It so difficult to constrain errors in identifying the cloud impact on Earth’s radiation budget that the orders-of-magnitude smaller radiative impact of CO2 cannot be distinguished from noise.
According to a new study using CERES data, the observed biases in detecting the radiative effects of clouds on climate are 2.5 to 6.25 W/m² for longwave (LW) and shortwave (SW), respectively (Sun et al., 2022). Standard deviations in cloud radiative effects amount to 8 (LW) to 20 (SW) W/m². This variability and built-in estimation error wipes out the isolation of CO2 as a detectable factor in top of atmosphere (TOA) climate forcing.
This is because the cloud radiative effects (CRE) bias and standard deviation values are 15 to 100 times larger than the presumed cumulative surface radiative effects of CO2 forcing over a span of 10 years (0.2 W/m²).
Image Source: Sun et al., 2022
It has long been estimated that when clouds are present they dominate as the driver of greenhouse effect forcing. Quantitatively, the greenhouse effect of clouds is larger than a 100-fold increase in the CO2 concentration (~40,000 ppm).
Image Source: Ramanathan et al., 1989
The shortwave radiative effect of clouds is even larger, with ranges of ±300 W/m² (Sedlar et al., 2022). These values are 3,000 times greater than the total effect of CO2 surface forcing (0.2 W/m²) over a span of 10 years (Feldman et al., 2015).
Image Source: Sedlar et al., 2022
In other words, we might as well be guessing.