Thank you for the link. It is easier to calculate the warming trend in the period when the CO2 goes from 280 to 560 ppm, without going through a smoothing or measurement averages.

Starting from your annual anomalies, year by year, from 1880 to 2021, I find a trend of +2.62°C, very close to my previous calculations. See the attached curve on:

http://www.dropbox.com/s/g1g4oeeekzv8zc9/curve%20CO2%20annuel.jpg?dl

OK. It all really depends on the definition of the original baseline from which we estimate net warming.

These are my annual temperature anomalies back to 1880 with a baseline of 1961-1990

https://clivebest.com/data/V4S4C-annual-triang-sphere-anoms.txt

]]>Tamino, in his site “Open mind” had a post on May 1, 2022 on the comparison between temperature and CO2, supplemented on May 5 by a comparison between temperature and radiative forcing of CO2.

For the graph I sent, I used your monthly anomalies for temperature and seasonally adjusted Mauna Loa estimates or Law Dome ice cores for CO2 level.

I looked for, every + 5ppm of CO2, your corresponding anomaly estimate, averaged over 6 to 22 months depending on the slope of the CO2 rate to limit the influences of volcanoes or Enso. Base 300 ppm between 1905 and 1907.

Based on measurement estimates from 1880 to 2022, I obtained ~ + 2.7°C during a doubling of the CO2 rate (see curve previously provided).

More simply, if I do the same calculation by directly comparing each monthly anomaly evolution with the corresponding CO2 rate, I obtain + 2.68°C.

If I want a ten-year vision, I use the Loess function with smoothing over a period of 120 months, to limit background noise, the correlation coefficient is much higher. I get +2.67°C for a doubling of C02 with a logarithmic regression.

If I understood your explanation correctly, the figure of 1.7°C, which you indicated on your curve, is the additional warming expected after 2022, when the CO2 level will reach 560 ppm.

My misunderstanding came from your last paragraph: “With these assumptions, a doubling of CO2 would lead to a net increase of 1.7°C in global temperatures compared to what appears to have been a colder period in the 19th century. »

It must therefore be added to the ~ +1.2°C of warming already achieved since the pre-industrial period. This would therefore be ~+2.9°C for a period in which the rate of warming will have doubled.

Slightly more than the values ??obtained by regression above.

But this does not represent the TCR or the ECS.

For example, in the period from 1970 to 2022, we must not forget that the positive radiative forcing of other greenhouse gases has also increased. It now represents more than half of that of CO2 and adds to it. At the same time, the negative aerosol forcing increased until 2011 and then stabilized.

Complete bullocks because the temperature of the new layer would be maintained by convection, regardless of the radiative imbalance I described (480 w/m2 output but only 240 w/m2 input).

]]>The back radiation argument is complete bollocks !

]]>Doesn’t look like my decadal data though !

What are you using? My annual data ?

Vous pouvez sempre utiliser un URL pour voir l’image.

]]>Nice!

Note that no-one else plots temperatures against CO2. My argument was the following: In the stable decadal trend between the1970s and the 2002’s we have a linear temperature increase with CO2 for a 0.8C rise in temperature. Therefore the extrapolation to reach 560 ppm implies a temperature increase of (160/72) * 160 = 1.77 C . So I agree the data implies TCR is more like 1.8C.

]]>@gpiton, looking at Clive’s previous post which describes his methodology, it looks like, for this model, Clive assumes that the temperature at 0ppm CO2 will be 284K, rather than letting this be a free-floating parameter to be determined by fitting.

The result of this assumption is a poorer fit in the last figure on this post, where it does indeed look like the slope of temperature-CO2 is too shallow.

For everyone reading along, go look at this last figure in the post above. Does the slope of the orange line (observations) match the slope of the black line (Clive’s model)? Or is the orange line a lot steeper than the black line?

That’s the bad fit. A better fit would show a steeper slope for the black line, matching the orange line better, which would also mean stronger CO2 sensitivity.

If we want to get mathy, we can also mathematically demonstrate that this is a poorer fit by calculating the RMS of the difference.

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