Climate Change Canada

 

4.3.2.2: Projected changes and uncertainties

In the future, extreme precipitation is projected to increase in Canada. Averaged for Canada, extreme precipitation with a return period20 of 20 years in the late century climate is projected to become a once in about 10-year event in 2031–2050 under a high emission scenario (RCP8.5) (see Figure 4.20). Beyond mid-century, these changes are projected to stabilize under the low emission scenario (RCP2.6), but to continue under the high emission scenarios (RCP8.5). An extreme event that currently occurs once in 20 years is projected to become about a once in five-year event by late century under the high emission scenario (RCP8.5). In other words, extreme precipitation of a given magnitude is projected to become more frequent. Moreover, the relative change in event frequency is larger for more extreme and rarer events. For example, an event that currently occurs once in 50 years is projected to occur once in 10 years by late 21st century under a high emission scenario (RCP8.5). The amount of precipitation with a certain recurrence interval is projected to increase. The amount of 24-hour extreme precipitation that occurs once in 20 years on average is projected to increase by about 5% under a low emission scenario (RCP2.6) and by 12% under a high emission scenario (RCP8.5) by 2031–2050, and to increase as much as 25% by 2081–2100 under a high emission scenario (RCP8.5). Differences in the projected percentage changes in annual maximum 24-hour precipitation among regions of Canada for the same emission scenario and time period are notably small. The median value for every region is in general within the range of 25th to 75th percentiles of other regions, except under the high emission scenario toward the late century (see Table 4.6).

While results from global climate model projections (such as those above) are useful for impact assessment and adaptation planning, there is an important caveat, especially for extreme precipitation. It is difficult to interpret these projections at local scales. The spatial resolution of global climate models is coarse (typically 100–250 km). The precipitation extremes in a model therefore represent averages over an area of several thousand square kilometres, and so convey different information than may be required for practical applications. More importantly, climate models may not include all of the physical processes that produce local intense rainstorms. This affects the confidence we can have in statistical downscaling products that transform precipitation from coarse resolution models to smaller areas. While regional climate models may operate at much smaller scales, conventional regional climate models, which are used to conduct most of the dynamical downscaling, do not accurately simulate important processes such as convection. These limitations must be kept in mind when using projections for the purpose of regional and local adaptation; in particular, the projected values given by these global or regional climate models should not be interpreted literally as the measured amount of precipitation at a point location.

Estimating changes in short-duration extreme precipitation at a point location is complex because of the lack of observations in many places and the discontinuous nature of precipitation at small scales. Projection of such extreme precipitation is also difficult because of the shortage of simulations by models with a very high resolution that resolve the physical processes that produce those extreme events (Zhang et al., 2017). Nevertheless, multiple lines of evidence support high confidence in projecting an increase in extreme precipitation globally. These lines of evidence include attribution of an observed increase in high-latitude total precipitation to human influence, consistency in projected future increases in extreme precipitation by multiple models, and the physical understanding that warming would result in an increase in atmospheric moisture. It is likely that extreme precipitation will increase in Canada in the future, although the magnitude of the increase is much more uncertain.

 

 

4.4: Attribution Of Extreme Events

Anthropogenic climate change has increased the likelihood of some types of extreme events, such as the 2016 Fort McMurray wildfire (medium confidence) and the extreme precipitation that produced the 2013 southern Alberta flood (low confidence).

There has been an increase in costly extreme weather and climate events worldwide (WMO, 2014) and across Canada (Kovacs and Thistlethwaite, 2014; OAGC, 2016; OPBO, 2016). Much of this rise is due to greater exposure to the effects of such extreme events, as Canada’s population and the value of its supporting infrastructure have both increased considerably. Changes in the intensity and frequency of damaging extreme weather and climate events due to climate change (IPCC, 2013) may also be playing a role. These extreme weather/ climate events attract attention because they are rare and often have notable impacts on our society and economy.

