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| Titel |
Application and evaluation of a new radiation code under McICA scheme in BCC_AGCM2.0.1 |
| VerfasserIn |
H. Zhang, X. Jing, J. Li |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1991-959X
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| Digitales Dokument |
URL |
| Erschienen |
In: Geoscientific Model Development ; 7, no. 3 ; Nr. 7, no. 3 (2014-05-06), S.737-754 |
| Datensatznummer |
250115613
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| Publikation (Nr.) |
 copernicus.org/gmd-7-737-2014.pdf |
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| Zusammenfassung |
This research incorporates the correlated k distribution BCC-RAD radiation
model into the climate model BCC_AGCM2.0.1 and examines the change in
climate simulation by implementation of the new radiation algorithm. It is
shown that both clear-sky radiation fluxes and cloud radiative forcings
(CRFs) are improved. The modeled atmospheric temperature and specific
humidity are also improved due to changes in radiative heating rates, which
most likely stem from the revised treatment of gaseous absorption.
Subgrid cloud variability, including vertical overlap of fractional clouds
and horizontal inhomogeneity in cloud condensate, is addressed by using the
Monte Carlo Independent Column Approximation (McICA) method. In McICA, a
cloud-type-dependent function for cloud fraction decorrelation length, which
gives zonal mean results very close to the observations of CloudSat/CALIPSO,
is developed. Compared to utilizing a globally constant decorrelation length,
the maximum changes in seasonal CRFs by the new scheme can be as large as 10
and 20 W m−2 for longwave (LW) and shortwave (SW) CRFs, respectively,
mostly located in the tropics. The inclusion of an observation-based
horizontal inhomogeneity of cloud condensate has also a significant impact on
CRFs, with global means of ~ 1.5 W m−2 and ~ 3.7 Wm−2
for LW and SW CRFs at the top of atmosphere (TOA), respectively. Generally,
incorporating McICA and horizontal inhomogeneity of cloud condensate in the
BCC-RAD model reduces global mean TOA and surface SW and LW flux biases in
BCC_AGCM2.0.1.
These results demonstrate the feasibility of the new model configuration to
be used in BCC_AGCM2.0.1 for climate simulations, and also indicate that
more detailed real-world information on cloud structures should be obtained
to constrain cloud settings in McICA in the future. |
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