Selected publications
[1] Darryl D Holm and Boris A Kupershmidt. Poisson brackets and Clebsch representations for magnetohydrodynamics, multifluid plasmas, and elasticity. Physica D: Nonlinear Phenomena 6.3 (1983), pp. 347–363.
[2] Darryl D Holm, Jerrold E Marsden, Tudor Ratiu, and Alan Weinstein. Nonlinear stability of fluid and plasma equilibria. Physics Reports 123.1-2 (1985), pp. 1–116.
[3] Darryl D Holm, Jerrold E Marsden, and Tudor S Ratiu. The Euler–Poincaré Equations and Semidirect Products with Applications to Continuum Theories. Advances in Mathematics 137.1 (1998), pp. 1–81.
[4] Darryl D Holm, Euler-Poincare dynamics of perfect complex fluids. In: Geometry, mechanics, and dynamics, edited by P. Newton, P. Holmes and A. Weinstein. Springer, pp. 113-167 (2002).
[5] Roberto Camassa and Darryl D Holm. An integrable shallow water equation with peaked solitons. Physical Review Letters 71.11 (1993), p. 1661.
[6] Antonio Degasperis, Darryl D Holm, and Andrew NW Hone. A new integrable equation with peakon solutions. Theoretical and Mathematical Physics 133.2 (2002), pp. 1463–1474.
[7] Darryl D Holm and Jerrold E Marsden. Momentum maps and measure-valued solutions (peakons, filaments, and sheets) for the EPDiff equation. The breadth of symplectic and Poisson geometry. Springer, 2005, pp. 203– 235.
[8] Darryl D Holm, J Tilak Ratnanather, Alain Trouvé, and Laurent Younes. Soliton dynamics in computational anatomy. NeuroImage 23 (2004), S170–S178.
[9] Martins Bruveris, François Gay-Balmaz, Darryl D. Holm, and Tudor S. Ratiu. The momentum map representation of images. Journal of Nonlinear Science 21.1 (2011), pp. 115–150.
[10] Shiyi Chen, Ciprian Foias, Darryl D Holm, Eric Olson, Edriss S Titi, and Shannon Wynne. Camassa-Holm equations as a closure model for turbulent channel and pipe flow. Physical Review Letters 81.24 (1998), p. 5338.
[11] Ciprian Foias, Darryl D Holm, and Edriss S Titi. The three dimensional viscous Camassa–Holm equations, and their relation to the Navier–Stokes equations and turbulence theory. Journal of Dynamics and Differential Equations 14.1 (2002), pp. 1–35.
[12] Bernard J Geurts and Darryl D Holm. Leray and LANS-α modelling of turbulent mixing. Journal of Turbulence 7 (2006), N10. (WP2) [13] Darryl D Holm and Vakhtang Putkaradze. Aggregation of finite-size particles with variable mobility. Physical Review Letters 95.22 (2005), p. 226106.
[14] Ildar Gabitov, Darryl D Holm, Arnold Mattheus, and Benjamin P Luce. Recovery of solitons with nonlinear amplifying loop mirrors. Optics Letters 20.24 (1995), pp. 2490–2492.
[15] Daniel David, Darryl D Holm, and MV Tratnik. Hamiltonian chaos in nonlinear optical polarization dynamics. Physics Reports 187.6 (1990), pp. 281–367.
[16] Gennady P Berman, Gary D Doolen, Darryl D Holm, and Vladimir I Tsifrinovich. Quantum computer on a class of one-dimensional Ising systems. Physics Letters A 193.5-6 (1994), pp. 444–450.
[17] Darryl D Holm and Peter Lynch. Stepwise precession of the resonant swinging spring. SIAM Journal on Applied Dynamical Systems 1.1 (2002), 44–64 (electronic).
[18] RH Cushman, HR Dullin, A Giacobbe, DD Holm, M Joyeux, P Lynch, DA Sadovskii, BI Zhilinskiı. CO2 molecule as a quantum realization of the 1:1:2 resonant swing-spring with monodromy. Physical Review Letters 93.2 (2004), p. 024302.
[19] Darryl D Holm. Variational principles for stochastic fluid dynamics. Proceedings of the Royal Society of London A: Mathematical, Physical and Engineering Sciences 471.2176 (2015).
[20] Dan Crisan, Franco Flandoli, and Darryl D. Holm. Solution properties of a 3D stochastic Euler fluid equation. Online at J Nonlinear Science, Preprint at arXiv:1704.06989 (2017).
