@ARTICLE
Boudier, P., Fillion, A., Gratton, S., Gürol, S. and Zhang, S. (2023) Data Assimilation Networks, Journal of Advances in Modeling Earth Systems, 15 (4) , pp. Article number e2022MS003353, doi: 10.1029/2022MS003353
[bibtex]
@ARTICLE{AR-PA-23-44,
author = {Boudier, P. and Fillion, A. and Gratton, S. and Gürol, S. and Zhang, S. },
title = {Data Assimilation Networks},
year = {2023},
number = {4},
volume = {15},
pages = {Article number e2022MS003353},
doi = {10.1029/2022MS003353},
journal = {Journal of Advances in Modeling Earth Systems}}
Goux, O., Gürol, S., Weaver, A.T., Diouane, Y. and Guillet, O. (2023) Impact of correlated observation errors on the conditioning of variational data assimilation problems, Numerical Linear Algebra with Applications, 31 (1) , pp. e2529, doi: 10.1002/nla.2529
[bibtex]
@ARTICLE{AR-PA-23-118,
author = {Goux, O. and Gürol, S. and Weaver, A.T. and Diouane, Y. and Guillet, O. },
title = {Impact of correlated observation errors on the conditioning of variational data assimilation problems},
year = {2023},
number = {1},
volume = {31},
pages = {e2529},
doi = {10.1002/nla.2529},
journal = {Numerical Linear Algebra with Applications}}
Peyron , M., Fillion, A., Gürol, S., Marchais, V., Gratton, S., Boudier, P. and Goret, G. (2021) Latent space data assimilation by using deep learning, Quarterly Journal of the Royal Meteorological Society, 147 (740) , pp. 3759-3777, doi: 10.1002/qj.4153
[bibtex]
[url]
@ARTICLE{AR-PA-21-120,
author = {Peyron , M. and Fillion, A. and Gürol, S. and Marchais, V. and Gratton, S. and Boudier, P. and Goret, G. },
title = {Latent space data assimilation by using deep learning},
year = {2021},
number = {740},
volume = {147},
pages = {3759-3777},
doi = {10.1002/qj.4153},
journal = {Quarterly Journal of the Royal Meteorological Society},
url = {https://rmets.onlinelibrary.wiley.com/doi/epdf/10.1002/qj.4153}}
Fillion, A., Bocquet, M., Gratton, S., Gürol, S. and Sakov, P. (2020) An Iterative Ensemble Kalman Smoother in Presence of Additive Model Error, SIAM/ASA Journal on Uncertainty Quantification, 8 (1) , pp. 198–228, ISSN 2166-2525, doi: 10.1137/19M1244147
[bibtex]
[url] [pdf]
@ARTICLE{AR-PA-20-47,
author = {Fillion, A. and Bocquet, M. and Gratton, S. and Gürol, S. and Sakov, P. },
title = {An Iterative Ensemble Kalman Smoother in Presence of Additive Model Error },
year = {2020},
number = {1},
volume = {8},
pages = {198–228},
issn = {2166-2525},
doi = {10.1137/19M1244147},
journal = {SIAM/ASA Journal on Uncertainty Quantification},
keywords = {data assimilation, ensemble variational methods, model error, weak constraint 4DVar, iterative ensemble Kalman filter, iterative ensemble Kalman smoother},
pdf = {https://doi.org/10.1137/19M1244147},
url = {https://epubs.siam.org/doi/10.1137/19M1244147}}
Boudier, P., Fillion, A., Gratton, S. and Gürol, S. (2020) DAN -- An optimal Data Assimilation framework based on machine learning Recurrent Networks
[bibtex]
@ARTICLE{AR-PA-20-151,
author = {Boudier, P. and Fillion, A. and Gratton, S. and Gürol, S. },
title = {DAN -- An optimal Data Assimilation framework based on machine learning Recurrent Networks},
year = {2020}}
Laloyaux, P., Bonavita, M., Chrust, M. and Gürol, S. (2020) Exploring the potential and limitations of weak‐constraint 4D‐Var, Quarterly Journal of the Royal Meteorological Society, 146 (733) , pp. 4067-4082, doi: 10.1002/qj.3891
[bibtex]
[url]
@ARTICLE{AR-PA-20-157,
author = {Laloyaux, P. and Bonavita, M. and Chrust, M. and Gürol, S. },
title = {Exploring the potential and limitations of weak‐constraint 4D‐Var},
year = {2020},
number = {733},
volume = {146},
pages = {4067-4082},
doi = {10.1002/qj.3891},
journal = {Quarterly Journal of the Royal Meteorological Society},
