Articles | Volume 9, issue 8
https://doi.org/10.5194/gmd-9-2833-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-9-2833-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Land-surface parameter optimisation using data assimilation techniques: the adJULES system V1.0
National Centre for Earth Observation, University of Exeter, Exeter EX4 4QF, UK
Tim E. Jupp
National Centre for Earth Observation, University of Exeter, Exeter EX4 4QF, UK
Peter M. Cox
National Centre for Earth Observation, University of Exeter, Exeter EX4 4QF, UK
Catherine M. Luke
National Centre for Earth Observation, University of Exeter, Exeter EX4 4QF, UK
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- Multi‐Objective Adaptive Surrogate Modeling‐Based Optimization for Distributed Environmental Models Based on Grid Sampling R. Sun et al. 10.1029/2020WR028740
- Combining local model calibration with the emergent constraint approach to reduce uncertainty in the tropical land carbon cycle feedback N. Raoult et al. 10.5194/esd-14-723-2023
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Latest update: 21 Nov 2024
Short summary
We present a set of "optimal" parameter values used to describe the influence of vegetation in a numerical climate model, and the software suite that we developed to find it. Observational data from ~ 100 locations were used, and the optimal parameters improve the fit in 90 % of the locations. The new parameter values will allow the climate model to give better predictions, and our software should prove useful in future calibrations.
We present a set of "optimal" parameter values used to describe the influence of vegetation in a...