Quantifying the structural uncertainty of the aerosol mixing state representation in a modal model
<p>Aerosol mixing state is an important emergent property that affects aerosol radiative forcing and aerosol–cloud interactions, but it has not been easy to constrain this property globally. This study aims to verify the global distribution of aerosol mixing state represented by modal models....
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| Autores principales: | , , , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Copernicus Publications
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/f30768e393b14c13a652849e4132d8c2 |
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| Sumario: | <p>Aerosol mixing state is an important emergent property that affects
aerosol radiative forcing and aerosol–cloud interactions, but it has
not been easy to constrain this property globally. This study aims to
verify the global distribution of aerosol mixing state represented by
modal models. To quantify the aerosol mixing state, we used the
aerosol mixing state indices for submicron aerosol based on the mixing
of optically absorbing and non-absorbing species (<span class="inline-formula"><i>χ</i><sub>o</sub></span>),
the mixing of primary carbonaceous and non-primary carbonaceous
species (<span class="inline-formula"><i>χ</i><sub>c</sub></span>), and the mixing of hygroscopic and
non-hygroscopic species (<span class="inline-formula"><i>χ</i><sub>h</sub></span>). To achieve a
spatiotemporal comparison, we calculated the mixing state indices
using output from the Community Earth System Model with the
four-mode version of the Modal Aerosol Module (MAM4)
and compared the results with the mixing state indices
from a benchmark machine-learned model trained on high-detail
particle-resolved simulations from the particle-resolved stochastic
aerosol model PartMC-MOSAIC.
The two methods yielded very different spatial patterns of the mixing
state indices. In some regions, the yearly averaged <span class="inline-formula"><i>χ</i></span> value
computed by the MAM4 model differed by up to 70 percentage points
from the benchmark values. These errors tended to be zonally
structured, with the MAM4 model predicting a more internally mixed
aerosol at low latitudes and a more externally mixed aerosol at high
latitudes compared to the benchmark.
Our study quantifies potential model bias in simulating mixing state
in different regions and provides insights into potential
improvements to model process representation for a more realistic
simulation of aerosols towards better quantification of radiative
forcing and aerosol–cloud interactions.</p> |
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