abstract = {Abstract The standard formulation of 4D-Var assumes random zero-mean errors for all sources of information used in the analysis. This assumption is usually not well verified in real-world applications. The performance of a weak-constraint 4D-Var formulation ('forcing' formulation) is studied in this paper in a simplified experimental setting using additive model errors of different length-scales and observing systems of different coverage and accuracy. A set of twin experiments is carried out and results show that weak-constraint 4D-Var can accurately estimate the actual model errors and the initial state only when background and model errors have different spatial scales and when the observations are unbiased and spatially homogeneous. We also present preliminary results from a different weak-constraint 4D-Var formulation ('state' formulation) which could in principle overcome some of these limitations, but at the cost of a substantial increase of computational and memory requirements. These findings help identify the potential but also the intrinsic limitations of the weak-constraint 4D-Var approach. They also help to clarify the experimental results seen in the operational ECMWF analysis system where the analysis and first-guess temperature bias is reduced by up to 50\% in the stratosphere.model error, scale separation, weak-constraint 4D-Var},
keywords = {model error, scale separation, weak-constraint 4D-Var},
url = {https://rmets.onlinelibrary.wiley.com/doi/pdf/10.1002/qj.3891}}
Mercier, F., Michel, Y., Montmerle, T., Jolivet, P. and Gürol, S. (2019) Speeding up the ensemble data assimilation system of the limited-area model of Météo-France using a block Krylov algorithm, Quarterly Journal of the Royal Meteorological Society, 145 (720) , pp. 910-929, doi: 10.1002/qj.3428
[bibtex]
[url] [pdf]
@ARTICLE{AR-PA-19-74,
author = {Mercier, F. and Michel, Y. and Montmerle, T. and Jolivet, P. and Gürol, S. },
title = {Speeding up the ensemble data assimilation system of the limited-area model of Météo-France using a block Krylov algorithm},
year = {2019},
number = {720},
volume = {145},
pages = {910-929},
doi = {10.1002/qj.3428},
journal = {Quarterly Journal of the Royal Meteorological Society},
pdf = { https://doi.org/10.1002/qj.3428},
url = {https://rmets.onlinelibrary.wiley.com/doi/10.1002/qj.3428}}
Guillet, O., Weaver, A.T., Vasseur, X., Michel, Y., Gratton, S. and Gürol, S. (2019) Modelling spatially correlated observation errors in variational data assimilation using a diffusion operator on an unstructured mesh, Quarterly Journal of the Royal Meteorological Society, 145 (722) , pp. 1947-1967, ISSN 0035-9009, doi: 10.1002/qj.3537
[bibtex] [pdf]
@ARTICLE{AR-PA-19-127,
author = {Guillet, O. and Weaver, A.T. and Vasseur, X. and Michel, Y. and Gratton, S. and Gürol, S. },
title = {Modelling spatially correlated observation errors in variational data assimilation using a diffusion operator on an unstructured mesh},
year = {2019},
number = {722},
volume = {145},
pages = {1947-1967},
issn = {0035-9009},
doi = {10.1002/qj.3537},
journal = {Quarterly Journal of the Royal Meteorological Society},
keywords = {correlation functions, diffusion operator, finite element method, observation errors, unstructured mesh, variational assimilation},
pdf = { https://doi.org/10.1002/qj.3537}}
Fisher, M., Gratton, S., Gürol, S., Trémolet , Y. and Vasseur, X. (2018) Low rank updates in preconditioning the saddle point systems arising from data assimilation problems, Optimization Methods and Software, 33 (1) , pp. 45-69, doi: 10.1080/10556788.2016.1264398
[bibtex] [pdf]
@ARTICLE{AR-PA-18-167,
author = {Fisher, M. and Gratton, S. and Gürol, S. and Trémolet , Y. and Vasseur, X. },
title = {Low rank updates in preconditioning the saddle point systems arising from data assimilation problems},
year = {2018},
number = {1},
volume = {33},
pages = {45-69},
doi = {10.1080/10556788.2016.1264398},
journal = {Optimization Methods and Software},
abstract = {The numerical solution of saddle point systems has received a lot of attention over the past few years in a wide variety of applications such as constrained optimization, computational fluid dynamics and optimal control, to name a few. In this paper, we focus on the saddle point formulation of a large-scale variational data assimilation problem, where the computations involving the constraint blocks are supposed to be much more expensive than those related to the (1, 1) block of the saddle point matrix. New low-rank limited memory preconditioners exploiting the particular structure of the problem are proposed and analysed theoretically. Numerical experiments performed within the Object-Oriented Prediction System are presented to highlight the relevance of the proposed preconditioners.},
