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

from the bunny fence experiment field campaign ( Lyons et al. 1993 ) showed preferential cloud formation over native vegetation as compared to agriculture in Western Australia ( Lyons et al. 1993 ; Lyons 2002 ; Ray et al. 2003 ). Ray et al. (2003) also showed that cumulus clouds occur preferentially over the native vegetation up to 10% of the time during the austral summer. Studies using single-column models have suggested that this is due to higher planetary boundary layer (PBL) heights over

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

in the both the Atlantic and Pacific ( Robinson 2002 ; Kunkel et al. 2006 ; Wang et al. 2009 ); and reduced sensible heat loss due to increased irrigation ( Christy et al. 2006 ; Puma and Cook 2010 ). In a comprehensive study of the southeastern United States, primarily the states of Mississippi, Alabama, and Georgia, Rogers (2013) found that 60% of the summer temperature variance was primarily described by soil moisture and cloud cover; however, all the predictor indices examined combined

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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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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

.1175/1520-0442(2004)017<2909:TSCBLG>2.0.CO;2 . Jacobson , M. Z. , 2014 : Effect of biomass burning on climate, accounting for heat and moisture fluxes, black and brown carbon, and cloud absorption effects . J. Geophys. Res. Atmos. , 119 , 8980 – 9002 , doi: 10.1002/2014JD021861 . Jones , A. , J. M. Haywood , and O. Boucher , 2007 : Aerosol forcing, climate response and climate sensitivity in the Hadley Centre climate model . J. Geophys. Res. , 112 , D20211 , doi: 10.1029/2007JD008688 . Ke , Y. , L. R. Leung

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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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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

surroundings as a consequence of urban/rural thermal energy budget differences ( Oke 1982 ). The magnitude and characteristics of the UHI are controlled by several factors. In general, UHI decreases with increasing wind speed and cloud cover, while it increases with city size and population density; it is also stronger during summer and, typically, the nighttime, depending on location ( Arnfield 2003 ). Even though the general UHI pattern is similar in all urban environments, each city is exposed to

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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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