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Title: Displacement data assimilation

Abstract

We show that modifying a Bayesian data assimilation scheme by incorporating kinematically-consistent displacement corrections produces a scheme that is demonstrably better at estimating partially observed state vectors in a setting where feature information is important. While the displacement transformation is generic, here we implement it within an ensemble Kalman Filter framework and demonstrate its effectiveness in tracking stochastically perturbed vortices.

Authors:
 [1];  [2];  [3];  [4]
  1. Pacific Northwest Laboratory, Richland, WA 99354 (United States)
  2. Department of Mathematics and Program in Applied Mathematics, University of Arizona, Tucson, AZ 85721 (United States)
  3. Rosenstiel School of Marine & Atmospheric Science, University of Miami, Miami, FL 33149 (United States)
  4. Department of Mathematics, Oregon State University, Corvallis, OR 97331 (United States)
Publication Date:
OSTI Identifier:
22622249
Resource Type:
Journal Article
Resource Relation:
Journal Name: Journal of Computational Physics; Journal Volume: 330; Other Information: Copyright (c) 2016 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved.; Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS; 97 MATHEMATICAL METHODS AND COMPUTING; ASSIMILATION; CORRECTIONS; FILTERS; STOCHASTIC PROCESSES; TRANSFORMATIONS; VORTICES

Citation Formats

Rosenthal, W. Steven, Venkataramani, Shankar, Mariano, Arthur J., and Restrepo, Juan M., E-mail: restrepo@math.oregonstate.edu. Displacement data assimilation. United States: N. p., 2017. Web. doi:10.1016/J.JCP.2016.10.025.
Rosenthal, W. Steven, Venkataramani, Shankar, Mariano, Arthur J., & Restrepo, Juan M., E-mail: restrepo@math.oregonstate.edu. Displacement data assimilation. United States. doi:10.1016/J.JCP.2016.10.025.
Rosenthal, W. Steven, Venkataramani, Shankar, Mariano, Arthur J., and Restrepo, Juan M., E-mail: restrepo@math.oregonstate.edu. Wed . "Displacement data assimilation". United States. doi:10.1016/J.JCP.2016.10.025.
@article{osti_22622249,
title = {Displacement data assimilation},
author = {Rosenthal, W. Steven and Venkataramani, Shankar and Mariano, Arthur J. and Restrepo, Juan M., E-mail: restrepo@math.oregonstate.edu},
abstractNote = {We show that modifying a Bayesian data assimilation scheme by incorporating kinematically-consistent displacement corrections produces a scheme that is demonstrably better at estimating partially observed state vectors in a setting where feature information is important. While the displacement transformation is generic, here we implement it within an ensemble Kalman Filter framework and demonstrate its effectiveness in tracking stochastically perturbed vortices.},
doi = {10.1016/J.JCP.2016.10.025},
journal = {Journal of Computational Physics},
number = ,
volume = 330,
place = {United States},
year = {Wed Feb 01 00:00:00 EST 2017},
month = {Wed Feb 01 00:00:00 EST 2017}
}