keywords = {data assimilation, limited memory preconditioning, saddle point system, weak-constraint},
pdf = {https://cerfacs.fr/wp-content/uploads/2016/09/TR-PA-16-142.pdf}}
Weaver, A.T., Gürol, S., Tshimanga, J., Chrust, M. and Piacentini, A (2018) "Time"-parallel diffusion-based correlation operators, Quarterly Journal of the Royal Meteorological Society
[bibtex]
@ARTICLE{AR-PA-18-63,
author = {Weaver, A.T. and Gürol, S. and Tshimanga, J. and Chrust, M. and Piacentini, A },
title = {“Time”-parallel diffusion-based correlation operators},
year = {2018},
journal = {Quarterly Journal of the Royal Meteorological Society}}
Gratton, S., Gürol, S., Simon, E. and Toint, Ph.-L. (2018) A note on preconditioning weighted linear least squares, with consequences for weakly-constrained variational data assimilation, Quarterly Journal of the Royal Meteorological Society, 144 (712) , pp. 934-940, doi: 10.1002/qj.3262
[bibtex] [pdf]
@ARTICLE{AR-PA-18-163,
author = {Gratton, S. and Gürol, S. and Simon, E. and Toint, Ph.-L. },
title = {A note on preconditioning weighted linear least squares, with consequences for weakly-constrained variational data assimilation},
year = {2018},
number = {712},
volume = {144},
pages = {934-940},
doi = {10.1002/qj.3262},
journal = {Quarterly Journal of the Royal Meteorological Society},
pdf = {https://doi.org/10.1002/qj.3262 }}
Mercier, F., Gürol, S., Jolivet, P., Michel, Y. and Montmerle, T. (2018) Block Krylov methods for accelerating ensembles of variational data assimilations, Quarterly Journal of the Royal Meteorological Society, 144 (717) , pp. 2463-2480, doi: 10.1002/qj.3329
[bibtex]
[url] [pdf]
@ARTICLE{AR-PA-18-165,
author = {Mercier, F. and Gürol, S. and Jolivet, P. and Michel, Y. and Montmerle, T. },
title = {Block Krylov methods for accelerating ensembles of variational data assimilations},
year = {2018},
number = {717},
volume = {144},
pages = {2463-2480},
doi = {10.1002/qj.3329},
journal = {Quarterly Journal of the Royal Meteorological Society},
pdf = {https://doi.org/10.1002/qj.3329},
url = {https://rmets.onlinelibrary.wiley.com/doi/full/10.1002/qj.3329}}
Gratton, S., Simon, E., Toint, Ph.-L. and Gürol, S. (2018) Guaranteeing the convergence of the saddle formulation for weakly‐constrained 4D‐VAR data assimilation, Quarterly Journal of the Royal Meteorological Society, 144 (717) , pp. 2592-2602, doi: 10.1002/qj.3355
[bibtex] [pdf]
@ARTICLE{AR-PA-18-166,
author = {Gratton, S. and Simon, E. and Toint, Ph.-L. and Gürol, S. },
title = {Guaranteeing the convergence of the saddle formulation for weakly‐constrained 4D‐VAR data assimilation},
year = {2018},
number = {717},
volume = {144},
pages = {2592-2602},
doi = {10.1002/qj.3355},
journal = {Quarterly Journal of the Royal Meteorological Society},
keywords = {data assimilation, variational methods, weakly‐constrained 4D‐VAR, saddle formulation, parallel computin},
pdf = {https://doi.org/10.1002/qj.3355}}
Weaver, A.T., Gürol, S., Tshimanga, J., Chrust, M. and Piacentini, A (2018) “Time”‐parallel diffusion‐based correlation operators, Quarterly Journal of the Royal Meteorological Society, 144, pp. 2067--2088, doi: 10.1002/qj.3302
[bibtex] [pdf]
@ARTICLE{AR-PA-18-168,
author = {Weaver, A.T. and Gürol, S. and Tshimanga, J. and Chrust, M. and Piacentini, A },
title = {“Time”‐parallel diffusion‐based correlation operators},
year = {2018},
volume = {144},
pages = {2067--2088},
doi = {10.1002/qj.3302},
journal = {Quarterly Journal of the Royal Meteorological Society},
pdf = {https://doi.org/10.1002/qj.3302}}
Guillet, O., Weaver, A.T., Vasseur, X., Michel, M., Gratton, S. and Gürol, S. (2018) Modelling spatially correlated observation errors in variational data assimilation using a diffusion operator on an unstructured mesh, Quarterly Journal of the Royal Meteorological Society
[bibtex]
@ARTICLE{AR-PA-18-201,
author = {Guillet, O. and Weaver, A.T. and Vasseur, X. and Michel, M. and Gratton, S. and Gürol, S. },
title = {Modelling spatially correlated observation errors in variational data assimilation using a diffusion operator on an unstructured mesh},
year = {2018},
journal = {Quarterly Journal of the Royal Meteorological Society}}
