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Xubin Zeng, Zhuo Wang, and Aihui Wang

1. Introduction Land–atmosphere interaction plays an important role in weather, climate, and global/regional environmental change. For this reason, various international programs have been established in the past three decades to address the relevant scientific issues, such as the Global Energy and Water Cycle Experiment (GEWEX; http://www.gewex.org ), the (earlier) Biospheric Aspects of the Hydrological Cycle (BASC; Kabat et al. 2004 ), and (its successor) integrated Land Ecosystem

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Keith J. Harding and Peter K. Snyder

Agriculture and satellite-derived irrigation estimates ( Ozdogan and Gutman 2008 ). The doubling of available water for evapotranspiration (ET) in the Great Plains ( Moore and Rojstaczer 2001 ) has altered the Bowen ratio ( Pielke 2001 ), driving additional partitioning of energy into latent heating at the expense of sensible heating ( Barnston and Schickedanz 1984 ; DeAngelis et al. 2010 ; Kueppers et al. 2007 ; Ozdogan et al. 2010 ; Pielke 2001 ; Sacks et al. 2009 ). Modifications to latent and

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Joseph A. Santanello Jr., Christa D. Peters-Lidard, Aaron Kennedy, and Sujay V. Kumar

1. Introduction Quantification of the land surface influence on extremes such as flood and drought is critical for both short-term weather and climate prediction. These dry and wet regimes are modulated by the strength and sensitivity of the land–atmosphere (L–A) coupling and, in particular, how anomalies in soil moisture are translated into and through the planetary boundary layer (PBL), ultimately favoring or suppressing the triggering and support of clouds and precipitation. Improved

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Keith J. Harding and Peter K. Snyder

minimize model edge effects. The goal of this study is to explore the impact that irrigation has on the hydrologic cycle using a high-resolution coupled land–atmosphere model. Simulations using the Weather Research and Forecasting Model (WRF; Skamarock et al. 2008 ) were performed both with and without irrigation for a suite of years for different precipitation regimes. This includes El Niño–Southern Oscillation (ENSO) years that have a marked influence on Great Plains precipitation ( Twine et al

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Craig R. Ferguson, Eric F. Wood, and Raghuveer K. Vinukollu

hydrologic and atmospheric model performance ( Betts 2004 , 2009 ). By linking the surface, PBL, and cloud processes, coupling encompasses complex cross-scale interactions that determine the climate state. Coupling strength varies on local (5–10 km) to regional scales (400 km) and temporally on daily to weekly time scales ( Betts 2004 ; Koster et al. 2003 ; Taylor and Ellis 2006 ), modulated by background synoptic weather (i.e., convergence/divergence, monsoons, and cloud fields) and larger scale (i

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