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| Titel |
Aerosol indirect effects in the ECHAM5-HAM2 climate model with subgrid cloud microphysics in a stochastic framework |
| VerfasserIn |
Juha Tonttila, Petri Räisänen, Heikki Järvinen |
| Konferenz |
EGU General Assembly 2015
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 17 (2015) |
| Datensatznummer |
250112358
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| Publikation (Nr.) |
 EGU/EGU2015-12511.pdf |
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| Zusammenfassung |
| Representing cloud properties in global climate models remains a challenging topic, which to
a large extent is due to cloud processes acting on spatial scales much smaller than the typical
model grid resolution. Several attempts have been made to alleviate this problem. One such
method was introduced in the ECHAM5-HAM2 climate model by Tonttila et al. (2013),
where cloud microphysical properties, along with the processes of cloud droplet activation
and autoconversion, were computed using an ensemble of stochastic subcolumns
within the climate model grid columns. Moreover, the subcolumns were sampled
for radiative transfer using the Monte Carlo Independent Column Approximation
approach.
The same model version is used in this work (Tonttila et al. 2014), where 5-year nudged
integrations are performed with a series of different model configurations. Each run is
performed twice, once with pre-industrial (PI, year 1750) aerosol emission conditions
and once with present-day (PD, year 2000) conditions, based on the AEROCOM
emission inventories. The differences between PI and PD simulations are used to
estimate the impact of anthropogenic aerosols on clouds and the aerosol indirect effect
(AIE).
One of the key results is that when both cloud activation and autoconversion are
computed in the subcolumn space, the aerosol-induced PI-to-PD change in the global-mean
liquid water path is up to 19 % smaller than in the reference with grid-scale computations.
Together with similar changes in the cloud droplet number concentration, this influences
the cloud radiative effects and thus the AIE, which is estimated as the difference
in the net cloud radiative effect between PI and PD conditions. Accordingly, the
AIE is reduced by 14 %, from 1.59ÂWÂm-2 in the reference model version to
1.37ÂWÂm-2 in the experimental model configuration. The results of this work explicitly
show that careful consideration of the subgrid variability in cloud microphysical
properties and consistent treatment of related physical processes make an important
contribution towards reducing biases in the model representation of the aerosol-cloud
interactions.
Tonttila, J., Räisänen, P., and Järvinen, H.: Monte Carlo-based subgrid parameterization
of vertical velocity and stratiform cloud microphysics in ECHAM5.5-HAM2, Atmos. Chem.
Phys., 13, 7551-7565, doi:10.5194/acp-13-7551-2013, 2013.
Tonttila, J., Järvinen, H., and Räisänen, P.: Explicit representation of subgrid variability
in cloud microphysics yields weaker aerosol indirect effect in the ECHAM5-HAM2 climate
model, Atmos. Chem. Phys. Discuss. (accepted), 14, 15523-15543, doi:10.5194/acpd-14-15523-
2014, 2014. |
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