Fisher, M. and Gürol, S. (2017) Parallelization in the time dimension of four-dimensional variational data assimilation, Quarterly Journal of the Royal Meteorological Society, 143 (703) , pp. 1136–1147, doi: 10.1002/qj.2997
[bibtex]
@ARTICLE{AR-PA-17-207,
author = {Fisher, M. and Gürol, S. },
title = {Parallelization in the time dimension of four-dimensional variational data assimilation},
year = {2017},
number = {703},
volume = {143},
pages = {1136–1147},
doi = {10.1002/qj.2997},
journal = {Quarterly Journal of the Royal Meteorological Society},
abstract = {The current evolution of computer architectures towards increasing parallelism requires a corresponding evolution towards more parallel data assimilation algorithms. In this article, we consider parallelization of weak-constraint four-dimensional variational data assimilation (4D-Var) in the time dimension. We categorize algorithms according to whether or not they admit such parallelization and introduce a new, highly parallel weak-constraint 4D-Var algorithm based on a saddle-point representation of the underlying optimization problem. The potential benefits of the new saddle-point formulation are illustrated with a simple two-level quasi-geostrophic model.},
keywords = {4D-Var, data assimilation, parallel algorithms, saddle-point methods},
supplementaryMaterial = {https://doi.org/10.1002/qj.2997}}
Mandel, J., Bergou, E., Gratton, S., Gürol, S. and Kasanicky, I. (2016) Hybrid Levenberg-Marquardt and weak constraint ensemble Kalman smoother method, Nonlinear Processes in Geophysics, 23, pp. 59-73
[bibtex] [pdf]
@ARTICLE{AR-PA-16-8,
author = {Mandel, J. and Bergou, E. and Gratton, S. and Gürol, S. and Kasanicky, I. },
title = {Hybrid Levenberg-Marquardt and weak constraint ensemble Kalman smoother method},
year = {2016},
volume = {23},
pages = {59-73},
journal = {Nonlinear Processes in Geophysics},
pdf = {http://www.nonlin-processes-geophys.net/23/59/2016/npg-23-59-2016.pdf}}
Emili, E., Gürol, S. and Cariolle, D. (2016) Accounting for model error in air quality forecasts: an application of 4DEnVar to the assimilation of atmospheric composition using QG-Chem 1.0, Geoscientific Model Development, 9 (11) , pp. 3933-3959, doi: 10.5194/gmd-9-3933-2016
[bibtex]
[url]
@ARTICLE{AR-AE-16-266,
author = {Emili, E. and Gürol, S. and Cariolle, D. },
title = {Accounting for model error in air quality forecasts: an application of 4DEnVar to the assimilation of atmospheric composition using QG-Chem 1.0},
year = {2016},
number = {11},
volume = {9},
pages = {3933-3959},
doi = {10.5194/gmd-9-3933-2016},
journal = {Geoscientific Model Development},
url = {http://www.geosci-model-dev.net/9/3933/2016/}}
Gürol, S., Weaver, A.T., Moore, A.M., Piacentini, A, Arango, H.G. and Gratton, S. (2014) B-preconditioned minimization algorithms for variational data assimilation with the dual formulation, Quarterly Journal of the Royal Meteorological Society, 140 (679) , pp. 539 - 556, ISSN 1477-870X, doi: 10.1002/qj.2150
[bibtex]
[url] [pdf]
@ARTICLE{AR-CMGC-14-22016,
author = {Gürol, S. and Weaver, A.T. and Moore, A.M. and Piacentini, A and Arango, H.G. and Gratton, S. },
title = {B-preconditioned minimization algorithms for variational data assimilation with the dual formulation},
year = {2014},
number = {679},
volume = {140},
pages = {539 - 556},
issn = {1477-870X},
doi = {10.1002/qj.2150},
journal = {Quarterly Journal of the Royal Meteorological Society},
pdf = {https://cerfacs.fr/wp-content/uploads/2016/06/2150_ftp.pdf},
url = {http://onlinelibrary.wiley.com/doi/10.1002/qj.2150/abstract}}
Gratton, S., Gürol, S. and Toint, Ph.-L. (2013) Preconditioning and globalizing conjugate gradients in dual space for quadratically penalized nonlinear-least squares problems, Computational Optimization and Applications, 54 (1) , pp. 1-25, ISSN 0926-6003
[bibtex]
[url]
@ARTICLE{AR-PA-13-28135,
author = {Gratton, S. and Gürol, S. and Toint, Ph.-L. },
title = {Preconditioning and globalizing conjugate gradients in dual space for quadratically penalized nonlinear-least squares problems},
year = {2013},
number = {1},
volume = {54},
pages = {1-25},
issn = {0926-6003},
journal = {Computational Optimization and Applications},
url = {http://dx.doi.org/10.1007/s10589-012-9478-7}}
