Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
11017518 | Environmental Modelling & Software | 2019 | 17 Pages |
Abstract
We demonstrate the advantages of this framework by using rLPJGUESS to perform several otherwise laborious tasks: first, a set of single simulations, followed by global and local sensitivity analyses, a Bayesian calibration with a Markov-Chain Monte Carlo (MCMC) algorithm, and a predictive simulation with multiple climate scenarios. Our example highlights the opportunities of interfacing existing models in earth and environmental sciences with state-of-the-art computing environments such as R.
Related Topics
Physical Sciences and Engineering
Computer Science
Software
Authors
Maurizio Bagnara, Ramiro Silveyra Gonzalez, Stefan Reifenberg, Jörg Steinkamp, Thomas Hickler, Christian Werner, Carsten F. Dormann, Florian Hartig,