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Edward Armstrong, Paul Valdes, Jo House, and Joy Singarayer

how this influences the extent to which LUC impacts climate. Section 2 gives a description of the HadCM3 climate model and the simulations used in this study. The results are outlined in section 3 followed by an energy balance analysis in section 4 . A discussion and summary is presented in section 5 . 2. Methods HadCM3 is a coupled Earth system model comprising a 3D dynamical atmosphere and ocean components and includes a thermodynamic/free-drift sea ice model ( Gordon et al. 2000 ). The

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Hongshou Li

WC of the soil to change; it can also cause the water vapor concentration within the air contained in the pore spaces of the soil to fluctuate ( Li et al. 2014 ). Water vapor fluctuations are bound to cause fluctuations in the vapor pressure. However, whether it can cause Earth–air pressure (EP) to fluctuate has not been reported. This heterothermozone exists as a continuum with the outside atmosphere, and it is generally thought that the air pressure in the soil of this zone is controlled by the

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Bappaditya Nag, V. Misra, and S. Bastola

description of the hydrological models in section 3 . Section 4 discusses the results, and the concluding remarks are summarized in section 5 . 2. Data Two sets of atmospheric reanalysis [Twentieth Century Reanalysis (20CR; Compo et al. 2011 ) and Florida Climate Institute–Florida State University Land–Atmosphere Regional Reanalysis version 1.0 (FLAReS1.0; DiNapoli and Misra 2012 ; Misra et al. 2013 )] and two independent rainfall observational datasets [viz., the Climate Research Unit (CRU

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Gregory T. Pederson, Stephen T. Gray, Daniel B. Fagre, and Lisa J. Graumlich

( Graumlich 1993 ; Cook et al. 2004 ; Stine 1994 ; Woodhouse and Overpeck 1998 ). These long-duration droughts and pluvials likely result from a complex set of forcings linked to low-frequency variations and state changes in sea surface temperature and pressure anomalies in both the Atlantic and Pacific Oceans ( McCabe et al. 2004 ; Gray et al. 2003a ; Cayan et al. 1998 ). Such mechanisms, based on ocean–atmosphere teleconnections, often produce regional to subcontinental drying or wetness ( Cook et

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Satish Bastola, Vasubandhu Misra, and Haiqin Li

then partitioned into four groups of equal size quartiles: bottom, lower middle, upper middle, and top. For a given river system, O and F [Equation (2) ] are the vectors of observed and forecasted rainfall quartiles for categories x and y . Similarly, rainfall distribution r_dist [Equation (3) ] is the vector of q ensemble members resampled from historical precipitation at the i th time step and for the j th subbasin, where . Here, n is the number of the time step and p is the

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K. Y. Li, R. De Jong, M. T. Coe, and N. Ramankutty

reduction factor as a function of pressure head h (L), S max (L 3 L −3 T −1 ) is the maximum possible root water extraction rate when soil water is not limiting, and z is the soil depth (L). Root water uptake modules differ from one another in the way that α ( h ) and S max ( h, z ) are conceptualized. Our proposed water stress function α ( h ) will be based on Ohm’s law analogy of soil–water–atmosphere–plant relations and on an experimental study conducted by Denmead and Shaw (Denmead and

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Jeffrey A. Hicke, David B. Lobell, and Gregory P. Asner

( Hicke et al., 2002b ; Lobell et al., 2002 ). Changes in agricultural production therefore have the potential to significantly impact the U.S. carbon cycle. Carbon fixed by crops may be transferred to the soil through root production or through residues remaining after harvest. In addition, the harvested mass (e.g., grain) is consumed and respired back to the atmosphere. This harvest may be respired locally, may be transported long distances within the United States before being consumed, or may be

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Marc L. Fischer, David P. Billesbach, Joseph A. Berry, William J. Riley, and Margaret S. Torn

as the interannual variations in growing season ecosystem–atmosphere exchange for unirrigated agriculture. Within seven unirrigated SGP fields planted with three different crop types, we measured NEE and latent heat, as well as sensible heat exchanges, aboveground biomass, and associated surface meteorological and soil variables. These measurements were made from July 2001 through summer 2003, as part of research conducted by the U.S. Department of Energy Atmospheric Radiation Measurement (ARM

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Grant L. Harley, James King, and Justin T. Maxwell

1. Introduction and background Mineral dust represents a substantial portion of the average global atmospheric loading. The largest current source of mineral dust aerosols to Earth’s atmosphere is northern Africa ( Ginoux et al. 2012 ). Dust mobilized from the Sahel and Sahara regions of Africa affects the climate system through radiative forcing ( Miller and Tegen 1998 ; Miller et al. 2004 ) and through changing cloud characteristics by acting as cloud condensation nuclei ( Lohmann and

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Keith J. Harding, Tracy E. Twine, and Yaqiong Lu

that can respond to variations in temperature and moisture stress ( Lu et al. 2015 ). The Great Plains have been previously identified as one of three global maxima in land–atmosphere coupling ( Koster et al. 2004 ), as variations in soil moisture are positively correlated with precipitation in the region ( Koster et al. 2003 ). The Great Plains low-level jet (GPLLJ), a nocturnal southerly wind maximum, is the primary driver of summertime convective rainfall in the region ( Higgins et al. 1997

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