The effective radiative forcing, which includes the instantaneous forcing plus adjustments
from the atmosphere and surface, has emerged as the key metric of evaluating human and …

Modern weather and climate models share a common heritage and often even components;
however, they are used in different ways to answer fundamentally different questions. As …

Cloud reflectivity is sensitive to atmospheric aerosol concentrations because aerosols
provide the condensation nuclei on which water condenses. Increased aerosol …

Despite a concerted research effort and extensive observational record, uncertainty in
climate sensitivity and aerosol forcing, the two largest contributions to future warming …

Machine learning (ML) algorithms are powerful tools to build models of clouds and climate
that are more faithful to the rapidly increasing volumes of Earth system data than commonly …

Abstract Changes in atmospheric composition, such as increasing greenhouse gases,
cause an initial radiative imbalance to the climate system, quantified as the instantaneous …

Many nations responded to the corona virus disease‐2019 (COVID‐19) pandemic by
restricting travel and other activities during 2020, resulting in temporarily reduced emissions …

The change in planetary albedo due to aerosol− cloud interactions during the industrial era
is the leading source of uncertainty in inferring Earth's climate sensitivity to increased …

Abstract Machine learning models can emulate chemical transport models, reducing
computational costs and enabling more experimentation. We developed emulators to predict …

Realistic simulation of the Earth's mean-state climate remains a major challenge, and yet it is
crucial for predicting the climate system in transition. Deficiencies in models' process …