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Cited by 874

The DOI matches its Crossref record; 13 of the 13 references it cites were found in a registry or an index.

A scheme for predicting layer clouds and their water content in a general circulation model

Smith, R. N. B.·1990·Quarterly Journal of the Royal Meteorological Society

Abstract

A cloud water variable has been included in the Meteorological Office atmospheric general circulation model. the cloud amount and water content are generated by a scheme which assumes a distribution of thermodynamic and water content variables about their grid‐box‐mean values. A parametrization of the rate of depletion of cloud water by precipitation is included. the model's boundary layer mixing is reformulated in terms of variables conserved during changes of state of water, allowing a more realistic calculation of atmospheric stability in cloudy regions. The scheme produces realistic cloud distributions and the predicted cloud water content verifies well against microwave radiometer data in all regions except the mid‐latitudes of the summer hemisphere. the parametrization of cloud optical properties in terms of the cloud water content will be an important future development of the model.

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Metadata

Authors
Smith, R. N. B.
Venue
Quarterly Journal of the Royal Meteorological Society
Publisher
Wiley
Published
1990-01
Volume
116
Issue
492
Pages
435-460
ISSN
  • 0035-9009 (ISSN-L)
  • 1477-870X
OpenAlex
W2150946542
Cited by
874
References
13
FWCI
8.83
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: A scheme for predicting layer clouds and their water content in a general circulation model. https://app.cochat.ai/papers/10.1002/qj.49711649210
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Smith, R. N. B. (1990). A scheme for predicting layer clouds and their water content in a general circulation model. Quarterly Journal of the Royal Meteorological Society. https://doi.org/10.1002/qj.49711649210

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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.