Publications

Publications at Google Scholar

  • Cocucci T, M Pulido, J Aparicio, J Ruiz, I Simoy, S Rosa, 2022: Inference in epidemiological agent-based models using ensemble-based data assimilation. PLoS ONE , 17, e0264892. doi 10.1371/journal.pone.0264892
  • Rodas C. and M. Pulido, 2021: Gravity wave focusing on the Antarctic polar vortex using Gaussian beam approximation in horizontally nonuniform flows Journal of Atmospheric Sciences, 78, 3836-3853 doi 10.1175/JAS-D-21-0066.1
  • van Leeuwen PJ, M. DeCaria, N Chakaborty and M Pulido, 2021: A new framework for causal discovery in non-intervenable systems. Chaos, 31, 123128 (2021) arXiv preprint arXiv:2010.02247 doi 10.1063/5.0054228
  • Lucini, M.M., van Leeuwen, P.J. and Pulido, M., 2021. Model uncertainty estimation using the expectation maximization algorithm and a particle flow filter. SIAM Jornal of Uncertainty Quantification, 9 , 681-707. doi:10.1137/19M1297300 arXiv preprint arXiv:1911.01511
  • Evensen G, J Amezcua , M Bocquet , A Carrassi, A Farchi , A Fowler , PL Houtekamer, CK Jones , RJ de Moraes, M Pulido , C Sampson, and FC Vossepoel, 2020: An international assessment of the COVID-19 pandemic using ensemble data assimilation. Foundations of Data Science . doi: 10.3934/fods.2021001
  • Tandeo P., P. Ailliot, M. Bocquet, A. Carrassi, T. Miyoshi, M. Pulido, Y. Zhen, 2020: Joint Estimation of Model and Observation Error Covariance Matrices in Data Assimilation: A review. Mon. Wea. Rev.l, 148, 3973--3994, https://arxiv.org/pdf/1807.11221
  • Cocucci, T.J., Pulido, M., Lucini, M. and Tandeo, P., 2020. Model error covariance estimation in particle and ensemble Kalman filters using an online expectation-maximization algorithm. Q. J. Roy. Met. Soc. doi DOI: 10.1002/qj.3931. arXiv preprint arXiv:2003.02109
  • Scheffler G., J. Ruiz and M. Pulido, 2019: Inference of stochastic parameterizations for model error treatment using nested ensemble Kalman filters. Q. J. Roy. Met. Soc. doi 10.1002/qj.3542 https://arxiv.org/pdf/1807.10858
  • Pulido M., and P. J. vanLeewen, 2019: Sequential Monte Carlo with kernel embedded mappings: The mapping particle filter. Journal of Computational Physics , 396, 400-415. doi: 10.1016/j.jcp.2019.06.060
  • Pulido M., P. J. vanLeewen and D. J. Posselt, 2019: Kernel embedded nonlinear observational mappings in the variational mapping particle filter. Lecture Notes on Computational Sciences, ICCS-2019, 141--155. 10.1007/978-3-030-22747-0 https://arxiv.org/pdf/1901.10426
  • Scheffler G., J. Ruiz and M. Pulido, 2019: Inference of stochastic parameterizations for model error treatment using nested ensemble Kalman filters. Q. J. Roy. Met. Soc. doi 10.1002/qj.3542 https://arxiv.org/pdf/1807.10858
  • Scheffler G., M. Pulido and C. Rodas, 2018: The Role of Gravity Wave Drag Optimization in the Splitting of the Antarctic Vortex in the 2002 Sudden Stratospheric Warming. Geophysical Research Letters doi 10.1029/2018GL077993
  • Pulido M., P. Tandeo, M. Bocquet, A. Carrassi and M. Lucini, 2018: Parameter estimation in stochastic multi-scale dynamical systems using expectation-maximization and Newton-Raphson maximum likelihood methods. Tellus. 70 , 1442099. doi 10.1080/16000870.2018.1442099 arxiv
  • Rodas C. and M. Pulido 2017: A climatology of Rossby wave generation in the middle atmosphere of the Southern hemisphere from MERRA reanalysis. J. Geophys. Res. , 122, 8982--8997 doi: 10.1002/2017JD026597
  • Lguensat R., P Tandeo, P Ailliot, M Pulido, R Fablet, 2017: The analog data assimilation. Mon. Wea. Rev. 145, 4093-4107 doi: 10.1175/MWR-D-16-0441.1
  • Scheffler G. and M. Pulido 2017: Estimation of gravity wave parameters to alleviate the delay in stratospheric final warmings of general circulation models. Q. J. Roy. Meteorol. Soc. , 143 , 2157--2167. doi: 10.1002/qj.3074
  • Pulido M. and O. Rosso, 2017: Model selection: Using information measures from ordinal symbolic analysis to select model sub-grid scale parameterizations. J. Atmos. Sci. , 74 , 3253--3269. doi: 10.1175/JAS-D-16-0340.1
  • Dreano D., P. Tandeo, M. Pulido, B. Ait-El-Fquih, T. Chonavel and I. Hoteit, 2017: Estimation of error covariances in nonlinear state-space models using the Expectation Maximization algorithm. Q. J. Roy. Meteorol. Soc. , 142 , 1877-1885. doi: 10.1002/qj.3048

  • Polavarapu S. and M. Pulido 2017: Stratospheric and Mesospheric Data Assimilation: The role of middle atmospheric dynamics. Chapter book Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications Vol. III, 429-454.. edited by Springer. doi: 10.1007/978-3-319-43415-5_19 pdf
  • Pulido M., G. Scheffler, J. Ruiz, M. Lucini and P. Tandeo, 2016: Estimation of the functional form of subgrid-scale schemes using ensemble-based data assimilation: a simple model experiment. Q. J. Roy. Meteorol. Soc. , 142 , 2974-2984. doi: 10.1002/qj.2879.
