Biogeosciences
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Articles | Volume 17, issue 7
Articles | Volume 17, issue 7
https://doi.org/10.5194/bg-17-1821-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-17-1821-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 17, issue 7
Research article
 | 
03 Apr 2020
Research article |  | 03 Apr 2020

Spatio-temporal variations and uncertainty in land surface modelling for high latitudes: univariate response analysis

Didier G. Leibovici, Shaun Quegan, Edward Comyn-Platt, Garry Hayman, Maria Val Martin, Mathieu Guimberteau, Arsène Druel, Dan Zhu, and Philippe Ciais

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Latest update: 22 Nov 2024
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Short summary
Analysing the impact of environmental changes due to climate change, e.g. geographical spread of climate-sensitive infections (CSIs) and agriculture crop modelling, may require land surface modelling (LSM) to predict future land surface conditions. There are multiple LSMs to choose from. The paper proposes a multivariate spatio-temporal data science method to understand the inherent uncertainties in four LSMs and the variations between them in Nordic areas for the net primary production.
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