The DOI matches its Crossref record; 53 of the 53 references it cites were found in a registry or an index.
Exposing Global Cloud Biases in the Community Atmosphere Model (CAM) Using Satellite Observations and Their Corresponding Instrument Simulators
Abstract
Satellite observations and their corresponding instrument simulators are used to document global cloud biases in the Community Atmosphere Model (CAM) versions 4 and 5. The model–observation comparisons show that, despite having nearly identical cloud radiative forcing, CAM5 has a much more realistic representation of cloud properties than CAM4. In particular, CAM5 exhibits substantial improvement in three long-standing climate model cloud biases: 1) the underestimation of total cloud, 2) the overestimation of optically thick cloud, and 3) the underestimation of midlevel cloud. While the increased total cloud and decreased optically thick cloud in CAM5 result from improved physical process representation, the increased midlevel cloud in CAM5 results from the addition of radiatively active snow. Despite these improvements, both CAM versions have cloud deficiencies. Of particular concern, both models exhibit large but differing biases in the subtropical marine boundary layer cloud regimes that are known to explain intermodel differences in cloud feedbacks and climate sensitivity. More generally, this study demonstrates that simulator-facilitated evaluation of cloud properties, such as amount by vertical level and optical depth, can robustly expose large and at times radiatively compensating climate model cloud biases.
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Cites
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Cited by
The Community Earth System Model: A Framework for Collaborative Research
Hurrell, J. W., Holland, M. M., Gent, P. R., Ghan, S., Kay, J. E., Kushner, P. J., Lamarque, J.-F., Large, W. G., Lawrence, D., Lindsay, K., et al. (2013) · Bulletin of the American Meteorological Society · doi:10.1175/bams-d-12-00121.1 · Cited by 2,686
Self-citationNeale, R. B., Richter, J., Park, S., Lauritzen, P. H., Vavrus, S. J., Rasch, P. J., & Zhang, M. (2013) · Journal of Climate · doi:10.1175/jcli-d-12-00236.1 · Cited by 788
The ‘too few, too bright’ tropical low-cloud problem in CMIP5 models.
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Gettelman, A., Morrison, H., Santos, S., Bogenschutz, P., & Caldwell, P. M. (2015) · Journal of Climate · doi:10.1175/jcli-d-14-00103.1 · Cited by 265
Self-citationLauer, A., & Hamilton, K. (2013) · Journal of Climate · doi:10.1175/jcli-d-12-00451.1 · Cited by 120
Metadata
- Authors
- Kay, J. E., Hillman, B. R., Klein, S. A., Zhang, Y., Medeiros, B., Pincus, R., Gettelman, A., Eaton, B., Boyle, J., Marchand, R., & Ackerman, T. P.
- Venue
- Journal of Climate
- Publisher
- American Meteorological Society
- Published
- 2012-08-01
- Volume
- 25
- Issue
- 15
- Pages
- 5190-5207
- ISSN
- 0894-8755 (ISSN-L)
- 1520-0442
- OpenAlex
- W2018515783
- Cited by
- 270
- References
- 53
- FWCI
- 21.90
- Type
- journal article
- Language
- en
- Open access
- closed
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- Kay, J. E., Hillman, B. R., Klein, S. A., Zhang, Y., Medeiros, B., Pincus, R., Gettelman, A., Eaton, B., Boyle, J., Marchand, R., & Ackerman, T. P. (2012). Exposing Global Cloud Biases in the Community Atmosphere Model (CAM) Using Satellite Observations and Their Corresponding Instrument Simulators. Journal of Climate. https://doi.org/10.1175/jcli-d-11-00469.1
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