  • Hannart A., A. Carrassi, M. Bocquet, M. Ghil, P. Naveau, M.Pulido, J. Ruiz, P. Tandeo, 2016: DADA: Data assimilation for the detection and attribution of weather- and climate-related events. Climate Change, 136: 155. doi:10.1007/s10584-016-1595-3 pdf
  • Sun J., C. J. Nappo, L. Mahrt, D. Belusic, B. Grisogono, D. R. Stauffer, M. Pulido, C. Staquet, Q. Jiang, A. Pouquet, C. Yague, B. Galperin, R. B. Smith, J. J. Finnigan, S. D. Mayor, G. Svensson, A. A. Grachev, and W. D. Neff, 2015: Review of Wave-Turbulence Interactions in the Stable Atmospheric Boundary Layer. Review in Geophysics. doi:10.1002/2015RG000487 . pdf
  • Scheffler G. and M. Pulido, 2015: Compensation between resolved and unresolved wave drag in the stratospheric final warmings of the Southern hemisphere. J. Atmos. Sci. pdf
  • Ruiz, J. J., and M. Pulido, 2015: Parameter Estimation Using Ensemble-Based Data Assimilation in the Presence of Model Error. Monthly Weather Review. . 143 , 1568-1582. DOI 10.1175/MWR-D-14-00017.1. pdf
  • Tandeo P., M. Pulido and F. Lott, 2015: Offline estimation of subgrid-scale orographic parameters using EnKF and maximum likelihood error covariance estimates. Q. J. Roy. Meteorol. Soc. 141 , 383-395 pdf
  • Rodas, C, and M. Pulido, 2014: The Breaking of Transience Inertio-Gravity Waves in a Shear Flow using Gaussian Beam Approximation Journal of Fluid Mechanics. 759, 676-700. pdf
  • Pulido, M. 2014: A simple technique to infer the missing gravity wave drag in a general circulation model: Potential vorticity budget. Journal of Atmospheric Sciences . 71, 453-469. pdf
  • Ruiz J., M. Pulido and T. Miyoshi, 2013: Estimating parameters with ensemble-based data assimilation: Parameter covariance treatment. J. Meteorol. Soc. Japan. 91, 453-469. pdf
  • Ruiz, J. J., M. Pulido, and T. Miyoshi, 2013: Estimating model parameters with ensemble-based data assimilation: A review. J. Meteorol. Soc. Japan, 91, 79-99. doi:10.2151/jmsj.2013-201. Invited review article. pdf
  • Pulido M., C. Rodas, D. Dechat, and M. Lucini, 2013: High Gravity Wave Activity Observed in Patagonia, Southern America: Generation by a Cyclone Passage over Andes Mountain Range. Q. J. Roy. Meteorol. Soc. , 139 , 451-466. DOI: 10.1002/qj.1983. pdf
  • Pulido M., S. Polavarapu, T. Shepherd and J. Thuburn, 2012: Estimation of optimal gravity wave parameters for climate models using data assimilation. Q. J. Roy. Meteorol. Soc. , 138 , 298-309. DOI: 10.1002/qj.932. pdf
  • Pulido M. and C. Rodas, 2011: A Higher Order Ray Approximation applied to Orographic Gravity Waves: Gaussian Beam Approximation. J. Atmos. Sci., 68 , 46-60. doi: 10.1175/2010JAS3468.1 . pdf
  • Alexander, M. J., M. Geller, C. McLandress, S. Polavarapu, P. Preusse, F. Sassi, K. Sato, S. Eckermann, M. Ern, A. Hertzog, Y. Kawatani, M. Pulido, T. Shaw, M. Sigmond, R. Vincent, S. Watanabe, 2010: Recent Developments in Gravity Wave Effects in Climate Models, and the Global Distribution of Gravity Wave Momentum Flux from Observations and Models. Q. J. Roy. Meteorol. Soc. , 136, 1103-1124. pdf
  • Pulido M. and J. Thuburn, 2008: The seasonal cycle of gravity wave drag in the middle atmosphere. J. Climate , 21, 4664-4679. pdf Pulido M. and J. Thuburn, 2009: Corregindum. J. Climate , 22 , 2572-2572.

