Mark Buehner
Current research and/or projects
Contributing to Environment Canada's mandate to improve meteorological forecasts by improving the use of atmospheric observations in the global analysis system.
- Estimation and modelling of background error covariances for global four-dimensional variational data assimilation.
- Research and evaluation of a new data assimilation approach (En-Var: ensemble-variational) for producing deterministic analyses.
- Application of variational data assimilation approaches to the analysis of sea ice conditions.
Professional activities / interests
Co-lead of sea-ice data assimilation project (collaboration with the Canadian Ice Service)
Research lead for testing and implementation of new data assimilation approach (En-Var) in the operational Global Deterministic Prediction System
Education and awards
Ph.D. Physical Oceanography, Dalhousie University, 2000
B.A.Sc. Systems Design Engineering, University of Waterloo, 1994
Key publications
Buehner, M., R. McTaggart-Cowan and S. Heilliette. 2017. An ensemble Kalman filter for numerical weather prediction based on variational data assimilation: VarEnKF. Monthly Weather Review. 145:617-635.
Carrieres, T., M. Buehner, J.-F. Lemieux, and L. T. Pederson (editors), 2017: Sea Ice Analysis and Forecasting. Cambridge University Press.
Buehner, M. and A. Shlyaeva. 2015. Scale-dependent background-error covariance localization. Tellus A, 67:28027.
Buehner, M., R. McTaggart-Cowan, A. Beaulne, C. Charette, L. Garand, S. Heilliette, E. Lapalme, S. Laroche, S. R. Macpherson, J. Morneau, and A. Zadra. 2015. Implementation of Deterministic Weather Forecasting Systems based on Ensemble-Variational Data Assimilation at Environment Canada. Part I: The Global System. Monthly Weather Review. 143:2532-2559.
Buehner, M. 2012. Evaluation of a Spatial/Spectral Covariance Localization Approach for Atmospheric Data Assimilation. Monthly Weather Review. 140:617-636.
Buehner, M., P. L. Houtekamer, C. Charette, H. L. Mitchell, and B. He. 2010. Intercomparison of Variational Data Assimilation and the Ensemble Kalman Filter for Global Deterministic NWP. Part I: Description and Single-Observation Experiments. Monthly Weather Review. 138:1550-1566.
Buehner, M., P. L. Houtekamer, C. Charette, H. L. Mitchell, and B. He. 2010. Intercomparison of Variational Data Assimilation and the Ensemble Kalman Filter for Global Deterministic NWP. Part II: One-Month Experiments with Real Observations. Monthly Weather Review. 138:1567-1586.
Buehner, M. and M. Charron. 2007. Spectral and spatial localization of background error correlations for data assimilation. Quart. J. Roy. Meteor. Soc. 133:615-630.
Buehner, M. 2005. Ensemble-derived stationary and flow-dependent background error covariances: Evaluation in a quasi-operational setting for NWP. Quart. J. Roy. Meteor. Soc. 131:1013-1044.