Useful models

Some models have a strong foundation anchored in the physical laws of nature. The best example is the models used for numerical weather prediction (NWP), which do not follow some of the rules proposed on the checklist. Predicting weather entails dealing with odds, owing to the innate lack of predictability associated with what mathematicians now call 'chaos,' the tremendous sensitivity of results to small perturbations whose importance grows over time, eventually rendering a weather forecast useless after 10 to 14 days. Processes not explicitly represented by the basic dynamical and thermodynamic variables in the equations on the grid of the model need to be included by parameterizations. These include processes on smaller scales than the grid such as convection and boundary layer friction and turbulence, processes that contribute to internal heating such as radiative transfer and precipitation, both of which require cloud prediction, and missing processes such as land surface, carbon cycle, chemistry; and aerosol processes.