Climate Change Impacts on Mountain Snowpacks

Canada 1 Water Collaborator Research Highlight

Mortezapour, M., Menounos, B., Jackson, P. L., & Erler, A. R. (2022). Future Snow Changes over the Columbia Mountains, Canada, using a Distributed Snow Model. In Climatic Change (Vol. 172, Issues 1–2). Springer Science and Business Media LLC. https://doi.org/10.1007/s10584-022-03360-9

We’re happy to highlight a new publication co-authored by Aquanty’s senior data scientist, Dr. Andre Erler, focused on the expected impacts that climate change will have on snow depth in mountainous regions. This research is highly relevant to the Canada 1 Water modelling initiative, since C1W relies solely on regional climate projections and is employing a very similar model configuration (WRF version 4). At the same time, climate change impacts on snow and water resources are a major focus of the project as well. The WRF simulations used in this paper are described in detail in Erler & Peltier (2017) and can be seen as a regional precursor to the C1W simulations.

Mountain snowpacks act to store precipitation during winter, and later, as the weather warms, melting snow provides water supply for many downstream communities in western North America. Projections of how future climate change will affect snowmelt water resources are thus of high interest to policy makers. Areas of British Columbia (BC) have warmed at a rate twice the global average between 1950 and 2010; this warming has shrunk glaciers and thinned seasonal snowpacks during the twentieth century.

Figure 1. Averaged snow water equivalent (SWE) changes between future simulations and reference period for end of century using dynamically downscaled (DD) and statistically downscaled (SD) forcing data averaged over the entire water year

In this study, we investigate how future climate could affect the distribution of snow depth and snow water equivalent (SWE) in the Columbia Basin using a physically based model that simulates the accumulation and melt of snow. The model is either forced by fully dynamical high-resolution regional climate projections generated using the Weather Research and Forecasting (WRF) model (version 3) or statistically downscaled temperature and precipitation from global climate models provided by the Pacific Climate Impacts Consortium (PCIC 2019). The simulations are done for a historical period (1979–1994) and two future projection periods (2045–2059, 2085–2099) based on the RCP 8.5 climate scenario.

Climate change has resulted in an overall decrease in low-elevation snow cover and snow duration in recent decades. The results presented here indicate that this trend will continue and that future snowpack losses may depend strongly on elevation and season. Snow depth and snow water equivalent (SWE) will be most affected for elevations below 2000 m asl, with a reduction of more than 60% in the end-century scenario, while losses above 2000 m may be significantly smaller.

In this context it is interesting to note that SWE losses and in particular their dependence on elevation are much more pronounced in the projections based on the dynamical regional climate model (WRF) than the one using statistically downscale data from global climate models. The reason is that high-resolution regional climate models resolve complex terrain much better than global models and consequently can represent the dynamic feedback between temperature and snow cover much better.

References

Link to this paper: https://link.springer.com/article/10.1007/s10584-022-03360-9

Link to Erler & Peltier (2017): https://journals.ametsoc.org/view/journals/clim/30/20/jcli-d-16-0870.1.xml