How is Climate Change Altering Alberta's Moisture Regime?

Emma Kary, Megan Ciocchetto, Christopher Chan, Leah Feng

Home

Summary

When examining the impacts of climate change on weather patterns, changes in precipitation has the potential to alter many environmental systems. Through looking at annual changes in mean annual precipitation, precipitation as snow, and climate moisture deficit, future management techniques can be designed to mitigate possible negative impacts. To determine patterns, a map of Alberta was divided with emphasis on four specific ecoregions. Within each ecoregion, a 20km by 20km grid was placed over and variables were measured at each grid intersection. From here, timeseries graphs were created to view overall historical trends. A regression analysis was completed to determine significance within each ecoregion among each variable (MAP, PAS, and CMD). Significant results were present in within each ecoregion except the Aspen Parkland. Significant results were present in within each ecoregion except the Aspen Parkland. Significant results were viewed within the Boreal Transition (PAS), Mid-Boreal Uplands (MAP, PAS, and CMD), and Western Alberta Upland (MAP, PAS, and CMD).

________________________________________________________________

Introduction

Background/Rationale

Weather conditions are drastically changing with increases in the frequency of warm/cold, wet/dry, and calm/severe weather. Specifically within Alberta, there is projected to be a 50% increase in the number of very wet days (>25mm in 24 hours) with a 5-10% increase in September to April precipitation (Hayhoe & Stoner, 2019). Additionally, terrestrial snow cover is changing across Canada, and is significantly decreasing in certain monthly time periods within Alberta (Figure 2). When considering Alberta winters, average temperatures are shown to increase across all seasons, with greater increases during the winter season; therefore causing lower amounts of snow cover (Biodiversity Management and Climate Change Adaptation (BMCCA), 2020; Mudryk et al., 2018). These changes are important to consider because changing climate patterns can indicate changes in magnitude and timing of streamflow, frequency of extreme weather events (ie droughts and floods), and available water amounts in certain watersheds (Schneider, 2013). Additionally, snow plays an important role in cooling the climate system as it is highly reflective and insulates underlying snow (Mudryk et al., 2018).

Figure 1 – Historical and projected mean annual temperature changes within various time periods between 1961-2100 (BMCAA,2020). 

A more granular understanding of changes to moisture regimes is needed. This is especially true for forests, which comprise a large proportion of Alberta’s land-use and provides significant ecosystem services as well as direct economic benefits to the province. Our goal is to characterize how precipitation patterns have changed and how they might change in the future as the climate changes.

Figure 2 – Changes in snow cover fraction across Canada from 1981-2015 (Mudryk et al., 2018). Changes are recorded in different seasons represented by JFM (Jan, Feb, and Mar), AMJ (Apr, May, Jun), JAS (Jul, Aug, Sep), and OND (Oct, Nov, Dec).Stippling on the map represented significance at the 90th percentile.

Research Objectives

As part of the research objectives, the goal is to examine historical precipitation records within certain ecoregions in Alberta in order to determine current and future implications. This will be achieved through comparing mean annual precipitation (MAP in mm), precipitation as snow (PAS in mm), and climate moisture deficit (CMD in mm) across four Alberta ecoregions. The purpose of the study is to determine current and future projections of precipitation (average annual precipitation and precipitation as snow) and how this may influence climate moisture deficit. Through studying the climatic moisture deficit, we will also be able to compare any amount of threat within a certain ecoregion. CMD measures the difference between precipitation and evapotranspiration, therefore altering how landscapes handle changing climates and changes in precipitation (Wang et al., 2012). From here, we can then apply findings to possible future management and mitigation regimes.

Expected Results

The expected results are assumed to coincide with previous research that provide projections that precipitation overall is increasing within Alberta while the amount of precipitation as snow is decreasing. Alternative results could imply that there are no significant changes within precipitation regimes within the selected Alberta ecoregions. Ultimately, the results may influence the future climate and watershed management regimes within Alberta.

________________________________________________________________

Methods

________________________________________________________________

Data

Data was extracted using the Climate WNA v4.62 software package available  here .

Within the simplified data table (Table 1), the sampling units consist of year, ID1, ID2 (which demonstrates the ecoregion), latitude, longitude, MAP, PAS, and CMD. Experimental units are millimeters (mm) for MAP, PAS, and CMD. The predictor variables include the ecoregion (location) and year while response variables include MAP, PAS, and CMD. Within the experiment the predictor variable(s) are being observed (changes throughout a timescale) and contain continuous and categorical variables (year and location respectively).

To mitigate errors within the data, real historical data was used between the years 1901-2009 and projected data was only used for the years 2020, 2050, and 2080, all using the same program. Therefore, error is minimized for future projections to 2020, 2050, and 2080 through using the same projection program. Additionally, data was sorted and organized before input into the R coding program for graph creation and analysis.

Table 1. Simplified data table used to conduct analyses where variables are represented through ID2 (ecoregion), MAP (mean annual precipitation in mm), and PAS (precipitation in snow in mm), and CMD (climate moisture deficit in mm). Historical data is represented within the table. ID2 abbreviations available in Methods.

