Curry read my article and said “I think you use a value of ECS that is far too low. LC is already very low, at the bottom end of what people are willing to accept as plausible.” LC isn’t “already very low”. It is the ECS based on the historical temperature record the the IPCC estimates of greenhouse gas forcing, assuming that all the temperature rise is due to those forcings. But the GHG forcing should be compared only to the portion of warming caused by GHG, excluding natural and UHIE warming. Rejecting the result of low climate sensitivity by reference to a fake consensus of what “people are willing to accept” is unscientific. If reader think the ECS given in the article is too low, point our errors in L&C2018, the UHIE papers I cite McKitrick and Michaels 2007 and De Latt and Maurellis 2005, the millennium cycle or the logic. Please don’t rely on the fake consensus.
Whatever the ECS really is, it certainly is NOT in the IPCC ECS > +2.5 ºC range.
55 Million years of relative climate stability since the PETM tells us that. The science liars at SkepSci simply ignore that fact that CO2 lags temps at those time scales. Ignore causality they do. Climarte liars are all around, just like Herr Fauci and the COVID liars are all around us.
There is no sensitivity to CO2 in the atmosphere. If there was a sensitivity to IR with CO2 in air then there would need to be two different specific heat values.
falsified a consensus
Ken G, thank you for this excellent work. I, and many others have long noted that the benefits of additional CO2 are very large, and very well known, whereas the projected harms are M.I.A.
When calculating the agricultural benefits, what was included? By this I mean not just the aerial fertilizer affect, but was increased production due to reduced frost considered. Most of any actual CO2 induced warming would be an increase in the low T, thus reduced frost damage. The same us true of drought tolerance, which is increased by additional CO2.
Also was water efficiency considered? All crops would be more water efficient. This is of immense benefit beyond the increased bio mass.
Also increased CO2 leads to increased nitrogen efficiency, thus reduced fertilization required per unit of bio-mass.
Another benefit beyond the fertilization affect is that all crops produce more growth per acre, thus a reduction in total costs per bio-mass unit produced is needed for all global crops. ( Just as with water efficiency, nitrogen efficiency, and reduced frost damage and increased drought tolerance mentioned, CO2 makes more produce, AND makes all existing produce less costly and more efficient.
Thanks for your work.
Just a supplementary comment to the above post supporting the thought that the CO2 benefits are likely understated.
The above study show that even a 15 percent rise in CO2 leads to a 29 to 46 percent increase in tree water efficiency.
In Southern California we have a strong drought this year. I was amazed at how much spring bloom our native vegetation had despite the drought. At 280 ppm CO2, there is no way this would have happened.
Palatable water is a real problem. Mostly a political choice problem, yet very real.
Another way to look at the benefits of CO2 is to ask what would happen if CO2 was suddenly reduced to 280 ppm?
The answer in very short order would be WWIII, as we would unquestionably experience dramatic global food and water shortages.
Are you referring to de Laat, A. T. J., and Maurellis, A. N. (2004), Industrial CO2 emissions as a proxy for anthropogenic influence on lower tropospheric temperature trends, Geophys. Res. Lett., 31, L05204, doi:10.1029/2003GL019024. ?
Yes, those results were used for the UHIE along with the McKitrick and Michaels 2007 paper. The link I gave in my article at “Making these adjustments, the likely range of ECS based on energy balance calculations ” gives a reference to “Evidence for influence of anthropogenic surface processes on lower tropospheric and surface temperature trends” A. T. J. De Laat, A. N. Maurellis (2016), which is a followup paper to A. T. J., and Maurellis, A. N. (2004). The abstract says “In this paper, we verify the robustness of the thresholding technique and confirm our earlier conclusions on the basis of an extended analysis and two additional data sets.”
Thanks for the article.
Although, a lot of effort has been put into these damage models, they can only be considered a first draft.
If we apply basic principles of addressing uncertainties and errors we would find all results meaningless.
I haven’t perused your spreadsheet, I have only read this article, and I believe you left out something based only on the fact you failed to mention it. What are the benefits of just plain old cheap energy? We already have empirical evidence that incorporating unreliables into the energy grid raises energy prices not only to the consumers but also on agriculture and manufacturing, causing a rise in prices, and this would be above and beyond just ordinary inflation or cost-of-living adjustments.
Also something you didn’t mention, what’s the value of a human life? I know, that’s morbid to say, but I also know that liability litigators have a number they can toss out off the top of their heads. So if access to cheap energy becomes problematic, how many people will die just because they have to lower their thermostats, or even the utility cuts them off because they can’t pay their bill? How many people will die because of worsening health after they adjust their thermostat beyond the comfort zone? How many people will die of malnutrition because the cost of all food has risen? How many people will die because they will not see a doctor when they need to ever since they had to make a choice between heating, eating, or medical insurance? Where is that number addressed in all of this?
