  Macroscopic models for spatially extended systems under random influences are
often described by stochastic partial differential equations (SPDEs).
  Some techniques for understanding solutions of such equations, such as
estimating correlations, Liapunov exponents and impact of noises, are
discussed. They are relevant for understanding predictability in spatially
extended systems with model uncertainty, for example, in physics, geophysics
and biological sciences. The presentation is for a wide audience.
