Abstract

The impact of snow-atmosphere coupling on climate variability and extremes over North America is investigated using modeling experiments with the fifth generation Canadian Regional Climate Model (CRCM5). To this end, two CRCM5 simulations driven by ERA-Interim reanalysis for the 1981–2010 period are performed, 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 and snow depth variability on the inter-annual variability of soil and air temperatures during winter and spring seasons. Inter-annual variability of air temperature is larger in the coupled simulation, with snow cover and depth variability accounting for 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. Snow cover/depth variability at different locations is also found to affect extremes. For instance, variability of cold-spell characteristics is sensitive to snow cover/depth variation over the Mid-west and Northern Great Plains, whereas, warm-spell variability is sensitive to snow variation primarily in regions with climatologically extensive snow cover such as northeast Canada and the Rockies. Furthermore, snow-atmosphere interactions appear to have contributed to enhancing the number of cold spell days during the 2002 spring, which is the coldest recorded during the study period, by over 50%, over western North America. Additional results also provide useful information on the importance of the interactions of snow with large-scale mode of variability in modulating temperature extreme characteristics.

Highlights

  • Several studies, including the Global Land Atmosphere Coupling Experiment (GLACE, Guo et al 2006; Koster et al 2006), have illustrated that land, in particular soil moisture, plays an important role in modulating the climate of selected regions such as the Great Plains during summer

  • The maximum duration of cold-spell/warmspell event is computed for each grid point. As it will be shown later snow-atmosphere coupling is stronger during spring season, and all the analysis related to temperature extremes are restricted to the March to May (MAM) months

  • This study presents the snow-atmosphere coupling characteristics over North America and its impact on selected extreme temperature characteristics

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Summary

Introduction

Several studies, including the Global Land Atmosphere Coupling Experiment (GLACE, Guo et al 2006; Koster et al 2006), have illustrated that land, in particular soil moisture, plays an important role in modulating the climate of selected regions such as the Great Plains during summer. The challenge with observational studies is that it is usually difficult to disentangle the atmospheric response to snow anomalies (or variability) from other large-scale forcings. In this context, carefully designed global and/ or regional climate model experiments can be used to. Isolate the effect of snow on atmosphere from all other potential factors Such previous modeling studies have followed different approaches. Some studies have investigated the influence of snow on mean atmospheric circulation by prescribing idealized or realistic snow cover/depth anomalies (e.g., Cohen and Entekhabi 2001; Gong et al 2004; Sobolowski et al 2010), while other studies focused on understanding the role of snow variation in modulating intra-seasonal (Xu and Dirmeyer 2011, 2013) or inter-annual atmospheric variability (e.g., Yang et al 2001; Kumar and Yang 2003; Dutra et al 2011)

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