Publication Abstracts

Xie et al. 2005

Xie, S., M. Zhang, M. Branson, R.T. Cederwall, A.D. Del Genio, Z.A. Eitzen, S.J. Ghan, S.F. Iacobellis, K.L. Johnson, M. Khairoutdinov, S.A. Klein, S.K. Krueger, W. Lin, U. Lohmann, M.A. Miller, D.A. Randall, R.C.J. Somerville, Y.C. Sud, G.K. Walker, A. Wolf, X. Wu, K.-M. Xu, J.J. Yio, G. Zhang, and J. Zhang, 2005: Simulations of midlatitude frontal clouds by single-column and cloud-resolving models during the Atmospheric Radiation Measurement March 2000 cloud intensive operational period. J. Geophys. Res., 110, D15S03, doi:10.1029/2004JD005119.

This study quantitatively evaluates the overall performance of nine single-column models (SCMs) and four cloud-resolving models (CRMs) in simulating a strong midlatitude frontal cloud system taken from the spring 2000 Cloud Intensive Observational Period at the Atmospheric Radiation Measurement (ARM) Southern Great Plains site. The evaluation data are an analysis product of constrained variational analysis of the ARM observations and the cloud data collected from the ARM ground active remote sensors (i.e., cloud radar, lidar, and laser ceilometers) and satellite retrievals. Both the selected SCMs and CRMs can typically capture the bulk characteristics of the frontal system and the frontal precipitation. However, there are significant differences in detailed structures of the frontal clouds. Both CRMs and SCMs overestimate high thin cirrus clouds before the main frontal passage. During the passage of a front with strong upward motion, CRMs underestimate middle and low clouds while SCMs overestimate clouds at the levels above 765 hPa. All CRMs and some SCMs also underestimated the middle clouds after the frontal passage. There are also large differences in the model simulations of cloud condensates owing to differences in parameterizations; however, the differences among intercompared models are smaller in the CRMs than the SCMs. In general, the CRM-simulated cloud water and ice are comparable with observations, while most SCMs underestimated cloud water. SCMs show huge biases varying from large overestimates to equally large underestimates of cloud ice. Many of these model biases could be traced to the lack of subgrid-scale dynamical structure in the applied forcing fields and the lack of organized mesoscale hydrometeor advections. Other potential reasons for these model errors are also discussed in the paper.

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BibTeX Citation

@article{xi02000x,
  author={Xie, S. and Zhang, M. and Branson, M. and Cederwall, R. T. and Del Genio, A. D. and Eitzen, Z. A. and Ghan, S. J. and Iacobellis, S. F. and Johnson, K. L. and Khairoutdinov, M. and Klein, S. A. and Krueger, S. K. and Lin, W. and Lohmann, U. and Miller, M. A. and Randall, D. A. and Somerville, R. C. J. and Sud, Y. C. and Walker, G. K. and Wolf, A. and Wu, X. and Xu, K.-M. and Yio, J. J. and Zhang, G. and Zhang, J.},
  title={Simulations of midlatitude frontal clouds by single-column and cloud-resolving models during the Atmospheric Radiation Measurement March 2000 cloud intensive operational period},
  year={2005},
  journal={J. Geophys. Res.},
  volume={110},
  pages={D15S03},
  doi={10.1029/2004JD005119},
}

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RIS Citation

TY  - JOUR
ID  - xi02000x
AU  - Xie, S.
AU  - Zhang, M.
AU  - Branson, M.
AU  - Cederwall, R. T.
AU  - Del Genio, A. D.
AU  - Eitzen, Z. A.
AU  - Ghan, S. J.
AU  - Iacobellis, S. F.
AU  - Johnson, K. L.
AU  - Khairoutdinov, M.
AU  - Klein, S. A.
AU  - Krueger, S. K.
AU  - Lin, W.
AU  - Lohmann, U.
AU  - Miller, M. A.
AU  - Randall, D. A.
AU  - Somerville, R. C. J.
AU  - Sud, Y. C.
AU  - Walker, G. K.
AU  - Wolf, A.
AU  - Wu, X.
AU  - Xu, K.-M.
AU  - Yio, J. J.
AU  - Zhang, G.
AU  - Zhang, J.
PY  - 2005
TI  - Simulations of midlatitude frontal clouds by single-column and cloud-resolving models during the Atmospheric Radiation Measurement March 2000 cloud intensive operational period
JA  - J. Geophys. Res.
VL  - 110
SP  - D15S03
DO  - 10.1029/2004JD005119
ER  -

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