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Cited by 302

The DOI matches its Crossref record; 67 of the 67 references it cites were found in a registry or an index.

Prediction of the number of cloud droplets in the ECHAM GCM

Open access
Lohmann, Ulrike, Feichter, Johann, Chuang, Catherine C., Penner, Joyce E.·1999·Journal of Geophysical Research: Atmospheres

Abstract

In this paper a prognostic equation for the number of cloud droplets (CDNC) is introduced into the ECHAM general circulation model. The initial CDNC is based on the mechanistic model of Chuang and Penner [1995], providing a more realistical prediction of CDNC than the empirical method previously used. Cloud droplet nucleation is parameterized as a function of total aerosol number concentration, updraft velocity, and a shape parameter, which takes the aerosol composition and size distribution into account. The total number of aerosol particles is obtained as the sum of marine sulfate aerosols produced from dimethyl sulfide, hydrophylic organic and black carbon, submicron dust, and sea‐salt aerosols. Anthropogenic sulfate aerosols only add mass to the preexisting aerosols but do not form new particles. The simulated annual mean liquid water path, column CDNC, and effective radius agree well with observations, as does the frequency distributions of column CDNC for clouds over oceans and the variations of cloud optical depth with effective radius.

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Crossref · 10.1029/1999jd900046

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Metadata

Authors
Lohmann, U., Feichter, J., Chuang, C. C., & Penner, J. E.
Venue
Journal of Geophysical Research: Atmospheres
Published
1999-04
Volume
104
Issue
D8
Pages
9169-9198
ISSN
0148-0227 (ISSN-L)
OpenAlex
W2019059884
Cited by
302
References
67
FWCI
15.85
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Prediction of the number of cloud droplets in the ECHAM GCM. https://app.cochat.ai/papers/10.1029/1999jd900046
The paper
Lohmann, U., Feichter, J., Chuang, C. C., & Penner, J. E. (1999). Prediction of the number of cloud droplets in the ECHAM GCM. Journal of Geophysical Research: Atmospheres. https://doi.org/10.1029/1999jd900046

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.