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Seungbum Hong, Venkat Lakshmi, and Eric E. Small

. 2001 , Weiss et al. 2004 ). Various studies have dealt with these interactions, including the development of land–atmosphere models ( Noilhan and Planton 1989 ; Pitman 1991 ; Xue et al. 1991 ) and the relation of vegetation dynamics to other land and climate variables ( Betts et al. 1997 ; Bounoua et al. 1999 ; Weiss et al. 2004 ). Meteorological and climatological conditions both impact and are influenced by vegetation distribution and dynamics ( Sellers et al. 1996 ; Betts et al. 1997

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Christine Delire, Nathalie de Noblet-Ducoudré, Adriana Sima, and Isabelle Gouirand

-term variability in the climate system. This hypothesis was first studied in semiarid areas where vegetation is water limited, like the Sahel. Over the past few centuries, the climate of the Sahel has been characterized by a succession of multidecadal dry and wet periods. In the rest of the world, however, wet and dry spells do not usually exceed 2–5 yr ( Nicholson 2000 ). In a review of observational and modeling work, Nicholson (2000) showed how vegetation modulates land–atmosphere interactions by

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Heather Tollerud, Jesslyn Brown, Tom Loveland, Rezaul Mahmood, and Norman Bliss

et al. (2009 , 2010) , and Saatchi et al. (2013) . Land–atmosphere feedbacks enhance the importance of drought impacts on vegetation. Climate-forced changes in vegetation produce feedbacks to the atmospheric system because of modifications in biogeophysical properties. When vegetation is water stressed, albedo increases and latent energy flux decreases, which may decrease atmospheric instability, convection, and cloud development. Human-forced LULC changes further complicate these land–atmosphere

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Yongkang Xue, Fernando De Sales, Ratko Vasic, C. Roberto Mechoso, Akio Arakawa, and Stephen Prince

-scale field studies of VBP–atmosphere relationships, and even fewer have intended to deduct relevant information from observational data to validate simulated vegetation–climate interactions. However, application of limited observation has been found to effectively highlight VBP effects in a few regional climate simulation studies ( Beljaars et al. 1996 ; Zeng et al. 1999 ; Hong and Kalnay 2000 ; Douville et al. 2001 ; Xue et al. 2001 , 2004b , 2006 ; Wang et al. 2004 ). In the present study we

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Fuyao Wang, Michael Notaro, Zhengyu Liu, and Guangshan Chen

1. Introduction The atmosphere and vegetation interact in a complex way. The atmosphere exerts a dominant control on vegetation through variations in air temperature, precipitation, solar radiation, wind, and CO 2 concentration ( Budyko 1974 ; Woodward 1987 ; Nemani et al. 2003 ; Woodward et al. 2004 ). As a result, the spatial distribution of major vegetation types is consistent with climate zones on a global scale ( Bryson 1966 ). Although this two-way interaction is dominated by the

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Li Liu, Renhe Zhang, and Zhiyan Zuo

, studying the relationship between vegetation and SM is particularly important for understanding the land–atmosphere system and its influence. According to the existing literature, the relationship between vegetation and SM is complex. More vegetation may correspond to either increased ( Bounoua et al. 2000 ; Buermann et al. 2001 ) or reduced SM ( Pielke et al. 1998 ; Wang et al. 2006 ). This study investigates the relationship between LAI and SM in different types of soil using observational data

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Tirtha Banerjee, Frederik De Roo, and Matthias Mauder

1. Introduction It is a standard practice in modeling land surface–atmosphere interaction that momentum or scalar fluxes can be parameterized by relating them to the mean velocity gradient or scalar concentration gradient by means of a turbulent diffusion coefficient, called gradient-diffusion parameterization or K theory ( Raupach and Thom 1981 ; Katul et al. 2013 ). The K theory has enjoyed a high degree of popularity over the years, especially because of the ease of usage. It has been

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Bruce B. Hicks

deposition case presently considered. They also question the applicability of the concept of a roughness length, on which much of the existing suite of resistance formations is based. Katul et al. (2006) extend the theoretical analysis for CO 2 to a uniformly forested hill and confirm that advection is a dominating factor in the overall air surface exchange. Ross and Vosper (2005) conclude that “dynamic interaction of forest canopies with the atmosphere over complex terrain . . . can lead to

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Toshihisa Matsui, Venkataraman Lakshmi, and Eric E. Small

force a one-way interaction from vegetation to atmosphere. In other word, variability of Fg is prescribed according to observations, regardless of the simulated soil moisture, radiation, and temperature states. In the use of the RCM, we need to note that the “freedom” of domain climatology should be stated as “climatological sensitivities from the forcing field,” because lateral boundary conditions (LBCs) prevent the domain climate from drifting much away from the climate represented by the LBCs

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Anil Kumar, Fei Chen, Michael Barlage, Michael B. Ek, and Dev Niyogi

1. Introduction The interaction between the surface layer and lower atmospheric layers is important for weather and climate models. The role of land–atmosphere interactions becomes even more important over a warm, moist surface covered by different vegetation types ( Ek et al. 2003 ; Dirmeyer et al. 2010 ). The value of improving land surface models to enhance operational forecasts is recognized by the different numerical weather prediction (NWP) centers (e.g., Beljaars et al. 1996 ; Betts

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