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Stephanie J. Jacobs, Ailie J. E. Gallant, Nigel J. Tapper, and Dan Li

reflective paint—are seen as an urban heat-mitigation option ( Santamouris 2014 ). They reflect incoming solar radiation more efficiently than darker roofs, reducing the amount of heat that is absorbed by the rooftop and the building itself and ultimately transferred to the atmosphere ( Kalkstein et al. 2013 ). This was demonstrated in an observational study of cool roofs in Melbourne in which the net radiation at midday was 78% lower than for a vegetated rooftop during summer ( Coutts et al. 2013

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Pedro A. Jimenez, Jordi Vila-Guerau de Arellano, Jorge Navarro, and J. Fidel Gonzalez-Rouco

There is an increasing awareness of land–atmosphere interactions (L-AI) in modulating local phenomena as well as weather and climate variability at regional scales. As a result, the increasing attention that L-AI processes are receiving nowadays is not surprising. Our understanding of the biophysical processes governing these interactions is still limited, thereby hampering improvement in model parameterizations and their influence at different spatial and temporal scales. LAND–ATMOSPHERE

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Larry K. Berg and Peter J. Lamb

1. Setting the research agenda It is well known that the exchange of heat and moisture between the surface and atmosphere plays a key role in the earth’s climate system (e.g., Randall et al. 2007 ). Science questions related to land–atmosphere interactions have remained an active topic of research, both inside and outside of the ARM Program, for a considerable period of time (e.g., Betts et al. 1996 ; Betts 2003 , 2004 ; Dirmeyer et al. 2006 ; Betts 2009 ; Santanello et al. 2009 ; Betts

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Matthew J. Haugland and Kenneth C. Crawford

1. Introduction The interaction between the land and the atmosphere has become a subject of great interest and speculation. The interaction has been modeled and observed by many, but relatively little is known about the complex and nonlinear relationship between land surface features and the atmosphere ( André et al. 1990 ; Pielke et al. 1991 ). Previous studies of land–atmosphere interactions have been limited by a lack of long-term, high quality mesoscale data. The purpose of this manuscript

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Randal D. Koster, Paul A. Dirmeyer, Andrea N. Hahmann, Ruben Ijpelaar, Lori Tyahla, Peter Cox, and Max J. Suarez

reasons, the four modeling groups used SST fields from different Julys: 1988 SSTs were used by NSIPP, 1983 SSTs by CCM3/BATS, 1986 SSTs by COLA, and 1981 SSTs by HadAM3. If certain SST conditions are more conducive than others to promoting land–atmosphere interaction, then the intermodel differences in prescribed SSTs may have compromised the comparisons in Figs. 3 and 4 . This issue is addressed with supplementary simulations performed with the NSIPP model. The NSIPP W and R ensembles were both

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Teddy R. Holt, Dev Niyogi, Fei Chen, Kevin Manning, Margaret A. LeMone, and Aneela Qureshi

1. Introduction The effect of land–vegetative processes and the corresponding dynamical impact on land–atmosphere interactions is investigated for simulations of the 24–25 May mesoscale convection event that was observed during the International H 2 O Project (IHOP_2002) field experiment ( Weckwerth et al. 2004 ). Land–vegetative processes, as driven by features such as surface heterogeneity ( Pielke 2001 ) or soil moisture gradients ( Zhang and Anthes 1982 ; Segal et al. 1989 ; Chang and

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Tzu-Shun Lin and Fang-Yi Cheng

processes, but also by the heterogeneity of topography, soil properties, and land-cover characteristics. Based on the past modeling and observational studies, Seneviratne et al. (2010) concluded that the soil moisture could have significant impacts on variations in temperature and precipitation when the soil moisture–atmosphere interactions are strong. In the Global Land–Atmosphere Coupling Experiment (GLACE), Koster et al. (2006) identified eastern China as one of the strong soil moisture

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Margaret A. LeMone, Robert L. Grossman, Richard L. Coulter, Marvin L. Wesley, Gerard E. Klazura, Gregory S. PouIos, William Blumen, Julie K. Lundquist, Richard H. Cuenca, Shaun F. Kelly, Edward A. Brandes, Steven P. Oncley, Robert T. McMillen, and Bruce B. Hicks

This paper describes the development of the Cooperative Atmosphere Surface Exchange Study (CASES), its synergism with the development of the Atmosphere Boundary Layer Experiments (ABLE) and related efforts, CASES field programs, some early results, and future plans and opportunities. CASES is a grassroots multidisciplinary effort to study the interaction of the lower atmosphere with the land surface, the subsurface, and vegetation over timescales ranging from nearly instantaneous to years. CASES scientists developed a consensus that observations should be taken in a watershed between 50 and 100 km across; practical considerations led to an approach combining long-term data collection with episodic intensive field campaigns addressing specific objectives that should always include improvement of the design of the long-term instrumentation. In 1997, long-term measurements were initiated in the Walnut River Watershed east of Wichita, Kansas. Argonne National Laboratory started setting up the ABLE array. The first of the long-term hydrological enhancements was installed starting in May by the Hydrologic Science Team of Oregon State University. CASES-97, the first episodic field effort, was held during April–June to study the role of surface processes in the diurnal variation of the boundary layer, to test radar precipitation algorithms, and to define relevant scaling for precipitation and soil properties. The second episodic experiment, CASES-99, was conducted during October 1999, and focused on the stable boundary layer. Enhancements to both the atmospheric and hydrological arrays continue. The data from and information regarding both the long-term and episodic experiments are available on the World Wide Web. Scientists are invited to use the data and to consider the Walnut River Watershed for future field programs.

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Jorge A. Ramírez and Sharika U. S. Senarath

by assessing the consequent responses of the energy and the water fluxes at the land surface. Two standard land surface schemes present in the column model are modified to include the new interception parameterization, namely the Biosphere–Atmosphere Transfer Scheme (BATS) of Dickinson et al. (1986) and the statistical–dynamical parameterization of Entekhabi and Eagleson (1989) . 3. Interception parameterization a. Interception capacity A strong dependence exists between interception

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C. R. Mechoso, R. Wood, R. Weller, C. S. Bretherton, A. D. Clarke, H. Coe, C. Fairall, J. T. Farrar, G. Feingold, R. Garreaud, C. Grados, J. McWilliams, S. P. de Szoeke, S. E. Yuter, and P. Zuidema

New focused measurements, analyses, and modeling of the southeast Pacific climate system are helping to improve our understanding of key atmospheric and oceanic processes and their interactions in the eastern tropical ocean regions. The Variability of American Monsoon Systems (VAMOS) 1 Ocean–Cloud–Atmosphere–Land Study (VOCALS) is an international research program focused upon improved understanding and modeling of the southeast Pacific (SEP) climate system on diurnal to interannual time

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