Uncertainty in climate projections and time of emergence of climate signals in the western Canadian Prairies

Abstract

Funding information Climate Research Branch of Environment and Climate Change CanadaThis paper has examined the relative significance of uncertainty in future climate projections from a subset of the coupled model intercomparison project phase 5 (CMIP5) global climate models for the Prairie Provinces of western Canada. This was undertaken by determining: (a) the contribution of model and scenario uncertainty and natural variability to the total variance of these future projections, and (b) the timing of climate signal emergence from the background noise of natural climate variability. We examined future projections of mean temperature, precipitation and summer climate moisture index (CMI). In this region, natural climate variability plays an important role in future uncertainty until the end of this century, particularly for precipitation and to a lesser extent, summer CMI. Model uncertainty also contributes to total uncertainty for these variables throughout this century, while scenario uncertainty becomes more important towards the end of the century. For the region as a whole, significant climate change (i.e., signal/noise >2) occurs earliest for summer mean temperature, with median time of emergence around 2035 for the RCP8.5 radiative forcing scenario. Although the median precipitation signal emerges from the noise (i.e., signal/noise >1) around the 2070s in winter and the 2080s in spring, significant values do not occur in any season for this variable before 2100. For summer CMI, the median time of emergence for significant change is around 2085. At the grid scale, signal-to-noise ratios are significant for all seasons for mean surface air temperature, with earliest times of emergence occurring in summer. In contrast, the summer precipitation signal is not significant this century; for summer CMI, significant values are obtained in the eastern half of the region, occurring from about 2065 onwards. Median times of emergence are towards the end of the century for summer CMI in western Saskatchewan and in Alberta, although some areas of Alberta do not exhibit significant signals this century. K E Y W O R D S CMIP5, natural variability, time of emergence, uncertainty, variance partitioning 1 | INTRODUCTIONNumerical climate models are "the primary tools available for investigating the response of the climate system to various forcings, for making climate predictions on seasonal to decadal time scales and for making projections of future climate over the coming century and beyond" (Flato et al., 2013). Applied properly, the climate change scenarios derived from these models are the most rigorous scientific basis for climate change impact assessment and the proactive

Doubling of U.S. Population Exposure to Climate Extremes by 2050

“…Likewise, the “time of emergence” (Giorgi & Bi, 2009), which is the time when future changes permanently exceed the baseline variability, is critical to understand how much of an increase in radiative forcing would lead compound extremes to exceed the levels to which humans and ecosystems have become adapted. While previous studies have calculated the time of emergence of changes in different mean climate quantities (Barrow & Sauchyn, 2019; Hawkins & Sutton, 2012; Lee et al, 2016), the spatial heterogeneity in the time of emergence of change in aggregate multivariate extreme climate has not yet been quantified.…”

Hydrological Extremes in the Canadian Prairies in the Last Decade due to the ENSO Teleconnection—A Comparative Case Study Using WRF

“…The variability in precipitation associated with ENSO has significant implications for the Canadian Prairies, the large region defined by a negative annual average water balance, and which accounts for more than 80% of the nation's agricultural land. Recent climate change projections [3,13] for western Canada suggest increased precipitation and inter-annual variation as a consequence of global warming. Previous research on the historical and projected hydroclimate of western Canada [1,2,[6][7][8]13,27,40,41] demonstrated the sensitivity of the surface and groundwater hydrology to climate change trends and to inter-annual to decadal scale variability related to teleconnections with large-scale climate patterns.…”

“…The Canadian Prairie provinces of Alberta, Saskatchewan, and Manitoba are known for their extreme seasonal climate and large interannual variability of hydrometeorological parameters [1,2]. Precipitation exhibits the largest spatial and temporal variability [3,4]. The major drivers of the interannual variability are the teleconnections with various large-scale climate patterns, especially El Niño Southern Oscillation (ENSO) [5][6][7][8].…”

Re-Evaluating the Climate Factor in Agricultural Land Assessment in a Changing Climate—Saskatchewan, Canada

“…However, with further warming of the climate of Saskatchewan, modifications to the climate rating in the land assessment model could be considered for the revaluation due in 2025. Due to a high degree of uncertainty in the projections of temperature and highly variable precipitation [33], we cannot speculate as to when the change in these variables will result in a change in crop yields that necessitates a change in the land assessment climate factor rating. However, based on the recent and projected climate changes documented within this paper, at some point a modification in the climate factor rating will be justified, and thus, we suggest that there should be periodic re-evaluation of the climate factor rating.…”