TAILLARDAT Maxime



Maxime TAILLARDAT

Météo-France - CNRM UMR 3589

Numerical Weather Prediction Research Department

Predictability Team

Tél. +33 (0) 4 26 73 73 89

maxime dot taillardat at meteo dot fr

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  Research interests

Also engineer in the Statistical Forecasting, Monitoring and Verification team in Météo-France, my research interests are at the crossing between computational statistics and environmental sciences :

 Statistical post-processing of ensemble forecasts and their economical value.

 Evaluation of probabilistic and ensemble forecasts.

 Extreme events.

 Applications of ensemble forecasts for decision making.

  Short resume

 2022 : Scientific visitor at the ECMWF and at the Isaac Newton Institute

 2014 - 2017 : Ph.D. in meteorology, oceanography and environmental sciences, Paris-Saclay University, Versailles, France : Non-Parametric Methods of post-processing for Ensemble Forecasting under the supervision of Philippe Naveau, Anne-Laure Fougères et Olivier Mestre

 2013 - 2014 : M.Sc. in computer science, ENSEEIHT-UPS, Toulouse, France

 2011 - 2014 : M.Sc. in Meteorology Engineering (specialty in Statistics and machine learning), ENM, Toulouse, France .

  Current projects

 2021 - 2024 : French funding agency for research, "T-REX" project, lead by Clément Dombry (LMB, Besançon)

  Past projects

 2019 - 2021 : Horizon 2020 - European Union, "EoCoE 2" project, lead by CEA (Saclay)

 2015 - 2018 : Horizon 2020 - European Union, "EoCoE" project, lead by CEA (Saclay)

 Publications

Working or accepted papers

Peer-reviewed articles

2023

 Taillardat, M., Fougères, A. L., Naveau, P., & De Fondeville, R. Evaluating probabilistic forecasts of extremes using continuous ranked probability score distributions. International Journal of Forecasting, 39(3), 1448-1459.

 Demaeyer, J., Bhend, J., Lerch, S., Primo, C., Van Schaeybroeck, B., Atencia, A., Ben Bouallègue, Z., Chen, J., Dabernig, M., Evans, G., Faganeli Pucer, J., Hooper, B., Horat, N., Jobst, D., Merše, J., Mlakar, P., Möller, A., Mestre, O., Taillardat, M., and Vannitsem, S. The EUPPBench postprocessing benchmark dataset v1.0. Earth Syst. Sci. Data, 15, 2635–2653.

 Pic, R., Dombry, C., Naveau, P., & Taillardat, M. Distributional regression and its evaluation with the CRPS: Bounds and convergence of the minimax risk. International Journal of Forecasting, 39(4), 1564-1572.

2021

 Vannitsem, S., Bremnes, J.B., Demaeyer, J., Evans, G.R., Flowerdew, J., Hemri, S., Lerch, S., Roberts, N., Theis, S., Atencia, A., Ben Bouallègue, Z., Bhend, J., Dabernig, M., De Cruz, L., Hieta, L., Mestre, O., Moret, L., Odak Plenković, I., Schmeits, M., Taillardat, M., Van den Bergh, J., Van Schaeybroeck, B., Whan, K., Ylhaisi, J. Statistical Postprocessing for Weather Forecasts—Review, Challenges and Avenues in a Big Data World. Bulletin of the American Meteorological Society, 102(3), 681-699.

 Tiberi-Wadier, A. L., Goutal, N., Ricci, S., Sergent, P., Taillardat, M., Bouttier, F., & Monteil, C. Strategies for hydrologic ensemble generation and calibration: on the merits of using model-based predictors. Journal of Hydrology, 599, 126233.

 Taillardat, M. Skewed and Mixture of Gaussian Distributions for Ensemble Postprocessing. Atmosphere, 12(8), 966.

 Evin, G., Lafaysse, M., Taillardat, M., & Zamo, M. Calibrated ensemble forecasts of the height of new snow using quantile regression forests and ensemble model output statistics , Nonlin. Processes Geophys., 28, 467–480.

2020

 Taillardat, M., & Mestre, O. From research to applications–examples of operational ensemble post-processing in France using machine learning. Nonlinear Processes in Geophysics, 27(2), 329-347.

 Hemri, S., Lerch, S., Taillardat, M., Vannitsem, S., & Wilks, D. S. (2020). Preface: Advances in post-processing and blending of deterministic and ensemble forecasts. Nonlinear Processes in Geophysics, 27(4), 519-521.

2019

 Taillardat, M., Fougères, A. L., Naveau, P., & Mestre, O. Forest-based and semiparametric methods for the postprocessing of rainfall ensemble forecasting. Weather and Forecasting, 34(3), 617-634.

2016

 Taillardat, M., Mestre, O., Zamo, M., & Naveau, P. Calibrated ensemble forecasts using quantile regression forests and ensemble model output statistics. Monthly Weather Review, 144(6), 2375-2393.

  Professional activities

 Associate Editor for Monthly Weather Review since 2021

 Guest Editor for Nonlinear Processes in Geophysics, 2019-2020

 Co-organization of the session Advances in statistical post-processing, blending and verification of deterministic and ensemble forecasts, European Geosciences Union General Assembly, Vienna (Austria) since 2019

 Member of the Environment group of the French Statistical Society

 Member of the European Geosciences Union

 Reviewer for Monthly Weather review, Nonlinear Processes in Geophysics, Meteorological Applications, Atmospheric Science Letters, Urban Climate, Quarterly Journal of the Royal Meteorological Society, Meteorologische Zeitschrift, Artificial Intelligence for the Earth Systems, DWD Extramurale Forschung.

  Invited presentations

2022

 Isaac Newton Institute GFD Satellite Program Workshop 2 (Reading, United Kingdom)
 ECMWF seminar (Reading, United Kingdom)

2021

 Journée CJD 85 (La Roche sur Yon -remotely-, France)
 SRNWP-EPS EUMETNET Workshop (Madrid -remotely-, Spain)

2020

 Journée Impacts-CJD AuRa (Grenoble, France)
 Interview for France 3 TV Alpes (Grenoble, France)
 VALPRED II Workshop (Aussois, France)
 ECMWF Machine Learning seminar series (Reading -remotely-, United Kingdom)

2019

 VALPRED Workshop (Aussois, France)
 Seminar at Centre d’Etude de la Neige (Grenoble, France)
 GRASPA-TIES seminar (Pescara, Italy)

2018

 ANR DESIRE Workshop (Rennes, France)

2017

 Journée Hydro-Stats Lyonnaise (Lyon, France)

2016

 NCAR CISL ToY Workshop (Boulder, USA)
 Rencontres Lyonnaises de Statistique (Lyon, France)

  Teaching

 2021- : Inferential Statistics, Lecture, Polytech’Lyon, Lyon.
 2016 : Statistical Analysis & Probability, Lecture, Polytech’Lyon, Lyon.
 2014 - 2016 : Bayesian Analysis, Lecture, ENM-ENSEEIHT, Toulouse.

  Miscellaneous

 R Package ExtremeIndex



No one shall be held responsible, scientifically or otherwise for the content of these pages / articles, but the authors themselves and in no way the responsibility of the CNRM. - Last update : 10/2023.