Search Results

You are looking at 1 - 8 of 8 items for :

  • Water budget/balance x
  • Biogeophysical Climate Impacts of Land Use and Land Cover Change (LULCC) x
  • All content x
Clear All
Keith J. Harding, Tracy E. Twine, and Yaqiong Lu

concentrated in heavily irrigated areas, we also consider the water balance for irrigated grid cells in the region. Much larger losses of irrigated water occur over irrigated grid cells as the 105.73-mm ET increase from irrigation in DYN simulations is much larger than the 12.83-mm simulated increase in rainfall ( Table 5 ). Irrigation results in an average 92.90-mm loss of water to the atmosphere that is not returned to irrigated grid cells as precipitation (86.1% of ET) when dynamic crop growth is

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

the southern Great Plains . Int. J. Climatol. , 30 , 1994 – 2003 , doi: 10.1002/joc.2093 . Goldewijk , K. K. , 2001 : Estimating global land use change over the past 300 years: The HYDE database . Global Biogeochem. Cycles , 15 , 417 – 433 , doi: 10.1029/1999GB001232 . Gopalakrishnan , R. , G. Bala , M. Jayaraman , L. Cao , R. Nemani , and N. H. Ravindranath , 2011 : Sensitivity of terrestrial water and energy budgets to CO 2 -physiological forcing: An investigation

Open access
Jean-Sébastien Landry, Navin Ramankutty, and Lael Parrott

. Ciais , 2005 : A dynamic global vegetation model for studies of the coupled atmosphere-biosphere system . Global Biogeochem. Cycles , 19 , GB1015 , doi: 10.1029/2003GB002199 . Kucharik , C. J. , and Coauthors , 2000 : Testing the performance of a dynamic global ecosystem model: Water balance, carbon balance, and vegetation structure . Global Biogeochem. Cycles , 14 , 795 – 825 , doi: 10.1029/1999GB001138 . Landry , J.-S. , H. D. Matthews , and N. Ramankutty , 2015 : A global

Full access
W. L. Ellenburg, R. T. McNider, J. F. Cruise, and John R. Christy

the southeastern United States . Climate Dyn. , 40 , 341 – 352 , doi: 10.1007/s00382-012-1437-6 . Sau , F. , K. J. Boote , W. M. Bostick , J. W. Jones , and M. I. Mínguez , 2004 : Testing and improving evapotranspiration and soil water balance of the DSSAT crop models . Agron. J. , 96 , 1243 – 1257 , doi: 10.2134/agronj2004.1243 . Saxena , V. K. , and S. Yu , 1998 : Searching for a regional fingerprint of aerosol radiative forcing in the southeastern US . Geophys. Res

Full access
Andres Schmidt, Beverly E. Law, Mathias Göckede, Chad Hanson, Zhenlin Yang, and Stephen Conley

simulate the net ecosystem exchange (NEE) of CO 2 . Turner et al. (2011) compared different approaches to estimate annual carbon budgets of Oregon and found generally higher net ecosystem production (NEP) for the top-down approach compared to a relatively simple bottom-up ecosystem process model Biome-BGC (Biogeochemical; Thornton et al. 2005 ). The CO 2 budgets from the two approaches differed by more than 80%, highlighting significant differences in results between the bottom-up and top

Full access
Pedro Sequera, Jorge E. González, Kyle McDonald, Steve LaDochy, and Daniel Comarazamy

(Noah LSM). Noah LSM uses four soil layers (for temperature, water + ice, and water), one vegetation type in each grid cell without dynamic vegetation and carbon budget ( Jin et al. 2010 ), and predicts soil moisture and temperature in four layers. The ground heat budget in the Noah LSM is calculated using a diffusion equation for soil temperature, and the surface skin temperature is determined using a single, linearized surface energy balance equation ( Chen and Dudhia 2001 ). The radiation

Full access
G. Strandberg and E. Kjellström

1. Introduction The land surface and its vegetation are part of the climate system; manmade and natural changes in the land cover can potentially have an impact on climate. Land cover influences climate in two ways: via biogeochemical exchanges—in particular, carbon dioxide (CO 2 )—with the atmosphere and via biogeophysical properties that influence energy balance and exchange at the land surface (e.g., Pielke et al. 1998 ; Findell et al. 2007 ). Biogeochemical changes occur because changes

Full access
Weiyue Zhang, Zhongfeng Xu, and Weidong Guo

responses in the LST ( Figure 3 ), which will be described in section 4.2 . Figure 3. LULCC-induced changes in surface temperature in (a) spring (March–May), (b) summer (June–August), (c) autumn (September–November), and (d) winter (December–February). The sitppled area denotes that the difference reaches the significance level of 0.05. The four regions are indicated by black boxes. Following Xu et al. (2015) , we compute each individual term that contributes to the land surface energy balance: The

Full access