By Andy May
IN part One We discussed the different estimates of climate sensitivity (ECS, TCR and observation-based values) and their implications, especially those reported in the latest AR6 report. of the IPCC. IN part 2 we discussed the uncertainty in estimating the cloud response to surface warming and the relationship of the cloud response to the ECS. IN part 3 We compared different estimates with each other and discussed the differences between them. In this section we will discuss how Lewis and Curry convert their observational estimates of climate sensitivity into ECS values equivalent to AR6. Most of the observational to model-based ECS conversions are done in a similar way.
Lewis and Curry 2018 (LC18) matched base and terminal phases based on a record of volcanic activity and a declining Atlantic Multi-Decade Oscillation (AMO). Other possible sources of natural variation, including solar conversion, have been omitted. Using these time periods, an ECS estimate is calculated using the equations and values in figure 1 below.
In the table of ECS and TCR estimates, all ECS estimates are below the lower limit of AR6 possibly 2.5°C. Lewis and Curry’s TCR estimates are both well below the AR6’s lower limit of possibly 1.4°C. This is true, although Lewis and Curry accepted most of the assumptions made by the IPCC in AR6.
In the equations, is the climate response parameter in W/m2 forced to increase with the degree of surface warming. LC18 assumes that λ is a constant. LC18 also assumes that:
where ΔR is the radiative response to a positive change in radiative forcing (ΔF) causing a positive change in the radiative imbalance from the descending top of the atmosphere (TOA) (N) . The term μr is a random residual term, meaning that zero denotes a variation of the weather or internal climate that is unrelated to a change in surface temperature (ΔT). In essence, R is the response to the change in surface temperature multiplied by the feedback parameter plus the internal climate variation, which is assumed to be random to zero over the selected time period. The time periods considered are listed in Figure 1.
By assuming that λ is constant for all selected time periods, then it does not depend on surface temperature, climate change, and radiative force change (ΔF). So:
λ= (ΔF-ΔN)/ΔT
The above equation is derived from the law of conservation of energy and assumes that the change in internal energy (μr) during the selected time period sums to zero. LC18 (and AR6) then assumes that the only external force is due to volcanism and CO changes.2F2xCO2. This means that the ECS can be calculated using the bottom equation in figure 1 if the periods are chosen such that the volcanic activity is almost the same and the periods fall into the same part of the 60-70 AMO cycle year. These are the same assumptions made by the IPCC.
Reality check
The LC18 uses a downtrend AMO, as shown in the chart above in figure 2. Downtrend emphasizes the periodicity in the AMO, but it removes the obvious long-term trend in the raw data that has not yet trended in the past. the chart below in figure 2.
The longer-term trend affects fundamental comparisons with the final period identified in figure 1. The cause of the underlying long-term trend in the AMO is unknown but may be due to the Present Solar Maximum. is defined in figure 3.
Changes in solar activity are generally small from one solar cycle to another and from low to high solar cycle. But they accumulate over time. Extended solar peaks such as modern solar peaks could have a major impact on climate if they persist long enough. The Modern Solar Maximum is the longest period of solar activity in 600 years (Viños, 2022, p. 210). Given this and the obvious trend in crude AMO, it seems likely that the difference between the LC18 base and the final stage is not entirely due to the CO change.2 as assumed by the equations in figure 1.
conclude
The AMO and solar activity trends have increased over the past 170 to 300 years, not as flat as is clearly assumed in LC18 and AR6. Therefore, their ECS and TCR values are maximum values and are not estimates of actual values. This is generally true of almost all observational and model-based estimates of the ECS and TCR.
However, nearly all observation-based estimates of ECS and TCR fall below the lower limit of likely reported in AR6. The problem with the new AR6 climate sensitivity estimates is not only that they are too high, they are also higher than the estimates maximum possible estimates based on observations. This is a point not made often enough.
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