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Ho-Chun Huang, Xin-Zhong Liang, Kenneth E. Kunkel, Michael Caughey, and Allen Williams

realistic configuration of model physics and dynamics as well as accurate incorporation of LBCs to reduce climate biases. As driven by the National Centers for Environmental Prediction/Department of Energy Atmospheric Model Intercomparison Project (AMIP-II) global reanalysis (R-2) data ( Kanamitsu et al. 2002 ), the RCM has realistically simulated summer 1993 flooding rainfall in the Midwest ( Liang et al. 2001 ). The RCM also realistically simulated surface temperature and soil moisture patterns ( Zhu

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John S. Irwin, William B. Petersen, and Steven C. Howard

moisture in the atmosphere) is routinely viewed and the model output is cast in a probabilistic manner. As another analogy, consider the problem of predicting the outcomes from a series of tosses of a pair of dice. We cannot predict exactly the sequence of individual outcomes in a series of tosses, but we can predict the distribution of outcomes and their respective probabilities of occurrence, including the mean, variance, and other moments of the distribution. One difference between modeling

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George Kallos, Marina Astitha, Petros Katsafados, and Chris Spyrou

farther driven toward the southern and eastern United States as it enters into the zone of the semipermanent “Bermuda” high pressure center. This case has been successfully simulated by Kallos et al. (2006) . Aerosols of anthropogenic origin, such as particulate sulfate, coexisting with aerosols of natural origin, such as desert dust and/or sea salt, in relatively high moisture environments produce PM of different sizes and properties. This situation can result in significant disturbance of cloud and

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