|Current Workshop | Overview||Back | Home | Search ||
Statistical Inference for Stochastic Process Models in Weather and Climate Science
process models occur in many areas of weather and climate science. They are
used in atmosphere and ocean science at different time scales ranging from
large-scale atmospheric flow at weather time scales, to interannual phenomena
such as the El Niņo Southern Oscillation (ENSO), to interdecadal variability.
In palaeoclimate such process models have been used for rapid glacial climate
transitions, the so-called Dansgaard-Oeschger events, or for
glacial-interglacial cycles. Motivation for deriving inverse models may be
manifold: They are used for predictive purposes and risk assessment, they may
serve to diagnose or interpret observational data or data from complex
physics-based models; or they may be meant to extract particular features or
processes with the goal to understand the dynamical mechanism behind these.