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Why are Aerosol-Cloud Interactions and Cloud Feedback Anti-Correlated in Earth System Models?

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Authors

Lead Presenter

Xiaohong Liu - Department of Atmospheric Sciences, Texas A&M University, College Station, TX, USA

Co-Author

Xi Zhao - Department of Atmospheric Sciences, Texas A&M University, College Station, TX, USA
Chuan Feng - Department of Atmospheric Sciences, Texas A&M University, College Station, TX, USA
Mark Zelinka - Lawrence Livermore National Laboratory, Livermore, CA, USA
Stephen A. Klein - Lawrence Livermore National Laboratory, Livermore, CA, USA
Yi Qin - Lawrence Livermore National Laboratory, Livermore, CA, USA, Pacific Northwest National Laboratory, Richland, WA, USA
Lin Lin - Department of Atmospheric Sciences, Texas A&M University, College Station, TX, USA , Lawrence Livermore National Laboratory, Livermore, CA, USA
Zheng Lu - Department of Atmospheric Sciences, Texas A&M University, College Station, TX, USA
Meng Zhang - Lawrence Livermore National Laboratory, Livermore, CA, USA
Kai Zhang - Pacific Northwest National Laboratory, Richland, WA, USA
Po-Lun Ma - Pacific Northwest National Laboratory, Richland, WA, USA
Yunpeng Shan - Pacific Northwest National Laboratory, Richland, WA, USA, Argonne National Laboratory, Lemont, IL, USA
Jiang Zhu - Climate and Global Dynamics Laboratory, National Center for Atmospheric Research, Boulder, CO, USA
Ramalingam Saravanan - Department of Atmospheric Sciences, Texas A&M University, College Station, TX, USA
Abstract

Previous studies have noticed that the Coupled Model Intercomparison Project Phase 6 (CMIP6) models with a stronger cooling from aerosol-cloud interactions (ACI) (ERFACI) also have an enhanced warming from positive cloud feedback, and these two opposing effects are counter-balanced in simulations of the historical period. However, reasons for this anti-correlation between cloud feedback and ERFACI are less explored.

In this study, we investigate this anti-correlation through both warm rain and ice microphysical processes using the two Earth System Models: the DOE’s Energy Exascale Earth System Model version 2 (E3SMv2) and the NCAR Community Earth System Model version 2 (CESM2). First, we perturb the autoconversion process in the two models and find that higher autoconversion rates which are associated with stronger ERFACI suppress the increase in cloud liquid water path (LWP) during global warming, thereby curtailing the rise in cloud optical depth, resulting in a diminished negative shortwave effect that contributes to intensified positive total cloud feedback. On the other hand, we perturb the cloud ice microphysical processes in the two models to obtain cloud liquid of varying amounts. We find that the model simulations with a larger LWP tend to have a stronger cooling from ACI and a stronger positive cloud feedback during warming. More liquid clouds in the mean-state present more opportunities for anthropogenic aerosol perturbations and also weaken the negative cloud feedback at middle to high latitudes. Our study offers new insights into the compensatory mechanisms between ERFACI and cloud feedback through both warm- and ice-phase cloud microphysics. Future work should focus on constraining modeled LWP from observations to reduce the uncertainties in both ERFACI and cloud feedback.

Related Meeting/Event
EESM PI Meeting 2024
Category
Model Uncertainties, Model Biases, and Fit-for-Purpose
Strengthening EESM Integrated Modeling Framework – Towards a Digital Earth
Biogeochemistry (Processes and Feedbacks)
Funding Program Area(s)
RGMA
Additional Resources:
NERSC (National Energy Research Scientific Computing Center)
Project(s)
Understanding Cloud Feedback and Climate Sensitivity in E3SMv1 and CMIP6 Models: Roles of Cloud Microphysics and Aerosol-Cloud Interactions
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