GMDSI Four Ways

Four Ways to Explore Model Predictive Uncertainty

This tutorial explains four ways to explore the uncertainties of two predictions made by a relatively simple, fast-running model. These are:
  • Linear analysis
  • Sampling a linearised posterior covariance matrix
  • Iterative ensemble smoother
  • Data space inversion
In doing this tutorial, you get to use the following programs:
  • PEST
  • DSI1
  • Other members of the PEST utility support suite