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Tosiyuki Nakaegawa

accuracy of less than 0.80 in a land cover dataset induces distinctive differences in precipitation through the interactions between the atmosphere and land surface ( Ge et al. 2007 ) and that more accurate land cover type classifications induce better reproducibility of simulated surface air temperatures ( Sertel et al. 2009 ), indicating present per-pixel agreements are not always sufficiently accurate for use in land surface sciences. In addition, uncertainty in global land cover datasets can

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Paul A. Dirmeyer

increasingly found that the progress of their understanding was encountering barriers at the boundaries between the disciplines. Further progress would require consideration of the larger system and the interactions between the components that were defined early in the century. Often specific phenomena served as the bridge between disciplines. For example, study of El Niño brought the atmosphere and ocean communities together to an unprecedented degree. A similar convergence has been occurring at the land–atmosphere

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Yadu Pokhrel, Naota Hanasaki, Sujan Koirala, Jaeil Cho, Pat J.-F. Yeh, Hyungjun Kim, Shinjiro Kanae, and Taikan Oki

hydrological models (GHMs) (see a comprehensive overview by Haddeland et al. 2011 ), land surface hydrologic processes are often treated in a rather conceptual way and surface energy balance critical to the evaporation process is not considered. In contrast, the land surface models (LSMs) used for climate modeling studies solve both water and energy balances. Since land surface hydrological processes exert profound influence on the overlying atmosphere ( Shukla and Mintz 1982 ; Koster et al. 2004 ), LSMs

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Akihiko Ito and Motoko Inatomi

–10 mmol CO 2 mol −1 H 2 O) than grasslands (1–4 mmol CO 2 mol −1 H 2 O). However, it is generally difficult to validate the estimated WUE distribution with observational data, mainly because of the lack of direct observation of broad-scale WUE. Dan and Ji (2007) estimated the global distribution of WUE using the Atmosphere–Vegetation Interaction Model (AVIM)–Global Ocean–Atmosphere–Land System Model (GOALS) and found higher WUE values in northern midlatitude ecosystems—a finding that is

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Pablo Imbach, Luis Molina, Bruno Locatelli, Olivier Roupsard, Gil Mahé, Ronald Neilson, Lenin Corrales, Marko Scholze, and Philippe Ciais

application of a global vegetation model coupling water and vegetation interactions with climate scenarios for Mesoamerica. This study joins a small subset of studies aimed at modeling the nonlinear interactions between climate and terrestrial ecosystems at high spatial resolution under a large number of climate scenarios ( Scholze et al. 2006 ). 2. Materials and methods a. Study area: Climate and vegetation The study area spans a 1 000 000 km 2 area of land between 6.5°–22°N and 76.5°–99°W (excluding

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Sante Laviola, Agata Moscatello, Mario Marcello Miglietta, Elsa Cattani, and Vincenzo Levizzani

strengthening the system. The interaction of the cold air from the Balkans with the warm and moist current from Africa drastically amplified the exchange of condensation latent heat, remarkably increasing the vigor of the convection. In such conditions of pronounced instability the local orography, although not too steep, reinforced the air lifting. The PMW soundings show a cold front from the north, presumably located in the first kilometers of the atmosphere, where low intensity scattering from frozen

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Dai Matsushima, Reiji Kimura, and Masato Shinoda

testing with Hydrologic Atmospheric Pilot Experiment-Sahel data . J. Geophys. Res. , 104 , 9445 – 9453 . Stull, R. B. , 1988 : An Introduction to Boundary-Layer Meteorology . Kluwer Academic, 666 pp . Sugita, M. , Asanuma J. , Tsujimura M. , Mariko S. , Lu M. , Kimura F. , Azzaya D. , and Adyasuren T. , 2007 : An overview of the rangelands atmosphere–hydrosphere–biosphere interaction study experiment in northeastern Asia (RAISE) . J. Hydrol. , 333 , 3 – 20 . Sugita, M

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