14.7 C
Wednesday, October 27, 2021

Are Climate Feedbacks Strongly Non-Linear?

By Bob Irvine

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

Feedback Factor (FF) is defined as the total temperature change at equilibrium for a given forcing divided by the calculated “no feedback” temperature from that forcing.

The term CO2 will be used here to represent all the non-compressing GHGs. (CO2, MH4, N2O, CFCs, HCFs etc.)


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

It is important here that we represent the alarmist position accurately and honestly. Gavin Schmidt, director of GISS, and his predecessor James Hansen have driven the alarmist narrative with regards to climate feedbacks.

Lacis, Schmidt et al. (2010) represents the alarmist narrative.

Pubs.GISS: Lacis et al. 2010: Atmospheric CO2: Principal control knob governing Earth’s temperature (nasa.gov)

They base their paper 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 of the terrestrial greenhouse effect (GT = TS – TE = 33 K). Assuming global energy balance, TE is also the Planck Radiation equivalent of the 240 W/m2 of global mean solar radiation absorbed by Earth.

They then attribute almost all the GH effect (33C) to CO2 with the water vapor component as a feedback only.

Noncondensing greenhouse gases, which account for 25% of the total terrestrial greenhouse effect, … provide the stable temperature structure that sustains the current levels of atmospheric water vapor and clouds via feedback processes that account for the remaining 75% of the greenhouse effect.”

A Feedback Factor of about 4 is implied by this 25% figure. They then take the next logical step and attribute nearly all climate change to CO2 with insignificant solar input and internal variability being the only other contributors.

These studies established long ago that water vapor and CO2 are indeed the principal terrestrial GHGs. Now, further consideration shows that CO2 is the one that controls climate change.

To the political mind the proof of all this is quite simple.

This misunderstanding is resolved through simple examination of the terrestrial greenhouse.

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

The scope of the climate impact becomes apparent in just 10 years. During the first year alone, global mean surface temperature falls by 4.6°C. After 50 years, the global temperature stands at –21°C, a decrease of 34.8°C. Atmospheric water vapor is at ~10% of the control climate value (22.6 to 2.2 mm). Global cloud cover increases from its 58% control value to more than 75%, and the global sea ice fraction goes from 4.6% to 46.7%, causing the planetary albedo of Earth to also increase from ~29% to 41.8%. This has the effect of reducing the absorbed solar energy to further exacerbate the global cooling.

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

Schmidt then implies that feedbacks to incremental temperature change during the Last Glacial Maxima apply to the warmer interglacial world we inhabit today.


“…the last glacial period is a good example of a large forcing (~7 W/m2 from ice sheets, greenhouse gases, dust and vegetation) giving a large temperature response (~5 ºC) and implying a sensitivity of about 3ºC (with substantial error bars). More formally, you can combine this estimate with others taken from the 20th century, the response to volcanoes, the last millennium, remote sensing etc. to get pretty good constraints on what the number should be. This was done by Annan and Hargreaves (2006), and they come up with, you guessed it, 3ºC.”

In this way a narrative is established. CO2 is promoted as the control knob of the climate with incremental changes in solar activity reduced to insignificant.


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

In their modelled experiment sea ice fraction goes from 4.6% to 46.7% “causing the planetary albedo of Earth to also increase from ~29% to 41.8%.”. 12.8% (41.8 – 29) of 340 w/m2 is a massive ice feedback of 43.5 w/m2 which dwarfs the 25 w/m2 for all the non-condensing GHGs.

In the modern world, ice has retreated to the colder poles where the suns angle is oblique. Ice feedbacks today are an order of magnitude weaker than found in the model experiment. If we take account of this, the feedback factor must be reduced significantly in a warmer world.

At the other extreme, a warmer world will drive greater convection, a huge negative feedback. Convection is allowed for in the models but is extremely complex. If the models have it wrong in any way, feedback factor could be significantly impacted. Certainly, this large negative feedback will be stronger in a warmer world.

Lacis, Schmidt 2010, specifically rule out any feedbacks that are unique to solar activity. These could include, cosmic ray effects, jet stream changes, and any number of others. The oceans temperature profile is overwhelmingly driven by solar forcing. Is it possible that a warmer ocean reacts more vigorously to solar change than a colder ocean?

As an illustration Figure 1 shows a possible relationship between CO2 and feedback factor (FF). There are of course enormous error bars involved here so this should only be treated as “for 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 a FF of 4 at -21C global temps for zero CO2 taken from a 1980 atmosphere), and at 100 ppm (Annan 2006, found a FF of 2.7 at 9C global temps which could apply with 100 ppm CO2).



These exaggerated positive feedbacks may not apply in a warmer interglacial and may have caused all the IPCCs forecasts to fail within 10 years of their announcement. Their forecasts have consistently failed since the first one was attempted by James Hansen in 1988. See Figure 2 below. The most recent of these is the predicted temperature increase in the Fourth Assessment Report 2007. See Figure 9 below.

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

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


These scenarios result in between 750ppm and 800 ppm CO2 concentration in the year 2100. Read the above link to get a sense of the IPCCs processes and their position on future warming.

Figure 3, The IPCC forecast from 2007 compared to actual temperatures. The red line is the Hadcrut4 temperature series.  It is similar to the NASA GISS series and has been adjusted many times. The blue line is the more accurate Mid Troposphere Satellite Temperature data. The yellow line is the NAS data from 1975. NAS was the precursor of NASA and was considered state of the art in 1975.  The 2007 model predictions (Grey Line) are already 0.7C warmer than the measured data in 2021.

Five-year averaged values of annual mean (1979-2015) global bulk (termed “midtropospheric” or “MT”) temperature as depicted by the average of 102 IPCC CMIP5 climate models (red), the average of 3 satellite datasets (green – UAH, RSS, NOAA) and 4 balloon datasets (blue, NOAA, UKMet, RICH, RAOBCORE).

Figure 4. The graph presented to the US House Committee on Science, Space and Technology by John Christy in 2016.  According to the GHG theory, Mid-Tropospheric temperature rise is the fingerprint of GHG warming. It is obvious that the models with their high feedbacks produce more warming in this area than do our most accurate temperature measure, the satellites.  The balloon data also agrees well with the satellites and is well below the models.


Article Rating

Source link

Latest news
Related news


Please enter your comment!
Please enter your name here