Exploratory Graphics

Exploratory graphics (Figures 3, 4, and 5) represent the raw data associated with historical variations among mean annual precipitation (MAP), precipitation as snow (PAS), and climate moisture deficit (CMD) from 1901-2009. From here, a linear regression model was applied to determine significant changes within ecoregions among each variable. 

Figure 3. Exploratory graphics of raw data of mean annual precipitation (MAP) among the four ecoregions (AP = Aspen Parkland, BT = Boreal Transition, MBU = Mid-Boreal Upland, and WAU = Western Alberta Upland).

Figure 4. Exploratory graphics of raw data of precipitation as snow (PAS) among the four ecoregions (AP = Aspen Parkland, BT = Boreal Transition, MBU = Mid-Boreal Upland, and WAU = Western Alberta Upland).

Figure 5. Exploratory graphics of raw data of climate moisture deficit (CMD) among the four ecoregions (AP = Aspen Parkland, BT = Boreal Transition, MBU = Mid-Boreal Upland, and WAU = Western Alberta Upland).

________________________________________________________________

Results & Discussion

Figure 6. Historical mean annual precipitation (MAP) and projected values among four Alberta ecoregions (from 1901-2009). Historical data was used to create a regression line to project future values from historical values. Projected regression values were then compared to projected values from the ClimateWNA program for the 2002s, 2050s and 2080s.

Figure 7. Historical precipitation as snow (PAS) and projected values among four Alberta ecoregions (from 1901-2009). Historical data was used to create a regression line to project future values from historical values. Projected regression values were then compared to projected values from the ClimateWNA program for the 2002s, 2050s and 2080s.

Figure 8. Historical climate moisture deficit (CMD) and projected values among four Alberta ecoregions (from 1901-2009). Historical data was used to create a regression line to project future values from historical values. Projected regression values were then compared to projected values from the ClimateWNA program for the 2002s, 2050s and 2080s.

Results

A regression analysis was completed in order to determine significance within trends among ecoregions. P-values were compared to an alpha value of 0.05, creating a 95% confidence interval. No significant results were viewed within the Aspen Parkland ecoregion.

Mean Annual Precipitation

Significant results were shown in both the Mid-Boreal Uplands (p= 0.00727) and in the Western Alberta Upland (p=0.004381) (Table 2). Neither of the Aspen Parklands or Boreal Transition displayed significant results (p= 0.3796 and p=0.2275 respectively).  Trends within the graph represent overall increases within mean annual precipitation but are relatively higher than projected data points from the ClimateWNA software (Figure 6).

Precipitation as Snow 

Significant results were shown in the Boreal Transition (p=0.01912), Mid-Boreal Upland (p=0.01843), and Western Alberta Upland (p=0.01309) (Table 2). The Aspen Parkland ecoregion did not display significant results (p=0.1359). Significant results were shown in the Boreal Transition (p=0.01912), Mid-Boreal Upland (p=0.01843), and Western Alberta Upland (p=0.01309) (REF FIG MAP). The Aspen Parkland ecoregion did not display a significant trend (p=0.1359). Trends within the graph represent overall decreases in precipitation as snow but regression values are relatively higher than projected data points from the ClimateWNA software (Figure 7).

Climate Moisture Deficit 

Significant results were shown in both the Mid-Boreal Uplands (p=0.02871) and in the Western Alberta Upland (p=0.002111) (Table 2). Neither of the Aspen Parkland or Boreal transition ecoregions displayed significant results (p=0.3716 and p=0.1498 respectively). Trends within the graph represent overall slight decreases in climate moisture deficit but regression values are relatively much lower  than projected data points from the ClimateWNA software (Figure 8).

Table 2. Regression analysis results, p-values and R-squared values were determined using through the R coding language (R Coding Team, 2019). An alpha level of 0.05 was used to determine significant p-values which are highlighted in light grey.

Discussion

When it comes to the different ecoregions, all mainly displayed some form of significant change within either MAP, PAS, and/or CMD. Although the Aspen Parkland ecoregion did not face any significant changes among any variable, the other three ecoregions experienced significant changes. Significant changes within mean annual precipitation occurred within the Mid-Boreal Upland and Western Alberta Upland. Possible future studies could include comparing specific variables between each other to test for significant interactions (i.e., PAS and MAP within the Aspen Parkland ecoregion). Additionally, future studies can be used to determine significance between the regression projections for future variable values (MAP, PAS, and CMD) and projected values from the ClimateWNA software.

