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Ensemble Riemannian data assimilation over the Wasserstein space

Tamang, S. K., Ebtehaj, A., Van Leeuwen, P. J. ORCID:, Zou, D. and Lerman, G. (2021) Ensemble Riemannian data assimilation over the Wasserstein space. Nonlinear Processes in Geophysics, 28 (3). pp. 295-309. ISSN 1023-5809

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To link to this item DOI: 10.5194/npg-28-295-2021


In this paper, we present an ensemble data assimilation paradigm over a Riemannian manifold equipped with the Wasserstein metric. Unlike the Euclidean distance used in classic data assimilation methodologies, the Wasserstein metric can capture the translation and difference between the shapes of square-integrable probability distributions of the background state and observations. This enables us to formally penalize geophysical biases in state space with nonGaussian distributions. The new approach is applied to dissipative and chaotic evolutionary dynamics, and its potential advantages and limitations are highlighted compared to the classic ensemble data assimilation approaches under systematic errors.

Item Type:Article
Divisions:Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
ID Code:99532
Publisher:European Geosciences Union


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