Dear Authors
Thank you for your very careful response to the reviews of the first version of the manuscript. At this stage I would recommend to go ahead with providing a revision that carefully addresses the many critical points the referees have raised.

When you work on the revision please keep specifically in mind:
1. That trial and error model tuning is never superior to Bayesian calibration. In accepting that calibrating the model properly was not possible, you accept that the information to constrain the complex model is not sufficient and, thus, the information on the generated parameters meaningless, i.e. one of potentially many possible solutions with no information on the parameter uncertainty and correlation with other parameters. In your response you seem to neglect this deficiency when writing: “The calibrated parameters we present in the paper may be of use for future modelling studies”. How can parameters that have been generated in a trial and error fashion be acceptable for the modelling community?
2. A very important concern is that both reviewers have expressed their impression that you didn’t motivate the study well enough. When you prepare the revision please make sure that the objectives of your study can be easily understood and are well reasoned. Clarification of the objectives and the achieved scientific progress will be an essential requirement for the acceptance of the manuscript. A statement ‘represent important contributions to the modeling community’ is not explicit enough.


With kind regards,
Andreas Ibrom

Dear Authors

I'm happy to inform you that the reviewers have indicated their satisfaction with your revisions and both recommend publication of the manuscript. Please consider the remaining minor comments.

Thank you very much for your constructive responses in the review process and good luck with the scientific impact of your work.

With kind regards,
Andreas