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Multivariate quantile mapping bias correction: an N-dimensional probability density function transform for climate model simulations of multiple variables

Climate dynamics, 2018, Vol.50 (1-2), p.31-49

Cannon, Alex J.

2018

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Multivariate Bias Correction of Climate Model Output: Matching Marginal Distributions and Intervariable Dependence Structure

Journal of climate, 2016-10, Vol.29 (19), p.7045-7064

Cannon, Alex J.

2016

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Non-crossing nonlinear regression quantiles by monotone composite quantile regression neural network, with application to rainfall extremes

Stochastic environmental research and risk assessment, 2018-11, Vol.32 (11), p.3207-3225

Cannon, Alex J.

2018

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Selecting GCM Scenarios that Span the Range of Changes in a Multimodel Ensemble: Application to CMIP5 Climate Extremes Indices

Journal of climate, 2015-02, Vol.28 (3), p.1260-1267

CANNON, ALEX J.

2015

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Reductions in daily continental-scale atmospheric circulation biases between generations of global climate models: CMIP5 to CMIP6

Environmental research letters, 2020-06, Vol.15 (6), p.64006

Cannon, Alex J

2020

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Bias Correction of GCM Precipitation by Quantile Mapping: How Well Do Methods Preserve Changes in Quantiles and Extremes?

Journal of climate, 2015-09, Vol.28 (17), p.6938-6959

2015

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Quantile regression neural networks: Implementation in R and application to precipitation downscaling

Computers & geosciences, 2011-09, Vol.37 (9), p.1277-1284

Cannon, Alex J.

2011

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Complexity in estimating past and future extreme short-duration rainfall

Nature geoscience, 2017-04, Vol.10 (4), p.255-259

2017

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A global climate model ensemble for downscaled monthly climate normals over North America

International journal of climatology, 2022-09, Vol.42 (11), p.5871-5891

2022

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flexible nonlinear modelling framework for nonstationary generalized extreme value analysis in hydroclimatology

Hydrological processes, 2010-03, Vol.24 (6), p.673-685

Cannon, Alex J

2010

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Intercomparison of projected changes in climate extremes for South Korea: application of trend preserving statistical downscaling methods to the CMIP5 ensemble

International journal of climatology, 2017-06, Vol.37 (8), p.3381-3397

2017

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Characterizing non-stationary compound extreme events in a changing climate based on large-ensemble climate simulations

Climate dynamics, 2021-03, Vol.56 (5-6), p.1389-1405

2021

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Wetter summers can intensify departures from natural variability in a warming climate

Nature communications, 2018-02, Vol.9 (1), p.783-9, Article 783

2018

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Multivariate bias corrections of climate simulations: which benefits for which losses?

Earth system dynamics, 2020-06, Vol.11 (2), p.537-562

2020

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A closer look at novel climates: new methods and insights at continental to landscape scales

Global change biology, 2017-09, Vol.23 (9), p.3934-3955

2017

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Daily streamflow forecasting by machine learning methods with weather and climate inputs

Journal of hydrology (Amsterdam), 2012-01, Vol.414, p.284-293

2012

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Crop yield forecasting on the Canadian Prairies by remotely sensed vegetation indices and machine learning methods

Agricultural and forest meteorology, 2016-03, Vol.218-219, p.74-84

2016

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Unprecedented Human‐Perceived Heat Stress in 2021 Summer Over Western North America: Increasing Intensity and Frequency in a Warming Climate

Geophysical research letters, 2023-12, Vol.50 (24), p.n/a

2023

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Hydrologic extremes – an intercomparison of multiple gridded statistical downscaling methods

Hydrology and earth system sciences, 2016-04, Vol.20 (4), p.1483-1508

2016

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Influences of atmospheric blocking on North American summer heatwaves in a changing climate: a comparison of two Canadian Earth system model large ensembles

Climatic change, 2022-05, Vol.172 (1-2), Article 5

2022

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Revisiting the nonlinear relationship between ENSO and winter extreme station precipitation in North America

International journal of climatology, 2015-11, Vol.35 (13), p.4001-4014

Cannon, Alex J.

2015

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Forecasting daily streamflow using online sequential extreme learning machines

Journal of hydrology (Amsterdam), 2016-06, Vol.537, p.431-443

2016

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Future changes in autumn atmospheric river events in British Columbia, Canada, as projected by CMIP5 global climate models

Journal of geophysical research. Atmospheres, 2015-09, Vol.120 (18), p.9279-9302

2015

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Attributing extreme fire risk in Western Canada to human emissions

Climatic change, 2017-09, Vol.144 (2), p.365-379

2017

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Multi‐site bias correction of climate model outputs for hydro‐meteorological impact studies: An application over a watershed in China

Hydrological processes, 2020-05, Vol.34 (11), p.2575-2598

2020

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Multivariate quantile mapping bias correction: an N-dimensional probability density function transform for climate model simulations of multiple variables

Multivariate Bias Correction of Climate Model Output: Matching Marginal Distributions and Intervariable Dependence Structure

Non-crossing nonlinear regression quantiles by monotone composite quantile regression neural network, with application to rainfall extremes

Selecting GCM Scenarios that Span the Range of Changes in a Multimodel Ensemble: Application to CMIP5 Climate Extremes Indices

Reductions in daily continental-scale atmospheric circulation biases between generations of global climate models: CMIP5 to CMIP6

Bias Correction of GCM Precipitation by Quantile Mapping: How Well Do Methods Preserve Changes in Quantiles and Extremes?

Quantile regression neural networks: Implementation in R and application to precipitation downscaling

Complexity in estimating past and future extreme short-duration rainfall

A global climate model ensemble for downscaled monthly climate normals over North America

flexible nonlinear modelling framework for nonstationary generalized extreme value analysis in hydroclimatology

Intercomparison of projected changes in climate extremes for South Korea: application of trend preserving statistical downscaling methods to the CMIP5 ensemble

Characterizing non-stationary compound extreme events in a changing climate based on large-ensemble climate simulations

Wetter summers can intensify departures from natural variability in a warming climate

Multivariate bias corrections of climate simulations: which benefits for which losses?

A closer look at novel climates: new methods and insights at continental to landscape scales

Daily streamflow forecasting by machine learning methods with weather and climate inputs

Crop yield forecasting on the Canadian Prairies by remotely sensed vegetation indices and machine learning methods

Unprecedented Human‐Perceived Heat Stress in 2021 Summer Over Western North America: Increasing Intensity and Frequency in a Warming Climate

Hydrologic extremes – an intercomparison of multiple gridded statistical downscaling methods

Influences of atmospheric blocking on North American summer heatwaves in a changing climate: a comparison of two Canadian Earth system model large ensembles

Revisiting the nonlinear relationship between ENSO and winter extreme station precipitation in North America

Forecasting daily streamflow using online sequential extreme learning machines

Future changes in autumn atmospheric river events in British Columbia, Canada, as projected by CMIP5 global climate models

Attributing extreme fire risk in Western Canada to human emissions

Multi‐site bias correction of climate model outputs for hydro‐meteorological impact studies: An application over a watershed in China

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