Reanalysis is a scientific method for developing a comprehensive record of how weather and climate are changing over time. In it, observations and a numerical model that simulates one or more aspects of the Earth system are combined objectively to generate a synthesized estimate of the state of the system. A reanalysis typically extends over several decades or longer, and covers the entire globe from the Earth’s surface to well above the stratosphere. Reanalysis products are used extensively in climate research and services, including for monitoring and comparing current climate conditions with those of the past, identifying the causes of climate variations and change, and preparing climate predictions. Information derived from reanalyses is also being used increasingly in commercial and business applications in sectors such as energy, agriculture, water resources, and insurance.
Numerical weather prediction uses data assimilation to incorporate a wide variety of available observational data to improve the accuracy of forecasts. Models used for climate projections, on the other hand, tend not to include detailed data or observations during the course of the run, except as initial conditions or as a basis for model evaluation. There is great potential, however, in having projection models capable of true data assimilation and numerical weather models capable of simulation over longer timescales.