Journal cover Journal topic
Nonlinear Processes in Geophysics An interactive open-access journal of the European Geosciences Union
Journal topic

Journal metrics

Journal metrics

  • IF value: 1.699 IF 1.699
  • IF 5-year value: 1.559 IF 5-year
    1.559
  • CiteScore value: 1.61 CiteScore
    1.61
  • SNIP value: 0.884 SNIP 0.884
  • IPP value: 1.49 IPP 1.49
  • SJR value: 0.648 SJR 0.648
  • Scimago H <br class='hide-on-tablet hide-on-mobile'>index value: 52 Scimago H
    index 52
  • h5-index value: 21 h5-index 21
Volume 25, issue 1
Nonlin. Processes Geophys., 25, 55–66, 2018
https://doi.org/10.5194/npg-25-55-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Nonlin. Processes Geophys., 25, 55–66, 2018
https://doi.org/10.5194/npg-25-55-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 30 Jan 2018

Research article | 30 Jan 2018

Optimal transport for variational data assimilation

Nelson Feyeux et al.
Related authors  
NEMOTAM: tangent and adjoint models for the ocean modelling platform NEMO
A. Vidard, P.-A. Bouttier, and F. Vigilant
Geosci. Model Dev., 8, 1245–1257, https://doi.org/10.5194/gmd-8-1245-2015,https://doi.org/10.5194/gmd-8-1245-2015, 2015
Short summary
An ETKF approach for initial state and parameter estimation in ice sheet modelling
B. Bonan, M. Nodet, C. Ritz, and V. Peyaud
Nonlin. Processes Geophys., 21, 569–582, https://doi.org/10.5194/npg-21-569-2014,https://doi.org/10.5194/npg-21-569-2014, 2014
Greenland ice sheet contribution to sea-level rise from a new-generation ice-sheet model
F. Gillet-Chaulet, O. Gagliardini, H. Seddik, M. Nodet, G. Durand, C. Ritz, T. Zwinger, R. Greve, and D. G. Vaughan
The Cryosphere, 6, 1561–1576, https://doi.org/10.5194/tc-6-1561-2012,https://doi.org/10.5194/tc-6-1561-2012, 2012
Related subject area  
Subject: Predictability, Data Assimilation | Topic: Climate, Atmosphere, Ocean, Hydrology, Cryosphere, Biosphere
Generalization properties of feed-forward neural networks trained on Lorenz systems
Sebastian Scher and Gabriele Messori
Nonlin. Processes Geophys., 26, 381–399, https://doi.org/10.5194/npg-26-381-2019,https://doi.org/10.5194/npg-26-381-2019, 2019
Short summary
Revising the stochastic iterative ensemble smoother
Patrick Nima Raanes, Andreas Størksen Stordal, and Geir Evensen
Nonlin. Processes Geophys., 26, 325–338, https://doi.org/10.5194/npg-26-325-2019,https://doi.org/10.5194/npg-26-325-2019, 2019
Short summary
Joint state-parameter estimation of a nonlinear stochastic energy balance model from sparse noisy data
Fei Lu, Nils Weitzel, and Adam H. Monahan
Nonlin. Processes Geophys., 26, 227–250, https://doi.org/10.5194/npg-26-227-2019,https://doi.org/10.5194/npg-26-227-2019, 2019
Short summary
Non-Gaussian statistics in global atmospheric dynamics: a study with a 10 240-member ensemble Kalman filter using an intermediate atmospheric general circulation model
Keiichi Kondo and Takemasa Miyoshi
Nonlin. Processes Geophys., 26, 211–225, https://doi.org/10.5194/npg-26-211-2019,https://doi.org/10.5194/npg-26-211-2019, 2019
Short summary
Fluctuations of finite-time Lyapunov exponents in an intermediate-complexity atmospheric model: a multivariate and large-deviation perspective
Frank Kwasniok
Nonlin. Processes Geophys., 26, 195–209, https://doi.org/10.5194/npg-26-195-2019,https://doi.org/10.5194/npg-26-195-2019, 2019
Short summary
Cited articles  
Asch, M., Bocquet, M., and Nodet, M.: Data assimilation: methods, algorithms, and applications, SIAM, 306 pp., 2016.
Benamou, J.-D. and Brenier, Y.: A computational fluid mechanics solution to the Monge-Kantorovich mass transfer problem, Numer. Math., 84, 375–393, 2000.
Bocquet, M. and Sakov, P.: An iterative ensemble Kalman smoother, Q. J. Roy. Meteor. Soc., 140, 1521–1535, https://doi.org/10.1002/qj.2236, 2014.
Bonneel, N., Van De Panne, M., Paris, S., and Heidrich, W.: Displacement interpolation using Lagrangian mass transport, in: ACM Transactions on Graphics (TOG), 30, No. 158, ACM, 2011.
Brenier, Y., Frisch, U., Hénon, M., Loeper, G., Matarrese, S., Mohayaee, R., and Sobolevskiĭ, A.: Reconstruction of the early Universe as a convex optimization problem, Mon. Not. R. Astron. Soc., 346, 501–524, 2003.
Publications Copernicus
Download
Short summary
In geophysics, numerical models are generally initialized through so-called data assimilation methods. They require computation of a distance between model fields and physical observations. The most common choice is the Euclidian distance. However, due to its local nature it is not well suited for capturing position errors. This papers investigates theoretical aspects of the use of the optimal transport-based Wasserstein distance in this context and shows that it is able to capture such errors.
In geophysics, numerical models are generally initialized through so-called data assimilation...
Citation