A strong constraint on radiative forcing of well-mixed greenhouse gases.
basic_science · Level V
Where this comes from
- Record sourced from PubMed, PMID 41851465.
- Also identified by DOI 10.1038/s41586-026-10289-x and PMC identifier 13043294.
- Licence recorded as CC BY.
- The licence permits redistribution, so the abstract is shown in full and the full text is available from the publisher.
Abstract
Radiative forcing from well-mixed greenhouse gases (WMGHGs) is a main driver of Earth's energy imbalance and global surface climate change<sup>1,2</sup>. It remains difficult to constrain, largely because its longwave (LW) instantaneous radiative forcing (IRF) component depends on atmospheric state and is subject to radiative parameterization error<sup>3-7</sup>. The IRF measures the immediate change in radiative fluxes at the tropopause<sup>8-10</sup> caused by perturbations in WMGHG concentrations. Here we show that increasing WMGHG concentrations have enhanced LW IRF by 3.69 ± 0.07 W m<sup>-2</sup> (95% confidence interval) since 1850. We first use global line-by-line radiative transfer simulations to provide a global benchmark of LW IRF for the main WMGHGs under realistic, all-sky conditions. We then identify a robust linear relationship between LW IRF and outgoing longwave radiation (OLR), enabling state-dependent LW IRF to be directly inferred from regressions against satellite-observed OLR. Furthermore, LW IRF explains 91% of the inter-model spread in effective radiative forcing (ERF, which includes rapid atmospheric adjustments beyond the IRF) for CO<sub>2</sub> (ref. <sup>11</sup>) across Earth system models. Benchmarking model-simulated IRF using the regression technique reveals that most discrepancies originate from radiation parameterizations and correcting LW IRF biases would reduce uncertainty in CO<sub>2</sub> ERF by 50%. Our results establish a simple and robust framework for quantifying state-dependent radiative forcing of WMGHGs, providing an observation-informed pathway for future climate assessments.