The DOI matches its Crossref record; 41 of the 41 references it cites were found in a registry or an index.
Development of an Effective Double-Moment Cloud Microphysics Scheme with Prognostic Cloud Condensation Nuclei (CCN) for Weather and Climate Models
Open accessAbstract
A new double-moment bulk cloud microphysics scheme, the Weather Research and Forecasting (WRF) Double-Moment 6-class (WDM6) Microphysics scheme, which is based on the WRF Single-Moment 6-class (WSM6) Microphysics scheme, has been developed. In addition to the prediction for the mixing ratios of six water species (water vapor, cloud droplets, cloud ice, snow, rain, and graupel) in the WSM6 scheme, the number concentrations for cloud and rainwater are also predicted in the WDM6 scheme, together with a prognostic variable of cloud condensation nuclei (CCN) number concentration. The new scheme was evaluated on an idealized 2D thunderstorm test bed. Compared to the simulations from the WSM6 scheme, there are greater differences in the droplet concentration between the convective core and stratiform region in WDM6. The reduction of light precipitation and the increase of moderate precipitation accompanying a marked radar bright band near the freezing level from the WDM6 simulation tend to alleviate existing systematic biases in the case of the WSM6 scheme. The strength of this new microphysics scheme is its ability to allow flexibility in variable raindrop size distribution by predicting the number concentrations of clouds and rain, coupled with the explicit CCN distribution, at a reasonable computational cost.
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Cites
A Description of the Advanced Research WRF Version 3
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Dudhia, J. (1989) · Journal of the Atmospheric Sciences · doi:10.1175/1520-0469(1989)046<3077:nsocod>2.0.co;2 · Cited by 5,352
Aerosols, Climate, and the Hydrological Cycle
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Bulk Parameterization of the Snow Field in a Cloud Model
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The WRF Single-Moment 6-Class Microphysics Scheme (WSM6)
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Self-citationHong, S.-Y., Dudhia, J., & Chen, S.-H. (2004) · Monthly Weather Review · doi:10.1175/1520-0493(2004)132<0103:aratim>2.0.co;2 · Cited by 2,581
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Cited by
Inclusion of biomass burning in WRF-Chem: impact of wildfires on weather forecasts
Grell, G., Freitas, S. R., Stuefer, M., & Fast, J. (2011) · Atmospheric Chemistry and Physics · doi:10.5194/acp-11-5289-2011 · Cited by 289
Gagne, D. J., McGovern, A., Haupt, S. E., Sobash, R. A., Williams, J. K., & Xue, M. (2017) · Weather and Forecasting · doi:10.1175/waf-d-17-0010.1 · Cited by 169
Metadata
- Authors
- Lim, K.-S. S., & Hong, S.-Y.
- Venue
- Monthly Weather Review
- Publisher
- American Meteorological Society
- Published
- 2010-05-01
- Volume
- 138
- Issue
- 5
- Pages
- 1587-1612
- ISSN
- 0027-0644 (ISSN-L)
- 1520-0493
- OpenAlex
- W2023778504
- Cited by
- 935
- References
- 41
- FWCI
- 6.38
- Type
- journal article
- Language
- en
- Open access
- bronze
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.