Impacts of Model Bias on the Climate Change Signal and Effects of Weighted Ensembles of Regional Climate Model Simulations: A Case Study over Southern Québec, Canada
作者： Hyung-Il Eum , Philippe Gachon , René Laprise
DOI: 10.1155/2016/1478514
关键词:
摘要: This study examined the impact of model biases on climate change signals for daily precipitation and minimum maximum temperatures. Through use multiple scenarios from 12 regional simulations, ensemble mean, three synthetic simulations generated by a weighting procedure, we investigated intermodel seasonal between current future periods, both median extreme precipitation/temperature values. A significant dependence over southern Quebec in Canada was detected temperatures, but not precipitation. suggests that temperature signal is affected local processes. Seasonally, bias affects mean values winter summer. In addition, potentially large increases extremes were projected. For scenarios, systematically less narrow range all variables projected compared to those simulations. found better capture spatial variability cold temperatures than scenario. These results indicate have greater potential reduce uncertainty projections events.
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