It has been my opinion, ever since I heard of the first one, that any SCC is a crock of s***. The ones building the program know what answer they’re supposed to produce, and they work backwards from there to construct their models, and no amount of prevarication on their parts will change my mind on that aspect.
You say “any SCC is a crock of s***” but the fact remains that we in Canada will soon be paying $100/tCO2 carbon tax, based on the IAM using IPCC climate sensitivity. I have shown that the “energy impacts” and the climate component in FUND is a crock of s***, so I don’t disagree with you. But saying that will convince nobody that CO2 is beneficial.
What are the benefits of just plain old cheap energy? Economist Dr. Richard Tol calculates that the global average private benefit of the use of fossil fuel at the margin (ie., the benefit of the last unit used) is about US$411/tCO2 in 2010 dollars. As soon as one restricts fossil fuel usage, the marginal benefits increase. The total benefits of fossil fuels in dollars per tonne is astronomically high. Fossil fuels is the driver of all industries.
We published this article https://blog.friendsofscience.org/2021/04/25/the-true-cost-of-wind-and-solar-electricity-in-alberta/ that shows using wind and solar without fossil fuels as backup power, but using batteries instead would increase the price of electricity by 100 times.
“what’s the value of a human life?” I gave a link to FUND. FUND scientific documentation section 5.12 says “The value of a statistical life is given by” a formula proportional to GDP/capita. “This calibration results in a best guess value of a statistical life that is 200 times per capita income (Cline, 1992).”
So, if Red94s point is acknowledged, then the cost of wind and solar above fossil fuel costs must be considered.
And it is cogent to note that just as additional C02 makes all current produce less expensive, wind and solar make all fossil fuel more expensive. This is done by making them grid stability tools that are regulated to play second fiddle to wind and solar, greatly reducing their energy production capacity, while increasing their operation costs.
Not to mention the direct subsidies to wind and solar!
Agreed! This article show that in Europe, the effective cost of wind and solar electrical power is 5.7 times that of electricity from other sources, mostly fossil fuels. This is because fossil fuel fired electricity is used as backup to wind and solar, and due to the requirement of rapidly ramping up and down to offset the wind and solar variability, electricity used as backup is much more expensive than electricity produced by fossil fuels as base load.
The value of statistical life used being 200x per capita income is just one example where the FUND model can only be considered a draft.
A fairer guess would be life expectancy x per capita income. Say 70 x per capita income.
But a detailed cost to health would be to realise elderly were the most impacted by heatwaves so each death from heatwaves May only cause a very small financial loss. Say 5 x per capita income.
There are too many of these type of global guesses in the FUND model
For what it’s worth, Naptown Numbers based a battery-back-up-cost calculation on Texas wind-turbine records:
I would suggest the “benefit” is possibly infinite, and therefore a “cost” cannot be calculated.
Does ECS to a doubling of CO2 even exist?
Only as a meaningless abstraction. Since CO2 does not determine temperature there is no unique ECS in nature. Nor is there ever equilibrium for that matter. Climate is what is called in nonlinear dynamics a far-from-equillibrium system.
Enjoying some nice grilled beef burgers and beef steaks this weekend I will. The Climate Marxists presume Americans will be docile whilst they take those middle class luxuries away.
I beg to differ.
But then that is also why the Marxists also want to disarm US citizens of their #2A.
They’re not Marxists. They’re too dumb for anything that requires any kind of thought process. They’re whichever-way-the-wind’s-blowing-to-get-a-vote-ists.
Well, that only applies to those pandering for votes. But they’re pandering to the Marxists, for the most part.
The worst flaw in all of that is that historically on a geologic timescale the Earth has ALWAYS had more atmosphere and temperature is regulated by gravity at sea level… so without any way at all of being able to determine how much atmosphere the Earth had 300 or 600 million years ago the data collected for gaseous ratios is absolutely worthless to actual science.
Economically, isn’t the benefit in $ at least what people are willing to PAY for the fuel ?….or they wouldn’t buy it ? So adding notional costs to reduce consumption is really just a societal class-distinction-by-wealth methodology ?
The “CO2 fertilization” claims in Original Post (O.P.) see to come from a link; link’s Fig.1 is specified as “global crop production … 1980-2017. Link says Fig. 1 shows the “… record since 1980 provides prima facie evidence … warming [1*C], CO2 fertilization [+ 68 ppm] …” is suitable for including into the O.P. link’s adjustment to prior calculations of % benefit due to CO2 fertilization.
