國立虎尾科技大學 |

Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications (Vol. IV)

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications (Vol. IV)/ edited by Seon Ki Park, Liang Xu.
other author:	Park, Seon Ki.
Description:	XXI, 705 p. 239 illus., 224 illus. in color.online resource. :
Contained By:	Springer Nature eBook
Subject:	Environmental sciences—Mathematics. -
Online resource:	https://doi.org/10.1007/978-3-030-77722-7
ISBN:	9783030777227

Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications (Vol. IV)
Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications (Vol. IV)[electronic resource] /edited by Seon Ki Park, Liang Xu. - 1st ed. 2022. - XXI, 705 p. 239 illus., 224 illus. in color.online resource.

Data Assimilation for Chaotic Dynamics -- Multifidelity Data Assimilation for Physical Systems -- Filtering with One-Step-Ahead Smoothing for Efficient Data Assimilation -- Sparsity-Based Kalman Filters for Data Assimilation -- Perturbations by the Ensemble Transform -- Stochastic Representations for Model Uncertainty in the Ensemble Data Assimilation System -- Second-Order Methods in Variational Data Assimilation -- Statistical Parameter Estimation for Observation Error Modelling: Application to Meteor Radars -- Observability Gramian and Its Role in the Placement of Observations in Dynamic Data Assimilation -- Placement of Observations for Variational Data Assimilation: Application to Burgers’ Equation and Seiche Phenomenon -- Analysis, Lateral Boundary, and Observation Impacts in a Limited Area Model -- An Overview of KMA’s Operational NWP Data Assimilation Systems.

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.

ISBN: 9783030777227

Standard No.: 10.1007/978-3-030-77722-7doiSubjects--Topical Terms:

1366051
Environmental sciences—Mathematics.

LC Class. No.: GE45.M38

Dewey Class. No.: 333.7

Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications (Vol. IV)
LDR:02943nam a22004215i 4500 001 1090571
003 DE-He213
005 20220114070853.0
007 cr nn 008mamaa
008 221228s2022 sz | s |||| 0|eng d
020 $a 9783030777227 $9 978-3-030-77722-7
024 7 $a 10.1007/978-3-030-77722-7 $2 doi
035 $a 978-3-030-77722-7
050 4 $a GE45.M38
072 7 $a RN $2 bicssc
072 7 $a PBW $2 bicssc
072 7 $a SCI026000 $2 bisacsh
072 7 $a RN $2 thema
072 7 $a PBW $2 thema
082 0 4 $a 333.7 $2 23
245 1 0 $a Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications (Vol. IV) $h [electronic resource] / $c edited by Seon Ki Park, Liang Xu.
250 $a 1st ed. 2022.
264 1 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2022.
300 $a XXI, 705 p. 239 illus., 224 illus. in color. $b online resource.
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
347 $a text file $b PDF $2 rda
505 0 $a Data Assimilation for Chaotic Dynamics -- Multifidelity Data Assimilation for Physical Systems -- Filtering with One-Step-Ahead Smoothing for Efficient Data Assimilation -- Sparsity-Based Kalman Filters for Data Assimilation -- Perturbations by the Ensemble Transform -- Stochastic Representations for Model Uncertainty in the Ensemble Data Assimilation System -- Second-Order Methods in Variational Data Assimilation -- Statistical Parameter Estimation for Observation Error Modelling: Application to Meteor Radars -- Observability Gramian and Its Role in the Placement of Observations in Dynamic Data Assimilation -- Placement of Observations for Variational Data Assimilation: Application to Burgers’ Equation and Seiche Phenomenon -- Analysis, Lateral Boundary, and Observation Impacts in a Limited Area Model -- An Overview of KMA’s Operational NWP Data Assimilation Systems.
520 $a 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.
650 0 $a Environmental sciences—Mathematics. $3 1366051
650 0 $a Mathematical optimization. $3 527675
650 0 $a Calculus of variations. $3 527927
650 0 $a Computer simulation. $3 560190
650 0 $a Oceanography. $3 654897
650 1 4 $a Mathematical Applications in Environmental Science. $3 1366053
650 2 4 $a Calculus of Variations and Optimization. $3 1366302
650 2 4 $a Computer Modelling. $3 1365730
650 2 4 $a Ocean Sciences. $3 1366156
700 1 $a Park, Seon Ki. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1076466
700 1 $a Xu, Liang. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 897207
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9783030777210
776 0 8 $i Printed edition: $z 9783030777234
776 0 8 $i Printed edition: $z 9783030777241
856 4 0 $u https://doi.org/10.1007/978-3-030-77722-7
912 $a ZDB-2-EES
912 $a ZDB-2-SXEE
950 $a Earth and Environmental Science (SpringerNature-11646)
950 $a Earth and Environmental Science (R0) (SpringerNature-43711)