<p><P>This book presents the most recent achievements in data assimilation in Geosciences, especially in regards to meteorology, oceanography and hydrology. It spans both theoretical and applied aspects with various methodologies including variational, Kalman filter, maximum likelihood ensemble filt
Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications
β Scribed by Seon K. Park, Liang Xu
- Publisher
- Springer
- Year
- 2009
- Tongue
- English
- Leaves
- 481
- Edition
- 1
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
This book presents the most recent achievements in data assimilation in Geosciences, especially in regards to meteorology, oceanography and hydrology. It spans both theoretical and applied aspects with various methodologies including variational, Kalman filter, maximum likelihood ensemble filter and other ensemble methods. Besides data assimilation, other important topics are also covered including targeting observation, parameter estimation, and remote sensing data retrieval. The book will be useful to individual researchers as well as graduate students as a reference in the field of data assimilation.
π SIMILAR VOLUMES
This book contains the most recent progress in data assimilation in meteorology, oceanography and hydrology including land surface.Β It spans both theoretical and applicative aspects with various methodologies such asΒ variational, Kalman filter, ensemble, Monte Carlo and artificial intelligence metho
<p>This book contains the most recent progress in data assimilation in meteorology, oceanography and hydrology including land surface. It spans both theoretical and applicative aspects with various methodologies such as variational, Kalman filter, ensemble, Monte Carlo and artificial intelligence me
<p>This book contains the most recent progress in data assimilation in meteorology, oceanography and hydrology including land surface. It spans both theoretical and applicative aspects with various methodologies such as variational, Kalman filter, ensemble, Monte Carlo and artificial intelligence me
This comprehensive text and reference work on numerical weather prediction covers for the first time, not only methods for numerical modeling, but also the important related areas of data assimilation and predictability. It incorporates all aspects of environmental computer modeling including an his