  • Pulido M. and C. Rodas, 2008: Do transience gravity waves in a shear flow break?. Q. J. Roy. Meteorol. Soc., 131 , 1215-1232. pdf
  • Pulido M. and J. Thuburn, 2006: Gravity wave drag estimation from global analyses using variational data assimilation principles. II: Case study. Q. J. R. Meteor. Soc. 132, 1527-1543. pdf
  • Pulido M. and H. Teitelbaum, 2006: Gravity wave generation and breaking observed with radiosondes at Ushuaia (Argentina), Proceedings of 8th ICSHMO, AMS , 627-632. ISBN 85-17-00023-4. pdf
  • Pulido M. 2005: On the Doppler shifting effect in an atmospheric gravity wave spectrum. Q. J. Roy. Meteorol. Soc., 131 , 1215-1232. pdf
  • Pulido M. and J. Thuburn, 2005: Gravity wave drag estimation from global analyses using variational data assimilation principles. I: Theory and implementation. Q. J. Roy. Meteorol. Soc., 131, 1821-1840. pdf
  • Rodas C. y M. Pulido, 2005: Los efectos de la viscocidad en la deposición de momento de ondas de gravedad transitorias. Anales de la AFA, 17, 144-147. pdf
  • Pulido M. y C. Rodas, 2005: La inestabilidad convectiva en ondas de gravedad transitorias. Proceedings de CLIMET (Congreso Latinoamericano e Iberico de Meteorologia , Buenos Aires, 4-7 Octubre. 8 pp. pdf
  • Pulido M., 2002: Spectral differences between a single gravity shear wave and a continuous superposition of modes. Atmospheric Science Letters, 3 , 104-111. pdf
  • Pulido M. and G. Chimonas, 2001: Forest canopy waves: The long wavelength component Boundary layer meteorology, 100, 209-224. pdf
  • Pulido M., N. Castellano y G. Caranti, 2001: Perturbaciones estacionarias sobre bosques ralos. Proceedings de CLIMET (Congreso Latinoamericano e Iberico de Meteorologia IX May 2001. 9pp. pdf
  • Pulido M. and G. Caranti, 2000: Spectral tail in a gravity wave train propagating in a shearing background. J. Atmos. Sci. , 57, 1473-1478. pdf
  • Pulido M. and G. Caranti, 2000: The vertical wavenumber power spectrum resulting from the propagation of a gravity wave spectrum under nonlinear advective interactions. Proceedings of the SPARC 2nd. General Assembly Nov. 2000. link
  • Pulido M. and G. Caranti, 2000: The convective instability in a nonlinear gravity wave approach. Proceedings of the SPARC 2nd. General Assembly , Nov. 2000. 8pp. link
  • Pulido M. and G. Caranti, 2000: Power spectrum of a gravity wave propagating in a shearing background, Geophys. Res. Lett., 27,101-104. pdf
  • Pulido M. and G. Caranti, 2000: Estimaciones de las Densidades Espectrales en las Irregularidades del Viento para la Campa\~na Pyrex. Anales de la Asociacion de Fisica Argentina. pdf
  • Pulido M., N. Castellano and G. Caranti, 2000: Perturbaciones en flujos sobre terrenos con variacion de la textura, Anales de la Asociacion de Fisica Argentina . pdf
  • Pulido M. and G. Caranti, 1998: Mediciones de efectos no ondulatorios en la cola del espectro de irregularidades del viento, Anales de la Asociacion de Fisica Argentina, 10, 376-379.
  • Pulido M. and G. Caranti, 1998: Climatologia de ondas de gravedad en el limite del vortice antartico, Anales de la Asociacion de Fisica Argentina, 10, 380-383.
  • Masuelli S., M. Pulido, M. Scavuzzo, and G. Caranti, 1998: Graupel trajectories and charging: a new numerical approach for cloud electrification studies. Q. J. R. Meteor. Soc., 124, 1329-1341. . pdf
  • Pulido M., M. Lamfri, M. Scavuzzo y G. Caranti, 1997: Estudio de parametros para caracterizar las ondas de gravedad, Anales de la Asociacion de Fisica Argentina, 9, 374-378.
  • Pulido M., M. Lamfri, M. Scavuzzo y G. Caranti, 1997: Analisis espectral de una onda de gravedad simple, Anales de la Asociacion de Fisica Argentina, 9, 379-383.
  • Pulido M., S. Masuelli, M. Scavuzzo y G. Caranti, 1997: Estudio de sensibilidad en zonas criticas de un diagrama de cargado. Anales de la Asociacion de Fisica Argentina, 9, 369-373.
  • Pulido M., S. Masuelli, M. Scavuzzo y G. Caranti, 1996: Un camino alternativo para el estudio de la electrificacion de tormentas. Modelo y resultados preliminares. Anales Asociacion de Fisica Argentina, 8, 218-222.