intermediate 9 min read
Earth sciences · Topic
Radiative Forcing
probability theory · differential equations
Radiative forcing (RF) quantifies how much an agent — such as increased CO₂ or aerosol emissions — perturbs the top-of-atmosphere energy balance before climate feedbacks respond. It is the standard metric for comparing drivers of climate change and anchors the relationship between emissions and temperature response.

Definition and types of radiative forcing

Instantaneous RF is the change in net irradiance at the tropopause immediately after imposing an agent, before any temperature or circulation adjustments:

\[\Delta F_{inst} = F_{perturbed} - F_{control} \quad [\text{W m}^{-2}]\]

Stratospherically adjusted RF (conventional RF): the stratosphere is allowed to re-equilibrate (typically ~2 months) while tropospheric temperatures are fixed. This removes the large but fast stratospheric response and gives a forcing more predictive of surface temperature change.

Effective RF (ERF): tropospheric adjustments (cloud cover, water vapor, land albedo) are also allowed to respond — only surface temperature is fixed. ERF is now preferred in IPCC AR6 because it better predicts transient warming:

\[ERF = \Delta F_{inst} + \text{rapid adjustments}\]

The forcing-response relationship is approximately linear:

\[\Delta T = \lambda \cdot ERF\]

where $\lambda \approx 0.8$ K (W m⁻²)⁻¹ is the equilibrium climate sensitivity parameter.

CO₂ logarithmic forcing

The radiative forcing from CO₂ follows a logarithmic relationship because the main absorption bands are already saturated; additional CO₂ absorbs in the band wings:

\[\Delta F_{CO_2} = \alpha\ln\left(\frac{C}{C_0}\right)\]

with $\alpha \approx 5.35$ W m⁻² (Myhre et al. 1998, IPCC AR5). At doubled CO₂ ($C = 2C_0$):

\[\Delta F_{2\times CO_2} = 5.35\ln 2 \approx 3.71 \text{ W m}^{-2}\]

The logarithmic dependence arises from the Voigt line shape of CO₂ absorption features. At very high concentrations the forcing transitions toward a square-root dependence as continuum absorption dominates.

Agent RF (W m⁻²) Uncertainty
CO₂ (1750–2019) +2.16 ±10%
CH₄ +0.54 ±20%
N₂O +0.21 ±10%
Halocarbons +0.41 ±10%
Total aerosol −1.1 ±50%
Solar +0.01 ±50%

Aerosol forcing: direct and indirect effects

Aerosols scatter and absorb solar radiation (direct effect) and modify cloud properties (indirect/Twomey effect).

Direct RF depends on aerosol optical depth $\tau$, single-scatter albedo $\omega_0$, and asymmetry factor $g$:

\[\Delta F_{direct} = -\frac{S_0}{4}T_{atm}^2(1-A_c)(1-\omega_0 f)\left[2\omega_0\beta\tau\right]\]

where $f = g^2$, $\beta$ is the backscatter fraction, and $A_c$ is cloud fraction.

Twomey (first indirect) effect: More aerosol $\Rightarrow$ more cloud condensation nuclei $\Rightarrow$ smaller droplets $\Rightarrow$ higher cloud albedo $\alpha_c$. For fixed liquid water path:

\[\frac{d\alpha_c}{d\ln N} \approx \frac{\alpha_c(1-\alpha_c)}{3}\]

The second indirect (lifetime) effect: smaller droplets suppress precipitation, increasing cloud lifetime and coverage. Total aerosol ERF is estimated at $-1.1 \pm 0.4$ W m⁻² (AR6), the largest uncertainty in the forcing budget.

Solar forcing and stratospheric ozone

Solar forcing varies with the 11-year sunspot cycle ($\Delta F \approx \pm 0.1$ W m⁻²) and longer-term changes in total solar irradiance (TSI). Since 1750, the net solar ERF is only $+0.01$ W m⁻² — negligible compared to greenhouse gas forcing.

Stratospheric ozone depletion (CFCs) exerts a negative RF through two mechanisms:

  1. Reduced ozone absorbs less solar UV $\Rightarrow$ less warming of stratosphere $\Rightarrow$ more OLR to space
  2. Less stratospheric ozone also reduces downward IR emission

The net ozone RF was approximately $-0.05$ W m⁻² over 1750–2019.

Transient vs equilibrium response and forcing efficacies

The transient climate response (TCR) is the warming at the time of CO₂ doubling under a 1% per year increase:

\[TCR = \lambda_{eff} \cdot \Delta F_{2\times} \approx 0.55 \times ECS\]

The ratio TCR/ECS $< 1$ because the ocean absorbs heat: the net forcing driving surface warming is $N = ERF - \lambda\Delta T$ where $N$ is ocean heat uptake rate.

Forcing efficacy $e$ accounts for different geographic/vertical patterns having different temperature impacts per unit forcing. Defined as:

\[e = \frac{ECS_i / \Delta F_{2\times CO_2}}{ECS_{CO_2} / \Delta F_{2\times CO_2}} = \frac{\lambda_{CO_2}}{\lambda_i}\]

Solar forcing has efficacy ~1.0; volcanic forcing has ~0.6 (short-lived aerosols at low latitudes); land-use albedo ~1.0; black carbon on ice ~3 (very high, as it affects the ice-albedo feedback strongly).

Attribution of observed warming

The energy budget attribution links observed warming $\Delta T_{obs} \approx 1.1$ K (1850–2019) to forcing components via:

\[\Delta T = \sum_i \lambda_i \cdot ERF_i\]

In a regression framework, observed temperature $\mathbf{y}$ is decomposed:

\[\mathbf{y} = \sum_k \beta_k \mathbf{x}_k + \boldsymbol{\varepsilon}\]

where $\mathbf{x}_k$ are GCM-simulated fingerprints (greenhouse gas, aerosol, natural) and $\beta_k$ are scaling factors estimated by optimal fingerprinting:

\[\hat{\boldsymbol{\beta}} = (X^T C^{-1} X)^{-1} X^T C^{-1} \mathbf{y}\]

Here $C$ is the internal variability covariance estimated from unforced control runs. IPCC AR6 concludes: it is unequivocal that human influence has warmed the climate. The greenhouse gas contribution is $+1.0$ to $+2.0$ K, partially offset by aerosol cooling of $−0.5$ to $−0.2$ K.