Data assimilation: From photon counts to Earth System forecasts

Full text not archived in this repository.

Please see our End User Agreement.

It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing.

Add to AnyAdd to TwitterAdd to FacebookAdd to LinkedinAdd to PinterestAdd to Email

Mathieu, P.-P. and O'Neill, A. (2007) Data assimilation: From photon counts to Earth System forecasts. Remote Sensing of Environment, 112 (4). 1258 -1267 . ISSN 0034-4257 doi: 10.1016/j.rse.2007.02.040

Abstract/Summary

Data assimilation – the set of techniques whereby information from observing systems and models is combined optimally – is rapidly becoming prominent in endeavours to exploit Earth Observation for Earth sciences, including climate prediction. This paper explains the broad principles of data assimilation, outlining different approaches (optimal interpolation, three-dimensional and four-dimensional variational methods, the Kalman Filter), together with the approximations that are often necessary to make them practicable. After pointing out a variety of benefits of data assimilation, the paper then outlines some practical applications of the exploitation of Earth Observation by data assimilation in the areas of operational oceanography, chemical weather forecasting and carbon cycle modelling. Finally, some challenges for the future are noted.

Altmetric Badge

Item Type Article
URI https://reading-clone.eprints-hosting.org/id/eprint/966
Identification Number/DOI 10.1016/j.rse.2007.02.040
Refereed Yes
Divisions Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
Uncontrolled Keywords Earth Observation; Data assimilation; Earth System modelling; Earth Observation System of systems; Kalman Filter; Variational assimilation
Publisher Elsevier
Download/View statistics View download statistics for this item

University Staff: Request a correction | Centaur Editors: Update this record

Search Google Scholar