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2020

Abdallah C., C. Afif, S. Sauvage, A. Borbon, T. Salameh, A. Kfoury, T. Leonardis, C. Karam, P. Formenti, J.F. Doussin, N. Locoge, K. Sartelet (2020), Determination of Gaseous and Particulate Emission Factors from Road Transport in a Middle Eastern capital. Transp. Res. Part D: Transport and Environment, 83, 102361, doi:10.1016/j.trd.2020.102361

André M., K. Sartelet, S. Moukhtar, J.M. André, M. Redaelli (2020) Diesel, petrol or electric vehicles: what choices to improve urban air quality in the Ile-de-France region? A simulation platform and case study. Atmos. Environ., 241, 117752, doi:10.1016/j.atmosenv.2020.117752

Bahlali, M.L., C. Henry, B. Carissimo (2020) On the Well-Mixed Condition and Consistency Issues in Hybrid Eulerian/Lagrangian Stochastic Models of Dispersion. Boundary-Layer Meteorol 174, 275–296, https://doi.org/10.1007/s10546-019-00486-9

Bocquet, M., J. Brajard, A. Carrassi, L. Bertino. Bayesian inference of chaotic dynamics by merging data assimilation, machine learning and expectation-maximization, Foundations of Data Science, 2, 55-80 (2020), doi:10.3934/fods.2020004

Brajard, J., A. Carrassi, M. Bocquet, L. Bertino (2020) Combining data assimilation and machine learning to emulate a dynamical model from sparse and noisy observations: a case study with the Lorenz 96 model. J. Comput. Sci., 44, 101171, 10.1016/j.jocs.2020.101171

Dumont Le Brazidec J., M. Bocquet, O. Saunier, Y. Roustan (2020) MCMC methods applied to the reconstruction of the autumn 2017 Ruthenium-106 atmospheric contamination source, Atmos. Environ.: X, 6, 10071, https://doi.org/10.1016/j.aeaoa.2020.100071

Fillion, A., M. Bocquet, S. Gratton, S. Gürol, P. Sakov (2020) An iterative ensemble Kalman smoother in presence of additive model error, SIAM-ASA J. Uncertain., 8, 198-228, 10.1137/19M1244147

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Fillion, A., M. Bocquet, S. Gratton, S. Gürol, P. Sakov (2020) An iterative ensemble Kalman smoother in presence of additive model error, SIAM-ASA J. Uncertain., 8, 198-228, 10.1137/19M1244147

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Fonty, T., Ferrand, M., Leroy, A., Violeau, D. (2020) Air Entrainment Modeling in the SPH Method: A Two-Phase Mixture Formulation with Open Boundaries. Flow Turbulence Combust, 105, 1149–1195, https://doi.org/10.1007/s10494-020-00165-7

Grudzien, C., M. Bocquet, A. Carrassi. On the numerical integration of the Lorenz-96 model, with scalar additive noise, for benchmark twin experiments, Geosci. Model Dev., 13, 1903-1924 (2020), doi: 10.5194/gmd-13-1903-2020

Lugon, L., K. Sartelet, Y. Kim, J. Vigneron, O. Chrétien (2020), Nonstationary modeling of NO2, NO and NOx in Paris using the Street-in-Grid model: coupling local and regional scales with a two-way dynamic approach. Atmos. Chem. Phys., 20, 7717-7740, https://doi.org/10.5194/acp-20-7717-2020

Majdi, M., Y. Kim, S. Turquety, K. Sartelet (2020) Impact of mixing state on aerosol optical properties during severe wildfires over the Euro-Mediterranean region, Atmos. Environ., 220, 117042

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Majdi, M., Y. Kim, S. Turquety, K. Sartelet (2020) Impact of mixing state on aerosol optical properties during severe wildfires over the Euro-Mediterranean region, Atmos. Environ., 220, 117042

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Sartelet K., F. Couvidat, Z. Wang, C. Flageul, Y. Kim (2020) SSH-Aerosol v1.1: A Modular Box Model to Simulate the Evolution of Primary and Secondary Aerosols. Atmosphere, 11, 525, doi:10.3390/atmos11050525

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Sartelet K., F. Couvidat, Z. Wang, C. Flageul, Y. Kim (2020) SSH-Aerosol v1.1: A Modular Box Model to Simulate the Evolution of Primary and Secondary Aerosols. Atmosphere, 11, 525, doi:10.3390/atmos11050525

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Tandeo, P., P. Ailliot, M. Bocquet, A. Carrassi, T. Miyoshi, M. Pulido, Y. Zhen (2020) A review of innovation-based methods to jointly estimate model and observation error covariance matrices in ensemble data assimilation. Mon. Wea. Rev., 148, 3973–3994, https://doi.org/10.1175/MWR-D-19-0240.1

Tondeur, M., A. Carrassi, S. Vannitsem, M. Bocquet (2020) On temporal scale separation in coupled data assimilation with the Ensemble Kalman filter. J. Stat. Phys., 179, 1161–1185, 10.1007/s10955-020-02525-z