In my previous blog posts1, 2, I’ve shared with you how land, particularly soil moisture, interacts with the atmosphere and modulates climate extremes in current climate1 (Diro et al., 2014) and amplify the projected future warming 2 (Diro and Sushama 2017) over selected regions of North America during summer months. Land, through its snow cover and depth, also plays an important role in modulating climate during cold seasons. The focus of this blog post is therefore, to highlight the result of the recent modelling study on snow-atmosphere coupling and its impact on extremes using the fifth generation Canadian Regional Climate Model (CRCM5).
As part of the investigation, we carried out two CRCM5 simulations driven by ERA-Interim reanalysis for the 1981-2010 period, where snow cover and depth are prescribed (uncoupled) in one simulation while they evolve interactively (coupled) during model integration in the second one. Results indicate systematic influence of snow cover/depth variability on the inter-annual variability of soil and air temperatures during winter and spring seasons. In the coupled simulation, the inter-annual variability of air temperature is found to be larger and snow variability explains around 40-60% of winter temperature variability over the Mid-west, Northern Great Plains and over the Canadian Prairies. The contribution of snow variability reaches even more than 70% during spring and the regions of high snow-temperature coupling extend north of the boreal forests. The dominant process contributing to the snow-atmosphere coupling is the albedo effect in winter, while the hydrological effect controls the coupling in spring. The impact of snow cover/depth is more apparent on extremes. For instance, Figure 1 shows the correlation between cold-spell days and snow cover frequency for spring from reanalysis datasets and CRCM5 simulations. Since the snow variability is suppressed in the uncoupled CRCM5 simulation, the snow cover frequency computed from coupled CRCM5 simulation is used in the correlation analysis of both coupled and uncoupled cases. Both the reanalysis and coupled CRCM5 simulation based estimates show a strong positive correlation (significant at the 0.05 level) between cold spell days and snow cover frequency over the northern Great Plains, the Canadian Prairies and over the Mid-West. In the CRCM5 uncoupled simulation, however, the relationship between snow cover frequency and cold-spell days is substantially reduced over most regions, suggesting that snow anomalies are important, at least, in the amplification of cold spell days over the northern Great Plains, the Canadian Prairies and over the Mid-West U.S. It has to be noted that the difference between coupled and uncoupled simulation is greater than the difference between the reanalysis and the control (coupled) simulations suggesting that the signal is higher than model biases and errors.