Performance of multi-model ensembles for the simulation of temperature variability over Ontario, Canada
- 180 Downloads
Climate ensembles utilize outputs from multiple climate models to estimate future climate patterns. These multi-model ensembles generally outperform individual climate models. In this paper, the performance of seven global climate model and regional climate model combinations were evaluated for Ontario, Canada. Two multi-model ensembles were developed and tested, one based on the mean of the seven combinations and the other based on the median of the same seven models. The performance of the multi-model ensembles were evaluated on 12 meteorological stations, as well as for the entire domain of Ontario, using three temperature variables (average surface temperature, maximum surface temperature, and minimum surface temperature). Climate data for developing and validating the multi-model ensembles were collected from three major sources: the North American Coordinated Regional Downscaling Experiment, the Digital Archive of Canadian Climatological Data, and the Climactic Research Unit’s TS v4.00 dataset. The results showed that the climate ensemble based on the mean generally outperformed the one based on the median, as well as each of the individual models. Future predictions under the Representative Concentration Pathway 4.5 (RCP4.5) scenario were generated using the multi-model ensemble based on the mean. This study provides credible and useful information for climate change mitigation and adaption in Ontario.
KeywordsRegional climate model NA-CORDEX Multi-model ensemble Temperature variability Ontario
This research was supported by the Natural Science and Engineering Research Council of Canada. We acknowledge the World Climate Research Programme’s Working Group on Regional Climate, and the Working Group on Coupled Modelling, former coordinating body of CORDEX and responsible panel for CMIP5. We also thank the climate modelling groups (listed in Table 2 of this paper) for producing and making available their model output. We also acknowledge the Earth System Grid Federation infrastructure an international effort led by the U.S. Department of Energy’s Program for Climate Model Diagnosis and Intercomparison, the European Network for Earth System Modelling and other partners in the Global Organisation for Earth System Science Portals (GO-ESSP). We would like to express our very great appreciation to Dr. Alessandro Selvitella for his valuable advice and guidance for the statistical techniques used in this research paper.
- Dasari HP, Salgado R, Perdigao J, Challa VS (2014) A regional climate simulation study using WRF-ARW model over Europe and evaluation for extreme temperature weather events International. J Atmos Sci 704079:1–22Google Scholar
- Demerse C (2016) Ignoring climate change will cost us too—big time. Clean Energy Canada. http://cleanenergycanada.org/ignoring-climate-change-will-cost-us-too-big-time/. Accessed 22 Sep 2017
- Giorgi F, Jones C, Asrar GR (2009) Addressing climate information needs at the regional level: the CORDEX framework. World Meteorol Organ (WMO) Bull 58:175Google Scholar
- Herrmann F, Kunkel R, Ostermann U, Vereecken H, Wendland F (2016) Projected impact of climate change on irrigation needs and groundwater resources in the metropolitan area of Hamburg (Germany) Environ Earth Sci 75 https://doi.org/10.1007/s12665-016-5904-y
- IPCC (2013) Climate change 2013: The physical science basis. In: Stocker TF, Qin D, Plattner G-K, Tignor M, Allen SK, Boschung J, Nauels A, Xia Y, Bex V, Midgley PM (eds) Contribution of working group I to the fifth assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge, pp 1535Google Scholar
- Jarsjo J, Tornqvist R, Su Y (2017) Climate-driven change of nitrogen retention-attenuation near irrigated fields: multi-model projections for Central Asia. Environ Earth Sci 76 https://doi.org/10.1007/s12665-017-6418-y
- MOECC (2011) Climate Ready: Ontario’s Adaptation Strategy and Action Plan 2011–2014. Ontario Ministry of the Environment and Climate Change, CanadaGoogle Scholar
- Perera AH, Euler D, Thompson ID (2000) Ecology of a managed terrestrial landscape: patterns and processes of forest landscapes in Ontario. UBC Press in cooperation with the Ontario Ministry of Natural Resources, VancouverGoogle Scholar
- Rotstayn LD, Jeffrey SJ, Collier MA, Dravitzki SM, Hirst AC, Syktus JI, Wong KK (2012) Aerosol- and greenhouse gas-induced changes in summer rainfall and circulation in the Australasian region: a study using single-forcing climate simulations. Atmos Chem Phys 12:6377–6404. https://doi.org/10.5194/acp-12-6377-2012 CrossRefGoogle Scholar
- Yan RH, Gao JF, Li LL (2016) Streamflow response to future climate and land use changes in Xinjiang basin, China. Environ Earth Sci 75 https://doi.org/10.1007/s12665-016-5805-0
- Zhang Q, Dool H, Saha S, Mendez M, Becker E, Peng P, Huang J (2011) Preliminary evaluation of multi-model ensemble system for monthly and seasonal prediction. In: 36th NOAA annual climate diagnostics and prediction workshop, Fort Worth, USA, 3–6 October 2011. Science and Technology Infusion Climate Bulletin, pp 124–131Google Scholar