Climate processes

Abstract:

Changes in aerosols since the preindustrial era have altered the top-of-the-atmosphere radiation balance by directly scattering solar radiation and indirectly interacting with clouds, known as aerosol effective radiative forcing (ERFaer). ERFaer persistently remains one of the most uncertain components in global climate model simulations, due to the imperfect representations of aerosol and cloud properties and processes. Perturbed parameter ensembles (PPEs) are increasingly used to quantify these sources of uncertainty and to constrain models with observations.Here, we first present a single-model PPE using the ICON-A-HAM2.3 model, designed to identify key sources of ERFaer uncertainty. This PPE comprises 383 simulations for both preindustrial and present-day conditions, in which 42 parameters related to aerosol emissions, aerosol properties and processes, cloud microphysics, convection, and turbulence are perturbed simultaneously. Gaussian process emulators are trained on model outputs to enable efficient sampling of this high-dimensional parameter space. Our analysis focuses on uncertainty quantification and attribution for aerosol and cloud properties as well as ERFaer, along with comparisons against satellite observations from SPEXone/PACE and MODIS. Our results show a global mean ERFaer of −1.10 W m⁻² (5–95 percentile: −1.54 to −0.68 W m⁻²), with the overall uncertainty dominated by aerosol-related processes, particularly aerosol emissions.Building on this single-model framework, we further propose a Multi-Model PPE (MMPPE) initiative within the AeroCom Phase IV experiments. This multi-model approach allows us to simultaneously address structural and parametric uncertainties across models, providing a coordinated pathway toward reducing ERFaer uncertainty in current climate models. An overview of the MMPPE design and objectives will be presented.

Abstract:

Plain Language Summary: Clouds have a big influence on Earth's climate. They affect how much sunlight is reflected or trapped, and how weather patterns form. But understanding clouds is very hard‐especially how they interact with tiny particles in the air called aerosols. These particles come from human activities and sources like wildfires, volcanoes. The way aerosols and clouds affect each other is one of the most uncertain parts of climate science. Because of this uncertainty, it's difficult to make accurate predictions about climate change and to give clear advice to decision‐makers. Scientists have made some progress in understanding aerosol‐cloud interactions, but more work is needed. With better tools, observations, and computer models, we can learn more over the next decade. However, because the climate is changing quickly and impacts are getting worse, we need faster action now. This summary explains the current knowledge on how aerosols and clouds interact, and why it's important to reduce the uncertainty. It also highlights what steps can help improve our understanding‐such as global collaboration and sharing knowledge between researchers, governments, and the public. Making faster progress in this area is key to better climate predictions, stronger climate policies, and lower risks for people and the planet.