NDLI: An ensemble-based three-dimensional variational data assimilation scheme

Content Provider	IEEE Xplore Digital Library
Author	Yueqi Han Zhong Zhong Zhuhui Wu Yunfeng Wang Xiaoping Cheng
Copyright Year	2011
Description	Author affiliation: Jinling Institute of Technology, Nanjing 211169, China (Zhuhui Wu) \|\| Institute of Meteorology, PLA University of Science and Technology, Nanjing 211101, China (Yueqi Han; Zhong Zhong; Yunfeng Wang; Xiaoping Cheng)
Abstract	A new ensemble-based three-dimensional variational data assimilation method (E-B3DVar) is presented. The analysis solution is obtained by minimization of a cost function that depends on a general nonlinear observation operator. The E-B3DVar belongs to the class of deterministic ensemble filters, since no perturbed observations are employed. As in variational and ensemble data assimilation methods, the cost function is derived using a Gaussian probability density function framework. Like other ensemble data assimilation algorithms, the E-B3DVar produces an estimate of the analysis uncertainty (e.g., analysis error covariance). In addition to the common use of ensembles in calculation of the forecast error covariance, the ensembles in E-B3DVar are exploited to efficiently calculate the gradient of the cost function. The E-B3DVar method is well suited for use with highly nonlinear observation operators, for a small additional computational cost of minimization. The consistent treatment of nonlinear observation operators through optimization is an advantage of the E-B3DVar over other ensemble data assimilation algorithms. The method is directly applicable to most complex forecast models and observation operators. In this paper, the E-B3DVar method is applied to data assimilation indicates potential wider applications of this new E-B3DVar method.
Starting Page	1961
Ending Page	1964
File Size	182243
Page Count	4
File Format	PDF
ISBN	9781612847719
e-ISBN	9781612847740
DOI	10.1109/ICMT.2011.6002613
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-07-26
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis Analysis error covariance Predictive models Minimization Three-dimensional variational data assimilation method Ensemble-based Kalman filters Mathematical model Data assimilation Meteorology
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

An ensemble-based variational inversion scheme

Inflation adjustment on error covariance matrix of ensemble Kalman filter

Ensemble-based atmospheric data assimilation (2004).

2004: Resilience of hybrid ensemble/3DVAR analysis schemes to model error and ensemble covariance error

A hybrid ensemble kalman filter / 3d-variational analysis scheme.

Ensemble-based data assimilation: a review (2002).

Coupling ensemble Kalman filter with four-dimensional variational data assimilation

2008b: An Ensemble-based Four-dimensional Variational Data Assimilation Scheme

A Three-Dimensional Variational Analysis Using Sequential Filter

An ensemble-based three-dimensional variational data assimilation scheme

Similar Documents

An ensemble-based variational inversion scheme

Inflation adjustment on error covariance matrix of ensemble Kalman filter

Ensemble-based atmospheric data assimilation (2004).

2004: Resilience of hybrid ensemble/3DVAR analysis schemes to model error and ensemble covariance error

A hybrid ensemble kalman filter / 3d-variational analysis scheme.

Ensemble-based data assimilation: a review (2002).

Coupling ensemble Kalman filter with four-dimensional variational data assimilation

2008b: An Ensemble-based Four-dimensional Variational Data Assimilation Scheme

A Three-Dimensional Variational Analysis Using Sequential Filter

An ensemble-based three-dimensional variational data assimilation scheme