[21] C. J. Cotter, G. A. Gottwald, and D. D. Holm, Stochastic partial differential fluid equations as a diffusive limit of deterministic Lagrangian multi-time dynamics, Proc Roy Soc A, 473: 20170388. Preprint at arXiv:1706.00287.
[22] Darryl D. Holm, YoungStatS: Transport Noise in Fluid Dynamics, IMS Bulletin, Vol. 53, issue 2 (2024); Available at: Institute of Mathematical Statistics | YoungStatS: Transport Noise in Fluid Dynamics (imstat.org)
Google Scholar, ORCID and arXiv pages:
Prof Darryl Holm:
[1] V. Resseguier, E. Mémin, D. Heitz and B. Chapron, Stochastic modeling and diffusion modes for POD models and small-scale flow analysis, Journ. of Fluid Mech., 828, 888-917, 2017.
[2] V. Resseguier, E. Mémin, B. Chapron, Geophysical flows under location uncertainty, Part I: Random transport and general models, Geophysical & Astrophysical Fluid Dynamics, 111(3): 149-176, 2017.
[3] V. Resseguier, E. Mémin, B. Chapron, Geophysical flows under location uncertainty, Part II: Quasigeostrophic models and efficient ensemble spreading, Geophysical & Astrophysical Fluid Dynamics, acceptepublication, 111(3): 177-208, 2017
[4] V. Resseguier, E. Mémin, B. Chapron, Geophysical flows under location uncertainty, Part III: SQG and frontal dynamics under strong turbulence, Geophysical & Astrophysical Fluid Dynamics, accepted for publication, 111(3): 209-227, 2017
[5] B. Chapron, P. Derain, E. Mémin, V. Resseguier, Large scale flows under location uncertainty: a consistent stocahstic framework, Q. J. Roy. Met. Soc., 144(710), 251-260, 2018
[6] F. Ardhuin et al., Measuring currents, ice drift, and waves from Space: the Sea surface Kinematics Multiscale monitoring (SKIM) concept, Ocean Science, 14(3), 337-354, 2018
[7] Rascle, N., J. Molemaker, L. Marié, F. Nouguier, B. Chapron, B. Lund, and A. Mouche,, Intense deformation field at oceanic front inferred from directional sea surface roughness observations, Geophys. Res. Lett., 44, 5599–5608, 2017
[8] Ardhuin, F., S. T. Gille, D. Menemenlis, C. B. Rocha, N. Rascle, B. Chapron, J. Gula, and J. Molemaker, Small-scale open ocean currents have large effects on wind wave heights, J. Geophys. Res. Oceans, 122, 4500– 4517, 2017
[9] Kudryavtsev, V., M. Yurovskaya, B. Chapron, F. Collard, and C. Donlon, Sun glitter imagery of surface waves. Part 2: Waves transformation on ocean currents, J. Geophys. Res. Oceans, 122, 1384–1399, 2017
[10] Rascle N., F. Nouguier, B. Chapron, A. Mouche and A. Ponte, Surface roughness changes by fine scale current gradients: Properties at multiple azimuth view angles, Journal of Physical Oceanography , 46(12), 368136942014, 2016.
[11] Rascle N., Chapron B., Ponte A., Ardhuin F. and P. Klein, Surface Roughness Imaging of Currents Shows Divergence and Strain in the Wind Direction, Journal of Physical Oceanography, 44(8), 2153-2163, 2014.
[12] Kudryavtsev, V., B. Chapron, and V. Makin, Impact of wind waves on the air-sea fluxes: A coupled model, J. Geophys. Res. Oceans, 119, 1217–1236, 2014.
[13] Ponte A, Klein P., Capet Xavier, Le Traon P.-Y., Chapron B., Lherminier P., Diagnosing Surface Mixed Layer Dynamics from High-Resolution Satellite Observations: Numerical Insights, Journal of Physical Oceanography, 43(7), 1345-1355, 2013
[14] Kudryavtsev, V., A. Myasoedov, B. Chapron, J. A. Johannessen, and F. Collard, Imaging mesoscale upper ocean dynamics using synthetic aperture radar and optical data, J. Geophys. Res., 117, C04029, 2012
[15] Collard, F., F. Ardhuin, and B. Chapron, Monitoring and analysis of ocean swell fields from space: New methods for routine observations, J. Geophys. Res., 114, C07023, 2009
[16] Ardhuin, F., B. Chapron, and F. Collard, Observation of swell dissipation across oceans, Geophys. Res. Lett., 36, L06607, 2009.