That claim of “prima facie” certainty about the actual role % CO2 fertilization plays seems, to me, something that should not be taken as accurate. For example, during the period starting in the same year of 1980 and running into 2002 there was a 15 ton/hectare/year increase in Northern China crop productivity for the wheat-maize rotation. According to 2017 research the increase was exemplified by an increase in nitrogen use efficiency from 36.5% in 1980 to 71% by 2002. Which is to point out that the O.P. graphs apportioning stupendous agricultural gains from CO2 fertilization lacks context.
Gringojay, you refer to figure 1 of Dayaratna, McKitrick and Michaels (D, M & M 2020). The paper gives a good review of the CO2 fertilization effect and good evidence that it is under represented in FUND, however the authors agree that it is not possible to place a firm number on this effect. So I agree that the 30% increase over the FUND estimate “should not be taken as accurate”, only a rough estimate.
I’ve seen comment that elevated CO2 (eCO2) “increases nitrogen efficiency”. This, I feel, merits some context; and will provide some here rather that step on someone’s thread. Since different plants respond to eCO2 in different ways in different context I won’t generalize.
In a soil region with high nitrogen content receiving adequate irrigation wheat grown at 12 separate sites averaged 25% higher yield under eCO2. And although soil nitrogen uptake was 20% greater under eCO2 the wheat bio-mass nitrogen content averaged up to 9% less, while the grain nitrogen content averaged 5% less.
When the same high soil nitrogen sector was given additional nitrogen (50-60kg N/hectare) no additional biomass gains occurred, no additional grain nitrogen occurred. The only extra nitrogen eCO2 delivered into the wheat was additional nitrogen in the wheat straw. Which is a mixed message concerning plant nitrogen usage.
When some eCO2 observers look at satellite evidence of greening and charts of decadal increases of agricultural productivity they speculate the eCO2 impact of a few decades is self evident. It is just as probable that agronomic developments are the productivity driver.
Wheat breeding has been ongoing and, for example, in Australia records going forward from 1950’s detail wheat nitrogen uptake. The actual wheat strain gains in nitrogen uptake (“increased nitrogen efficiency”) is due to improvements in how the wheat root system brings in nitrogen.
This wheat nitrogen efficiency was surprisingly not a feature of breeding for greater length roots, nor density of the long roots. Which is another discrepancy contrary to supposition that eCO2 is “prima facie” increasing nitrogen efficiency and thus yields; since eCO2 commonly results in plants partitioning assimilated carbon to their roots.
Gotta love this line: “…the optimum policy would be to subsidize CO2 emissions equal to the calculated net benefits.”
Not a carbon tax, a carbon subsidy. Get a tax credit for using fossil fuels. I like it.
Warmer Is Better. Fight The Ice.
Sorry for this dumb question but- it seems to this non scientist that the belief that there is such a thing as the ECS must presume that CO2 is the control knob over the planet’s temperature. Since, I think, most of you don’t believe CO2 is that control knob- then why not more criticism of the reality of the ECS?
That concern is discussed in the head post. The author takes a low ECS number, backed by numerous studies. So you are incorrect, as a low ECS does NOT mean that CO2 is the control nob.
One can argue that ECS is .0001 degrees, or even negative, but stating any ECS number does not make CO2 the control nob, just one factor of many. And I would guess that most here think CO2 has some warming affect and is net beneficial.
I believe that the ECS probability distribution I presented in figure 1 is a good estimate based on the current climate science literature. The energy balance method is based on the law of conservation of energy and it is the only reasonable method to determine ESC. Climate modeler just guess cloud and water feedbacks to get the high ESC values they want. This isn’t science. An ECS of 1.1 C for double CO2 means that CO2 is not a control knob for climate, but CO2 emissions do have a significant effect.
You keep writing ESC, is that supposed to be ECS?
It’s not a dumb question. It’s the key question. From here at 420ppm, it’s gonna take what 200 years to double it? That’s three 60-year climate cycles, more than a few AMOs and a lot of El Ninos and La Ninas – which have equilibria on a monthly time scale and have temperature swings greater than anything proposed by normal people for CO2’s pathetic, indistinguishable from zero contribution. This whole CO2 farce is over. Can we please give it a decent burial?
No they don’t. Dr. Spencer made two mistakes. First, he compared the CMIP6 ‘tas’ field, which is the modeled 2m temperature, to observed SST. That is an apples-to-oranges comparison. He should have used the ‘tos’ field, which is the modeled SST, to compare with observed SST. Near surface temperatures warm faster than SST. Second, he cherry-picked or at least severely overweighed the CanESM5 model, probably unwittingly, which is the highest outlier among all CMIP6 models. 50 of the 68 members came from CanESM5. Nick Stokes and Dr. Hausfather have a good review of the real skill of the CMIP6 suite of models. Please fix and resubmit for review.
