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Engineering and Technology

D-Index
52
Citations
9641
World Ranking
3650
National Ranking
63

Overview

Marc Bocquet is affiliated with the École des Ponts ParisTech in France. Their research spans multiple fields of study, with a focus on Earth and Planetary Sciences and Environmental Science. Within these broad areas, they concentrate on subfields including Atmospheric Science, Global and Planetary Change, Electrical and Electronic Engineering, Environmental Engineering, and Artificial Intelligence.

The main topics in their work include Meteorological Phenomena and Simulations, Climate Variability and Models, Atmospheric and Environmental Gas Dynamics, Model Reduction and Neural Networks, Arctic and Antarctic Ice Dynamics, Advanced Memory and Neural Computing, and Wind and Air Flow Studies.

Marc Bocquet's recent publications reflect these research interests. Notable papers include:

  • "Pushing the frontiers in climate modelling and analysis with machine learning," 2024, published in Nature Climate Change
  • "Machine Learning With Data Assimilation and Uncertainty Quantification for Dynamical Systems: A Review," 2023, published in IEEE/CAA Journal of Automatica Sinica
  • "Combining data assimilation and machine learning to infer unresolved scale parametrization," 2021, published in Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences
  • "Using machine learning to correct model error in data assimilation and forecast applications," 2021, published in Quarterly Journal of the Royal Meteorological Society
  • "A Review of Innovation-Based Methods to Jointly Estimate Model and Observation Error Covariance Matrices in Ensemble Data Assimilation," 2020, published in Monthly Weather Review

The venues where Marc Bocquet frequently publishes demonstrate their engagement with leading journals and repositories in their fields. These include arXiv (Cornell University), Geoscientific Model Development, Quarterly Journal of the Royal Meteorological Society, The Cryosphere, and Journal of Advances in Modeling Earth Systems.

Collaborative work is a significant part of their career, with frequent co-authors including Alban Farchi, Alberto Carrassi, Tobias Sebastian Finn, Joffrey Dumont Le Brazidec, and Julien Brajard.

Best Publications

  • Data assimilation in the geosciences: An overview of methods, issues, and perspectives

    Alberto Carrassi;Marc Bocquet;Laurent Bertino;Geir Evensen

  • Real-time air quality forecasting, part I: History, techniques, and current status

    Yang Zhang;Yang Zhang;Marc Bocquet;Marc Bocquet;Vivien Mallet;Vivien Mallet;Christian Seigneur

  • On the representation error in data assimilation

    T. Janjic;N. Bormann;M. Bocquet;J. A. Carton

  • Data Assimilation: Methods, Algorithms, and Applications

    Mark Asch;Marc Bocquet;Maëlle Nodet

  • Data assimilation in atmospheric chemistry models: current status and future prospects for coupled chemistry meteorology models

    M. Bocquet;M. Bocquet;H. Elbern;H. Eskes;M. Hirtl

  • Beyond Gaussian Statistical Modeling in Geophysical Data Assimilation

    Marc Bocquet;Carlos A. Pires;Lin Wu

  • Combining data assimilation and machine learning to emulate a dynamical model from sparse and noisy observations: a case study with the Lorenz 96 model

    Julien Brajard;Alberto Carrassi;Marc Bocquet;Laurent Bertino

  • Rotating neutron star models with a magnetic field.

    M. Bocquet;S. Bonazzola;E. Gourgoulhon;J. Novak

  • Real-time air quality forecasting, part II: State of the science, current research needs, and future prospects

    Yang Zhang;Marc Bocquet;Vivien Mallet;Christian Seigneur

  • An iterative ensemble Kalman smoother

    Marc Bocquet;Marc Bocquet;Pavel Sakov

  • An inverse modeling method to assess the source term of the Fukushima Nuclear Power Plant accident using gamma dose rate observations

    Olivier Saunier;Anne Mathieu;Damien Didier;Marilyne Tombette

  • Combining data assimilation and machine learning to infer unresolved scale parametrization

    Julien Brajard;Alberto Carrassi;Marc Bocquet;Laurent Bertino

  • Estimation of Errors in the Inverse Modeling of Accidental Release of Atmospheric Pollutant: Application to the Reconstruction of the Cesium-137 and Iodine-131 Source Terms from the Fukushima Daiichi Power Plant

    Victor Winiarek;Victor Winiarek;Marc Bocquet;Marc Bocquet;Olivier Saunier;Anne Mathieu

  • Disordered 2d quasiparticles in class D: Dirac fermions with random mass, and dirty superconductors

    M. Bocquet;D. Serban;M.R. Zirnbauer

  • Using machine learning to correct model error in data assimilation and forecast applications

    Alban Farchi;Patrick Laloyaux;Massimo Bonavita;Marc Bocquet

  • What eddy-covariance measurements tell us about prior land flux errors in CO2-flux inversion schemes

    Frédéric Chevallier;Tao Wang;Philippe Ciais;Fabienne Maignan

  • Bayesian inference of chaotic dynamics by merging data assimilation, machine learning and expectation-maximization

    Marc Bocquet;Julien Brajard;Alberto Carrassi;Laurent Bertino

  • Finite-temperature dynamical magnetic susceptibility of quasi-one-dimensional frustrated spin- 1 2 Heisenberg antiferromagnets

    Marc Bocquet;Fabian H. L. Essler;Alexei M. Tsvelik;Alexander O. Gogolin

  • A review of innovation-based methods to jointly estimate model and observation error covariance matrices in ensemble data assimilation

    Pierre Tandeo;Pierre Ailliot;Marc Bocquet;Alberto Carrassi;Alberto Carrassi

  • A Comparison Study of Data Assimilation Algorithms for Ozone Forecasts

    Lin Wu;Lin Wu;Vivien Mallet;Vivien Mallet;Marc Bocquet;Marc Bocquet;Bruno Sportisse;Bruno Sportisse

  • Estimation of the caesium-137 source term from the Fukushima Daiichi nuclear power plant using a consistent joint assimilation of air concentration and deposition observations

    Victor Winiarek;Marc Bocquet;Nora Duhanyan;Yelva Roustan

  • Estimation of errors in the inverse modeling of accidental release of atmospheric pollutant: Application to the reconstruction of the cesium-137 and iodine-131 source terms from the Fukushima Daiichi power plant: ESTIMATION OF ERRORS IN INVERSE MODELING

    Victor Winiarek;Marc Bocquet;Olivier Saunier;Anne Mathieu

  • Data Assimilation in the Geosciences - An overview on methods, issues and perspectives.

    Alberto Carrassi;Marc Bocquet;Laurent Bertino;Geir Evensen

Frequent Co-Authors

Laurent Bertino
Laurent Bertino Bjerknes Centre for Climate Research
Michael Ghil
Michael Ghil École Normale Supérieure
Thomas Lauvaux
Thomas Lauvaux Pennsylvania State University
F. Chevallier
F. Chevallier University of Paris-Saclay
Patrick Chazette
Patrick Chazette French Alternative Energies and Atomic Energy Commission (CEA)
Kenneth J. Davis
Kenneth J. Davis Pennsylvania State University
Christopher K. R. T. Jones
Christopher K. R. T. Jones University of North Carolina at Chapel Hill
Geir Evensen
Geir Evensen NORCE Research
Mikhail Sofiev
Mikhail Sofiev Finnish Meteorological Institute
Alexander Baklanov
Alexander Baklanov University of Copenhagen

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