DCHM-V Gross Primary Productivity

 

The data sets below are time-variant gross primary productivity (GPP) outputs from the Duke Coupled Hydrology Model with Vegetation (DCHM-V). All time-variant data are provided in binary files. Please click here for the description of the data format and sample codes for reading binary files.

 

Control Simulation: Modelled GPP using the control atmospheric forcing data.

 

Experimental Simulation: Modelled GPP using the reduced atmospheric forcing data, where periods of tropical cyclone activity are replaced with climatology.

 

For further description of these data, please see Lowman and Barros (2016).

 

Data Access: To access these data, please contact Lauren Lowman at lel7@duke.edu .

 

GPP Data Citation

Lowman, L. E. L., and A. P. Barros (2016), Interplay of Drought and Tropical Cyclone Activity in SE US Gross Primary Productivity. J. Geophys. Res. Biogeosci., 120, doi: 10.1002/2015JG003279.

 

References for the DCHM-V

  1. Barros, A. P. (1995), Adaptive multilevel modeling of land-atmosphere interactions, J. Clim., 8, 2144–2160.
  2. Devonec, E., and A. P. Barros (2002), Exploring the transferability of a land-surface hydrology model, J. Hydrol., 265, 258–282.
  3. Garcia-Quijano, J. F., and A. P. Barros (2005), Incorporating canopy physiology into a hydrological model: Photosynthesis, dynamic respiration, and stomatal sensitivity, Ecol. Model., 185, 29–49, doi:10.1016/j.ecolmodel.2004.08.024.
  4. Gebremichael, M., and A. P. Barros (2006), Evaluation of MODIS gross primary productivity (GPP) in tropical monsoon regions, Remote Sens. Environ., 100, 150–166, doi:10.1016/j.rse.2005.10.009.
  5. Lowman, L. E. L., and A. P. Barros (2016), Interplay of Drought and Tropical Cyclone Activity in SE US Gross Primary Productivity. J. Geophys. Res. Biogeosci., 120, doi: 10.1002/2015JG003279.
  6. Tao, J., and A. P. Barros (2013), Prospects for flash flood forecasting in mountainous regions—An investigation of Tropical Storm Fay in the Southern Appalachians, J. Hydrol., 506, 69–89, doi:10.1016/j.jhydrol.2013.02.052.
  7. Tao, J., and A. P. Barros (2014), Coupled prediction of flood response and debris flow initiation during warm- and cold-season events in the Southern Appalachians, USA, Hydrol. Earth Syst. Sci., 18, 367–388, doi:10.5194/hess-18-367-2014.
  8. Yildiz, O. (2001), Assessment and simulation of hydrologic extremes by a physically-based spatially distributed hydrologic model, PhD Dissertation, Department of Civil and Environmental Engineering, The Pennsylvania State University, University Park, Pa., 214 pp.
  9. Yildiz, O., and A. P. Barros (2005), Climate variability, water resources, and hydrologic extremes—Modeling the water and energy budgets, in Climate and Hydrology, in Mountain Areas, edited by C. de Jong, et al., John Wiley, Chichester, U. K., doi:10.1002/0470858249.ch20.
  10. Yildiz, O., and A. P. Barros (2007), Elucidating vegetation controls on the hydroclimatology of a mid-latitude basin, J. Hydrol., 333, 431–448, doi:10.1016/j.jhydrol.2006.09.010.
  11. Yildiz, O., and A. P. Barros (2009), Evaluating spatial variability and scale effects on hydrologic processes in a midsize river basin, Sci. Res. Essays, 4, 217–225.