image: (A) Illustration of Nature’s climate feedback “circuit”, (B) global mean surface energy balance in the climate mean state, and (C) perturbation surface energy balance in response to external energy perturbation ΔFext. In panel (A), the garnet, solid orange, and solid blue arrows represent the external energy input, amplified external energy input, and energy output from Earth's climate system, respectively. The top (blue) box represents the thermal radiative emissions of individual layers in an atmosphere-surface column, and the bottom (orange) box corresponds to the total climate feedback kernel, which equals the product of the energy gain kernel of temperature feedback (matrix on the right) and the non-temperature feedback kernel (matrix on the left). In panel (B), the garnet, orange, and blue arrows represent the climate mean total solar energy absorbed by the surface, the downward thermal energy emitted from the atmosphere, and the total energy output from the surface equal to the sum of surface thermal energy emission and surface sensible and latent heat fluxes, respectively. The numbers next to the arrows are their climate mean and global mean values. In panel (C), the mixed-color and blue arrows represent the total input energy and thermal emission perturbations at the surface, respectively. The strength of the total input energy perturbations equals the product of the input energy perturbation (ΔFext), temperature feedback kernel (G), and surface element of the non-temperature feedback kernel. The surface element of the non-temperature feedback kernel for the perturbed climate state is approximated to have the same value as the amplification of the total solar energy input at the surface in the climate mean state.
Credit: ©Science China Press
A research team led by Professor Ming Cai from Florida State University, in collaboration with researchers from Sun Yat-sen University, Peking University, and the Massachusetts Institute of Technology, recently published a groundbreaking paper in National Science Review. Titled “Principles-Based Adept Predictions of Global Warming from Climate Mean States”, the study introduces a novel framework that accurately predicts the magnitude and spatial pattern of global warming caused by greenhouse gas emissions, without relying on complex climate models or statistical analysis. For the first time, this study confirms that observed global warming is driven by human-caused greenhouse gas emissions, independently of these conventional approaches.
This new framework incorporates energy balance principles and the coupled atmosphere-surface thermal absorption and emission processes, modeled similarly to feedback loops in electrical circuits. It directly quantifies the amplification of external energy inputs through climate feedback processes, using the information from climate mean states. Unlike climate models, this approach bypasses the need for costly time integrations to equilibrium and instead directly and efficiently calculates the equilibrium response of the global climate system to external energy perturbations.
The observed global mean warming from 1980–2000 to 2000–2020 is 0.414 K, while the framework predicts a warming of 0.403 K based solely on observed CO₂ concentration changes, excluding natural climate variability and aerosols. In comparison, climate simulations by CMIP6 models overestimate the observed warming by 50%. Additionally, the new framework’s predictions have a smaller global mean absolute error compared to CMIP6 models. This study also tested the framework under two assumed CO₂ scenarios: a sudden quadrupling of CO₂ and a 1% annual increase in CO₂. The framework accurately reproduced the global warming projections for each of these scenarios from CMIP6 models, with smaller uncertainty in warming predictions compared to the models. These results highlight the new framework's reliability and broad applicability.
Journal
National Science Review
Method of Research
Computational simulation/modeling