[17] Isern-Fontanet, J., B. Chapron, G. Lapeyre, and P. Klein, Potential use of microwave sea surface temperatures for the estimation of ocean currents, Geophys. Res. Lett., 33, L24608, 2006
[18] Chapron, B., F. Collard, and F. Ardhuin, Direct measurements of ocean surface velocity from space: Interpretation and validation, J. Geophys. Res., 110, C07008, 2005
Research Gate link
Prof Bertrand Chapron
- O Lang, D. Crisan, Dan; É. Mémin, Analytical properties for a stochastic rotating shallow water model under location uncertainty, J. Math. Fluid Mech. 25, no. 2, 2023.
- D Crisan, M Ghil, Asymptotic behavior of the forecast–assimilation process with unstable dynamics, Chaos: An Interdisciplinary Journal of Nonlinear Science 33 (2), 1. 2023.
- D Crisan, O Lang, Well-posedness Properties for a Stochastic Rotating Shallow Water Model, Journal of Dynamics and Differential Equations, 1-31, 6, 2023
- D Crisan, DD Holm, E Luesink, PR Mensah, W Pan, Theoretical and computational analysis of the thermal quasi-geostrophic model, Journal of Nonlinear Science 33 (5), 96, 8, 2023.
- D. Crisan, D.D. Holm, O. Lang, P.R. Mensah, W. Pan, Theoretical analysis and numerical approximation for the stochastic thermal quasi-geostrophic model, Stochastics and Dynamics, 2023.
- D Crisan, DD Holm, P Korn, An implementation of Hasselmann’s paradigm for stochastic climate modelling based on stochastic Lie transport, Nonlinearity 36 (9), 4862, 2023.
- Lang, D Crisan, Well-posedness for a stochastic 2D Euler equation with transport noise, Stochastics and Partial Differential Equations: Analysis and Computations 11, 13, 2023.
- O Lang, PJ Van Leeuwen, D Crisan, R Potthast, Bayesian inference for fluid dynamics: a case study for the stochastic rotating shallow water model, Frontiers in Applied Mathematics and Statistics 8, 949354, 3, 2022.
- D Crisan, OD Street, On the analytical aspects of inertial particle motion, Journal of Mathematical Analysis and Applications 516 (1), 2022.
- D Crisan, DD Holm, JM Leahy, T Nilssen, Variational principles for fluid dynamics on rough paths, Advances in Mathematics 404, 108409, 10, 2022
- D Crisan, DD Holm, JM Leahy, T Nilssen, Solution properties of the incompressible Euler system with rough path advection, Journal of Functional Analysis 283 (9), 10963, 2, 2022.
- B Dufée, E Mémin, D Crisan, Stochastic parametrization: an alternative to inflation in Ensemble Kalman filters, Quarterly Journal of the Royal Meteorological Society 148 (744), 1075-1091, 3, 2022.
- O Lang, D Crisan, Well-posedness for a stochastic 2D Euler equation with transport noise, Stochastics and Partial Differential Equations: Analysis and Computations, 1-45, 2. 2022.
- D Crisan, O Lang, Local well-posedness for the great lake equation with transport noise, Rev Roumaine Math. Pures Appl. 66, 1, 131–155, 2021.
- D Crisan, DD Holm, OD Street, Wave–current interaction on a free surface, Studies in Applied Mathematics 147 (4), 1277-1338, 3, 2021.
- OD Street, D Crisan, Semi-martingale driven variational principles, Proceedings of the Royal Society A 477 (2247), 20200957 23, 2021.
- C Cotter, D Crisan, DD Holm, W Pan, I Shevchenko, A particle filter for stochastic advection by Lie transport: a case study for the damped and forced incompressible two-dimensional Euler equation, SIAM/ASA Journal on Uncertainty Quantification 8 (4), 1446-1492, 31, 2020.
- C Cotter, D Crisan, D Holm, W Pan, I Shevchenko, Data assimilation for a quasi-geostrophic model with circulation-preserving stochastic transport noise, Journal of Statistical Physics, 1-36, 2020
- D Crisan, F Flandoli, DD Holm, Solution properties of a 3D stochastic Euler fluid equation, Journal of Nonlinear Science 29 (3), 813-870, 60, 2019.
- C Cotter, D Crisan, DD Holm, W Pan, I Shevchenko, Numerically modeling stochastic Lie transport in fluid dynamics, Multiscale Modeling & Simulation 17 (1), 192-232, 27, 2019
- D Crisan, DD Holm, Wave breaking for the Stochastic Camassa–Holm equation, Physica D: Nonlinear Phenomena 376, 138-143, 2018.
