Weather prediction

Abstract

Current weather forecast skill is strongly driven by the sophistication of the physical processes represented in numerical models and advanced data assimilation schemes allowing vast amounts of data from conventional sources and satellites to be used. Globally, more than 40 million observations per day are used from about 50 different satellite instruments to produce atmospheric analyses with which the forecast models are initialized. The most important instruments are passive radiometers that measure infrared and microwave radiation emitted by the surface-atmosphere system and that are mostly exploited to derive information on temperature and moisture structures. Increasingly, observations of clouds and rain, surface waves, land surface characteristics, and atmospheric trace gases are added. In parallel, numerical models become increasingly capable of representing more complex physical and chemical processes at smaller scales. Ensemble analysis and forecasting systems allow the estimation of analysis and forecasting uncertainties - a crucial information in forecasting highly nonlinear atmospheric phenomena. Future satellite observing systems will develop toward more hyper-spectral instruments covering wider spectral ranges with fine spectral resolution as well as active instruments that sample vertical structures and wind very accurately.