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This study shows that especially for process-based modelling approaches, not only comprehensive validation and calibration approaches need to be applied, but also knowledge of input data uncertainty and variability of the modelling results need to be assessed.
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The variability of the model under a moderate amount of stochastic forcing, meant to emulate the random variability of the atmosphere affecting the coupled model's interdecadal THC variability, is studied.
The predictive error caused by model uncertainty was evaluated through analysis of the variability of the model performance and parameters.
Furthermore, this paper presents different combinations of lead-time and demand scenarios to demonstrate the variability of the model.
How to characterize the cross-site variability of the model bias factor is important for design of pile foundations based on site-specific load test data.
PTFs could explain 12 48% of variability of the model's parameters, and the inclusion of topographic attributes (i.e. SSPFs) significantly increased R2 values.
The computational cost associated with uncertainty quantification of engineering problems featuring localized phenomenon can be reduced by confining the random variability of the model parameters within a region of interest.
The influence of all the other parameters in the variability of the model output is small.
Hence, we need to consider variability of the model (Ali et al. 2010) as described in next sub-process.
Further data mining will be carried out to extract quantitative and qualitative information about the dynamical variability of the model, bifurcations of its solutions, and so on.
The accuracy and variability of the model can be evaluated by R 2. The R 2 value is always between 0 and 1.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com