Climate Model Approximations of Aerosol Sizes Lead to Inaccurate Cloud Droplet Nucleation
Figure 1. Aerosol effects on clouds and radiation are a large source of uncertainty in understanding human impacts on the climate system. New modeling framework reveals how errors from the numerical approximations of aerosol properties in Earth system models propagate to generate large errors in cloud droplet nucleation. | Photo by Carlos Torres via Unsplash
Researchers introduce new strategy for evaluating models of atmospheric aerosol particles.
The Science
Aerosol particles have a large impact on climate (Fig. 1), but they are difficult to represent in climate models. Particles are tremendously diverse, and their properties change as they move through the atmosphere. However, these particle-level details must be simplified in climate models, and errors from these simplifications are not well understood. To address this need, researchers at Pacific Northwest National Laboratory developed a framework for evaluating the simplified aerosol scheme, the 4-mode version of the Modal Aerosol Module (MAM4) that is used in the U.S. Department of Energy’s Energy Exascale Earth System Model (E3SM), against a detailed particle-resolved aerosol model. They found that the approximations of aerosol sizes in MAM4 introduce large errors in predictions of aerosol particles’ ability to form cloud droplets; errors were greatest in areas with more air pollution.
The Impact
Climate models cannot simulate individual aerosol particles and errors from approximations of particle properties are not known. In this study, researchers used a detailed aerosol model that resolves complex aerosol physical and chemical processes to evaluate how approximations of aerosol particle properties in E3SM influence predictions of aerosol properties that impact climate. They found that errors from approximations in particle sizes contribute to inaccurate cloud droplet nucleation, resulting in errors in the estimated aerosol effects on climate (Fig. 2).
Figure 2. Benchmarking study reveals large errors in aerosol size distributions simulated by MAM4 in comparison with the particle-resolved model PartMC-MOSAIC (left). These errors in the size distribution cause large errors in aerosol activation (right).
Summary
Aerosol effects on clouds and radiation are a large source of uncertainty in our understanding of human impacts on the climate system. Uncertainty from the numerical representation of particle properties in climate models has not been well quantified. In this study, researchers introduced a framework for quantifying errors from the numerical approximation of aerosol sizes in MAM4, the aerosol model in E3SM. They performed identical simulations with MAM4 and PartMC–MOSAIC to ensure that process parameters and inputs between the two models were the same. This analysis revealed large errors in the simulation of aerosol particle sizes that lead to large errors in predictions of particles’ ability to form cloud droplets. These structural deficiencies lead to uncertainties in its earth system predictions. They could quantify errors in aerosol size distributions and cloud condensation nuclei (CCN) in MAM4 as the aerosols age. These findings provide insights into future model development directions for a better aerosol representation in Earth system models, in particular aerosol effects on clouds.
Publication
- Fierce, Laura, Yu Yao, Richard Easter, Po-Lun Ma, Jian Sun, Hui Wan, and Kai Zhang. 2024. “Quantifying Structural Errors In Cloud Condensation Nuclei Activity From Reduced Representation Of Aerosol Size Distributions”. Journal Of Aerosol Science 181. Elsevier BV: 106388. doi:10.1016/j.jaerosci.2024.106388.
Funding
- This work was supported by the Earth System Model Development program area of the Department of Energy, Office of Science, Biological and Environmental Research program.
Contact
- Po-Lun Ma, Pacific Northwest National Laboratory
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