Data Assimilation for the Earth System / NATO Science Series: IV: Bd.26 (PDF)
(Sprache: Englisch)
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. The technique has wide applications across a range of earth sciences, a...
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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. The technique has wide applications across a range of earth sciences, a major application being the production of operational weather forecasts. Others include oceanography, atmospheric chemistry, climate studies, and hydrology.
Data Assimilation for the Earth System is a comprehensive survey of both the theory of data assimilation and its application in a range of earth system sciences. Data assimilation is a key technique in the analysis of remote sensing observations and is thus particularly useful for those analysing the wealth of measurements from recent research satellites.
This book is suitable for postgraduate students and those working on the application of data assimilation in meteorology, oceanography and other earth sciences.
Data Assimilation for the Earth System is a comprehensive survey of both the theory of data assimilation and its application in a range of earth system sciences. Data assimilation is a key technique in the analysis of remote sensing observations and is thus particularly useful for those analysing the wealth of measurements from recent research satellites.
This book is suitable for postgraduate students and those working on the application of data assimilation in meteorology, oceanography and other earth sciences.
Bibliographische Angaben
- 2012, 2003, 377 Seiten, Englisch
- Herausgegeben: Richard Swinbank, Victor Shutyaev, William Albert Lahoz
- Verlag: Springer Netherlands
- ISBN-10: 9401000298
- ISBN-13: 9789401000291
- Erscheinungsdatum: 06.12.2012
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