Articles | Volume 12, issue 4
https://doi.org/10.5194/tc-12-1137-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-12-1137-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
04 Apr 2018
Research article |
| 04 Apr 2018
| 04 Apr 2018
Canadian snow and sea ice: assessment of snow, sea ice, and related climate processes in Canada's Earth system model and climate-prediction system
Department of Physics, University of Toronto, Toronto, M5S 1A7, Canada
Lawrence R. Mudryk
Climate Research Division, Environment and Climate Change Canada, Toronto, M3H
5T4, Canada
William Merryfield
Climate Research Division, Environment and Climate Change Canada, Toronto, M3H
5T4, Canada
Jaison T. Ambadan
Department of Geography, University of Guelph, Guelph, N1G 2W1, Canada
Aaron Berg
Department of Geography, University of Guelph, Guelph, N1G 2W1, Canada
Adéline Bichet
CNRS-LGGE/MEOM, 38041 Grenoble, France
Ross Brown
Climate Research Division, Environment and Climate Change Canada, Toronto, M3H
5T4, Canada
Chris Derksen
Climate Research Division, Environment and Climate Change Canada, Toronto, M3H
5T4, Canada
Stephen J. Déry
Department of Environmental Science, University of Northern British
Columbia, Prince George, V2N 4Z9, Canada
Arlan Dirkson
School of Earth and Ocean Sciences, University of Victoria, Victoria, V8W 2Y2,
Canada
Greg Flato
Climate Research Division, Environment and Climate Change Canada, Toronto, M3H
5T4, Canada
Christopher G. Fletcher
Department of Geography and Environmental Management, University of
Waterloo, Waterloo, N2L 3G1, Canada
John C. Fyfe
Climate Research Division, Environment and Climate Change Canada, Toronto, M3H
5T4, Canada
Nathan Gillett
Climate Research Division, Environment and Climate Change Canada, Toronto, M3H
5T4, Canada
Christian Haas
Department of Earth and Space Science and Engineering, York
University, Toronto, M3J 1P3, Canada
Climate Sciences Division, Alfred Wegener Institute, 27570 Bremerhaven, Germany
Stephen Howell
Climate Research Division, Environment and Climate Change Canada, Toronto, M3H
5T4, Canada
Frédéric Laliberté
Climate Research Division, Environment and Climate Change Canada, Toronto, M3H
5T4, Canada
Kelly McCusker
Department of Atmospheric Sciences, University of Washington, Seattle, 98195-1640, USA
Michael Sigmond
Climate Research Division, Environment and Climate Change Canada, Toronto, M3H
5T4, Canada
Reinel Sospedra-Alfonso
Climate Research Division, Environment and Climate Change Canada, Toronto, M3H
5T4, Canada
Neil F. Tandon
Climate Research Division, Environment and Climate Change Canada, Toronto, M3H
5T4, Canada
Chad Thackeray
Department of Geography and Environmental Management, University of
Waterloo, Waterloo, N2L 3G1, Canada
Bruno Tremblay
Department of Atmospheric and Oceanic Sciences, McGill University,
Montréal,
H3A 0B9, Canada
Francis W. Zwiers
Pacific Climate Impacts Consortium, University of Victoria, Victoria, V8P 5C2,
Canada
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Cited
25 citations as recorded by crossref.
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- Using CloudSat‐CPR Retrievals to Estimate Snow Accumulation in the Canadian Arctic F. King & C. Fletcher 10.1029/2019EA000776
- JAMES BUTTLE REVIEW: A resilience framework for physical hydrology B. Newton & C. Spence 10.1002/hyp.14926
- Climate drivers of Arctic tundra variability and change using an indicators framework U. Bhatt et al. 10.1088/1748-9326/abe676
- Canadian snow and sea ice: historical trends and projections L. Mudryk et al. 10.5194/tc-12-1157-2018
- Evaluation of Historical Snow Cover over the Tibetan Plateau in CMIP6 F. Liu et al. 10.1007/s00376-024-4212-9
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- Using a nested single-model large ensemble to assess the internal variability of the North Atlantic Oscillation and its climatic implications for central Europe A. Böhnisch et al. 10.5194/esd-11-617-2020
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- Applying machine learning for drought prediction in a perfect model framework using data from a large ensemble of climate simulations E. Felsche & R. Ludwig 10.5194/nhess-21-3679-2021
- Large ensemble climate model simulations: introduction, overview, and future prospects for utilising multiple types of large ensemble N. Maher et al. 10.5194/esd-12-401-2021
- Updates to the Design of Buildings for NBCC 2025 for Climate Adaptation, Resilience, and Associated Initial Cost Impact S. Li et al. 10.1061/JSENDH.STENG-14645
- Uncertainty in El Niño-like warming and California precipitation changes linked by the Interdecadal Pacific Oscillation L. Dong et al. 10.1038/s41467-021-26797-5
- Emergence of seasonal delay of tropical rainfall during 1979–2019 F. Song et al. 10.1038/s41558-021-01066-x
- Anthropogenic Aerosols Modulated 20th‐Century Sahel Rainfall Variability Via Their Impacts on North Atlantic Sea Surface Temperature S. Zhang et al. 10.1029/2021GL095629
- Spatiotemporal trends in temperature and precipitation for Prince Edward Island over 1971–2020 R. Nawaz et al. 10.1139/cjce-2023-0186
- Roles of External Forcing and Internal Variability in Precipitation Changes of a Sub‐Region of the U.S. Mid‐Atlantic During 1979–2019 L. Dong & L. Leung 10.1029/2022JD037493
- Extreme metrics from large ensembles: investigating the effects of ensemble size on their estimates C. Tebaldi et al. 10.5194/esd-12-1427-2021
- Arctic sea ice variation in the Northwest Passage in 1979–2017 and its response to surface thermodynamics factors X. Shen et al. 10.1016/j.accre.2021.08.004
- The potential of unused small-scale water reservoirs for climate change adaptation: A model- and scenario based analysis of a local water reservoir system in Thuringia, Germany C. Heinzel et al. 10.3389/frwa.2022.892834
- No Impact of Anthropogenic Aerosols on Early 21st Century Global Temperature Trends in a Large Initial‐Condition Ensemble T. Oudar et al. 10.1029/2018GL078841
- Evaluation of Arctic sea ice drift and its dependency on near-surface wind and sea ice conditions in the coupled regional climate model HIRHAM–NAOSIM X. Yu et al. 10.5194/tc-14-1727-2020
- Impact of internal variability on climate change for the upcoming decades: analysis of the CanESM2-LE and CESM-LE large ensembles G. Rondeau-Genesse & M. Braun 10.1007/s10584-019-02550-2
24 citations as recorded by crossref.
