The DOI matches its Crossref record; 56 of the 56 references it cites were found in a registry or an index.
Entrainment and detrainment in cumulus convection: an overview
Abstract
Entrainment and detrainment processes have been recognised for a long time as key processes for cumulus convection and have recently witnessed a regrowth of interest mainly due to the capability of large‐eddy simulations (LES) to diagnose these processes in more detail. This article has a twofold purpose. Firstly, it provides a historical overview of the past research on these mixing processes, and secondly, it highlights more recent important developments. These include both fundamental process studies using LES aiming to improve our understanding of the mixing process, but also more practical studies targeted toward an improved parametrised representation of entrainment and detrainment in large‐scale models. A highlight of the fundamental studies resolves a long‐lasting controversy by showing that lateral entrainment is the dominant mixing mechanism in comparison with the cloud‐top entrainment in shallow cumulus convection. The more practical studies provide a wide variety of new parametrisations with sometimes conflicting approaches to the way in which the effect of the free tropospheric humidity on the lateral mixing is taken into account. An important new insight that will be highlighted is that, despite the focus in the literature on entrainment, it appears that it is rather the detrainment process that determines the vertical structure of the convection in general and the mass flux especially. Finally, in order to speed up progress and stimulate convergence in future parametrisations, stronger and more systematic use of LES is advocated. Copyright © 2012 Royal Meteorological Society
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Cites
An Introduction to Boundary Layer Meteorology
(1988) · Springer eBooks · doi:10.1007/978-94-009-3027-8 · Cited by 10,224
The Kain–Fritsch Convective Parameterization: An Update
Kain, J. S. (2004) · Journal of Applied Meteorology · doi:10.1175/1520-0450(2004)043<0170:tkcpau>2.0.co;2 · Cited by 4,964
A Comprehensive Mass Flux Scheme for Cumulus Parameterization in Large-Scale Models
Tiedtke, M. (1989) · Monthly Weather Review · doi:10.1175/1520-0493(1989)117<1779:acmfsf>2.0.co;2 · Cited by 3,648
Detection of a 40–50 Day Oscillation in the Zonal Wind in the Tropical Pacific
Madden, R. A., & Julian, P. R. (1971) · Journal of the Atmospheric Sciences · doi:10.1175/1520-0469(1971)028<0702:doadoi>2.0.co;2 · Cited by 3,254
Turbulent gravitational convection from maintained and instantaneous sources
Morton, B. R., Taylor, G. I., & Turner, J. S. (1956) · Proceedings of the Royal Society of London. Series A. Mathematical and Physical Sciences · doi:10.1098/rspa.1956.0011 · Cited by 2,566
Interaction of a Cumulus Cloud Ensemble with the Large-Scale Environment, Part I
Arakawa, A., & Schubert, W. H. (1974) · Journal of the Atmospheric Sciences · doi:10.1175/1520-0469(1974)031<0674:ioacce>2.0.co;2 · Cited by 2,481
Kain, J. S., & Fritsch, J. M. (1990) · Journal of the Atmospheric Sciences · doi:10.1175/1520-0469(1990)047<2784:aodepm>2.0.co;2 · Cited by 2,065
Yanai, M., Esbensen, S., & Chu, J.-H. (1973) · Journal of the Atmospheric Sciences · doi:10.1175/1520-0469(1973)030<0611:dobpot>2.0.co;2 · Cited by 1,872
Quantification of modelling uncertainties in a large ensemble of climate change simulations.
Murphy, J. M., Sexton, D. M. H., Barnett, D. N., Jones, G. S., Webb, M. J., Collins, M., & Stainforth, D. A. (2004) · Nature · doi:10.1038/nature02771 · Cited by 1,655
Baldauf, M., Seifert, A., Förstner, J., Majewski, D., Raschendorfer, M., & Reinhardt, T. (2011) · Monthly Weather Review · doi:10.1175/mwr-d-10-05013.1 · Cited by 1,284
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Self-citationRepresenting Equilibrium and Nonequilibrium Convection in Large-Scale Models
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Metadata
- Authors
- de Rooy, W. C., Bechtold, P., Fröhlich, K., Hohenegger, C., Jonker, H., Mironov, D., Pier Siebesma, A., Teixeira, J., & Yano, J.
- Venue
- Quarterly Journal of the Royal Meteorological Society
- Publisher
- Wiley
- Published
- 2012-06-07
- Volume
- 139
- Issue
- 670
- Pages
- 1-19
- ISSN
- 0035-9009 (ISSN-L)
- 1477-870X
- OpenAlex
- W2066559078
- Cited by
- 384
- References
- 56
- FWCI
- 15.02
- Type
- journal article
- Language
- en
- Open access
- closed
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- de Rooy, W. C., Bechtold, P., Fröhlich, K., Hohenegger, C., Jonker, H., Mironov, D., Pier Siebesma, A., Teixeira, J., & Yano, J. (2013). Entrainment and detrainment in cumulus convection: an overview. Quarterly Journal of the Royal Meteorological Society. https://doi.org/10.1002/qj.1959
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