Portrait of Long Li

Long Li

Postdoctoral Researcher · CNRS · Inria · Université Côte d'Azur, France

long.li@univ-cotedazur.fr long.li@inria.fr CV Google Scholar ORCID GitHub LinkedIn

Research

I am an applied mathematician working at the interface of stochastic modeling and scientific computing. My research develops mathematically grounded and computationally efficient methods for simulating high-dimensional nonlinear systems under uncertainty, combining mathematical derivation, numerical methods, high-performance computing and statistical analysis. Since my PhD, I have concentrated on stochastic approaches to geophysical fluid dynamics and turbulence, with a particular emphasis on reliable ensemble forecasting systems.

Ensemble of global ocean simulations: individual members, their mean and their spread
Stochastic Modeling Uncertainty Quantification Data Assimilation Numerical Methods Geophysical Fluid Dynamics Turbulence

Experience

Education

Students

PhD students

Francesco Tucciarone (2021–2024)

Co-advised with Etienne Mémin (Inria) · defended 10 April 2024 · now Research Engineer at Inria

Stochastic parametrization of ocean models through high-resolution observations.

Thesis

Master's students

Antoine Guines (INSA Rouen, 2024)

Co-advised with Etienne Mémin (Inria)

Numerical study of a stochastic ocean model in the Mediterranean configuration.

Publications

Submitted preprints

  • 2026
    Simulating passive scalar advection in rough Kraichnan flows L. Li, A. L. P. Considéra, S. Thalabard arXiv preprint, arXiv:2608.29321 arXiv PDF Code Data

Journal articles

  • 2025
    A generalized stochastic formulation of the Ekman–Stokes model with statistical analyses L. Li, E. Mémin, B. Chapron J. Phys. Oceanogr., 55, 1389–1407 DOI PDF Code
  • 2025
    Derivation and numerical assessment of a stochastic large-scale hydrostatic primitive model F. Tucciarone, L. Li, E. Mémin, P. Chandramouli J. Adv. Model. Earth Syst., 17, e2024MS004783 DOI PDF Code Data
  • 2025
    Link between stochastic grid perturbation and location uncertainty framework S. Clement, E. Blayo, L. Debreu, J.-M. Brankart, P. Brasseur, L. Li, E. Mémin J. Adv. Model. Earth Syst., 17, e2024MS004528 DOI PDF Code Data
  • 2024
    A unified formulation of quasi-geostrophic and shallow water equations via projection L. Thiry, L. Li, E. Mémin, G. Roullet J. Adv. Model. Earth Syst., 16, e2024MS004510 DOI PDF Code
  • 2024
    MQGeometry-1.0: a multi-layer quasi-geostrophic solver on non-rectangular geometries L. Thiry, L. Li, G. Roullet, E. Mémin Geosci. Model Dev., 17, 1749–1764 DOI PDF Code
  • 2023
    Stochastic data-driven parameterization of unresolved eddy effects in a baroclinic quasi-geostrophic model L. Li, B. Deremble, N. Lahaye, E. Mémin J. Adv. Model. Earth Syst., 15, e2022MS003297 DOI PDF Code Data
  • 2021
    Rotating shallow water flow under location uncertainty with a structure-preserving discretization R. Brecht, L. Li, W. Bauer, E. Mémin J. Adv. Model. Earth Syst., 13, e2021MS002492 DOI PDF Code Data
  • 2021
    New trends in ensemble forecast strategy: uncertainty quantification for coarse-grid computational fluid dynamics V. Resseguier, L. Li, G. Jouan, P. Dérian, E. Mémin, B. Chapron Arch. Computat. Methods Eng., 28, 215–261 DOI PDF Code
  • 2020
    Stochastic representation of mesoscale eddy effects in coarse-resolution barotropic models W. Bauer, P. Chandramouli, L. Li, E. Mémin Ocean Model., 151, 101646 DOI PDF
  • 2020
    Deciphering the role of small-scale inhomogeneity on geophysical flow structuration: a stochastic approach W. Bauer, P. Chandramouli, B. Chapron, L. Li, E. Mémin J. Phys. Oceanogr., 50, 983–1003 DOI PDF
  • 2020
    Global sensitivity analysis for models described by stochastic differential equations P. Étoré, C. Prieur, D. K. Pham, L. Li Methodol. Comput. Appl. Probab., 22, 803–831 DOI PDF

