D-Index & Metrics Best Publications

D-Index & Metrics D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines.

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Environmental Sciences D-index 31 Citations 4,235 91 World Ranking 6108 National Ranking 271

Overview

What is he best known for?

The fields of study he is best known for:

  • Statistics
  • Climate change
  • Ecology

Alex J. Cannon mainly investigates Climatology, Climate model, Precipitation, Downscaling and Climate change. His Climatology study incorporates themes from Streamflow and Meteorology. His Meteorology study combines topics from a wide range of disciplines, such as Bootstrap aggregating, Linear regression, Artificial neural network, Regression and Quantile regression.

His Climate model research includes elements of Statistics, Quantile and Range. His work carried out in the field of Precipitation brings together such families of science as Atmospheric sciences, Hydrology, Hydrology, Hydrograph and General Circulation Model. Alex J. Cannon has included themes like Cluster analysis and Surface water in his Climate change study.

His most cited work include:

  • Bias Correction of GCM Precipitation by Quantile Mapping: How Well Do Methods Preserve Changes in Quantiles and Extremes? (292 citations)
  • Coupled modelling of glacier and streamflow response to future climate scenarios (196 citations)
  • Quantile regression neural networks: Implementation in R and application to precipitation downscaling (176 citations)

What are the main themes of his work throughout his whole career to date?

His main research concerns Climatology, Precipitation, Climate model, Climate change and Downscaling. His Climatology research is multidisciplinary, relying on both Linear regression, Artificial neural network, Streamflow, Meteorology and Hydrology. As a part of the same scientific study, Alex J. Cannon usually deals with the Precipitation, concentrating on Global warming and frequently concerns with Mean radiant temperature.

As part of the same scientific family, Alex J. Cannon usually focuses on Climate model, concentrating on Quantile and intersecting with Quantile regression and Regression. His study in Climate change is interdisciplinary in nature, drawing from both Hydrology, Watershed, Hydrological modelling and Forcing. The Downscaling study combines topics in areas such as General Circulation Model, Atmospheric circulation and Range.

He most often published in these fields:

  • Climatology (55.30%)
  • Precipitation (34.85%)
  • Climate model (28.03%)

What were the highlights of his more recent work (between 2018-2021)?

  • Climatology (55.30%)
  • Climate model (28.03%)
  • Precipitation (34.85%)

In recent papers he was focusing on the following fields of study:

The scientist’s investigation covers issues in Climatology, Climate model, Precipitation, Climate change and Global warming. His Climatology research includes themes of Extreme events, Streamflow and Downscaling. The various areas that Alex J. Cannon examines in his Downscaling study include General Circulation Model, Coupled model intercomparison project and Atmospheric circulation.

His Climate model research focuses on Multivariate statistics and how it connects with Projection and Bias correction. Alex J. Cannon combines subjects such as Snow, Water balance and Evapotranspiration with his study of Precipitation. Alex J. Cannon has researched Climate change in several fields, including Fire season, Watershed and Spatial dependence.

Between 2018 and 2021, his most popular works were:

  • Attribution of the Influence of Human‐Induced Climate Change on an Extreme Fire Season (31 citations)
  • A long-term, temporally consistent, gridded daily meteorological dataset for northwestern North America (23 citations)
  • Climate change impacts on Canadian yields of spring wheat, canola and maize for global warming levels of 1.5 °C, 2.0 °C, 2.5 °C and 3.0 °C (19 citations)

In his most recent research, the most cited papers focused on:

  • Statistics
  • Climate change
  • Ecology

His main research concerns Climatology, Climate change, Climate model, Precipitation and Global warming. His Climatology research is multidisciplinary, incorporating elements of Streamflow, Downscaling and Statistical dispersion. His studies deal with areas such as Fire season and Canola as well as Climate change.

His Climate model study combines topics in areas such as Agriculture and Environmental planning. The concepts of his Precipitation study are interwoven with issues in Wind speed, Water balance and Evapotranspiration. His Global warming research incorporates themes from Matching, Generalized extreme value distribution and Mean radiant temperature.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

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

Alex J. Cannon;Stephen R. Sobie;Trevor Q. Murdock.
Journal of Climate (2015)

496 Citations

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

Alex J. Cannon.
Computers & Geosciences (2011)

270 Citations

Coupled modelling of glacier and streamflow response to future climate scenarios

K. Stahl;K. Stahl;R. D. Moore;J. M. Shea;D. Hutchinson.
Water Resources Research (2008)

267 Citations

Groundwater–surface water interaction under scenarios of climate change using a high-resolution transient groundwater model

Jacek Scibek;Diana M. Allen;Alex J. Cannon;Paul H. Whitfield.
Journal of Hydrology (2007)

254 Citations

Downscaling recent streamflow conditions in British Columbia, Canada using ensemble neural network models

Alex J Cannon;Paul H Whitfield.
Journal of Hydrology (2002)

243 Citations

Recent Variations in Climate and Hydrology in Canada

Paul H. Whitfield;Alex J. Cannon.
Canadian Water Resources Journal (2000)

231 Citations

Complexity in estimating past and future extreme short-duration rainfall

Xuebin Zhang;Francis W. Zwiers;Guilong Li;Hui Wan.
Nature Geoscience (2017)

186 Citations

Downscaling Extremes—An Intercomparison of Multiple Statistical Methods for Present Climate

G. Bürger;T. Q. Murdock;A. T. Werner;S. R. Sobie.
Journal of Climate (2012)

184 Citations

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

Alex J. Cannon.
Climate Dynamics (2018)

179 Citations

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

Kabir Rasouli;William W. Hsieh;Alex J. Cannon.
Journal of Hydrology (2012)

176 Citations

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