Rain-on-snow events can cause severe flooding in snow-dominated regions. These are expected to become more frequent in the future as climate change shifts the precipitation from snowfall to rainfall. However, little is known about how winter rainfall interacts with an evergreen canopy and affects the underlying snowpack. In this study, we document 5 years of rain-on-snow events and snowpack observations at two boreal forested sites of eastern Canada. Our observations show that rain-on-snow events over a boreal canopy lead to the formation of melt–freeze layers as rainwater refreezes at the surface of the sub-canopy snowpack. They also generate frozen percolation channels, suggesting that preferential flow is favoured in the sub-canopy snowpack during rain-on-snow events. We then used the multi-layer snow model SNOWPACK to simulate the sub-canopy snowpack at both sites. Although SNOWPACK performs reasonably well in reproducing snow height (RMSE = 17.3 cm), snow surface temperature (RMSE = 1.0 °C), and density profiles (agreement score = 0.79), its performance declines when it comes to simulating snowpack stratigraphy, as it fails to reproduce many of the observed melt–freeze layers. To correct for this, we implemented a densification function of the intercepted snow in the canopy module of SNOWPACK. This new feature allows the model to reproduce 33 % more of the observed melt–freeze layers that are induced by rain-on-snow events. This new model development also delays and reduces the snowpack runoff. In fact, it triggers the unloading of dense snow layers with small rounded grains, which in turn produces fine-over-coarse transitions that limit percolation and favour refreezing. Our results suggest that the boreal vegetation modulates the sub-canopy snowpack structure and runoff from rain-on-snow events. Overall, this study highlights the need for canopy snow property measurements to improve hydrological models in forested snow-covered regions.

In the boreal forest of eastern Canada, winter temperatures are projected to increase substantially by 2100. This region is also expected to receive less solid precipitation, resulting in a reduction in snow cover thickness and duration. These changes are likely to affect hydrological processes such as snowmelt, the soil thermal regime, and snow metamorphism. The exact impact of future changes is difficult to pinpoint in the boreal forest, due to its complex structure and the fact that snow dynamics under the canopy are very different from those in the gaps. In this study, we assess the influence of a low-snow and warm winter on snowmelt dynamics, soil freezing, snowpack properties, and spring streamflow in a humid and discontinuous boreal catchment of eastern Canada (47.29° N, 71.17° W; ≈ 850 m a.m.s.l.) based on observations and SNOWPACK simulations. We monitored the soil and snow thermal regimes and sampled physical properties of the snowpack under the canopy and in two forest gaps during an exceptionally low-snow and warm winter, projected to occur more frequently in the future, and during a winter with conditions close to normal. We observe that snowmelt was earlier but slower, top soil layers were cooler, and gradient metamorphism was enhanced during the low-snow and warm winter. However, we observe that snowmelt duration increased in forest gaps, that soil freezing was enhanced only under the canopy, and that snow permeability increased more strongly under the canopy than in either gap. Our results highlight that snow accumulation and melt dynamics are controlled by meteorological conditions, soil freezing is controlled by forest structure, and snow properties are controlled by both weather forcing and canopy discontinuity. Overall, observations and simulations suggest that the exceptionally low spring streamflow in the winter of 2020–2120 was mainly driven by low snow accumulation, slow snowmelt, and low precipitation in April and May rather than enhanced percolation through the snowpack and soil freezing.

In the Arctic, shrubs are expanding and are covered by snow most of the year. Shrub branches buried in snow absorb solar radiation, reducing irradiance. This modifies the profile of radiative energy absorption in the snowpack and therefore its temperature gradient and metamorphism. Perhaps more importantly, it also reduces photochemical reaction rates and the emission of reactive and climatically active molecules to the atmosphere. No study is currently available to quantify the reduction in photochemical rates caused by shrubs buried in snow. Here, we monitor irradiance in the photochemically active range using a filter at 390 ± 125 nm in snow-covered Alnus incana (gray alders) shrubs in the boreal forest near Université Laval and on nearby grassland during a whole winter by placing light sensors at fixed heights in shrubs and on grassland and observed that irradiance in shrubs was greatly reduced. We performed radiative transfer simulations, testing the hypothesis that shrub branches behave as homogeneous absorbers such as soot. At 390 nm, dense shrub branches reduce irradiance similarly to about 140 ppb of soot. Since ice is much more absorbent at longer wavelengths, we also used a filter to monitor the 715–1000 nm wavelengths (effective 760 nm) to investigate the spectral dependence of shrub impacts on radiative energy absorption. Because of competing ice absorption at 760 nm, the effect of shrubs was much weaker than at 390 nm. We calculate that a high branch density will reduce photochemical reaction rates integrated over the whole snowpack by about a factor of 2. This may affect the composition of the lower-Arctic atmosphere in winter and spring in numerous ways, including a lower oxidative capacity, lower level of nitrogen oxides and modified secondary aerosol production. Climatic effects are expected from these compositional changes.