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A L. Hirsch, A. J. Pitman, J. Kala, R. Lorenz, and M. G. Donat

evapotranspiration ( Fischer et al. 2007 ; Lorenz et al. 2010 ; Jaeger and Seneviratne 2011 ; Zhang and Wu 2011 ; Mueller and Seneviratne 2012 ; Roundy et al. 2014 ). LUC modifies the biophysical characteristics of the land surface, the surface energy balance ( Boisier et al. 2012 ), and how the land connects to the boundary layer. In Australia, LUC is most commonly associated with a change from native forest to grasslands and crops and is known through observations to affect the atmosphere. Early studies

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Weiyue Zhang, Zhongfeng Xu, and Weidong Guo

as Europe and North America, LULCC can result in a surface temperature cooling of 1° to 2°C primarily because of the increased land surface albedo ( Brovkin et al. 1999 ; Betts et al. 2007 ; Oleson et al. 2004 ; Bala et al. 2007 ; Davin and de Noblet-Ducoudré 2010 ; de Noblet-Ducoudré et al. 2012 ). Lawrence and Chase (2010) found that land-cover change results in a widespread regional warming and drying of the near-surface atmosphere but has a limited global influence on near

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Jean-Sébastien Landry, Navin Ramankutty, and Lael Parrott

1. Introduction Each grid cell in coupled climate–terrestrial vegetation models is bound to include major spatial heterogeneities that span various orders of magnitude and influence the processes represented ( Giorgi and Avissar 1997 ). The basic approaches accounting for subgrid cell heterogeneity in these models can be divided into two main categories. The composite (also named aggregated) approach computes land–atmosphere exchanges as a function of a single “representative” state of the grid

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Edward Armstrong, Paul Valdes, Jo House, and Joy Singarayer

how this influences the extent to which LUC impacts climate. Section 2 gives a description of the HadCM3 climate model and the simulations used in this study. The results are outlined in section 3 followed by an energy balance analysis in section 4 . A discussion and summary is presented in section 5 . 2. Methods HadCM3 is a coupled Earth system model comprising a 3D dynamical atmosphere and ocean components and includes a thermodynamic/free-drift sea ice model ( Gordon et al. 2000 ). The

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Keith J. Harding, Tracy E. Twine, and Yaqiong Lu

that can respond to variations in temperature and moisture stress ( Lu et al. 2015 ). The Great Plains have been previously identified as one of three global maxima in land–atmosphere coupling ( Koster et al. 2004 ), as variations in soil moisture are positively correlated with precipitation in the region ( Koster et al. 2003 ). The Great Plains low-level jet (GPLLJ), a nocturnal southerly wind maximum, is the primary driver of summertime convective rainfall in the region ( Higgins et al. 1997

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Andres Schmidt, Beverly E. Law, Mathias Göckede, Chad Hanson, Zhenlin Yang, and Stephen Conley

1. Introduction The vertical exchange of CO 2 between the terrestrial biosphere and the atmosphere constitutes the largest, single-component flux in the global carbon cycle (e.g., Beer et al. 2010 ). Spatiotemporal patterns of flux exchange display pronounced variability between regions. The Pacific Northwest (PNW) of the United States represents one of the strongest carbon sinks in North America (e.g., Law et al. 2004 ; Law and Waring 2015 ). Accurate quantification of the magnitude of

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