Data integration and simulation: assimilation
Data assimilation is the combination of information from observations and models of a particular physical system in order to get the best possible estimate of the state of that system.
Data assimilation methods were largely developed for operational weather forecasting but in recent years, they have been applied to an increasing range of earth science disciplines and more specifically in Atmospheric Chemistry.
For exemple, there are many reasons for the assimilation of ozone observations:
(1) data assimilation provides an improved mapping of ozone fields from multiple data sources,
(2) it enables short-term ozone forecasts for the determination of surface UV radiation,
(3) it is one of the best approaches for the estimation of tropospheric ozone at global scale, from the combination of satellite observation of stratospheric ozone with meteorological information provided by the model and
(4) ozone data assimilation provides improved wind analyses as ozone measurements in the lower stratosphere contain information about the wind field, owing to the long photochemical lifetime of ozone in that region.
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