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The Greenhouse Effect
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31 Articles

Climate Sensitivity by Energy Balance with Urban and Natural Warming

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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 1.04 °C and 0.83 °C, respectively. Global average temperatures are forecast to increase by 0.63 °C from 2019 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 and assuming an ECS of 1.0 °C, calculates that a 2 °C GMST rise from 2000 would increase global wealth by 1.45% by 2147, equivalent to 2019US$1.26 trillion.

Total Precipitable Water and the Greenhouse Effect

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Total precipitable water is an important climate parameter as it is a measure of the total amount of water vapour which is the most important greenhouse gas in the atmosphere. Water vapor increases with global warming and in the climate models it amplifies the direct small warming caused by anthropogenic greenhouse gas emissions. It is often incorrectly assumed that an increase in total precipitable water corresponds to a positive water vapour feedback. The greenhouse effect is very sensitive to water vapour in the upper atmosphere. This article shows that based on humidity data from a major reanalysis dataset, declining humidity in the upper atmosphere offsets the greenhouse effect of increasing humidity in the lower atmosphere. The greenhouse effect of increasing water vapour in the atmosphere may not have caused a positive water vapor feedback, contrary to climate models. This may explain why the climate models have simulated a global surface warming from 1979 to 2019 of twice the satellite observed warming. Eliminating the water vapour feedbacks from climate models would reduce the mean climate sensitivity from 3.2 °C to 1.7°C.

New 80-Year Deep-Ocean Temperature Dataset Compared to a 1D Climate Model

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A new paper Cheng et al 2020 presents a dataset of 0-2000 m ocean heat content (OHC) from 1940 to 2019 that uses “optimum interpolation�? to extend the geographic coverage of limited data. The ARGO network of floats has dramatically improved the global coverage as it was deployed 2001-2005. Dr. Roy Spencer updated his 1D model of ocean temperature with this dataset to match its warming trend over the 80-year period. The model includes El Nino and La Nina (ENSO) variability to capture year-to-year temperature changes. If it is assumed that all of the ocean warming was human-caused, the best fit to the data gives an equilibrium climate sensitivity (ECS) of 1.85 °C. Spencer says this is only about 50% of the ECS from climate models.

Richard Lindzen on Climate Sensitivity

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Dr. Richard Lindzen wrote this special report on climate sensitivity for the CO2 Coalition. It is commonly accepted that increasing CO2 in the atmosphere should lead to some warming, but the amount depends on how the initial warming by CO2 will affect water vapour and clouds. Simple descriptions of the greenhouse effect (GHE) consider clear skies without clouds, but the infrared opacity of upper-level cirrus clouds is often large enough that when such clouds are above the emission level for the greenhouse gases, they block the infrared radiation from from the gases, and the new emission level is near the top of these clouds. Climate models fail to describe the behavior of upper-level cirrus clouds. The areal coverage of such clouds decreases with temperature, acting as a negative feedback. The observations of top of the atmosphere radiative fluxes show that there are no long-wave positive feedbacks and that they may well be negative. This means that CS above 1.5 °C are very unlikely and that it is likely around only 1 °C, which would be beneficial to the global economy.

How Much CO2 and the Sun Contribute to Global Warming

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A simplified climate model and extensive line-by-line radiation transfer calculations are used to investigate the contribution of greenhouse gases, mostly CO2, and solar effects to global warming over the 20th century. The simulations reproduce the direct, no-feedback equilibrium climate sensitivity (ECS) of CO2 as estimated by the IPCC within a few percent. The model gives a positive water vapour feedback of not more that 14%, which is 1/7 of the IPCC's value. The model shows that the surface temperatures increase faster than air temperatures, so warming causes more convection and evaporation and precipitation, resulting in strong negative feedbacks. The simulations show that the global warming and cloud changes can best be explained when the temperature feedback on clouds has only a minor effect but the sun induced lower cloud cover. The author estimates the climate sensitivity of 0.7 °C and a solar sensitivity of 0.17 °C for a 0.1% increase in TSI. The sun contributed 60% and GHG contributed 40% of the warming over 100 years.