DayCent data and results for "Robust paths to net greenhouse gas mitigation and negative emissions via advanced biofuels"

DayCent data and results for:<br>J. L. Field, T. L. Richard, E. A. Smithwick, H. Cai, M. S. Laser, D. S. LeBauer, S. P. Long, K. Paustian, Z. Qin, J. J. Sheehan, P. Smith, M. Q. Wang, L. R. Lynd, Robust paths to net greenhouse gas mitigation and negative emissions via advanced biofuels. Proceedings of the National Academy of Sciences (2020). https://doi.org/10.1073/pnas.1920877117<br><br>This zip file contains a UNIX-format DayCent model executable, input files, automation code, and associated directory structure necessary to re-produce the DayCent analysis underlying the manuscript. The main script 'autodaycent.py' (written for Python 2.7) opens an interactive command line routine that facilitates:<br>* Calibrating the DayCent pine growth model.<br>* Initializing DayCent for a set of case studies sites.<br>* Executing an ensemble of model runs representing case study site reforestation, grassland restoration, or conversion to switchgrass cultivation.<br>* Results analysis &amp; generation of manuscript Fig. 3.<br><br>Note that the interactive analysis code requires that all input files to be contained in the directory structure as uploaded, without modification. Executable versions of the DayCent model (https://www2.nrel.colostate.edu/projects/daycent/) compatible with other operating systems are available upon request. <br><br>Please send questions/comments to [e-mail]