Articles | Volume 15, issue 10
https://doi.org/10.5194/acp-15-5987-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/acp-15-5987-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Reliable, robust and realistic: the three R's of next-generation land-surface modelling
Department of Biological Sciences, Macquarie University, North Ryde, New South Wales 2109, Australia
AXA Chair of Biosphere and Climate Impacts, Grand Challenges in Ecosystems and the Environment and Grantham Institute – Climate Change and the Environment, Department of Life Sciences, Silwood Park Campus, Ascot, Imperial College London, UK
X. Liang
Department of Civil and Environmental Engineering, University of Pittsburgh, Pennsylvania, USA
B. E. Medlyn
Hawesbury Institute for the Environment, University of Western Sydney, Locked Bag 1797, Penrith, New South Wales, Australia
Department of Biological Sciences, Macquarie University, North Ryde, New South Wales 2109, Australia
Y.-P. Wang
CSIRO Ocean and Atmosphere Flagship, Private Bag 1, Aspendale, Victoria, Australia
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- Modelled net carbon gain responses to climate change in boreal trees: Impacts of photosynthetic parameter selection and acclimation J. Stinziano et al. 10.1111/gcb.14530
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Short summary
Land surface models (LSMs) describe how carbon and water fluxes react to environmental change. They are key component of climate models, yet they differ enormously. Many perform poorly, despite having many parameters. We outline a development strategy emphasizing robustness, reliability and realism, none of which is guaranteed by complexity alone. We propose multiple constraints, benchmarking and data assimilation, and representing unresolved processes stochastically, as tools in this endeavour.
Land surface models (LSMs) describe how carbon and water fluxes react to environmental change....
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