Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications (Vol. II)
Nonfiction, Science & Nature, Science, Other Sciences, Meteorology, Computers, Advanced Computing, Artificial Intelligence
| Author: | ISBN: | 9783642350887 | |
| Publisher: | Springer Berlin Heidelberg | Publication: | May 22, 2013 |
| Imprint: | Springer | Language: | English |
| Author: | |
| ISBN: | 9783642350887 |
| Publisher: | Springer Berlin Heidelberg |
| Publication: | May 22, 2013 |
| Imprint: | Springer |
| Language: | English |
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 methods. Besides data assimilation, other important topics are also covered including targeting observation, sensitivity analysis, and parameter estimation. The book will be useful to individual researchers as well as graduate students for a reference in the field of data assimilation.
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 methods. Besides data assimilation, other important topics are also covered including targeting observation, sensitivity analysis, and parameter estimation. The book will be useful to individual researchers as well as graduate students for a reference in the field of data assimilation.