Book chapters

  • 2026
    A stochastic Ekman–Stokes model for coupled ocean–wave–atmosphere dynamics L. Li, E. Mémin, B. Chapron In: B. Chapron et al. (eds), Stochastic Transport in Upper Ocean Dynamics IV, Mathematics of Planet Earth 15, 105–131, Springer, Cham DOI PDF Code
  • 2025
    Transport noise defined from wavelet transform for model-based stochastic ocean models F. Tucciarone, L. Li, E. Mémin, L. Thiry In: B. Chapron et al. (eds), Stochastic Transport in Upper Ocean Dynamics III, Mathematics of Planet Earth 13, 287–303, Springer, Cham DOI PDF
  • 2024
    Linear wave solutions of a stochastic shallow water model E. Mémin, L. Li, N. Lahaye, G. Tissot, B. Chapron In: B. Chapron et al. (eds), Stochastic Transport in Upper Ocean Dynamics II, Mathematics of Planet Earth 11, 223–245, Springer, Cham DOI PDF Code
  • 2024
    Data-driven stochastic primitive equations with dynamic mode decomposition F. Tucciarone, E. Mémin, L. Li In: B. Chapron et al. (eds), Stochastic Transport in Upper Ocean Dynamics II, Mathematics of Planet Earth 11, 321–336, Springer, Cham DOI PDF
  • 2024
    Toward a stochastic parameterization for oceanic deep convection Q. Jamet, E. Mémin, F. Dumas, L. Li, P. Garreau In: B. Chapron et al. (eds), Stochastic Transport in Upper Ocean Dynamics II, Mathematics of Planet Earth 11, 143–157, Springer, Cham DOI PDF
  • 2023
    Stochastic parameterization with dynamic mode decomposition L. Li, E. Mémin, G. Tissot In: B. Chapron et al. (eds), Stochastic Transport in Upper Ocean Dynamics, Mathematics of Planet Earth 10, 179–193, Springer, Cham DOI PDF Code
  • 2023
    Modified (hyper-)viscosity for coarse-resolution ocean models L. Thiry, L. Li, E. Mémin In: B. Chapron et al. (eds), Stochastic Transport in Upper Ocean Dynamics, Mathematics of Planet Earth 10, 273–285, Springer, Cham DOI PDF Code
  • 2023
    Primitive equations under location uncertainty: analytical description and model development F. Tucciarone, E. Mémin, L. Li In: B. Chapron et al. (eds), Stochastic Transport in Upper Ocean Dynamics, Mathematics of Planet Earth 10, 287–300, Springer, Cham DOI PDF
  • 2023
    A two-step numerical scheme in time for surface quasi-geostrophic equations under location uncertainty C. Fiorini, P.-M. Boulvard, L. Li, E. Mémin In: B. Chapron et al. (eds), Stochastic Transport in Upper Ocean Dynamics, Mathematics of Planet Earth 10, 57–67, Springer, Cham DOI PDF

Presentations

Conferences & workshops

  • Oct 2026
    Data-driven stochastic parameterization for unresolved ocean dynamics Workshop Machine Learning + Simulation · Laboratoire J.-A. Dieudonné, Nice, France Slides
  • Jun 2026
    Numerical study of passive scalar advection by turbulent random flows Journées des GDR « Mécanique des Fluides Géophysiques et Astrophysiques » et « Navier-Stokes 2.00 » · Toulouse, France Slides
  • Sep 2025
    Stochastic approaches to air–sea boundary layer dynamics 6th STUOD Annual Workshop · ICMS, The Bayes Centre, Edinburgh, UK Slides
  • Oct 2024
    A stochastic formulation of the Ekman–Stokes model Atelier sur la représentation des fines échelles océaniques dans les simulations numériques · Ifremer, Plouzané, France Slides
  • Sep 2024
    A generalized stochastic formulation of the Ekman–Stokes model with statistical analyses 5th STUOD Annual Workshop · Inria Rennes, France Slides
  • Sep 2023
    Uncertainty quantification of mesoscale air–sea interaction under transport noise 4th STUOD Annual Workshop · Ifremer, Plouzané, France Slides
  • Mar 2023
    Linear wave solutions of a stochastic shallow water model 22nd STUOD Sandbox Workshop · Online Slides
  • Sep 2022
    Stochastic transport in an idealized ocean–atmosphere coupled model 3rd STUOD Annual Workshop · Imperial College London, UK Slides
  • May 2022
    Stochastic transport in an idealized ocean–atmosphere coupled system EGU General Assembly · Vienna, Austria Slides
Earlier presentations (2019–2021)
  • Nov 2021
    Numerically modelling location uncertainty in geophysical fluid dynamics 11th STUOD Sandbox Workshop · Online Slides
  • Sep 2021
    Statistically data-driven modelling location uncertainty in mesoscale dynamics 2nd STUOD Annual Workshop · Online Slides
  • Apr 2021
    Stochastic modeling of mesoscale eddies EGU General Assembly · Online Slides
  • Feb 2021
    Stochastic modeling of the oceanic mesoscale eddies 6th STUOD Sandbox Workshop · Online Slides
  • Sep 2020
    Stochastic modeling of the oceanic mesoscale eddies 1st STUOD Annual Workshop · Online Slides
  • Sep 2020
    Rotating shallow water flow under location uncertainty 3rd STUOD Sandbox Workshop · Online Slides
  • Sep 2019
    Stochastic modeling of mesoscale eddies in oceanic dynamics Workshop on Frontiers of Uncertainty Quantification in Fluid Dynamics · Pisa, Italy Slides
  • Jul 2019
    Stochastic modeling of mesoscale eddies in barotropic wind-driven circulation Workshop on Stochastic Parameterizations and Their Use in Data Assimilation · Imperial College London, UK Poster
  • Apr 2019
    Oceanic dynamics under location uncertainty — towards a consistent stochastic modeling Workshop on Conservation Principles, Data and Uncertainty in Atmosphere–Ocean Modeling · Potsdam, Germany Slides

Invited seminars

  • Mar 2025
    Stochastic modeling in geophysical fluid dynamics ANGE Project-Team · Inria Paris, France Slides
  • Oct 2024
    Stochastic modeling in geophysical fluid dynamics CALISTO Project-Team · Inria Sophia-Antipolis, France Slides
  • Sep 2024
    Stochastic modeling in geophysical fluid dynamics Research Center for Mathematics and Interdisciplinary Sciences · Shandong University, Qingdao, China Slides
  • Nov 2022
    Stochastic transport in an idealized ocean–atmosphere coupled model AIRSEA Project-Team · Inria Grenoble, France Slides