10 citations as recorded by crossref.

1. Assimilation de données par méthode variationnelle utilisant l’adjoint d’un code de circulation côtière tridimensionnel J. Devenon et al. https://doi.org/10.1016/S0399-1784(01)01158-6
2. Peut-on optimiser les constantes d'un modèle de turbulence marine par assimilation d'observations ? Y. Leredde et al. https://doi.org/10.1016/S1251-8050(00)01425-7
3. A Fast and Generic Method to Identify Parameters in Complex and Embedded Geophysical Models: The Example of Turbulent Mixing in the Ocean C. Aldebert et al. https://doi.org/10.1029/2020MS002245
4. Circulation in a stratified and wind-forced Gulf of Lions, NW Mediterranean Sea: in situ and modeling data A. Petrenko et al. https://doi.org/10.1016/j.csr.2004.09.004
5. Data assimilation experiments using diffusive back-and-forth nudging for the NEMO ocean model G. Ruggiero et al. https://doi.org/10.5194/npg-22-233-2015
6. Epistemic uncertainties in RANS model free coefficients L. Margheri et al. https://doi.org/10.1016/j.compfluid.2014.06.029
7. Estimation of Turbulent Viscosity and Diffusivity in Adjoint Recovery of Atmospheric Boundary Layer Flow Structures T. Chai & C. Lin https://doi.org/10.1137/S1540345902411414
8. A POD reduced‐order 4D‐Var adaptive mesh ocean modelling approach F. Fang et al. https://doi.org/10.1002/fld.1911
9. An adaptive mesh adjoint data assimilation method F. Fang et al. https://doi.org/10.1016/j.ocemod.2006.02.002
10. Retrieval of Urban Boundary Layer Structures from Doppler Lidar Data. Part I: Accuracy Assessment Q. Xia et al. https://doi.org/10.1175/2007JAS2328.1