Articles | Volume 9, issue 9
https://doi.org/10.5194/gmd-9-3161-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-9-3161-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Model evaluation paper
| 
15 Sep 2016
Model evaluation paper |
| 15 Sep 2016
The weather@home regional climate modelling project for Australia and New Zealand
Mitchell T. Black
CORRESPONDING AUTHOR
School of Earth Sciences and ARC Centre of Excellence for Climate System Science, The University of Melbourne, Melbourne, Australia
David J. Karoly
School of Earth Sciences and ARC Centre of Excellence for Climate System Science, The University of Melbourne, Melbourne, Australia
Suzanne M. Rosier
National Institute of Water and Atmospheric Research, Wellington, New Zealand
Sam M. Dean
National Institute of Water and Atmospheric Research, Wellington, New Zealand
Andrew D. King
School of Earth Sciences and ARC Centre of Excellence for Climate System Science, The University of Melbourne, Melbourne, Australia
Neil R. Massey
Environmental Change Institute, Oxford University, Oxford, UK
Sarah N. Sparrow
Oxford e-Research Centre, Oxford University, Oxford, UK
Andy Bowery
Oxford e-Research Centre, Oxford University, Oxford, UK
David Wallom
Oxford e-Research Centre, Oxford University, Oxford, UK
Richard G. Jones
Environmental Change Institute, Oxford University, Oxford, UK
Met Office Hadley Centre, Exeter, UK
Friederike E. L. Otto
Environmental Change Institute, Oxford University, Oxford, UK
Myles R. Allen
Environmental Change Institute, Oxford University, Oxford, UK
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Cited
17 citations as recorded by crossref.
- Impacts of Anthropogenic Forcings and El Niño on Chinese Extreme Temperatures N. Freychet et al. 10.1007/s00376-018-7258-8
- Lessons learnt from a real-time attribution and contextualisation trial in a National Meteorological and Hydrological Service P. Hope et al. 10.1088/2752-5295/ad7da8
- weather@home 2: validation of an improved global–regional climate modelling system B. Guillod et al. 10.5194/gmd-10-1849-2017
- Climate change attribution and the economic costs of extreme weather events: a study on damages from extreme rainfall and drought D. Frame et al. 10.1007/s10584-020-02729-y
- The Guiana Shield rainforests—overlooked guardians of South American climate C. Bovolo et al. 10.1088/1748-9326/aacf60
- Increasing temperature extremes in New Zealand and their connection to synoptic circulation features A. Thomas et al. 10.1002/joc.7908
- High‐Resolution CCAM Simulations Over New Zealand and the South Pacific for the Detection and Attribution of Weather Extremes P. Gibson et al. 10.1029/2023JD038530
- The effect of experiment conditioning on estimates of human influence on extreme weather D. Stone et al. 10.1016/j.wace.2022.100427
- Evaluation of a large ensemble regional climate modelling system for extreme weather events analysis over Bangladesh R. Rimi et al. 10.1002/joc.5931
- Anthropogenic influence on precipitation in Aotearoa New Zealand with differing circulation types A. Thomas et al. 10.1016/j.wace.2024.100727
- Different Ways of Framing Event Attribution Questions: The Example of Warm and Wet Winters in the United Kingdom Similar to 2015/16 N. Christidis et al. 10.1175/JCLI-D-17-0464.1
- Deep learning for stochastic precipitation generation – deep SPG v1.0 L. Bird et al. 10.5194/gmd-16-3785-2023
- Consequences of 1.5 °C and 2 °C global warming levels for temperature and precipitation changes over Central Africa W. Mba et al. 10.1088/1748-9326/aab048
- Processes and principles for producing credible climate change attribution messages: lessons from Australia and New Zealand M. Grose et al. 10.1088/2752-5295/ad53f5
- Robust changes to the wettest and driest days of the year are hidden within annual rainfall projections: a New Zealand case study L. Harrington et al. 10.1088/1748-9326/ad585a
- Enabling BOINC in infrastructure as a service cloud system D. Montes et al. 10.5194/gmd-10-811-2017
- Investigating differences between event-as-class and probability density-based attribution statements with emerging climate change L. Harrington 10.1007/s10584-017-1906-3
16 citations as recorded by crossref.
- Impacts of Anthropogenic Forcings and El Niño on Chinese Extreme Temperatures N. Freychet et al. 10.1007/s00376-018-7258-8
- Lessons learnt from a real-time attribution and contextualisation trial in a National Meteorological and Hydrological Service P. Hope et al. 10.1088/2752-5295/ad7da8
- weather@home 2: validation of an improved global–regional climate modelling system B. Guillod et al. 10.5194/gmd-10-1849-2017
- Climate change attribution and the economic costs of extreme weather events: a study on damages from extreme rainfall and drought D. Frame et al. 10.1007/s10584-020-02729-y
- The Guiana Shield rainforests—overlooked guardians of South American climate C. Bovolo et al. 10.1088/1748-9326/aacf60
- Increasing temperature extremes in New Zealand and their connection to synoptic circulation features A. Thomas et al. 10.1002/joc.7908
- High‐Resolution CCAM Simulations Over New Zealand and the South Pacific for the Detection and Attribution of Weather Extremes P. Gibson et al. 10.1029/2023JD038530
- The effect of experiment conditioning on estimates of human influence on extreme weather D. Stone et al. 10.1016/j.wace.2022.100427
- Evaluation of a large ensemble regional climate modelling system for extreme weather events analysis over Bangladesh R. Rimi et al. 10.1002/joc.5931
- Anthropogenic influence on precipitation in Aotearoa New Zealand with differing circulation types A. Thomas et al. 10.1016/j.wace.2024.100727
- Different Ways of Framing Event Attribution Questions: The Example of Warm and Wet Winters in the United Kingdom Similar to 2015/16 N. Christidis et al. 10.1175/JCLI-D-17-0464.1
- Deep learning for stochastic precipitation generation – deep SPG v1.0 L. Bird et al. 10.5194/gmd-16-3785-2023
- Consequences of 1.5 °C and 2 °C global warming levels for temperature and precipitation changes over Central Africa W. Mba et al. 10.1088/1748-9326/aab048
- Processes and principles for producing credible climate change attribution messages: lessons from Australia and New Zealand M. Grose et al. 10.1088/2752-5295/ad53f5
- Robust changes to the wettest and driest days of the year are hidden within annual rainfall projections: a New Zealand case study L. Harrington et al. 10.1088/1748-9326/ad585a
- Enabling BOINC in infrastructure as a service cloud system D. Montes et al. 10.5194/gmd-10-811-2017
Saved (preprint)
Latest update: 20 Nov 2024
Short summary
This study presents a citizen science computing project, known as weather@home Australia–New Zealand, which runs climate models on thousands of home computers. By harnessing the power of volunteers' computers, this project is capable of simulating extreme weather events over Australia and New Zealand under different climate scenarios.
This study presents a citizen science computing project, known as weather@home Australia–New...
