Articles | Volume 15, issue 5
https://doi.org/10.5194/gmd-15-1931-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-15-1931-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model evaluation paper
| 
09 Mar 2022
Model evaluation paper |
| 09 Mar 2022
| 09 Mar 2022
A new snow module improves predictions of the isotope-enabled MAIDENiso forest growth model
Ignacio Hermoso de Mendoza
CORRESPONDING AUTHOR
Centre de Recherche sur la dynamique du système Terre (GEOTOP), Université du Québec Montréal (UQAM), Montréal, Quebec, H2X 3R9, Canada
Etienne Boucher
Centre de Recherche sur la dynamique du système Terre (GEOTOP), Université du Québec Montréal (UQAM), Montréal, Quebec, H2X 3R9, Canada
Centre d'études nordiques (CEN), Université de Laval, Québec City, Quebec, G1V 0A6, Canada
Fabio Gennaretti
Institut de Recherche sur les Forêts (IRF), Université du Québec en Abitibi-Témiscamingue (UQAT), Amos, Quebec, J9T 2L8, Canada
Aliénor Lavergne
Carbon Cycle Research Group, Space and Atmospheric Physics, Physics Department, Imperial College London, London, SW7 2AZ, United Kingdom
Robert Field
NASA Goddard Institute for Space Studies, Applied Physics and Applied Mathematics, Columbia University, New York, NY, USA
Laia Andreu-Hayles
Tree-Ring Laboratory, Lamont-Doherty Earth Observatory, Columbia University, Palisades, NY, 10964, USA
Ecological and Forestry Applications Research Centre (CREAF), Bellaterra (Cerdanyola del Vallés), Barcelona, Spain
Catalan Institution for Research and Advanced Studies (ICREA), Pg. Lluís Companys 23, Barcelona, Spain
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Short summary
We modify the numerical model of forest growth MAIDENiso by explicitly simulating snow. This allows us to use the model in boreal environments, where snow is dominant. We tested the performance of the model before and after adding snow, using it at two Canadian sites to simulate tree-ring isotopes and comparing with local observations. We found that modelling snow improves significantly the simulation of the hydrological cycle, the plausibility of the model and the simulated isotopes.
We modify the numerical model of forest growth MAIDENiso by explicitly simulating snow. This...
