Articles | Volume 8, issue 7
https://doi.org/10.5194/gmd-8-2263-2015
https://doi.org/10.5194/gmd-8-2263-2015
Development and technical paper
 | 
28 Jul 2015
Development and technical paper |  | 28 Jul 2015

Improving the dynamics of Northern Hemisphere high-latitude vegetation in the ORCHIDEE ecosystem model

D. Zhu, S. S. Peng, P. Ciais, N. Viovy, A. Druel, M. Kageyama, G. Krinner, P. Peylin, C. Ottlé, S. L. Piao, B. Poulter, D. Schepaschenko, and A. Shvidenko

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Cited articles

Augspurger, C. K.: Spring 2007 warmth and frost: phenology, damage and refoliation in a temperate deciduous forest, Funct. Ecol., 23, 1031–1039, 2009.
Beer, C., Lucht, W., Gerten, D., Thonicke, K. and Schmullius, C.: Effects of soil freezing and thawing on vegetation carbon density in Siberia: a modeling analysis with the Lund-Postdam-Jena dynamic global vegetation model (lpj-dgvm), Global Biogeochem. Cy., 21, GB1012, https://doi.org/10.1029/2006GB002760, 2007.
Bicheron, P., Leroy, M., Brockmann, C., Krämer, U., Miras, B., Huc, M., Ninô, F., Defourny, P., Vancutsem, C., Arino, O., Ranera, F., Petit, D., Amberg, V., Berthelot, B., and Gross, D.: GLOBCOVER: A 300m global land cover product for 2005 using ENVISAT/MERIS time series, Proceedings of the Second Recent Advances in Quantitative Remote Sensing Symposium, 538–543, 2006.
Bokhorst, S. F., Bjerke, J. W., Tømmervik, H., Callaghan, T. V., and Phoenix, G. K.: Winter warming events damage sub-arctic vegetation: consistent evidence from an experimental manipulation and a natural event, J. Ecol., 97, 1408–1415, 2009.
Bond, W. J., Woodward, F. I., and Midgley, G. F.: The global distribution of ecosystems in a world without fire, New Phytol., 165, 525–538, 2005.
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Short summary
This study presents a new parameterization of the vegetation dynamics module in the process-based ecosystem model ORCHIDEE for mid- to high-latitude regions, showing significant improvements in the modeled distribution of tree functional types north of 40°N. A new set of metrics is proposed to quantify the performance of ORCHIDEE, which integrates uncertainties in the observational data sets.