The DOI matches its Crossref record; 47 of the 47 references it cites were found in a registry or an index.
Parameterization of Cloud Microphysics Based on the Prediction of Bulk Ice Particle Properties. Part I: Scheme Description and Idealized Tests
Open accessAbstract
A method for the parameterization of ice-phase microphysics is proposed and used to develop a new bulk microphysics scheme. All ice-phase particles are represented by several physical properties that evolve freely in time and space. The scheme prognoses four ice mixing ratio variables, total mass, rime mass, rime volume, and number, allowing 4 degrees of freedom for representing the particle properties using a single category. This approach represents a significant departure from traditional microphysics schemes in which ice-phase hydrometeors are partitioned into various predefined categories (e.g., cloud ice, snow, and graupel) with prescribed characteristics. The liquid-phase component of the new scheme uses a standard two-moment, two-category approach. The proposed method and a complete description of the new predicted particle properties (P3) scheme are provided. Results from idealized model simulations of a two-dimensional squall line are presented that illustrate overall behavior of the scheme. Despite its use of a single ice-phase category, the scheme simulates a realistically wide range of particle characteristics in different regions of the squall line, consistent with observed ice particles in real squall lines. Sensitivity tests show that both the prediction of the rime mass fraction and the rime density are important for the simulation of the squall-line structure and precipitation.
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Cites
A Description of the Advanced Research WRF Version 3
Skamarock, W. C., Klemp, J. B., Dudhia, J., Gill, D., Barker, D. M., Wang, W., Huang, X., & Duda, M. (2008) · UCAR/NCAR · doi:10.5065/d68s4mvh · Cited by 8,925
Microphysics of Clouds and Precipitation
Pruppacher, H. R., & Klett, J. D. (1978) · Springer eBooks · doi:10.1007/978-94-009-9905-3 · Cited by 3,975
Bulk Parameterization of the Snow Field in a Cloud Model
Lin, Y.-L., Farley, R. D., & Orville, H. D. (1983) · Journal of Climate and Applied Meteorology · doi:10.1175/1520-0450(1983)022<1065:bpotsf>2.0.co;2 · Cited by 3,481
Thompson, G., Field, P. R., Rasmussen, R. M., & Hall, W. D. (2008) · Monthly Weather Review · doi:10.1175/2008mwr2387.1 · Cited by 3,156
Morrison, H., Thompson, G., & Tatarskii, V. (2009) · Monthly Weather Review · doi:10.1175/2008mwr2556.1 · Cited by 2,438
Self-citationTHE TERMINAL VELOCITY OF FALL FOR WATER DROPLETS IN STAGNANT AIR
Gunn, R., & Kinzer, G. D. (1949) · Journal of Meteorology · doi:10.1175/1520-0469(1949)006<0243:ttvoff>2.0.co;2 · Cited by 1,597
The Dependence of Numerically Simulated Convective Storms on Vertical Wind Shear and Buoyancy
Weisman, M. L., & Klemp, J. B. (1982) · Monthly Weather Review · doi:10.1175/1520-0493(1982)110<0504:tdonsc>2.0.co;2 · Cited by 1,232
Morrison, H., Curry, J. A., & Khvorostyanov, V. I. (2005) · Journal of the Atmospheric Sciences · doi:10.1175/jas3446.1 · Cited by 1,176
Self-citationThompson, G., Rasmussen, R. M., & Manning, K. (2004) · Monthly Weather Review · doi:10.1175/1520-0493(2004)132<0519:efowpu>2.0.co;2 · Cited by 1,159
Production of secondary ice particles during the riming process
HALLETT, J., & MOSSOP, S. C. (1974) · Nature · doi:10.1038/249026a0 · Cited by 1,107
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Metadata
- Authors
- Morrison, H., & Milbrandt, J. A.
- Venue
- Journal of the Atmospheric Sciences
- Publisher
- American Meteorological Society
- Published
- 2015-01-01
- Volume
- 72
- Issue
- 1
- Pages
- 287-311
- ISSN
- 0022-4928 (ISSN-L)
- 1520-0469
- OpenAlex
- W2040017785
- Cited by
- 664
- References
- 47
- FWCI
- 12.80
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Morrison, H., & Milbrandt, J. A. (2015). Parameterization of Cloud Microphysics Based on the Prediction of Bulk Ice Particle Properties. Part I: Scheme Description and Idealized Tests. Journal of the Atmospheric Sciences. https://doi.org/10.1175/jas-d-14-0065.1
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