ABSTRACT

Changes in mass, extent, duration, and physical properties of snow are key elements for studying associated climate change feedbacks in northern regions. In this study, we analyzed snowpack physical properties along a ‘mega’ transect from 47°N to 83°N (4,000 km) in northeastern Canada, which includes marked transitions between ecozones from boreal forest to subarctic and arctic ecosystems. Our unique dataset of 391 detailed snowpits acquired over the last 20 years, complemented with snow data from weather stations, shows that snowpack properties such as snow water equivalent, snow depth, density, grain size and basal depth hoar fraction (DHF) are strongly linked to vegetation type. Based on these results, we propose an updated classification of snow types in three classes: boreal forest snow (47–58°N), tundra snow (58–74°N) and polar desert snow (74–83°N), which is more appropriate to the study area than the general north hemisphere classification commonly used. We also show that shrub presence along the transect contributes to a significant increase in DHF development which contributes most strongly to the thermal insulation properties of the snowpack. Overall, our analysis suggests that snow–vegetation interactions have a positive feedback effect on warming at northern latitudes.

摘要

雪的质量、范围、持续时间和物理特性的变化是研究北方地区相关气候变化反馈的关键要素。在这项研究中，我们分析了加拿大东北部从 47°N 到 83°N（4,000 公里）的“巨型”断面沿线的积雪物理特性，其中包括从北方森林到亚北极和北极生态系统的生态区之间的显着过渡。我们在过去 20 年中获得的 391 个详细雪坑的独特数据集，辅以气象站的积雪数据，表明积雪特性，如雪水当量、雪深、密度、粒度和基础深度白化率 (DHF) 密切相关到植被类型。基于这些结果，我们提出了三类雪类型的更新分类：北方森林雪（47-58°N），苔原雪（58-74°N）和极地沙漠雪（74-83°N），这比常用的一般北半球分类更适合研究区域。我们还表明，沿横断面的灌木有助于显着增加 DHF 的发展，这对积雪的隔热性能贡献最大。总体而言，我们的分析表明，雪-植被相互作用对北纬地区的变暖具有正反馈作用。