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Professeur adjoint, Sciences de l'atmosphère, Université de la Colombie-Britannique (UBC)

PRIX / ÉTUDES

Ph.D. Sciences de l'atmosphère, UBC

M.Sc. Climatologie, Dip. Météorologie, B.Sc. Géographie physique

OMM Bourse de recherche pour jeunes scientifiques

SCMO Les Prix Tertia M.C. Hughes

Environnement Canada mention d'excellence

 

Dr. Alex J. Cannon

Chercheur scientifique - La recherche sur les phénomènes climatiques extrêmes et les projections climatiques.

RECHERCHE / S-T ACTUELLE - Activités qui contribuent à la compréhension de l'état, des tendances et de la variabilité climatiques ainsi que des conditions climatiques extrêmes à l'échelle mondiale et régionale.

ACTIVITÉS PROFESSIONNELLES / INTÉRÊTS

Éditeur-en-chef (Sciences météorologiques et hydrologiques), Atmosphere-Ocean

Éditeur associé, Stochastic Environmental Research and Risk Assessment

Conseil consultatif de rédaction, Computers & Geosciences

Comité sur l'intelligence artificielle Applications aux sciences de l'environnement, American Meteorological Society (2011-2017)

PRINCIPALES PUBLICATIONS

Cannon, A.J., 2017. Multivariate quantile mapping bias correction: An N-dimensional probability density function transform for climate model simulations of multiple variables. Climate Dynamics, doi:10.1007/s00382-017-3580-6

Zhang, X., F.W. Zwiers, G. Li, X. Wan, and A.J. Cannon, 2017. Complexity in estimating past and future extreme short-duration rainfall. Nature Geoscience, doi:10.1038/NGEO2911

Mahony, C., A.J. Cannon, T. Wang, and S. Aitken, 2017. A closer look at novel climates: new method and insights at continental to landscape scales. Global Change Biology, doi:10.1111/gcb.13645

Cannon, A.J., 2016. Multivariate bias correction of climate model outputs: matching marginal distributions and inter-variable dependence structure. Journal of Climate, 29(19):7045–7064. doi:10.1175/JCLI-D-15-0679.1

Werner, A.T. and A.J. Cannon, 2016. Hydrologic extremes – An intercomparison of multiple gridded statistical downscaling methods. Hydrology and Earth System Sciences, 20: 1483-1508. doi:10.5194/hess-20-1483-2016

Cannon, A.J., 2015. Selecting GCM scenarios that span the range of changes in a multimodel ensemble: application to CMIP5 climate extremes indices. Journal of Climate, 28(3): 1260-1267. doi:10.1175/JCLI-D-14-00636.1

Cannon, A.J., S.R. Sobie, and T.Q. Murdock, 2015. Bias correction of simulated precipitation by quantile mapping: how well do methods preserve relative changes in quantiles and extremes? Journal of Climate, 28(17): 6938-6959. doi:10.1175/JCLI-D-14-00754.1

Cannon, A.J., 2015. Revisiting the nonlinear relationship between ENSO and winter extreme station precipitation in North America. International Journal of Climatology, 35: 4001-4014. doi:10.1002/joc.4263

Radic, V., A.J. Cannon, B. Menounos, and C. Gi, 2015. Future changes in autumn atmospheric river events in British Columbia, Canada, as projected by CMIP5 global climate models. Journal of Geophysical Research: Atmospheres, 120(18): 9279-9302. doi:10.1002/2015JD023279

Schnorbus, M.A. and A.J. Cannon, 2014. Statistical emulation of streamflow projections from a distributed hydrological model: application to CMIP3 and CMIP5 climate projections for British Columbia, Canada. Water Resources Research, 50(11): 8907-8926. doi:10.1002/2014WR015279

Bürger, G., S.R. Sobie, A.J. Cannon, A.T. Werner, and T.Q. Murdock, 2013. Downscaling extremes - an intercomparison of multiple methods for future climate. Journal of Climate, 26: 3429-3449. doi:10.1175/JCLI-D-12-00249.1

Bürger, G., T.Q. Murdock, A.T. Werner, S.R. Sobie, and A.J. Cannon, 2012. Downscaling extremes - an intercomparison of multiple statistical methods for present climate. Journal of Climate, 25: 4366–4388. doi:10.1175/JCLI-D-11-00408.1

Cannon, A.J., 2011. Quantile regression neural networks: implementation in R and application to precipitation downscaling. Computers & Geosciences, 37: 1277-1284, doi:10.1016/j.cageo.2010.07.005

Cannon, A.J., 2010. A flexible nonlinear modelling framework for nonstationary generalized extreme value analysis in hydroclimatology. Hydrological Processes, 24: 673-685.

Cannon, A.J., 2008. Probabilistic multi-site precipitation downscaling by an expanded Bernoulli-gamma density network. Journal of Hydrometeorology, 9(6):1284-1300.

Cannon, A.J. and W.W. Hsieh, 2008. Robust nonlinear canonical correlation analysis: Application to seasonal climate forecasting. Nonlinear Processes in Geophysics, 15: 221-232.

Stahl, K., R.D. Moore, J.M. Shea, D. Hutchinson, and A.J. Cannon, 2008. Coupled modelling of glacier and streamflow response to future climate scenarios. Water Resources Research, 44: W02422, doi:10.1029/2007WR005956

Scibek, J., D.M. Allen, A.J. Cannon, and P.H. Whitfield, 2007. Groundwater-surface water interaction under scenarios of climate change using a high-resolution transient groundwater model. Journal of Hydrology, 333: 165-181.

Cannon, A.J. and P.H. Whitfield, 2002. Downscaling recent streamflow conditions in British Columbia, Canada using ensemble neural network models. Journal of Hydrology, 259: 136-151.

Cannon, A.J., P.H. Whitfield, and E.R. Lord, 2002. Synoptic map-pattern classification using recursive partitioning and principal component analysis. Monthly Weather Review, 130(5): 1187-1206.

Whitfield, P.H. and A.J. Cannon, 2000. Recent variations in climate and hydrology in Canada. Canadian Water Resources Journal, 25(1): 19-65.

Catégories d'expertises associées à cet expert des sciences et technologies :

Air
     Adaptation et incidence
          Climat
          Analyse informatique et modélisation par ordinateur
          Mise au point de méthodes
Climat
     Changements et processus climatiques
          Adaptation et incidence
          Effets
          Prévision
          Tendances et variabilité
Technologie
     Ordinateurs
          Intelligence artificielle
          Modélisation
          Inondations
          Prévision environnementale
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