@CONFERENCE
Destouches, M., Mycek, P., Briant, J., Gürol, S., Weaver, A.T., Gratton, S. and Simon, E. (2022) Multilevel Monte Carlo estimation of background error covariances in ensemble variational data assimilation, EGU General Assembly, Vienna, Austria and online, EGU22-336., 5 2022, doi: 10.5194/egusphere-egu22-336
[bibtex]
[url]
@CONFERENCE{PR-PA-22-64,
author = {Destouches, M. and Mycek, P. and Briant, J. and Gürol, S. and Weaver, A.T. and Gratton, S. and Simon, E. },
title = {Multilevel Monte Carlo estimation of background error covariances in ensemble variational data assimilation},
year = {2022},
month = {5},
booktitle = {EGU General Assembly, Vienna, Austria and online, EGU22-336},
doi = {10.5194/egusphere-egu22-336},
url = {https://meetingorganizer.copernicus.org/EGU22/EGU22-336.html}}
Gürol, S., Peyron , M., Fillion, A., Gratton, S., Boudier, P., Marchais, V. and Goret, G. (2022) Latent Space Data Assimilation - Invited conference, Recent Advances in Numerical Linear Algebra for PDEs, Optimization, and Data Assimilation, ICMS, Bayes Centre, Edinburgh., 4 2022
[bibtex]
@CONFERENCE{PR-PA-22-101,
author = {Gürol, S. and Peyron , M. and Fillion, A. and Gratton, S. and Boudier, P. and Marchais, V. and Goret, G. },
title = {Latent Space Data Assimilation - Invited conference},
year = {2022},
month = {4},
booktitle = {Recent Advances in Numerical Linear Algebra for PDEs, Optimization, and Data Assimilation, ICMS, Bayes Centre, Edinburgh},
keywords = {Invited Speaker}}
Gazaix, A., Gallard, F., Ambert, V., Guénot, D., Hamadi, M., Grihon, S., Sarouille, P., Druot, T., Brézillon, J., Gachelin, V., Plakoo, J., Desfachelles, N., Bartoli, N., Lefebvre, T., Gürol, S., Pauwels, B., Vanaret, C. and Lafage, R. (2019) Industrial Application of an Advanced Bi-level MDO Formulation to Aircraft Engine Pylon Optimization, AIAA 2019-3109. AIAA Aviation 2019 Forum, Dallas, Texas, 6 2019, doi: 10.2514/6.2019-3109
[bibtex] [pdf]
@CONFERENCE{PR-PA-19-230,
author = {Gazaix, A. and Gallard, F. and Ambert, V. and Guénot, D. and Hamadi, M. and Grihon, S. and Sarouille, P. and Druot, T. and Brézillon, J. and Gachelin, V. and Plakoo, J. and Desfachelles, N. and Bartoli, N. and Lefebvre, T. and Gürol, S. and Pauwels, B. and Vanaret, C. and Lafage, R. },
title = {Industrial Application of an Advanced Bi-level MDO Formulation to Aircraft Engine Pylon Optimization},
year = {2019},
month = {6},
booktitle = {AIAA 2019-3109},
organization = {AIAA Aviation 2019 Forum},
address = {Dallas, Texas},
doi = {10.2514/6.2019-3109},
pdf = {https://arc.aiaa.org/doi/10.2514/6.2019-3109}}
Gazaix, A., Gallard, F., Gachelin, V., Druot, T., Grihon, S., Ambert, V., Guénot, D., Lafage, R., Vanaret, C., Pauwels, B., Bartoli, N., Lefebvre, T., Sarouille, P., Desfachelles, N., Brézillon, J., Hamadi, M. and Gürol, S. (2017) Towards the Industrialization of New MDO Methodologies and Tools for Aircraft Design, 18th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, 2017, Denver, Colorado . AIAA AVIATION Forum, Denver, Colorado, USA 2017, doi: 10.2514/6.2017-3149
[bibtex] [pdf]
@CONFERENCE{PR-PA-17-208,
author = {Gazaix, A. and Gallard, F. and Gachelin, V. and Druot, T. and Grihon, S. and Ambert, V. and Guénot, D. and Lafage, R. and Vanaret, C. and Pauwels, B. and Bartoli, N. and Lefebvre, T. and Sarouille, P. and Desfachelles, N. and Brézillon, J. and Hamadi, M. and Gürol, S. },
title = {Towards the Industrialization of New MDO Methodologies and Tools for Aircraft Design},
year = {2017},
booktitle = {18th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, 2017, Denver, Colorado },
publisher = {American Institute of Aeronautics and Astronautics},
series = {AIAA 2017-3149},
pages = {1-23},
isbn = {eISBN: 978-1-62410-507-4},
organization = {AIAA AVIATION Forum},
address = {Denver, Colorado, USA},
doi = {10.2514/6.2017-3149},
pdf = {https://doi.org/10.2514/MMAO17}}
Gürol, S. (2017) Parallelization in the time dimension of geophysical data assimilation problems, PARNUM 2017, International Workshop on Parallel Numerics, Waischenfeld, Germany, 19-21 April, 2017., 4 2017
[bibtex]
@CONFERENCE{PR-PA-17-330,
author = {Gürol, S. },
title = {Parallelization in the time dimension of geophysical data assimilation problems},
