The amount of water vapor injected into the stratosphere (SWV) after the eruption of Hunga Tonga-Hunga Ha'apai (HTHH) was unprecedented. This new paper evaluated the surface temperature and precipitation impacts of the HTHH water vapour perturbation using a chemistry climate model simulation. The paper’s abstract says “The simulations show that the SWV anomalies lead to strong and persistent warming of Northern Hemisphere landmasses in boreal winter, and austral winter cooling over Australia, years after eruption, demonstrating that large SWV forcing can have surface impacts on a decadal timescale. Surface temperatures across large regions of Northern Hemisphere increase by over 1.5 °C for several years

Dr. Roy Spencer said "If we assume ALL *observed* warming of the deep oceans and land since 1970 has been due to humans, we get an effective climate sensitivity to a doubling of atmospheric CO2 of around 1.9 deg. C." He and Dr. John Christy used a 1-D climate model that conserves energy to calculate the climate sensitivity that best fits the warming measured in the land, air and oceans. The lower UAH value indicates that the climate impact of increasing carbon dioxide concentrations is much less that that based on other climate models. 3-D climate models used by the IPCC do not conserve energy which makes then useless of public policy. The model uses variety of observational datasets of warming between 1970 and 2021 of the deep ocean and land. The estimate of 1.9 °C uses the new SSP2-45 emissions scenario. The global urban heat island effect from 1980 to 2021 is estimated at 0.168 °C and the millennium cycle recover from the Little Ice Age may have contributed 0.043 °C to the measured warming. Taking these warming sourced into account reduces the effective climate sensitivity from 1.9 °C to 1.4 °C for a doubling of CO2.

We use temperature, pressure and relative humidity data of 12 atmospheric layers obtained from two state-of-the-art global reanalysis datasets and results from a line-by-line radiative code to calculate the water vapour feedback. The results suggest that the water vapour feedback is about 66% of the IPCC’s assessed value; 67% using the ERA5 dataset and 65% using the NECP2 dataset. A change of water vapour mass in the 100-150 mbar pressure atmospheric layer causes a change in radiative forcing that is 284 times greater than in the 1000-1013 mbar near-surface layer. The relative humidity values in the Polar Regions are much different between the two datasets. ERA5 gives the relative humidity at the 250 mbar pressure level at the South Pole at 2.5% while NECP2 says it is 64%. Large humidity discrepancies between the datasets and water vapour feedback estimates show that climate science is far from settled.

In 2015 over thirty experts attended a week-long workshop in Ringberg Castle to assess gaps in understanding of Earth’s climate sensitivities. This culminated in the publication in 2020 of a paper by Steven Sherwood and 24 co-authors (Sherwood20) which was cited over twenty times in the relevant AR6 chapter. The paper used a Subjective Bayesian statistical approach which result in unrealistic estimates. Nic Lewis redid the calculation using an Objective Bayesian approach. He also found important conceptual errors and inconsistencies in Sherwood20. After fixing these problems , the resulting estimate of climate sensitivity fell substantially. The abstract of this paper says "This study corrects Sherwood et al.'s likelihood estimation, producing estimates from three methods that agree closely with each other, but differ from those that they derived." The corrected calculated climate sensitivity is median 2.16°C, 17−83% likely range 1.75−2.7°C, 5−95% very likely range 1.55−3.2°C. This is much lower than the AR6 value based on Sherwood20 of central value 3°C, very likely range 2.0−5.0°C. Lewis wrote "climate sensitivity remains difficult to ascertain, and that values between 1.5°C and 2°C are quite plausible." The Transient Climate Response (TCR) estimate is 1.54°C (17-83% likely range 1.25–2.0°C).

Global climate models used in the last IPCC climate assessment report (AR6) predict equilibrium climate sensitivity (ECS) values ranging between 1.8 and 5.7 °C. Dr. Nicola Scafetta published this paper which reduces the ECS range by comparing the models’ accuracy and precision in hindcasting to four global surface temperatures datasets as well as the UAH satellite dataset over the period 1980 to 2021. The 38 climate models were assigned to low, medium and high ECS groups. Only the low ECS group, with ECS values between 1.5 °C and 3.0 °C are consistent with the surface temperature data. The satellite data has a lower trend because it isn't affected as much by urban warming. Assuming the UAH satellite data is representative of the warming at the surface, the low ECS group should be scaled down by 33%, giving an ECS range of 1.0 °C and 2.0 °C. Adjusting the ECS for natural climate oscillations could reduce the ECS range to 0.7 °C to 1.7 °C.

The paper LC2018 presents estimates of climate sensitivity parameters ECS and TCR with uncertainty analysis. Unfortunately, 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 urban heat island effect (UHIE) from the temperature record. This study presents corrected estimates of ECS and TCR with uncertainty estimates by including the UHIE and natural warming. The median (best estimate) of ECS and TCR are estimated at 1.19 °C and 0.95 °C, respectively. Global average temperatures are forecast to increase by 0.87 °C from 2020 to 2100, assuming the GHG concentrations in the atmosphere increase exponentially and no natural climate change. The FUND economic model, using updated energy impacts and CO2 fertilization effects calculates that a 2 °C GMST rise from 2020 would increase global wealth by 9.8% of 2020 world income by 2146, equivalent to 2020US$8.8 trillion.