Problems with the models

  • Models represent a "simplified" atmosphere - not every real process in atmosphere can be resolved in the models
  • Many are not global in coverage
  • Initial atmospheric state is not well-known - want a dense, global network of observations
  • Have many data-parse regions, particularly over the oceans
  • The data may also have errors in it
  • The model equations compute quantities at grid points. Currently, grid spacing ranges from 30-50 km apart. Any phenomena smaller in size that grid spacing will not be resolved in models (e.g., thunderstorm) -->>
  • small-scale terrain features will not be handled properly
  • models can not resolve boundary layer very well.
  • The atmosphere is fundamentally chaotic - small differences in the model initial conditions can produce radically different results later in time
  • Each model can produce different predictions.... which do you believe????


Explain how the phrase "sensitive dependence on initial conditions" relates to the final outcome of a computer-based weather forecast.