Colloquium with Ming Cai (2026-03-04)

"Principle-Based Climate Feedback Framework and Its Application for Adept Predictions of Global Warming from Climate Mean States"

Ming Cai
Department of Earth, Ocean, and Atmospheric Science (EOAS)
Florida State University (FSU)

Wednesday, Mar 4, 2026

Colloquium - 499 DSL Seminar Room: 03:30 to 04:30 PM Eastern Time (US and Canada)

Abstract:

Distinguishing anthropogenic warming from natural variability in observations and reducing uncertainty in global warming projections by climate models remain critical challenges for climate scientists. In our work, we present a groundbreaking principle-based framework for adept predictions of the global mean warming and its spatial pattern in response to external energy perturbations from climate mean states without running climate models or relying on statistical trend analysis.

The principle-based framework is built on a climate feedback kernel, referred to as the "energy gain kernel" (EGK). EGK is directly derived from physical principles without additional definition. EGK captures the temperature feedback’s amplification of energy perturbations initiated both from external forcing and internal non-temperature feedback processes. EGK allows for disentangling positive and negative aspects of temperature feedback, rectifying the common misconception in existing temperature kernels that portray temperature feedback as predominantly negative. We extract the information of surface energy amplification by non-temperature feedback from the ratio of downward longwave energy emission from the atmosphere to solar energy absorbed by the surface in climate mean states. The product of amplification rates by temperature and non-temperature feedbacks corresponds to the total amplification of energy perturbations at the surface caused by CO₂ increasing.

When applied to the observed climate mean state of 1980-2000, our framework accurately predicts the global warming observed from 1980-2000 to 2000-2020, with a prediction of 0.403 K compared to an observed value of 0.414 K. For the first time, this study confirms that observed global warming is driven by human-caused greenhouse gas emissions, independently of climate model simulations and statistical analyses. 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 CMIP6 models. These results highlight the new framework's reliability and broad applicability.

Ming Cai