It is generally not feasible to answer the question, Did human-induced climate change cause a particular weather or climate event? Often, that event could have occurred in the absence of human effects. Instead, recent research has focused on whether human activity has influenced the probability of particular weather or climate events or, in some cases, the strength or intensity of the events. As the climate changes, largely due to anthropogenic influences, the likelihood of a particular class of events — all events as extreme as or more extreme than the one defined in the study — also changes (NASEM, 2016). In this sense, an extreme event may be attributable to causes external to the natural climate system. Thus, a new branch of climate science, called event attribution, has emerged that evaluates how the probability or intensity of an extreme event, or more generally, a class of extreme events, has changed as a result of increases in atmospheric GHGs from human activity.

A growing number of extreme events in Canada and worldwide are being examined in this way (e.g., Herring et al., 2017; NASEM 2016). Several of these event attribution analyses are relevant to Canadians (see Table 4.7). Two examples are highlighted in this section, including a description of methods of analysis in Box 4.3.

 

4.4.1: Attribution of two recent events

4.4.1.1: 2013 Southern Alberta flood

In June 2013, an extreme flood event in southern Alberta became Canada’s costliest natural disaster to that date, with significant damage to property and infrastructure throughout the region, including in the City of Calgary. The flood displaced almost 100,000 people and resulted in $6 billion in damage, including $2 billion in insured losses (ECCC, 2017).

A storm producing heavy rainfall over the region triggered the flooding event in the Bow River basin, but a combination of both meteorological and hydrological factors led to the extreme flooding. A recent study (Teufel et al., 2017) assessed the contributions of several of these factors, including anthropogenic GHG emissions.

The study used the Canadian Regional Climate Model (CRCM5) to run large ensembles of high-resolution simulations for North America. To assess the contribution of human climate change, simulations of the model were run using present-day levels of GHGs and also using pre-industrial levels to represent the time before humans had a discernable impact on the climate.

To estimate the probability of the event, return periods were calculated for three-day rainfall totals during May and June exceeding the observed amount. The return period for the observed event in the present-day climate in the Bow River was estimated to be about 60 years. Using climate projections, the return period is estimated to be reduced to about 20 years by the late 21st century (under both an intermediate emission scenario [RCP4.5] and a high emission scenario [RCP8.5]), implying that the type of extreme rainfall that led to the southern Alberta flooding event will become much more common in the future.

Estimated return periods were compared between the present-day and pre-industrial climates, in order to determine the human contribution (see Figure 4.22). Including human GHG emissions resulted in shorter return periods (the event is more likely) for three-day maximum precipitation over the entire southern Alberta region than for pre-industrial levels (see Figure 4.22a). Weather and climate variability tends to be larger for smaller regions, resulting in a smaller ratio between the anthropogenic influence and natural internal variability. Therefore, the anthropogenic influence on the rainfall events over the smaller Bow River basin region was less pronounced (see Figure 4.22b). There is no discernable difference for maximum three-day surface runoff, and thus no anthropogenic influence is detected for this variable (see Figure 4.22c). The authors acknowledge the uncertainties in modelling complex surface hydrological processes and suggest that any increase in rainfall could be offset by decreases in snowpack or frozen ground conditions.

In summary, human influence was detected for the flood-producing rainfall, particularly over the larger region, but human influence could not be detected for the flood itself. A flood event is the result of many factors in addition to the amount of rainfall, including the ground conditions, characteristics of the snowpack, and size and orientation of the storm. As a result, two events with the same rainfall amounts do not necessarily produce floods of the same magnitude. The complex hydrological processes that occur after the rainfall reaches the ground add additional uncertainty which decreases the ability to detect human influence.

Increased GHG emissions, largely due to human activities, result in increased temperatures. Increased temperatures allow more moisture to be available in the atmosphere for precipitation, leading to increased intensity of extreme rainfall events. The 2013 southern Alberta flood was the result of a combination of many factors, and this study demonstrated that human-induced emission of GHGs had increased the likelihood of an extreme amount of precipitation in southern Alberta, at least as large as the amount observed during this event.