A big thanks to all participants / lecturers of our 2017 PROFOUND spring school on Bayesian calibration, forecasting and multi-model predictions of process-based vegetation models, and the subsequent WG3 meeting on the same topic.
The aim of the spring school was, as ever, to teach Bayesian methods for the calibration of process-based models. The training used a range of products developed by PROFOUND, in particular the new BayesianTools R package for model calibration.
The WG meeting was focused on discussing work / publications for ongoing WG3 task groups.
Programs for both events can be found under the respective links above.