Journal metrics

Journal metrics

  • IF value: 4.252 IF 4.252
  • IF 5-year value: 4.890 IF 5-year 4.890
  • CiteScore value: 4.49 CiteScore 4.49
  • SNIP value: 1.539 SNIP 1.539
  • SJR value: 2.404 SJR 2.404
  • IPP value: 4.28 IPP 4.28
  • h5-index value: 40 h5-index 40
  • Scimago H index value: 51 Scimago H index 51
Volume 10, issue 12 | Copyright
Geosci. Model Dev., 10, 4693-4722, 2017
https://doi.org/10.5194/gmd-10-4693-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Development and technical paper 22 Dec 2017

Development and technical paper | 22 Dec 2017

Towards a more detailed representation of high-latitude vegetation in the global land surface model ORCHIDEE (ORC-HL-VEGv1.0)

Arsène Druel et al.
Related authors
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
Geosci. Model Dev., 8, 2263-2283, https://doi.org/10.5194/gmd-8-2263-2015,https://doi.org/10.5194/gmd-8-2263-2015, 2015
Related subject area
Climate and Earth System Modeling
Dynamic hydrological discharge modelling for coupled climate model simulations of the last glacial cycle: the MPI-DynamicHD model version 3.0
Thomas Riddick, Victor Brovkin, Stefan Hagemann, and Uwe Mikolajewicz
Geosci. Model Dev., 11, 4291-4316, https://doi.org/10.5194/gmd-11-4291-2018,https://doi.org/10.5194/gmd-11-4291-2018, 2018
BGC-val: a model- and grid-independent Python toolkit to evaluate marine biogeochemical models
Lee de Mora, Andrew Yool, Julien Palmieri, Alistair Sellar, Till Kuhlbrodt, Ekaterina Popova, Colin Jones, and J. Icarus Allen
Geosci. Model Dev., 11, 4215-4240, https://doi.org/10.5194/gmd-11-4215-2018,https://doi.org/10.5194/gmd-11-4215-2018, 2018
An EC-Earth coupled atmosphere–ocean single-column model (AOSCM.v1_EC-Earth3) for studying coupled marine and polar processes
Kerstin Hartung, Gunilla Svensson, Hamish Struthers, Anna-Lena Deppenmeier, and Wilco Hazeleger
Geosci. Model Dev., 11, 4117-4137, https://doi.org/10.5194/gmd-11-4117-2018,https://doi.org/10.5194/gmd-11-4117-2018, 2018
Development and evaluation of a variably saturated flow model in the global E3SM Land Model (ELM) version 1.0
Gautam Bisht, William J. Riley, Glenn E. Hammond, and David M. Lorenzetti
Geosci. Model Dev., 11, 4085-4102, https://doi.org/10.5194/gmd-11-4085-2018,https://doi.org/10.5194/gmd-11-4085-2018, 2018
Compact Modeling Framework v3.0 for high-resolution global ocean–ice–atmosphere models
Vladimir V. Kalmykov, Rashit A. Ibrayev, Maxim N. Kaurkin, and Konstantin V. Ushakov
Geosci. Model Dev., 11, 3983-3997, https://doi.org/10.5194/gmd-11-3983-2018,https://doi.org/10.5194/gmd-11-3983-2018, 2018
Cited articles
Aiba, S.-I. and Kohyama, T.: Tree Species Stratification in Relation to Allometry and Demography in a Warm-Temperate Rain Forest, J. Ecol., 84, 207–218, https://doi.org/10.2307/2261356, 1996.
Ball, J. T., Woodrow, I. E., and Berry, J. A.: A Model Predicting Stomatal Conductance and its Contribution to the Control of Photosynthesis under Different Environmental Conditions, in: Progress in Photosynthesis Research, edited by: Biggins, J., 221–224, Springer Netherlands, Dordrecht, available at: http://link.springer.com/10.1007/978-94-017-0519-6_48 (last access: 28 April 2016), 1987.
Bastrikov, V., MacBean, N., Peylin, P., Bacour, C., Santaren, D., and Kuppel, S.: Land surface model parameter optimisation using in-situ flux data: comparison of gradient-based versus random search algorithms, in preparation, Geosci. Model Dev., 2018.
Baudena, M., Dekker, S. C., van Bodegom, P. M., Cuesta, B., Higgins, S. I., Lehsten, V., Reick, C. H., Rietkerk, M., Scheiter, S., Yin, Z., Zavala, M. A., and Brovkin, V.: Forests, savannas, and grasslands: bridging the knowledge gap between ecology and Dynamic Global Vegetation Models, Biogeosciences, 12, 1833–1848, https://doi.org/10.5194/bg-12-1833-2015, 2015.
Bentley, J. R., Seegrist, D., and Blakeman, D. A.: A technique for sampling low shrub vegetation, by cromwn volume classes, Res Note PSW-RN-215 Berkeley CA US Dep. Agric. For. Serv. Pac. Southwest For. Range Exp. Stn., 12 pp., 1970.
Publications Copernicus
Download
Short summary
To improve the simulation of vegetation–climate feedbacks at high latitudes, three new circumpolar vegetation types were added in the ORCHIDEE land surface model: bryophytes (mosses) and lichens, Arctic shrubs, and Arctic grasses. This article is an introduction to the modification of vegetation distribution and physical behaviour, implying for example lower productivity, roughness, and higher winter albedo or freshwater discharge in the Arctic Ocean.
To improve the simulation of vegetation–climate feedbacks at high latitudes, three new...
Citation
Share