£135.68

Springer Data Assimilation for Atmospheric, Oceanic and Hydrologic Vol II

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Description

This comprehensive volume from Springer provides the latest progress in data assimilation across meteorology, oceanography, and hydrology, including land surface studies. It serves as a deep resource for understanding both the theoretical foundations and the practical applications required in modern earth sciences. The text covers a wide range of methodologies, including variational, Kalman filter, ensemble, Monte Carlo, and artificial intelligence methods. Beyond core assimilation techniques, the book addresses vital related topics such as targeting observation, sensitivity analysis, and parameter estimation. Designed for a technical audience, this book acts as a reliable reference for individual researchers and graduate students. It bridges the gap between complex mathematical theory and real-world application in atmospheric and oceanic sciences, making it an essential addition to any academic or professional library in the field of computer science and machine learning.

Key Features

Covers recent progress in data assimilation for meteorology, oceanography, and hydrology including land surface applications.

Explores diverse methodologies such as variational, Kalman filter, ensemble, Monte Carlo, and artificial intelligence methods.

Includes essential topics like targeting observation, sensitivity analysis, and parameter estimation for a complete technical overview.

Provides both theoretical and applicative aspects to support both academic study and practical research implementation.

Serves as a dedicated reference for graduate students and individual researchers working in earth science and machine learning.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
03 June 2013
Listed Since
18 October 2012

Barcode

No barcode data available

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