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Rongqian Yang, Kenneth Mitchell, Jesse Meng, and Michael Ek

prediction results from a given general circulation model (GCM) are sensitive to how the land component of the GCM is initialized and the starting dates used in the integrations (e.g., Dirmeyer 2001 ; Koster et al. 2000 , 2006 ). Therefore, harnessing the impact of land surface anomalies for seasonal predictions is a promising challenge that requires not only a large number of members in the ensemble set of seasonal predictions (e.g., Tribbia and Baumhefner 1988 ; Brankovic et al. 1994 ) but also

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Thomas R. Loveland and Rezaul Mahmood

Sustained assessment of the climatic impacts of land use and land cover change is essential. Land use and land cover change (LULCC) plays an important role in the climate system. Many studies have documented the impacts of LULCC on local, regional, and global climate. The National Climate Assessment Report ( Melillo et al. 2014 ) identifies LULCC as a “cross cutting” issue of future climate change studies. This report, and the previous U.S. Climate Change Science Program strategic plan (2003

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Menglin Jin and Shunlin Liang

problem in CLM2 when soil emissivity is set as constant since this variable can shift more than 10% around the globe from the MODIS observations we present below. The goal of this work is to examine whether the constant- ε assumption currently used in land surface models is realistic, and to study the impact of ε on land surface modeling. To achieve that, we employed two methods. First, the emissivity products from MODIS were analyzed to demonstrate the global distribution, seasonal variation, and

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Xubin Zeng, Mike Barlage, Chris Castro, and Kelly Fling

rainfall provides information about the origin of the water molecules. In general, condensation depletes heavy isotope contents in rainfall as the air moves from ocean to land. Therefore, a small isotope gradient from ocean to continental interior might indicate a relatively large contribution of land surface E to P . While the isotope data are useful qualitatively, using them to quantify the land surface effect on local precipitation has large uncertainties because of the variability in isotope

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A. L. Hirsch, A. J. Pitman, and V. Haverd

–atmosphere coupling to model physics (e.g., Santanello et al. 2011 ; Hirsch et al. 2014b ). Research on land–atmosphere interactions commonly focuses on the influence of soil moisture variability on surface temperature. One of the most well-known methods of quantifying how the land surface affects the atmosphere in a climate model is the “coupling strength” approach introduced by Koster et al. (2004) . The first Global Land–Atmosphere Coupling Experiment (GLACE-1; Koster et al. 2006 ) used a methodology for

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Chunlei Meng, Chaolin Zhang, and Ronglin Tang

been implemented and tested ( Margulis et al. 2005 ; McLaughlin 2002 ; Sabater et al. 2007 ). Variational data assimilation algorithms can combine the advantages of in situ measurement, remote sensing, and model simulations, and these algorithms have been applied widely in recent years. Many studies have used variational data assimilation methods for assimilating land surface temperature (LST) and/or soil moisture data using the adjoint model to evaluate the cost function gradient, and various

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Gidon Eshel, Pamela A. Martin, and Esther E. Bowen

( Paerl 1997 ). Prudent food production must therefore minimize Nr use (and thus discharge; Bergström and Brink 1986 ) while maximizing land’s human-destined caloric output. Nr use per human-edible calorie, the quotient of per acre Nr use and human-edible caloric yield, combines the two optimizations and is the relevant performance metric of food production systems in this context. Because Nr and land-use minimizations are coupled, their combined benefits may exceed the sum of the benefits of either

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Christopher M. Taylor, Eric F. Lambin, Nathalie Stephenne, Richard J. Harding, and Richard L. H. Essery

, examination of the Advanced Very High Resolution Radiometer (AVHRR) record over the past 20 years suggest that there is no regional-scale evidence of advancing desertification ( Prince et al. 1998 ). Instead the vegetation cover, as quantified by the normalized difference vegetation index (NDVI), shows marked interannual variability largely in step with rainfall anomalies. Exaggerated changes in land cover were used in the previously mentioned degradation modeling studies in order to increase the

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Kingtse C. Mo and Dennis P. Lettenmaier

of hydrological drought. As a result of the sparseness of observations of SM and the complexities of the relationships between (spatially distributed) runoff and observed streamflow, the use of model-derived SM and runoff from efforts like the North American Land Data Assimilation System (NLDAS) ( Mitchell et al. 2004 ; Xia et al. 2012 ) and extensions thereof by Maurer et al. (2002) and Livneh et al. (2013) have become popular. The Environmental Modeling Center (EMC) of the National Centers

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M. Baldi, G. A. Dalu, and R. A. Pielke Sr.

Rasmussen 1998 ). The development of thermally forced secondary circulations is favored by the absence of ambient flow, since they are suppressed by ambient flows with a wind speed exceeding 6 m s −1 for surface inhomogeneities larger than 50 km, or by weaker winds for smaller inhomogeneities ( Segal and Arritt 1992 ). From a climatic point of view, land-use changes have an impact on the regional and global scale, since spatially heterogeneous land-use effects may be at least as important in altering

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