Exposing Global Cloud Biases in the Community Atmosphere Model (CAM) Using Satellite Observations and Their Corresponding Instrument Simulators

• Published in: Journal of climate Vol. 25; no. 15; pp. 5190 - 5207
• Main 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.
• Format: Journal Article
• Language: English
• Published: Boston, MA American Meteorological Society 01-08-2012
• Subjects: Atmosphere; Atmospheric models; Atmospheric sciences; Bias; Boundary layers; Climate; Climate models; Climate sensitivity; Cloud physics; Cloud properties; Clouds; Convection clouds; Datasets; Earth, ocean, space; Exact sciences and technology; External geophysics; Meteorology; Modeling; Modelling; Optical analysis; Optical properties; Optical thickness; Physics; Precipitation; Radiative forcing; Representations; Satellite observation; Satellites; Science; Simulation; Simulations; Simulators; Snow; Software; SPECIAL CCSM Earth System Model CESM1 COLLECTION; Stratocumulus clouds; Atmosphere model; sensitivity analysis; Marine atmosphere; Bias; radiative transfer; Space remote sensing; Satellite observation; Climate models; clouds; subtropical zone; feedback; Atmospheric boundary layer; snow; Effect on climate; Optical thickness; Forcing; Comparative study
• ISSN: 0894-8755; 1520-0442
• DOI: 10.1175/JCLI-D-11-00469.1

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.