Author: Y.K. Sasaki
Publisher: Elsevier
Published: 2012-12-02
Total Pages: 320
ISBN-13: 0444597123
DOWNLOAD EBOOK →The last few decades have seen a spectacular growth in the use of variational methods, one of the most classic and elegant methods in physical and mathematical sciences, as powerful tools of optimization and numerical analysis. The tremendous accumulation of information on the use of variational methods in the area of the geosciences, which includes meteorology, oceanography, hydrology, geophysics and seismology, indicated the need for the first symposium on Variational Methods in Geosciences to be organized and held in Norman on October 15-17, 1985. The value of this symposium was enhanced by the number of stimulating and informative papers presented.
Author: Seon Ki Park
Publisher: Springer Nature
Published: 2021-11-09
Total Pages: 707
ISBN-13: 3030777227
DOWNLOAD EBOOK →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 adaptive observations, sensitivity analysis, parameter estimation and AI applications. The book is useful to individual researchers as well as graduate students for a reference in the field of data assimilation.
Author: University of Wisconsin--Madison. Department of Statistics
Publisher:
Published: 1972
Total Pages: 476
ISBN-13:
DOWNLOAD EBOOK →Author: Steven J. Fletcher
Publisher: Elsevier
Published: 2022-11-16
Total Pages: 1130
ISBN-13: 0323972535
DOWNLOAD EBOOK →Data Assimilation for the Geosciences: From Theory to Application, Second Edition brings together all of the mathematical and statistical background knowledge needed to formulate data assimilation systems into one place. It includes practical exercises enabling readers to apply theory in both a theoretical formulation as well as teach them how to code the theory with toy problems to verify their understanding. It also demonstrates how data assimilation systems are implemented in larger scale fluid dynamical problems related to land surface, the atmosphere, ocean and other geophysical situations. The second edition of Data Assimilation for the Geosciences has been revised with up to date research that is going on in data assimilation, as well as how to apply the techniques. The new edition features an introduction of how machine learning and artificial intelligence are interfacing and aiding data assimilation. In addition to appealing to students and researchers across the geosciences, this now also appeals to new students and scientists in the field of data assimilation as it will now have even more information on the techniques, research, and applications, consolidated into one source. Includes practical exercises and solutions enabling readers to apply theory in both a theoretical formulation as well as enabling them to code theory Provides the mathematical and statistical background knowledge needed to formulate data assimilation systems into one place New to this edition: covers new topics such as Observing System Experiments (OSE) and Observing System Simulation Experiments; and expanded approaches for machine learning and artificial intelligence