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W. L. Ellenburg, R. T. McNider, J. F. Cruise, and John R. Christy

surface fluxes at various spatial scales. As a result, the U.S. National Research Council ( Jacob et al. 2005 ) has recommended expanding research into the influence of land-cover processes on climate as a forcing. It has been conjectured that the climate response to land-use and land-cover change could possibly even exceed greenhouse gas contributions, making for very important local, regional, and even global implications ( Dirmeyer et al. 2010 ). While other studies have investigated the Southeast

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Yaqian He and Eungul Lee

vegetation with lower albedo compared with sand absorbed more solar radiation, which might create more rainfall over Africa. Los et al. (2006) concluded that vegetation effects accounted for about 30% of annual rainfall variation in the Sahel. It appears that both regional land surface and remote ocean forcings may be responsible for the variability of the Sahel rainfall. While the previous studies are concerned with the land and ocean factors separately, the relative contribution of the two different

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Jean-Sébastien Landry, Navin Ramankutty, and Lael Parrott

quickly with the user-selected value. 3) This improvement was robust to the use of nonoptimal (but reasonable) threshold values to determine the domain of each LF. 4) When the disturbance rate was the same, between approaches were quantitatively similar, and qualitatively equivalent, for even-aged logging management and spatially random fire events of constant size. 4. Discussion 4.1. Consequences of subgrid cell dynamic heterogeneity 4.1.1. Net radiative forcing from stand-clearing disturbances

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

beyond, it is important to constrain how the biogeophysical impact of LUC may change under higher CO 2 forcing. A previous study by Pitman et al. (2011) showed that the biogeophysical impact of LUC depended on the background state of the climate. They attributed a reduction in the winter impact of temperate LUC at higher concentrations of CO 2 to a reduced snow albedo effect. On the contrary, summertime impacts are shown to increase due to CO 2 -induced increase in precipitation and latent

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G. Strandberg and E. Kjellström

temperature as a consequence of deforestation but that this cooling effect is much smaller than the warming effect from greenhouse gas forcing (e.g., Brovkin et al. 2006 ; Bala et al. 2007 ; Betts et al. 2007 ; Forster et al. 2007 ; Teuling et al. 2010 ; Brovkin et al. 2013 ). Other experimental climate model studies with prescribed deforestation in large parts of the globe show a similar cooling effect on global mean temperature ( Kleidon et al. 2000 ). Some studies have also shown regional effects

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Weiyue Zhang, Zhongfeng Xu, and Weidong Guo

Report of the Intergovernmental Panel on Climate Change (IPCC; Myhre et al. 2013 ) noted that global land-use change has led to a change in radiative forcing by −0.15 ± 0.10 W m −2 due to the increased land surface albedo, which in turn caused a decrease in the land surface temperature (LST). However, the nonradiative influence of land-use change [e.g., changes in plant phenology and evapotranspiration (ET)] led to an increase in the LST because of the decrease in ET ( Pitman et al. 2009

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

). We also used LIS to run CABLE offline simulations to provide equilibrated soil moisture and temperature initial conditions for the fully coupled WRF simulations following Hirsch et al. (2014a , b ). LIS offline simulations require appropriate surface meteorological forcing to solve the governing equations of the soil–vegetation–snow system and predict the surface turbulent energy fluxes and soil states. For coupled simulations, LIS–CABLE provides the surface turbulent energy fluxes to WRF, and

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Zhao Yang, Francina Dominguez, Hoshin Gupta, Xubin Zeng, and Laura Norman

systems (GIS) format into ASCII text files, culminating in 43 070 rows and 35 000 columns of information, to be used as input to the WRF Model. They were then superimposed on the default WRF Model MODIS 20-level classification scheme. 2.4. Lateral boundary conditions The same climate forcings were used to drive the WRF Model for the two different sets of land-use data. The lateral boundary conditions were obtained from the North American Regional Reanalysis (NARR) data ( Mesinger et al. 2006

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

; Means 1954 ). Abundant low-level convergence, cyclonic shear, and moisture convergence to the north of the GPLLJ maximum dynamically force convective development above the planetary boundary layer at night. For these reasons, the diurnal maximum in warm-season rainfall occurs at night instead of during peak heating when instability is the greatest ( Bonner 1968 ; Helfand and Schubert 1995 ; Weaver and Nigam 2011 ). Variations in the GPLLJ are influenced by fluctuations in the gradient between the

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Pedro Sequera, Jorge E. González, Kyle McDonald, Steve LaDochy, and Daniel Comarazamy

understanding the combined effects of large-scale (GHG and PDO) and regional-scale (UHI) factors on summer coastal cooling following the methodology developed by Comarazamy et al. (2010 , 2013 ). This approach integrates ground and remote sensing information ( Comarazamy et al. 2010 ) as well as mesoscale atmospheric modeling and statistical techniques ( Comarazamy et al. 2013 ), allowing quantification of the individual and combined contributions of LCLU changes and large-scale forcings to the magnitude

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