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Principles of data assimilation /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Principles of data assimilation // Seon Ki Park, Ewha Womans University, Milija Zupanski, Colorado State University.
Author:	Park, Seon Ki,
other author:	Zupanski, Milija,
Description:	1 online resource (xiii, 398 pages) :digital, PDF file(s). :
Notes:	Title from publisher's bibliographic system (viewed on 22 Sep 2022).
Subject:	Meteorology - Data processing. -
Online resource:	https://doi.org/10.1017/9781108924238
ISBN:	9781108924238 (ebook)

Principles of data assimilation /
Park, Seon Ki,1961-

Principles of data assimilation /Seon Ki Park, Ewha Womans University, Milija Zupanski, Colorado State University. - 1 online resource (xiii, 398 pages) :digital, PDF file(s).

Title from publisher's bibliographic system (viewed on 22 Sep 2022).

Data assimilation is theoretically founded on probability, statistics, control theory, information theory, linear algebra, and functional analysis. At the same time, data assimilation is a very practical subject, given its goal of estimating the posterior probability density function in realistic high-dimensional applications. This puts data assimilation at the intersection between the contrasting requirements of theory and practice. Based on over twenty years of teaching courses in data assimilation, Principles of Data Assimilation introduces a unique perspective that is firmly based on mathematical theories, but also acknowledges practical limitations of the theory. With the inclusion of numerous examples and practical case studies throughout, this new perspective will help students and researchers to competently interpret data assimilation results and to identify critical challenges of developing data assimilation algorithms. The benefit of information theory also introduces new pathways for further development, understanding, and improvement of data assimilation methods.

ISBN: 9781108924238 (ebook)Subjects--Topical Terms:

965516
Meteorology
--Data processing.

LC Class. No.: QC874.3 / .P37 2022

Dewey Class. No.: 551.630285/63

Principles of data assimilation /
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