High-Resolution Regional Climate Projections for Ontario and the Canadian Great Lakes Basins

The IPCC-endorsed multiple model/scenario approach and a state-of-the-science combined downscaling methodology were applied to project the future climate changes over Ontario and the Canadian Great Lakes basins. Significant warming is expected across the province under all RCPs. Relative to 1986–2005 averages, the highest temperature rise is projected to occur in Ontario’s Far North, 7.3°C warmer by the 2080s. The temperature over the Great Lakes Basin is projected to increase by 1.3–5.7°C. Ontario’s annual total precipitation is projected to increase 86.9 mm (11%) by the 2080s under RCP 8.5, while summer precipitation is projected to decrease by 32.9 mm (12%) and winter precipitation to increase by 52.4 mm (48%). In the Great Lakes Basin, the greatest increase in annual average temperature (1.7–5.3°C) is projected to occur in the Lake Superior sub-basin by the 2080s. Winter warming is projected to exceed summer warming in all sub-basins. Annual total precipitation is projected to increase in all five sub-basins, with the largest increase in the Lake Superior sub-basin. Summer (winter) is projected to be drier (wetter) across the entire Great Lakes Basin. These projected changes could have implications on future water levels in the Great Lakes and many aspects over the study area

Interdecadal variation of ENSO predictability in multiple models

Abstract In this study, we performed ENSO (El Niño and the Southern Oscillation) retrospective forecasts for the 120 years from 1881-2000 using three realistic models that assimilate the historic dataset of sea surface temperature (SST). By examining these retrospective forecasts and corresponding observations, as well as the oceanic analyses from which forecasts were initialized, we have explored several important issues related to ENSO predictability including its interdecadal variability and the dominant factors that control the interdecadal variability. The prediction skill of the three models showed a very consistent interdecadal variation, with high skill in the late 19th century and in the middle-late 20th century, and low skill during the period from 1900-1960. The interdecadal variation in ENSO predictability is in good agreement with that in the signal of interannual variability and in the degree of asymmetry of ENSO system. A good relationship was also identified between the degree of asymmetry and the signal of interannual variability, and the former is highly related to the latter. Generally the high predictability is attained when ENSO signal strength and the degree of asymmetry are enhanced, and vice versa. The atmospheric noise generally degrades overall prediction skill, especially for the skill of mean square error, but is able to favor some individual prediction cases. The possible reasons why these factors control ENSO predictability were also discussed