year = {2017},
month = {4},
booktitle = {PARNUM 2017, International Workshop on Parallel Numerics, Waischenfeld, Germany, 19-21 April, 2017},
keywords = {invite}}
Gürol, S. (2016) Algorithms for weak-constraint 4D-Var, Météorologie: de l'atmosphère à l'espace - 2. Assimilation de données, Météo-France, Toulouse, 8-9 November 2016., 11 2016
[bibtex]
@CONFERENCE{PR-PA-16-387,
author = {Gürol, S. },
title = {Algorithms for weak-constraint 4D-Var},
year = {2016},
month = {11},
booktitle = {Météorologie: de l'atmosphère à l'espace - 2. Assimilation de données, Météo-France, Toulouse, 8-9 November 2016},
keywords = {invite}}
Gürol, S. (2016) Numerical solution of the time-parallelized weak-constraint 4DVAR, Platform for Advanced Scientific Computing Conference (PASC), Lausanne, Switzerland, 8-10 June 2016., 6 2016
[bibtex]
@CONFERENCE{PR-PA-16-389,
author = {Gürol, S. },
title = {Numerical solution of the time-parallelized weak-constraint 4DVAR},
year = {2016},
month = {6},
booktitle = {Platform for Advanced Scientific Computing Conference (PASC), Lausanne, Switzerland, 8-10 June 2016},
keywords = {invite}}
Gürol, S. (2016) Low rank updates in preconditioning the saddle point systems arising from geophysical inverse problems, Seminar, School of Mathematics of the University of Manchester, UK, May 6 2016., 5 2016
[bibtex]
@CONFERENCE{PR-PA-16-390,
author = {Gürol, S. },
title = {Low rank updates in preconditioning the saddle point systems arising from geophysical inverse problems},
year = {2016},
month = {5},
booktitle = {Seminar, School of Mathematics of the University of Manchester, UK, May 6 2016},
keywords = {invite}}
Gürol, S. (2016) Time-Parallel Algorithms for Variational Data Assimilation, 17th SIAM Conference on Parallel Processing for Scientific Computing, Paris, France, April 12-15, 2016., 4 2016
[bibtex]
@CONFERENCE{PR-PA-16-392,
author = {Gürol, S. },
title = {Time-Parallel Algorithms for Variational Data Assimilation},
year = {2016},
month = {4},
booktitle = {17th SIAM Conference on Parallel Processing for Scientific Computing, Paris, France, April 12-15, 2016},
keywords = {invite}}
Gürol, S. (2015) Numerical solution for a time-parallelized formulation of 4D-Var, Workshop on Meteorological Sensitivity Analysis and Data Assimilation, 1-5 June 2015 Roanoke, West Virginia, USA., 6 2015
[bibtex]
@CONFERENCE{PR-PA-15-83,
author = {Gürol, S. },
title = {Numerical solution for a time-parallelized formulation of 4D-Var},
year = {2015},
month = {6},
booktitle = {Workshop on Meteorological Sensitivity Analysis and Data Assimilation, 1-5 June 2015 Roanoke, West Virginia, USA},
keywords = {invite}}
Gürol, S. (2015) Preconditioning Saddle Point Formulation of the Variational Data Assimilation, ISMP 2015, the 22nd International Symposium on Mathematical Programming, Pittsburgh, PA, U.S.A. 12-17 July., 7 2015
[bibtex]
@CONFERENCE{PR-PA-15-84,
author = {Gürol, S. },
title = {Preconditioning Saddle Point Formulation of the Variational Data Assimilation},
year = {2015},
month = {7},
booktitle = {ISMP 2015, the 22nd International Symposium on Mathematical Programming, Pittsburgh, PA, U.S.A. 12-17 July},
keywords = {invite}}
Gürol, S., Weaver, A.T., Gratton, S., Moore, A.M., Piacentini, A and Arango, H.G. (2013) B-preconditioned minimization algorithm for variational assimilation with the dual formulation 6th WMO international symposium on data assimilation, NCEP, 7-11 october, Washington, USA 2013
[bibtex]
@CONFERENCE{PR-CMGC-13-22014,
author = {Gürol, S. and Weaver, A.T. and Gratton, S. and Moore, A.M. and Piacentini, A and Arango, H.G. },
title = {B-preconditioned minimization algorithm for variational assimilation with the dual formulation},
year = {2013},
organization = {6th WMO international symposium on data assimilation, NCEP, 7-11 october},
address = {Washington, USA}}
Moore, A.M., Edwards, C., Fiechter, J., Drake, P., Arango, H., Neveu, E., Weaver, A.T. and Gürol, S. (2013) A 4d-var analysis system for the california current: a prototypefor an operational regional ocean data assimilation system., Data assimilation for atmospheric, oceanic and hydrologic applicationsvol ii, s.k park and l. xu (eds.) springer. 2013
[bibtex]
@CONFERENCE{PR-CMGC-13-22169,