Google Scholar, ORCID and arXiv pages:
Prof Dan Crisan:
[1] Cai, S., Mémin, E., Dérian, P., Chao, X., (2018), Motion estimation under location uncertainty for turbulent flows, accepted for publication, Exp. In Fluids, 59(8). Use of stochastic transport equation to devise a parameter free accurate fluid motion estimator.
[2] Chapron, B., Dérian, P., Mémin, E., Resseguier, V., (2018), Large-scale flows under location uncertainty: a consistent stochastic framework, Quart. J. of Roy. Meteo. Soc., 144: 251 – 260. Derivation of a stochastic Lorenz-63 system though Holm-Mémin paradigm; demonstration of the relevance of the Holm-Memin theory in comparison with ad hoc forcing schemes.
[3] S. Kadri-Harouna and E. Mémin (2017), Stochastic representation of the Reynolds transport theorem: revisiting large-scale modeling, Comp. and Fluids, 156 :456-469. Large-scale flow models derived from the Holm-Mémin theory.
[4] V. Resseguier, E. Mémin, D. Heitz and B. Chapron, Stochastic modeling and diffusion modes for POD models and small-scale flow analysis, Journ. of Fluid Mech., 828, 888-917, 2017. Setup of reduced order models and analysis of residual data.
[5] Y. Yang and E. Mémin, High-resolution data assimilation through stochastic subgrid tensor and parameter estimation from 4DEnVar, 2017, Tellus A, 69 (1), 2017. This paper describes how the Holm-Memin theory can be used to couple large scale models and high resolution data.
[6] V. Resseguier, E. Mémin, B. Chapron, Geophysical flows under location uncertainty, Part I: Random transport and general models, Geophysical & Astrophysical Fluid Dynamics, 111(3): 149-176, 2017. This paper develops the derivation of stochastic geophysical models of a stochastic PDE in the Holm-Memin theory.
[7] V. Resseguier, E. Mémin, B. Chapron, Geophysical flows under location uncertainty, Part II: Quasigeostrophic models and efficient ensemble spreading, Geophysical & Astrophysical Fluid Dynamics,111(3): 177-208, 2017
[8] V. Resseguier, E. Mémin, B. Chapron, Geophysical flows under location uncertainty, Part III: SQG and frontal dynamics under strong turbulence, Geophysical & Astrophysical Fluid Dynamics, accepted for publication, 111(3): 209-227, 2017 [9] Y. Yang, C. Robinson, D. Heitz and E., Mémin. Enhanced ensemble-based 4DVar scheme for data assimilation. Computer and Fluids, 115, 201--210, 2015. Definition of an efficient ensemble data assimilation strategy.
[10] A. Cuzol and E., Mémin. Monte carlo fixed-lag smoothing in state-space models. Nonlin. Processes Geophys., 21, 633-643, 2014.
[11] E. Mémin. Fluid flow dynamics under location uncertainty. Geophysical & Astrophysical Fluid Dynamics, 108(2): 119-146, 2014. Foundational paper of the Holm-Memin theory on flow dynamics represention from stochastic transport.
[12] C. Avenel, E. Mémin, P. Pérez. Stochastic level set dynamics to track closed curves through image data. Journ of Math. Imaging and Vision, 49:296-316., 2014.
[13] S. Kadri Harouna, P. Dérian, P. Héas, E. Mémin. Divergence-free Wavelets and High Order Regularization. International Journal of Computer Vision, 103(1):80-99, May 2013.
[14] S. Beyou, A. Cuzol, S. Gorthi, E. Mémin. Weighted Ensemble Transform Kalman Filter for Image Assimilation. Tellus A, 65(18803), January 2013.
[15] G. Artana, A. Cammilleri, J. Carlier, E. Mémin. Strong and weak constraint variational assimilation for reduced order fluid flow modeling. Journ. of Comp. Physics, 213(8):3264-3288, April 2012.
[16] N. Papadakis, E. Mémin, A. Cuzol, N. Gengembre. Data assimilation with the Weighted Ensemble Kalman Filter. Tellus-A, 62(5):673-697, 2010.
[17] Cuzol, E. Mémin. A stochastic filtering technique for fluid flows velocity fields tracking. IEEE Trans. on Pattern Anal. and Mach. Intel., 31(7):1278-1293, 2009.
