Prepared by Paul Quay (University of Washington) and Will
Frangos (James Madison University). Since models only
approximate natural phenomena, they are inherently inexact. The
mathematical description can be imperfect and/or our
understanding of phenomenon may not be complete. The
mathematical parameters used in models to represent real
processes are often uncertain because these parameters are
empirically determined or represent multiple processes.
Additionally, the initial or starting conditions and/or the
boundary conditions in a model may not be well known. Despite
these weaknesses, models are very powerful tools to represent
natural processes. Often models are the only means we have to
extrapolate to large spatial scales or predict the future.
Because of their importance in the earth sciences, we try to
assess model accuracy by calibratingand validating models. To
help quantify the uncertainty of the model output we determine
the sensitivity of the output to the model parameters. The
mathematical paramet