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: 1.558 IF 1.558
  • IF 5-year value: 1.475 IF 5-year
    1.475
  • CiteScore value: 2.8 CiteScore
    2.8
  • SNIP value: 0.921 SNIP 0.921
  • IPP value: 1.56 IPP 1.56
  • SJR value: 0.571 SJR 0.571
  • Scimago H <br class='hide-on-tablet hide-on-mobile'>index value: 55 Scimago H
    index 55
  • h5-index value: 22 h5-index 22
Volume 24, issue 1
Nonlin. Processes Geophys., 24, 9–22, 2017
https://doi.org/10.5194/npg-24-9-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
Nonlin. Processes Geophys., 24, 9–22, 2017
https://doi.org/10.5194/npg-24-9-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 16 Jan 2017

Research article | 16 Jan 2017

Estimating the state of a geophysical system with sparse observations: time delay methods to achieve accurate initial states for prediction

Zhe An et al.

Related authors

Precision Annealing Monte Carlo Methods for Statistical Data Assimilation: Metropolis-Hastings Procedures
Adrian S. Wong, Kangbo Hao, Zheng Fang, and Henry D. I. Abarbanel
Nonlin. Processes Geophys. Discuss., https://doi.org/10.5194/npg-2019-1,https://doi.org/10.5194/npg-2019-1, 2019
Preprint withdrawn
Short summary
Improved variational methods in statistical data assimilation
J. Ye, N. Kadakia, P. J. Rozdeba, H. D. I. Abarbanel, and J. C. Quinn
Nonlin. Processes Geophys., 22, 205–213, https://doi.org/10.5194/npg-22-205-2015,https://doi.org/10.5194/npg-22-205-2015, 2015
Short summary

Related subject area

Subject: Predictability, Data Assimilation | Topic: Climate, Atmosphere, Ocean, Hydrology, Cryosphere, Biosphere
From research to applications – examples of operational ensemble post-processing in France using machine learning
Maxime Taillardat and Olivier Mestre
Nonlin. Processes Geophys., 27, 329–347, https://doi.org/10.5194/npg-27-329-2020,https://doi.org/10.5194/npg-27-329-2020, 2020
Short summary
Correcting for model changes in statistical postprocessing – an approach based on response theory
Jonathan Demaeyer and Stéphane Vannitsem
Nonlin. Processes Geophys., 27, 307–327, https://doi.org/10.5194/npg-27-307-2020,https://doi.org/10.5194/npg-27-307-2020, 2020
Short summary
Brief communication: Residence time of energy in the atmosphere
Carlos Osácar, Manuel Membrado, and Amalio Fernández-Pacheco
Nonlin. Processes Geophys., 27, 235–237, https://doi.org/10.5194/npg-27-235-2020,https://doi.org/10.5194/npg-27-235-2020, 2020
Short summary
Simulating model uncertainty of subgrid-scale processes by sampling model errors at convective scales
Michiel Van Ginderachter, Daan Degrauwe, Stéphane Vannitsem, and Piet Termonia
Nonlin. Processes Geophys., 27, 187–207, https://doi.org/10.5194/npg-27-187-2020,https://doi.org/10.5194/npg-27-187-2020, 2020
Short summary
Data-driven versus self-similar parameterizations for stochastic advection by Lie transport and location uncertainty
Valentin Resseguier, Wei Pan, and Baylor Fox-Kemper
Nonlin. Processes Geophys., 27, 209–234, https://doi.org/10.5194/npg-27-209-2020,https://doi.org/10.5194/npg-27-209-2020, 2020
Short summary

Cited articles

Abarbanel, H. D. I.: Analysis of Observed Chaotic Data, Springer, New York, 1996.
Abarbanel, H. D. I.: Predicting the Future: Completing Models of Observed Complex Systems, Springer-Verlag, New York, 2013.
Abarbanel, H. D. I., Creveling, D. R., Farsian, R., and Kostuk, M.: Dynamical State and Parameter Estimation, SIAM J. Appl. Dyn. Syst., 8, 1341–1381, 2009.
Aeyels, D.: Generic observability of differentiable systems, SIAM J. Control Optim., 19, 595–603, 1981a.
Aeyels, D.: On the number of samples necessary to achieve observability, Syst. Control Lett., 1, 92–94, 1981b.
Publications Copernicus
Download
Citation