# A strong constraint on radiative forcing of well-mixed greenhouse gases

**Authors:** Jing Feng, David Paynter, Raymond Menzel, Ryan Kramer

PMC · DOI: 10.1038/s41586-026-10289-x · Nature · 2026-03-18

## TL;DR

This study provides a new method to accurately measure the longwave radiative forcing of greenhouse gases using satellite data and simulations, improving climate predictions.

## Contribution

A robust linear relationship between longwave radiative forcing and outgoing longwave radiation is established for better climate modeling.

## Key findings

- LW IRF from WMGHGs increased by 3.69 ± 0.07 W m−2 since 1850.
- LW IRF explains 91% of CO2 ERF inter-model spread in Earth system models.
- Correcting LW IRF biases could reduce CO2 ERF uncertainty by 50%.

## Abstract

Radiative forcing from well-mixed greenhouse gases (WMGHGs) is a main driver of Earth’s energy imbalance and global surface climate change1,2. 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 error3–7. The IRF measures the immediate change in radiative fluxes at the tropopause8–10 caused by perturbations in WMGHG concentrations. Here we show that increasing WMGHG concentrations have enhanced LW IRF by 3.69 ± 0.07 W m−2 (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 CO2 (ref. 11) 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 CO2 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.

Comparing line-by-line transfer simulations using the radiation code GRTcode with regressions against satellite-observed ongoing longwave radiation shows that instantaneous longwave radiative forcing from well-mixed greenhouse gases has increased by 3.69 ± 0.07 W m−2 since 1850.

## Full-text entities

- **Diseases:** CKD (MESH:D012080), PD (MESH:D014786), WMGHGs (MESH:C536693)
- **Chemicals:** GHG (MESH:D000074382), N2O (MESH:D009609), CFCs (MESH:D017402), CO2 (MESH:D002245), water (MESH:D014867), CH4 (MESH:D008697), AMIP (-), C (MESH:D002244), O3 (MESH:D010126), HFC-134a (MESH:C063006), CFC-12 (MESH:C007782)
- **Mutations:** C - C0

## Full text

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## Figures

15 figures with captions in the complete paper: https://tomesphere.com/paper/PMC13043294/full.md

## References

11 references — full list in the complete paper: https://tomesphere.com/paper/PMC13043294/full.md

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Source: https://tomesphere.com/paper/PMC13043294