author = {Moore, A.M. and Edwards, C. and Fiechter, J. and Drake, P. and Arango, H. and Neveu, E. and Weaver, A.T. and Gürol, S. },
title = {A 4d-var analysis system for the california current: a prototypefor an operational regional ocean data assimilation system.},
year = {2013},
booktitle = {Data assimilation for atmospheric, oceanic and hydrologic applicationsvol ii, s.k park and l. xu (eds.) springer}}
Gürol, S., Weaver, A.T., Gratton, S., Moore, A.M., Piacentini, A and Arango, H.G. (2012) B-preconditionned minimization algorithm for variational assimilation with the dual formulation 4eme colloque national sur l'assimilation de données, 17-19 december, Nice, France 2012
[bibtex]
@CONFERENCE{PR-CMGC-12-22015,
author = {Gürol, S. and Weaver, A.T. and Gratton, S. and Moore, A.M. and Piacentini, A and Arango, H.G. },
title = {B-preconditionned minimization algorithm for variational assimilation with the dual formulation},
year = {2012},
organization = {4eme colloque national sur l'assimilation de données, 17-19 december},
address = {Nice, France}}
@TECHREPORT
Diouane, Y., Gürol, S., Mouhtal, O. and Orban, D. (2024) An efficient scaled spectral preconditioner for sequences of symmetric positive definite linear systems, Cerfacs, Technical report
[bibtex] [pdf]
@TECHREPORT{TR-PA-24-134,
author = {Diouane, Y. and Gürol, S. and Mouhtal, O. and Orban, D. },
title = {An efficient scaled spectral preconditioner for sequences of symmetric positive definite linear systems},
year = {2024},
institution = {Cerfacs},
type = {Technical report},
pdf = {https://cerfacs.fr/wp-content/uploads/2024/10/Technical-Report_TR_PA_24_134.pdf}}
Destouches, M., Mycek, P. and Gürol, S. (2023) Multivariate extensions of the Multilevel Best Linear Unbiased Estimator for ensemble-variational data assimilation, Cerfacs, Technical report
[bibtex]
[url] [pdf]
@TECHREPORT{TR-PA-23-67,
author = {Destouches, M. and Mycek, P. and Gürol, S. },
title = {Multivariate extensions of the Multilevel Best Linear Unbiased Estimator for ensemble-variational data assimilation},
year = {2023},
institution = {Cerfacs},
type = {Technical report},
pdf = {https://cerfacs.fr/wp-content/uploads/2023/06/MLBLUE_extensions_TR_PA_23_67.pdf},
url = {https://arxiv.org/abs/2306.07017}}
Diouane, Y., Gürol, S., Scotto di Perrotolo, A. and Vasseur, X. (2022) A general error analysis for randomized low-rank approximation methods, Cerfacs - Toulouse, France, Technical report
[bibtex]
[url]
@TECHREPORT{TR-PA-22-242,
author = {Diouane, Y. and Gürol, S. and Scotto di Perrotolo, A. and Vasseur, X. },
title = {A general error analysis for randomized low-rank approximation methods},
year = {2022},
institution = {Cerfacs - Toulouse, France},
type = {Technical report},
url = {https://arxiv.org/abs/2206.08793}}
Weaver, A.T., Chrust, M., Ménétrier, B., Piacentini, A, Gürol, S., Tshimanga, J., Yang, Y. and Zuo, H. (2018) Using ensemble-estimated background error variances and correlation scales in the NEMOVAR system, Cerfacs TR-PA-18-15, Technical report
[bibtex] [pdf]
@TECHREPORT{TR-PA-18-15,
author = {Weaver, A.T. and Chrust, M. and Ménétrier, B. and Piacentini, A and Gürol, S. and Tshimanga, J. and Yang, Y. and Zuo, H. },
title = {Using ensemble-estimated background error variances and correlation scales in the NEMOVAR system},
year = {2018},
institution = {Cerfacs TR-PA-18-15},
type = {Technical report},
keywords = {data assimilation, variational assimilation, ensemble methods, covariance modelling},
pdf = {https://cerfacs.fr/wp-content/uploads/2018/01/TR-PA-18-15.pdf},
supplementaryMaterial = {https://cerfacs.fr/wp-content/uploads/2018/10/TR-PA-18-15.pdf}}
Weaver, A.T., Gürol, S., Tshimanga, J., Chrust, M. and Piacentini, A (2017) Time-parallel diffusion-based correlation operators, CERFACS TR-PA-17-119, Technical report
[bibtex] [pdf]
@TECHREPORT{TR-PA-17-119,
author = {Weaver, A.T. and Gürol, S. and Tshimanga, J. and Chrust, M. and Piacentini, A },
title = {Time-parallel diffusion-based correlation operators},
year = {2017},
institution = {CERFACS TR-PA-17-119},
type = {Technical report},
abstract = {Correlation operators based on the solution of an implicitly formulated diffusion equation can be implemented numerically using the Chebyshev iteration method.