I selected one member from the 13 CMIP6 models via Climate Explorer to compare to the ERSSTv5 dataset, Climate Explorer has only surface air temperature for CMIP6, so I subtracted the model SST of CMIP5 from the model surface air temperature over the sea of CMIP5. The difference of trends is 0.0210 C/decade. I subtracted the ‘air – sea’ temperatures of CMIP5 from the monthly CMIP6 near surface air temperatures to get a CMIP6 sea surface temperature. This assumes the near surface air temperature difference to sea surface temperature in CMIP5 is the same as in CMIP6, which is very likely. The resulting CMIP6 sea surface temperature trend January 1979 to April 2021 is 0.1767 C/decade. The ERSSTv5 trend is 0.1166 C/decade. The model trend is 152% of the ERSST measurements. See my graph here.
That seems like a reasonable approach. I would have done the same. One thing to note is that CMIP6 has a higher surface air temperature trend compared to CMIP5 especially for post 1979 period. This may be a result of the newer cloud microphysics schemes incorporated into CMIP6. But over the period 1880 to 2020 CMIP6 effectively nails the warming trend showing +0.07C/decade vs the +0.07C/decade that was actually observed. Anyway, here is a tweet from Gavin Schmidt showing modeled vs observed SSTs from the CMIP6 suite with more models than is available on KNMI Explorer. CanESM is clearly a hot outlier as it always is (it was in CMIP5 as well). Even keeping the CanESM with equally weighting as the other models it still looks CMIP6 performs reasonably well to me.
An easier way to show little if any problem is to look at cooling degree days. This is from the U.S. government so it can’t be wrong! (/sarc) This is used by HVAC folks all the time to calculate size of cooling equipment. It is probably a better view of the energy in the atmosphere at any given period of time than pure temperature and certainly better than temperature anomalies that are subject to lots of mathematical manipulation.
With a predetermined temperature cutoff, it is only possible to manipulate the value of cooling degree days at the margin. This minimizes any data manipulation schemes. It also minimizes the uncertainty in temperature measurements since it is only at the cutoff value that any error would present itself. Any temperature more than 1 degree above the cutoff could have an error or uncertainty that is within reason without causing a large change in the number of cooling degree days calculation.
Is the horizontal line in the graph the best fit line? Is the graph of the USA average? It looks like there is a zero trend. The problem with trying to use cooling degree day to determine changes in space cooling expenditure with increasing temperatures is that the cutoff increases with temperature as people acclimatize to their environments. This is true when comparing residential cooling expenditures per capita of northern states to southern states.
The one thing I can say for sure is if our politicians raise the costs of transportation, through a CO2 tax, or anything else, they are going to seriously harm the U.S. economy.
Transportation taxes of ANY kind should be banned going forward. They directly affect the economy and everyone in it in a detrimental way.
Gasoline prices have increased over a dollar a gallon since Biden took office. That means the U.S. GDP will decline by one percent from here if the prices stay that way.
Increasing the cost of gasoline/transportation even more with a CO2 tax will only reduce U.S. GDP further.
And transportation taxes hurt the poor in society the most, as it raises the cost of everything they buy.
Politicians need to figure out a way to go forward minus any transportation taxes. Get the money needed from General Tax funds, which would not raise transportation costs, and would not, therefore, raise costs on the poor, or the rest of us.
Politicians need to get off their addiction to transpotation taxes. It’s bad, counterproductive policy.
OMB is taking comments on the nonsensical SC-GHG metric. Comments on the absurdity of SC-GHG can be made here: https://www.regulations.gov/document/OMB_FRDOC_0001-0292
I discuss this comment call here: https://www.cfact.org/2021/05/19/epas-obama-era-endangerment-finding-fails-iqa-requirements-2/ (the URL is mistitled).
I urge people to comment!
EPA has cooked up its own goofy Social Cost metric for HFCs. See my
https://www.cfact.org/2021/05/25/major-february-global-temperature-drop-reveals-the-real-climate-control-knob-5/ (URL is mistitled). They too are taking comments, on the whole stupid HFC phaseout for climate change regulation, which is supposedly justified solely by the Social Cost, going out 300 years!
Comment here: https://www.regulations.gov/document/EPA-HQ-OAR-2021-0044-0039
Can’t we come up with a better term than CO2 Fertilization? That is like referring to a meal of steak and potatoes as vitamins. CO2 is the food, not a trace element fertilizer.
Right on- just call it “the primary plant food”.
Exactly! CO2 is the global food supply. No one says this. The last thing we want to do is stop it’s growth.
McKinsey Consulting will gen up a social cost for you for a fee and tune it for an extra fee.