Design and Implementation of a Parallel Multivariate Ensemble Kalman Filter for the Poseidon Ocean General Circulation Model PDF Download
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Author: National Aeronautics and Space Administration (NASA)
Publisher: Createspace Independent Publishing Platform
ISBN: 9781720459163
Category :
Languages : en
Pages : 48
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Book Description
A multivariate ensemble Kalman filter (MvEnKF) implemented on a massively parallel computer architecture has been implemented for the Poseidon ocean circulation model and tested with a Pacific Basin model configuration. There are about two million prognostic state-vector variables. Parallelism for the data assimilation step is achieved by regionalization of the background-error covariances that are calculated from the phase-space distribution of the ensemble. Each processing element (PE) collects elements of a matrix measurement functional from nearby PEs. To avoid the introduction of spurious long-range covariances associated with finite ensemble sizes, the background-error covariances are given compact support by means of a Hadamard (element by element) product with a three-dimensional canonical correlation function. The methodology and the MvEnKF configuration are discussed. It is shown that the regionalization of the background covariances; has a negligible impact on the quality of the analyses. The parallel algorithm is very efficient for large numbers of observations but does not scale well beyond 100 PEs at the current model resolution. On a platform with distributed memory, memory rather than speed is the limiting factor.Keppenne, Christian L. and Rienecker, Michele M. and Koblinsky, Chester (Technical Monitor)Goddard Space Flight CenterPARALLEL PROCESSING (COMPUTERS); OCEAN MODELS; OCEAN CURRENTS; KALMAN FILTERS; STATE VECTORS; PARALLEL COMPUTERS; MULTIVARIATE STATISTICAL ANALYSIS; ERRORS; COVARIANCE; ARCHITECTURE (COMPUTERS)
Author: National Aeronautics and Space Administration (NASA)
Publisher: Createspace Independent Publishing Platform
ISBN: 9781720459163
Category :
Languages : en
Pages : 48
Get Book Here
Book Description
A multivariate ensemble Kalman filter (MvEnKF) implemented on a massively parallel computer architecture has been implemented for the Poseidon ocean circulation model and tested with a Pacific Basin model configuration. There are about two million prognostic state-vector variables. Parallelism for the data assimilation step is achieved by regionalization of the background-error covariances that are calculated from the phase-space distribution of the ensemble. Each processing element (PE) collects elements of a matrix measurement functional from nearby PEs. To avoid the introduction of spurious long-range covariances associated with finite ensemble sizes, the background-error covariances are given compact support by means of a Hadamard (element by element) product with a three-dimensional canonical correlation function. The methodology and the MvEnKF configuration are discussed. It is shown that the regionalization of the background covariances; has a negligible impact on the quality of the analyses. The parallel algorithm is very efficient for large numbers of observations but does not scale well beyond 100 PEs at the current model resolution. On a platform with distributed memory, memory rather than speed is the limiting factor.Keppenne, Christian L. and Rienecker, Michele M. and Koblinsky, Chester (Technical Monitor)Goddard Space Flight CenterPARALLEL PROCESSING (COMPUTERS); OCEAN MODELS; OCEAN CURRENTS; KALMAN FILTERS; STATE VECTORS; PARALLEL COMPUTERS; MULTIVARIATE STATISTICAL ANALYSIS; ERRORS; COVARIANCE; ARCHITECTURE (COMPUTERS)
Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 50
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Book Description
Author: Christian L. Keppenne
Publisher:
ISBN:
Category : Multivariate analysis
Languages : en
Pages : 35
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Book Description
Author: SEON KI PARK
Publisher: Springer Science & Business Media
ISBN: 3540710566
Category : Science
Languages : en
Pages : 481
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Book Description
Data assimilation (DA) has been recognized as one of the core techniques for modern forecasting in various earth science disciplines including meteorology, oceanography, and hydrology. Since early 1990s DA has been an important s- sion topic in many academic meetings organized by leading societies such as the American Meteorological Society, American Geophysical Union, European G- physical Union, World Meteorological Organization, etc. nd Recently, the 2 Annual Meeting of the Asia Oceania Geosciences Society (AOGS), held in Singapore in June 2005, conducted a session on DA under the - tle of “Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications.” nd This rst DA session in the 2 AOGS was a great success with more than 30 papers presented and many great ideas exchanged among scientists from the three different disciplines. The scientists who participated in the meeting suggested making the DA session a biennial event. th Two years later, at the 4 AOGS Annual Meeting, Bangkok, Thailand, the DA session was of cially named “Sasaki Symposium on Data Assimilation for At- spheric, Oceanic and Hydrologic Applications,” to honor Prof. Yoshi K. Sasaki of the University of Oklahoma for his life-long contributions to DA in geosciences.
Author:
Publisher:
ISBN:
Category : Meteorology
Languages : en
Pages : 850
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Book Description
Author: Olwijn Leeuwenburgh
Publisher:
ISBN: 9789036922678
Category : Kalman filtering
Languages : en
Pages : 27
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Book Description
Author:
Publisher:
ISBN:
Category : Geophysics
Languages : en
Pages : 642
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Book Description
Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 44
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Book Description
Author: Ginalber Luiz Serra
Publisher: BoD – Books on Demand
ISBN: 9535138278
Category : Mathematics
Languages : en
Pages : 315
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Book Description
This book presents recent issues on theory and practice of Kalman filters, with a comprehensive treatment of a selected number of concepts, techniques, and advanced applications. From an interdisciplinary point of view, the contents from each chapter bring together an international scientific community to discuss the state of the art on Kalman filter-based methodologies for adaptive/distributed filtering, optimal estimation, dynamic prediction, nonstationarity, robot navigation, global navigation satellite systems, moving object tracking, optical communication systems, and active power filters, among others. The theoretical and methodological foundations combined with extensive experimental explanation make this book a reference suitable for students, practicing engineers, and researchers in sciences and engineering.
Author: Mohinder S. Grewal
Publisher: John Wiley & Sons
ISBN: 111898496X
Category : Technology & Engineering
Languages : en
Pages : 639
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Book Description
The definitive textbook and professional reference on Kalman Filtering – fully updated, revised, and expanded This book contains the latest developments in the implementation and application of Kalman filtering. Authors Grewal and Andrews draw upon their decades of experience to offer an in-depth examination of the subtleties, common pitfalls, and limitations of estimation theory as it applies to real-world situations. They present many illustrative examples including adaptations for nonlinear filtering, global navigation satellite systems, the error modeling of gyros and accelerometers, inertial navigation systems, and freeway traffic control. Kalman Filtering: Theory and Practice Using MATLAB, Fourth Edition is an ideal textbook in advanced undergraduate and beginning graduate courses in stochastic processes and Kalman filtering. It is also appropriate for self-instruction or review by practicing engineers and scientists who want to learn more about this important topic.
