Are local weather feedbacks strongly non-linear? – Watts with that?

By Bob Irvine

Is it possible that the Earth system is heavily buffered, with strong positive ice and dust feedbacks prevailing at colder temperatures and strong negative convection / evaporation feedbacks prevailing at warmer times?

The feedback factor (FF) is defined as the total equilibrium temperature change for a given drive divided by the calculated no feedback temperature from that drive.

The term CO2 is used here to represent all non-compressing greenhouse gases. (CO2, MH4, N2O, CFC, HCF etc.)


It is certainly possible that in a world where H2O is present as vapor in the atmosphere, as well as water and ice, strong positive feedbacks can occur.

Here it is important that we take the alarmist position precisely and honestly. Gavin Schmidt, director of GISS, and his predecessor James Hansen drove the alarmist narrative regarding climate feedback.

Lacis, Schmidtet al. (2010) represents the alarmist narrative.

Pubs.GISS: Lacis et al. 2010: Atmospheric CO2: Main controller for the temperature of the earth (

They base their work on the following assumption, which I accept.

The difference between the nominal global mean surface temperature (TS = 288 K) and the global mean effective temperature (TE = 255 K) is a common measure for the terrestrial greenhouse effect (GT = TS – TE = 33 K). Assuming a global energy balance, TE is also the Planck radiation equivalent of the 240 W / m2 of global mean solar radiation that is absorbed by the earth.

They then attribute almost the entire GH effect (33 ° C) to CO2, with the water vapor component only serving as feedback.

non-condensing greenhouse gases, which make up 25% of the total terrestrial greenhouse effect … provide the stable temperature structure that maintains the current levels of atmospheric water vapor and clouds via feedback processes that make up the remaining 75% of the greenhouse effect. “

A feedback factor of around 4 is implied by this 25% figure. Then they take the next logical step and attribute almost all climate change to CO2, with insignificant solar input and internal variability being the only other factors.

These studies determined a long time ago that water vapor and CO2 are indeed the major terrestrial greenhouse gases. Now, a further consideration shows that CO2 is the one controlling climate change.

To the political mind, the evidence for all of this is quite simple.

This misunderstanding is resolved by a simple study of the terrestrial greenhouse.

The idea of ​​“CO2 as a climate controller” is then reinforced by removing all of the CO2 from the 1980 atmosphere using the GISS Model E climate model [G. A. Schmidt et al., J. Clim. 19, 153 (2006)]. The resulting enormous temperature drop after feedback is described below in Lacis, Schmidt et al. 2010.

The extent of the climate impact will be visible in just 10 years. In the first year alone, the global mean surface temperature drops by 4.6 ° C. After 50 years the global temperature will be –21 ° C, a decrease of 34.8 ° C. The atmospheric water vapor is ~ 10% of the control climate value (22.6 to 2.2 mm). The global cloud cover increases from its control value of 58% to more than 75%, and the global sea ice percentage increases from 4.6% to 46.7%, which also increases the planetary albedo of the earth from ~ 29% to 41.8%. This has the effect of reducing the absorbed solar energy to further exacerbate global cooling.

Some of the water vapor is then attributed to the sun (10%), you can believe, which leaves an approximate CO2 forcing feedback factor of 3.3. The official number has not changed to this day.

Schmidt then implies that feedbacks on incremental temperature changes during the maxima of the last Ice Age also apply to the warmer interglacial period that we inhabit today.

The CO2 problem in 6 easy steps

“… the last ice age is a good example of a large drive (~ 7 W / m2 through ice sheets, greenhouse gases, dust and vegetation), which results in a large temperature reaction (~ 5 ° C) and implies a sensitivity of around 3 ° C ( with significant error bars). Formally, you can combine this estimate with others from the 20th century, volcano reaction, last millennium, remote sensing, etc. to get pretty good limits on the number. That was done by Annan and Hargreaves (2006), and they come on, you guessed it, 3 ° C. “

This is how a narrative is created. CO2 is promoted as a control button of the climate, gradually reducing changes in solar activity to an insignificant one.


