Contents


Preface

*In the information age of ridiculously enormous and complex data set,*

*everybody feels stupid, unless one has the right tools and methodology to deal with.*

This book provides a comprehensive introduction to data assimilation, a vital tool used mostly in atmospheric science and oceanography. Ensemble data assimilation methods have been applied with remarkable success in several real-life historymatching problems. However, performance is severely degraded as data assimilation methods are based on Gaussian assumptions. This problem can be overcome with artificial neural networks, machine learning, and deep learning. The synergy of these complementary technologies leverages their benefits and results in the emergence of one of the most efficient tools for handling linear and non-linear models predicting the evolution of the atmosphere. This hybrid approach emulates hidden, chaotic dynamics and predicts future states with desired accuracy. The most known use of data assimilation is predicting the state of the atmosphere using meteorological data. Data assimilation is a vital step in numerical modeling, specifically in the atmospheric sciences and oceanography. However, even with a good understanding of the underlying physical laws that drive it, its chaotic nature makes it extremely difficult to determine the state of the environment, specifically atmospheric variables like temperature, humidity, pressure, and so on, with accuracy in a given spatio-temporal domain. This book presents the material in a clear, simple style and examines the many challenges and opportunities in the field of data assimilation.

I would like to convey our appreciation to all authors for their contributions. I owe special thanks to Author Service Managers Ms. Ivana Barac and Ms. Sara Debeuc, and Commissioning Editor Ms. Klara Mestrovic, at IntechOpen, London, UK, for their kind support and great efforts in bringing this book to fruition. In addition, I am grateful to all those who worked behind the scenes and assisted in formatting

*Anonymous*

**Dr. Dinesh G. Harkut** Dean and Associate Professor,

Badnera-Amravati, M.S., India

Department of Computer Science and Engineering,

Prof Ram Mehge College of Engineering and Management,

*It's alright, sweetie.*

the book.
