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Measuring How Well Climate Models Calculate Effects of Clouds on Earth's Warming
Published: February 17, 2012
Posted: May 30, 2012

Cloud fraction is the dominant modulator of radiative fluxes. For this study, DOE scientists at Pacific Northwest National Laboratory and Lawrence Livermore National Laboratory evaluated cloud fraction simulated in the IPCC AR4 GCMs against long-term, ground-based measurements. They focused on the vertical structure, total amount of cloud, and its effect on cloud shortwave transmissivity. Comparisons were performed for three climate regimes represented by the Atmospheric Radiation Measurement (ARM) sites: Southern Great Plains (SGP); Manus, Papua New Guinea; and North Slope of Alaska (NSA). Both inter-model deviation and model bias against observation were investigated. The results show that the model observation and inter-model deviations have similar magnitudes for the total cloud fraction and the normalized cloud effect, and these deviations are larger than those in surface downward solar radiation and cloud transmissivity. Similar deviation patterns between inter-model and model measurement comparisons suggest that the climate models tend to generate larger biases against observations for variables with larger inter-model deviation. The ARM measurements enabled the team to evaluate the seasonal variation of cloud vertical structures in the GCMs.

Reference: Qian, Y., C. N. Long, H. Wang, J. M. Comstock, S. A. McFarlane, and S. Xie. 2012. "Evaluation of Cloud Fraction and Its Radiative Effect Simulated by IPCC AR4 Global Models Against ARM Surface Observations," Atmospheric Chemistry and Physics 12, 1785-1810. DOI: 10.5194/acp-12-1785-2012. (Reference link)

Contact: Wanda Ferrell, SC-23.1, (301) 903-0043, Dorothy Koch, SC-23.1, (301) 903-0105, Ashley Williamson, SC-23.1, (301) 903-3120
Topic Areas:

  • Research Area: Earth and Environmental Systems Modeling
  • Research Area: Atmospheric System Research
  • Facility: DOE ARM User Facility

Division: SC-33.1 Earth and Environmental Sciences Division, BER

 

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