As global temperatures rise, moisture regimes are also expected to change as well. More specifically, changes among mean annual precipitation and precipitation are expected to occur. One result of less precipitation as snow is a shortage in water supply due to loss of streamflow support throughout summer months. Additionally, it can also lead to drought and increased risk of wildfires in Alberta's forest regions. Therefore, when it comes to management systems, existing methods are now considered to be less reliable when considering future conditions (Alberta Water Portal Society, 2019). Therefore, when considering the future of water management within Alberta, the idea of adaptive management is becoming more common. Additionally, by examining the future projections, appropriate precautions, especially involving risk, can be taken in attempts to mitigate negative impacts (ie floods). Also, due to changing moisture regimes, we can then expect differences within the ecoregions of Alberta, influencing each differently. Therefore, overall adaptive management regimes that promote flexibility and proactive are deemed beneficial for the future of Alberta.

Conclusion

Main takeaways from our study include:

Some future avenues of investigation include:

________________________________________________________________

Literature Cited:

Alberta Water Portal Society. (2019). The history of climate in Alberta and effects of climate change on Alberta's watersheds. Retrieved from: https://albertawater.com/history-and-effects-of-climate-change-on-alberta-s-watersheds

Biodiversity Management and Climate Change Adaptation (BMCCA). (2020). About Climate Change. Retrieved December 12, 2020, from http://biodiversityandclimate.abmi.ca/about-climate-change/

Hayhoe, K., Stoner, A. (2019). Alberta's Climate Future Report. Retrieved from: https://open.alberta.ca/dataset/89a69583-a11b-4e31-a857-b311ab6563cc/resource/17ce2d24-ba7b-466c-acd9-33a2cf6beb69/download/aep-alberta-climate-report-arc.pdf

Mudryk, L. R., Derksen, C., Howell, S., Laliberté, F., Thackeray, C., Sospedra-Alfonso, R., . . . Brown, R. (2018). Canadian snow and sea ice: Historical trends and projections. The Cryosphere, 12(4), 1157-1176. doi:10.5194/tc-12-1157-2018

R Core Team (2019). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/.

Schneider, R. R. (2013). Alberta’s Natural Subregions Under a Changing Climate: Past, Present, and Future, 97. Retrieved from http://biodiversityandclimate.abmi.ca/wp-content/uploads/2015/01/Schneider_2013_AlbertaNaturalSubregionsUnderaChangingClimate.pdf

Wang, T., Hamann, A., Spittlehouse, D. L., & Murdock, T. Q. (2012). ClimateWNA—High-Resolution Spatial Climate Data for Western North America. Journal of Applied Meteorology and Climatology, 51(1), 16-29. doi:10.1175/jamc-d-11-043.1

ClimateWNA v4.62 software package

https://sites.ualberta.ca/~ahamann/data/climatewna.html

Introductory Winter Photo

https://www.amatravel.ca/articles/getaway-to-the-rockies-this-winter

Figure 1 – Historical and projected mean annual temperature changes within various time periods between 1961-2100 (BMCAA,2020). 

Figure 2 – Changes in snow cover fraction across Canada from 1981-2015 (Mudryk et al., 2018). Changes are recorded in different seasons represented by JFM (Jan, Feb, and Mar), AMJ (Apr, May, Jun), JAS (Jul, Aug, Sep), and OND (Oct, Nov, Dec).Stippling on the map represented significance at the 90th percentile.

Table 1. Simplified data table used to conduct analyses where variables are represented through ID2 (ecoregion), MAP (mean annual precipitation in mm), and PAS (precipitation in snow in mm), and CMD (climate moisture deficit in mm). Historical data is represented within the table. ID2 abbreviations available in Methods.

Figure 3. Exploratory graphics of raw data of mean annual precipitation (MAP) among the four ecoregions (AP = Aspen Parkland, BT = Boreal Transition, MBU = Mid-Boreal Upland, and WAU = Western Alberta Upland).

Figure 4. Exploratory graphics of raw data of precipitation as snow (PAS) among the four ecoregions (AP = Aspen Parkland, BT = Boreal Transition, MBU = Mid-Boreal Upland, and WAU = Western Alberta Upland).

Figure 5. Exploratory graphics of raw data of climate moisture deficit (CMD) among the four ecoregions (AP = Aspen Parkland, BT = Boreal Transition, MBU = Mid-Boreal Upland, and WAU = Western Alberta Upland).

Figure 6. Historical mean annual precipitation (MAP) and projected values among four Alberta ecoregions (from 1901-2009). Historical data was used to create a regression line to project future values from historical values. Projected regression values were then compared to projected values from the ClimateWNA program for the 2002s, 2050s and 2080s.

Figure 7. Historical precipitation as snow (PAS) and projected values among four Alberta ecoregions (from 1901-2009). Historical data was used to create a regression line to project future values from historical values. Projected regression values were then compared to projected values from the ClimateWNA program for the 2002s, 2050s and 2080s.

Figure 8. Historical climate moisture deficit (CMD) and projected values among four Alberta ecoregions (from 1901-2009). Historical data was used to create a regression line to project future values from historical values. Projected regression values were then compared to projected values from the ClimateWNA program for the 2002s, 2050s and 2080s.

Table 2. Regression analysis results, p-values and R-squared values were determined using through the R coding language (R Coding Team, 2019). An alpha level of 0.05 was used to determine significant p-values which are highlighted in light grey.