Google Scholar, ORCID and arXiv pages:
Prof Etienne Mémin
2020
- Stochastic modelling in fluid dynamics: Itô versus Stratonovich, Darryl D. Holm, Published: May 2020; https://doi.org/10.1098/rspa.2019.0812
- Stochastic representation of mesoscale eddy effects in coarse-resolution barotropic models, Werner Bauer, Pranav Chandramouli, Long Li, EtienneMémin, Published: July 2020: https://doi.org/10.1016/j.ocemod.2020.101646
- Stochastic Variational Formulations of Fluid Wave-Current Interaction, Dan Crisan, Darryl D. Holm, James-Michael Leahy, Torstein Nilssen, Pubilished: April 2020: [2004.07829] Variational principles for fluid dynamics on rough paths (arxiv.org)
- Stochastic Variational Formulations of Fluid Wave-Current Interaction, Darryl D Holm, J Nonlinear Sci 31, 4 (2021), December 2020: https://doi.org/10.1007/s00332-020-09665-2
- Stochastic wave-current interaction in thermal shallow water dynamics, Darryl D Holm, Erwin Luesink, Published: December 2020, [1910.10627] Stochastic wave-current interaction in thermal shallow water dynamics (arxiv.org)
- 4D large scale variational data assimilation of a turbulent flow with a dynamics error model, Pranav Chandramouli, Etienne Mémin, Dominique Heitz (2020), Journal of Computational Physics, 412, 109446, https://hal.inria.fr/hal-02547763/; DOI : 10.1016/j.jcp.2020.109446
- Deciphering the role of small-scale inhomogeneity on geophysical flow structuration: a stochastic approach, Werner Bauer, Pranav Chandramouli, Bertrand Chapron, Long Li, Etienne Mémin (2020) Journal of Physical Oceanography, 50 (4), 983-1003, https://archimer.ifremer.fr/doc/00610/72194/70975.pdf
2021
- Local well-posedness for the great lake equation with transport noise, Dan Crisan and Oana Lang, Published: January 2021, 10.pdf (imar.ro)
- Log-Normalization Constant Estimation using the Ensemble Kalman-Bucy Filter with Application to High-Dimensional Models, Dan Crisan, Pierre Del Moral , Ajay Jasra & Hamza Ruzayqat, Published: January 2021, https://arxiv.org/pdf/2101.11460.pdf
- Stochastic linear modes in a turbulent channel flow Gilles Tissot, André Cavalieri, Etienne Mémin (2021), Journal of Fluid Mechanics, Volume 912. https://doi.org/10.1017/jfm.2020.1168; https://hal.inria.fr/hal-03081978/
- New trends in ensemble forecast strategy: uncertainty quantification for coarse-grid computational fluid dynamics, Valentin Resseguier, Long Li, Gabriel Jouan, Pierre Dérian, Etienne Mémin, Chapron Bertrand (2021), Archives of Computational Methods in Engineering, 28: 215–261, https://hal.inria.fr/hal-02558016/ DOI : 10.1007/s11831-020-09437-x
- Rotating shallow water flow under location uncertainty with a structure-preserving discretization,Rüdiger Brecht, Long Li, Werner Bauer, Etienne Mémin (2021), arXiv:2102.03783 [physics.flu-dyn], https://arxiv.org/abs/2102.03783/
- Stochastic Wave–Current Interaction in Thermal Shallow Water Dynamics, Darryl D. Holm and Erwin Luesink, Journal of Nonlinear Science volume 31, Article number: 29 (2021), https://doi.org/10.1007/s00332-021-09682-9
- Stochastic mesoscale circulation dynamics in the thermal ocean, Darryl D. Holm, Erwin Luesink, and Wei Pan, Phys. Fluids 33, 046603 (2021); doi.org/10.1063/5.0040026
- Quantifying truncation-related uncertainties in unsteady fluid dynamics reduced order models, Valentin Resseguier, Agustin Picard, Etienne Mémin, Bertrand Chapron, SIAM/ASA Journal on Uncertainty Quantification (2021); https://hal.archives-ouvertes.fr/hal-03169957v2
- Testing a one-closure equation turbulence model in neutral boundary layers, Benoît Pinier, Roger Lewandowski, Etienne Mémin, Pranav Chandramouli, Computer Methods in Applied Mechanics and Engineering (2021), DOI: 10.1016/j.cma.2020.113662; https://hal.archives-ouvertes.fr/hal-01875464v4
- Stochastic effects of waves on currents in the ocean mixed layer, Darryl D. Holm and Ruiao Hu, Journal of Mathematical Physics 62, 073102 (2021); https://doi.org/10.1063/5.0045010