The attractive properties of the algorithm for modelling correlation functions on high-performance computers have been discussed in a recent paper. The current paper describes a straightforward variant of that algorithm that allows the matrix-vector products involved in the sequential pseudo-time diffusion process to be performed in parallel.
Contrary to the original algorithm, which requires solving a sequence of linear systems involving a symmetric positive-definite (SPD) matrix, the ``time''-parallel algorithm requires solving a single linear system involving a nonsymmetric positive-definite (NSPD) matrix.
The key information required by the Chebyshev iteration for solving the NSPD problem is an estimate of the extreme eigenvalues of the NSPD matrix. For the problem under consideration, the extreme eigenvalues of the NSPD matrix are the same as those of the original SPD matrix, and can be pre-computed using a Lanczos algorithm.
The convergence properties of the algorithm are studied from a theoretical perspective and using numerical experiments with a diffusion-based covariance model employed with a variational data assimilation system for the global ocean. Results suggest that time-parallelization can reduce the run-time of an implicit diffusion-based correlation operator by greater than a factor of two.
It can be implemented practically using a hybrid parallelization approach that combines MPI tasks in the spatial domain with OpenMP threads spanning the pseudo-time dimension.
The sensitivity of the results to preconditioning, to the choice of first guess and to the stopping criterion is discussed.},
keywords = {correlation functions, covariance modelling, background error, Chebyshev iteration, time parallelization, nonsymmetric linear solver, variational assimilation, ocean data assimilation},
pdf = {https://cerfacs.fr/wp-content/uploads/2017/08/TR-PA-17-119.pdf},
supplementaryMaterial = {https://cerfacs.fr/wp-content/uploads/2018/10/TR-PA-17-119.pdf}}
Fisher, M. and Gürol, S. (2016) Parallelisation in the Time Dimension of Four-Dimensional Variational Data Assimilation, Cerfacs, Technical report
[bibtex]
@TECHREPORT{TR-PA-16-189,
author = {Fisher, M. and Gürol, S. },
title = {Parallelisation in the Time Dimension of Four-Dimensional Variational Data Assimilation},
year = {2016},
institution = {Cerfacs},
month = {8},
type = {Technical report},
abstract = {The current evolution of computer architectures towards increasing parallelism requires a corresponding evolution towards more parallel data assimilation algorithms.
In this paper, we consider parallelisation of weak-constraint 4D-Var in the time dimension. We categorise algorithms according to whether or not they admit such parallelisation, and we introduce a new, highly parallel weak-constraint 4D-Var algorithm based on a saddle-point representation of the underlying optimisation problem.},
keywords = {4D-Var, Data Assimilation, Parallel Algorithms, Saddle point methods}}
Gürol, S., Weaver, A.T., Moore, A.M., Piacentini, A, Arango, H.G. and Gratton, S. (2012) ${B}$-preconditioned minimization algorithms with the dual formulation, Cerfacs, Toulouse, France, Technical report
[bibtex]
[url]
@TECHREPORT{TR-PA-12-20311,
author = {Gürol, S. and Weaver, A.T. and Moore, A.M. and Piacentini, A and Arango, H.G. and Gratton, S. },
title = {${B}$-preconditioned minimization algorithms with the dual formulation},
year = {2012},
institution = {{Cerfacs}, Toulouse, France},
type = {Technical report},
url = {https://cerfacs.fr/algor/reports/2012/TR_PA_12_118.pdf}}
Gürol, S., Weaver, A.T., Moore, A.M., Piacentini, A, Arango, H.G. and Gratton, S. (2012) B-preconditioned minimization algorithms for variationnal data assimilation using the dual-space formulation, URA SUC 1875, CERFACS-CNRS, TR-CMGC-12-22017, Technical report
[bibtex]
@TECHREPORT{TR-CMGC-12-22017,
author = {Gürol, S. and Weaver, A.T. and Moore, A.M. and Piacentini, A and Arango, H.G. and Gratton, S. },
title = {B-preconditioned minimization algorithms for variationnal data assimilation using the dual-space formulation},
year = {2012},
institution = {URA SUC 1875, CERFACS-CNRS, TR-CMGC-12-22017},
address = {Toulouse, France},
type = {Technical report}}
Gratton, S., Gürol, S. and Toint, Ph.-L. (2010) Preconditioning and globalizing conjugate gradients in dual space for quadratically penalized nonlinear-least squares problems, Cerfacs, Toulouse, France, Technical report
[bibtex]
[url]
@TECHREPORT{TR-PA-10-20330,
author = {Gratton, S. and Gürol, S. and Toint, Ph.-L. },
title = {Preconditioning and globalizing conjugate gradients in dual space for quadratically penalized nonlinear-least squares problems},
year = {2010},
institution = {{Cerfacs}, Toulouse, France},
type = {Technical report},
url = {https://cerfacs.fr/algor/reports/2010/TR_PA_10_136.pdf}}
