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Zhe Feng, Fengfei Song, Koichi Sakaguchi, and L. Ruby Leung

1. Introduction Realistic representation of the hydrologic cycle and related extremes in Earth system models has important societal benefits. As Earth continues to warm, hydrological cycle changes such as “the wet get wetter and the dry get drier” ( Held and Soden 2006 ; Trenberth 2011 ) have significant implications for infrastructure planning and management of water resources. More importantly, the increased water vapor supply to storms under a warmer climate and the additional latent heat

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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

software framework to entrain these PODs to allow ease of use by modeling centers. The second section describes existing institutional efforts and needs, including details on the MDTF and modeling center perspectives. Existing community efforts at process-oriented diagnosis are then discussed. The fourth section provides examples of key PODs and metrics developed by the MDTF during its first three years and plans for expansion of this diagnostic set. The integrative open-source software framework to

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Catherine M. Naud, James F. Booth, Jeyavinoth Jeyaratnam, Leo J. Donner, Charles J. Seman, Ming Zhao, Huan Guo, and Yi Ming

front centered. The former is a plan view as a passive instrument would observe, while the latter is a vertical transect spanning both sides of the cold front as observed by active instruments. Composites are an average, as such all variability is smoothed out and the resulting distributions are representing the most salient features and do not necessarily look like any of the individual cases that went into it. However, they present a great advantage for model evaluation as they allow multiple

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