- Wave–current interaction on a free surface, Dan Crisan, Darryl D. Holm, Oliver D. Street, Studies in Applied Mathematics published by Wiley Periodicals, (2021), https://onlinelibrary.wiley.com/doi/full/10.1111/sapm.12425
- Nonlinear dispersion in wave-current interactions, Darryl Holm, Ruiao Hu, August (2021) https://arxiv.org/pdf/2108.05213.pdf
2022
- Well-posedness for a stochastic 2D Euler equation with transport noise, Oana Lang and Dan Crisan, Stoch PDE: Anal Comp (2022), https://doi.org/10.1007/s40072-021-00233-7
- An application of the splitting-up method for the computation of a neural network representation for the solution for the filtering equations, Dan Crisan, Alexander Lobbe and Salvador Ortiz-Latorre, Stoch PDE: Anal Comp (2022), https://doi.org/10.1007/s40072-022-00260-y
- Analytical Properties for a Stochastic Rotating Shallow Water Model under Location Uncertainty, Oana Lang, Dan Crisan, Etienne Memin, June (2022), https://doi.org/10.48550/arXiv.2206.12451
- Bayesian inference for fluid dynamics: A case study for the stochastic rotating shallow water model, Oana Lang, Peter Jan van Leeuwen, Dan Crisan, Roland Potthast, Front. Appl. Math. Stat., 18 October 2022, Sec. Dynamical Systems, https://doi.org/10.3389/fams.2022.949354
2023
- Deterministic and stochastic Euler–Boussinesq convection, Darryl D. Holm and Wei Pan, Physica D 444 (2023) 133584, https://doi.org/10.1016/j.physd.2022.133584
- Conference proceedings: Stochastic Transport in Upper Ocean Dynamics (2023). https://link.springer.com/book/10.1007/978-3-031-18988-3 . This book is open access, which means that you have free and unlimited access. Brings selected, peer-reviewed studies in variability and uncertainty in upper ocean dynamics. Discusses means of quantifying the effects of local patterns of sea-level rise, heat uptake, carbon storage, and more.
- Well-Posedness Properties for a Stochastic Rotating Shallow Water Model, Dan Crisan and Oana Lang, Journal of Dynamics and Differential Equations (2023), https://doi.org/10.1007/s10884-022-10243-1
- Analytical Properties for a Stochastic Rotating Shallow Water Model Under Location Uncertainty, Oana Lang, Dan Crisan, Étienne Mémin, Journal of Mathematical Fluid Mechanics (2023), https://doi.org/10.1007/s00021-023-00769-9
- A Consistent Stochastic Large-Scale Representation of the Navier–Stokes Equations, Arnaud Debussche, Berenger Hug & Etienne Mémin, Journal of Mathematical Fluid Mechanics volume 25, Article number: 19 (2023), https://doi.org/10.1007/s00021-023-00764-0
- Stochastic data-driven parameterization of unresolved eddy effects in a baroclinic quasi-geostrophic model. Li, L., Deremble, B., Lahaye, N., & Mémin, E. (2023). Journal of Advances in Modeling Earth Systems, 15, e2022MS003297. https://doi.org/10.1029/2022MS003297
- An implementation of Hasselmann's paradigm for stochastic climate modelling based on stochastic Lie transport, D. Crisan, D. Holm and P. Korn, (2023), Nonlinearity 36 4862, DOI 10.1088/1361-6544/ace1ce
- Existence and uniqueness of maximal solutions to SPDEs with applications to viscous fluid equations, Daniel Goodair, Dan Crisan, Oana Lang, Stochastics and Partial Differential Equations: Analysis and Computations (2023), 10.1007/s40072-023-00305-w.
- Theoretical analysis and numerical approximation for the stochastic thermal quasi-geostrophic model, Dan Crisan, Darryl Holm, Oana Lang, Romeo Mensah, Wei Pan, Stochastic & Dynamics, 10.1142/S02194937235003.
- Geometric Mechanics of the Vertical Slice, Darryl D. Holm, Ruiao Hu, and Oliver D. Street, For Volume 1, Issue 1 of Geometric Mechanics (2023) https://arxiv.org/pdf/2309.02602.pdf
- Dan Crisan, Oana Lang, Alexander Lobbe, Peter-Jan van Leeuwen, Roland Potthast. Noise calibration for SPDEs: A case study for the rotating shallow water model. Foundations of Data Science (2023). doi: 10.3934/fods.2023012