The alarmist narrative is too simple and all climate models are running hot. This means that all predictions based on these models have failed (see Appendix “A”). There are some areas where the Lacis, Schmidt 2010 approach is of immediate concern.

In their modeled experiment, the proportion of sea ice increases from 4.6% to 46.7% “Which leads to the fact that the planetary albedo of the earth also increases from ~ 29% to 41.8%.” 12.8% (41.8 – 29) of 340 W / m2 is massive ice feedback of 43.5 W / m2, which dwarfs the 25 W / m2 for all non-condensing greenhouse gases.

In the modern world, the ice has retreated to the colder poles where the angle of the sun is crooked. Ice feedback is now an order of magnitude weaker than found in model experiments. Taking this into account, the feedback factor must be reduced significantly in a warmer world.

On the other hand, a warmer world will lead to more convection, a huge negative feedback. Convection is taken into account in the models, but it is extremely complex. If the models are wrong in any way, the feedback factor could be significantly affected. Surely that big negative feedback will be stronger in a warmer world.

Lacis, Schmidt 2010, expressly exclude any feedback that can only be traced back to solar activity. This can include cosmic ray effects, jet stream changes, and any number of others. The temperature profile of the oceans is mainly determined by solar propulsion. Is it possible that a warmer ocean is more responsive to the sun’s change than a colder ocean?

To illustrate this, Figure 1 shows a possible relationship between CO2 and the feedback factor (FF). There are of course enormous error bars here, so this should only be treated as “Discussion Only”.

Figure 1. A possible comparison between CO2 concentration and feedback factor (FF). The low modern feedback factor reflects my own prejudices. The other two control points are at zero CO2 ppm (Lacis 2010, found an FF of 4 at -21 ° C global temperatures for zero CO2 from an atmosphere from 1980) and at 100 ppm (Annan 2006, found an FF of 2.7 at 9 ° C global) Temperatures that could apply with 100 ppm CO2).



This overly positive feedback may not apply to a warmer interglacial period and may have caused all IPCC predictions to fail within 10 years of their announcement. Their predictions have consistently failed since James Hansen’s first attempt in 1988. See Figure 2 below. The most recent of these is the projected temperature rise in the Fourth Assessment Report 2007. See Figure 9 below.

Figure 2. Hansen’s failed predictions from 1988. CO2 concentrations have actually increased faster than in scenario “A”. The black and red lines are the heavily adjusted surface record (always adding extra warming on average).

Current CO2 concentrations are rising at a rate similar to the A1T and B2 scenarios in the 4AR IPCC report copied here. I used them for this reason.

These scenarios lead to a CO2 concentration between 750 ppm and 800 ppm in the year 2100. Read the link above for a glimpse of the IPCC processes and their position on future warming.

Figure 3, The IPCC 2007 forecast compared to actual temperatures. The red line is the Hadcrut4 temperature series. It is similar to the NASA GISS series and has been adapted several times. The blue line is the more accurate data of the satellite temperature in the middle troposphere. The yellow line is NAS data from 1975. NAS was the forerunner of NASA and was considered state of the art in 1975. The model predictions from 2007 (gray line) are already 0.7C warmer than the measurement data from 2021.

Five-year mean values ​​of the annual mean (1979-2015) of the global mass temperature (referred to as “midtropospheric” or “MT”) as determined by the average of 102 IPCC CMIP5 climate models (red), the average of 3 satellite data sets (green – UAH, RSS , NOAA) and 4 balloon data sets (blue, NOAA, UKMet, RICH, RAOBCORE).

Figure 4. The graphic presented by John Christy to the US House of Representatives Science, Space and Technology Committee in 2016. According to the GHG theory, the temperature rise in the middle troposphere is the fingerprint of GHG warming. It is obvious that the models, with their high levels of feedback, generate more heating in this area than our most accurate temperature measurement, the satellites. The balloon data also agree well with the satellites and are well below the models.


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