- Climate Models as Guidance for the Design of Observing Systems: the Case of Polar Climate and Sea Ice Prediction F. Massonnet 10.1007/s40641-019-00151-w
- Anthropogenic Aerosols Dominate Forced Multidecadal Sahel Precipitation Change through Distinct Atmospheric and Oceanic Drivers H. Hirasawa et al. 10.1175/JCLI-D-19-0829.1
- Using CloudSat‐CPR Retrievals to Estimate Snow Accumulation in the Canadian Arctic F. King & C. Fletcher 10.1029/2019EA000776
- JAMES BUTTLE REVIEW: A resilience framework for physical hydrology B. Newton & C. Spence 10.1002/hyp.14926
- Climate drivers of Arctic tundra variability and change using an indicators framework U. Bhatt et al. 10.1088/1748-9326/abe676
- Canadian snow and sea ice: historical trends and projections L. Mudryk et al. 10.5194/tc-12-1157-2018
- Evaluation of Historical Snow Cover over the Tibetan Plateau in CMIP6 F. Liu et al. 10.1007/s00376-024-4212-9
- On the Time of Emergence of Tropical Width Change X. Quan et al. 10.1175/JCLI-D-18-0068.1
- Distribution of Living Benthic Foraminifera in the Baffin Bay and Nares Strait in the Summer and Fall Periods: Relation with Environmental Parameters C. Racine et al. 10.3390/jmse11112049
- Using a nested single-model large ensemble to assess the internal variability of the North Atlantic Oscillation and its climatic implications for central Europe A. Böhnisch et al. 10.5194/esd-11-617-2020
- The extremely warm summer of 2018 in Sweden – set in a historical context R. Wilcke et al. 10.5194/esd-11-1107-2020
- Applying machine learning for drought prediction in a perfect model framework using data from a large ensemble of climate simulations E. Felsche & R. Ludwig 10.5194/nhess-21-3679-2021
- Large ensemble climate model simulations: introduction, overview, and future prospects for utilising multiple types of large ensemble N. Maher et al. 10.5194/esd-12-401-2021
- Updates to the Design of Buildings for NBCC 2025 for Climate Adaptation, Resilience, and Associated Initial Cost Impact S. Li et al. 10.1061/JSENDH.STENG-14645
- Uncertainty in El Niño-like warming and California precipitation changes linked by the Interdecadal Pacific Oscillation L. Dong et al. 10.1038/s41467-021-26797-5
- Emergence of seasonal delay of tropical rainfall during 1979–2019 F. Song et al. 10.1038/s41558-021-01066-x
- Anthropogenic Aerosols Modulated 20th‐Century Sahel Rainfall Variability Via Their Impacts on North Atlantic Sea Surface Temperature S. Zhang et al. 10.1029/2021GL095629
- Spatiotemporal trends in temperature and precipitation for Prince Edward Island over 1971–2020 R. Nawaz et al. 10.1139/cjce-2023-0186
- Roles of External Forcing and Internal Variability in Precipitation Changes of a Sub‐Region of the U.S. Mid‐Atlantic During 1979–2019 L. Dong & L. Leung 10.1029/2022JD037493
- Extreme metrics from large ensembles: investigating the effects of ensemble size on their estimates C. Tebaldi et al. 10.5194/esd-12-1427-2021
- Arctic sea ice variation in the Northwest Passage in 1979–2017 and its response to surface thermodynamics factors X. Shen et al. 10.1016/j.accre.2021.08.004
- The potential of unused small-scale water reservoirs for climate change adaptation: A model- and scenario based analysis of a local water reservoir system in Thuringia, Germany C. Heinzel et al. 10.3389/frwa.2022.892834
- No Impact of Anthropogenic Aerosols on Early 21st Century Global Temperature Trends in a Large Initial‐Condition Ensemble T. Oudar et al. 10.1029/2018GL078841
- Evaluation of Arctic sea ice drift and its dependency on near-surface wind and sea ice conditions in the coupled regional climate model HIRHAM–NAOSIM X. Yu et al. 10.5194/tc-14-1727-2020
Discussed (final revised paper)
Latest update: 03 Jul 2025
Short summary
Here, the Canadian research network CanSISE uses state-of-the-art observations of snow and sea ice to assess how Canada's climate model and climate prediction systems capture variability in snow, sea ice, and related climate parameters. We find that the system performs well, accounting for observational uncertainty (especially for snow), model uncertainty, and chaotic climate variability. Even for variables like sea ice, where improvement is needed, useful prediction tools can be developed.
Here, the Canadian research network CanSISE uses state-of-the-art observations of snow and sea...
