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Eric D. Maloney, Andrew Gettelman, Yi Ming, J. David Neelin, Daniel Barrie, Annarita Mariotti, C.-C. Chen, Danielle R. B. Coleman, Yi-Hung Kuo, Bohar Singh, H. Annamalai, Alexis Berg, James F. Booth, Suzana J. Camargo, Aiguo Dai, Alex Gonzalez, Jan Hafner, Xianan Jiang, Xianwen Jing, Daehyun Kim, Arun Kumar, Yumin Moon, Catherine M. Naud, Adam H. Sobel, Kentaroh Suzuki, Fuchang Wang, Junhong Wang, Allison A. Wing, Xiaobiao Xu, and Ming Zhao

centers. Traditionally, diagnostics for climate models are based on monthly mean statistics and climatologies. Increasingly, models are being analyzed in more detail against observations of specific processes, and the MDTF is approaching PODs in this spirit. The closer to a model process the observations and evaluation are, the better the ability to constrain the process and hence provide a guide to parameterization improvement. For a simple example: cloud radiative effects at the top of the

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