Investigation of vegetation-snow-permafrost-climate interactions for improved predictions of the permafrost thermal regime

全球变暖导致的永久冻土融化可能会以二氧化碳和甲烷的形式向大气中释放数十pg的碳。在气候变暖的情况下，这可能构成一个重大的积极反馈。此外，永久冻土融化对北方社区和北极的发展也有重大影响。因此，量化永冻土的演化速度并减轻其影响是一个具有科学、社会和经济利益的问题。今天，由于对决定永冻土热状况的过程了解不够，因此无法准确预测永冻土的融化。特别是，陆面模型忽略或过度简化了许多关键过程，如雪和表层土壤的物理性质。尤其是雪、表层土壤和植被层的导热系数，以及这些变量如何依赖于植被类型。由于雪是限制多年冻土冬季冷却的绝缘层，因此必须准确地量化积雪对地表能量收支的影响。我们建议在亚北极和北极建立雪仪器站，连续监测雪和表层土壤的物理性质，特别是它们的导热系数。为此，我们将使用我们在阿尔卑斯山测试过的新型系统。我们还将通过测量雪面的比表面积来研究雪面的辐射收支，重点是光散射。我们选择了从北方森林到高北极冻土带的地点。所获得的数据将用于在雪-土壤耦合模式中产生新的参数化，该模式将被耦合到LSM以预测变暖情景下永久冻土的热演化。已经建立了与极地植被和永冻土专家的合作，特别是那些参与NSERC资助的适应项目的专家。已经开始与建模小组(法国气象局和加拿大气候模拟中心)合作，我们还将作为这两个小组之间的纽带。

The thawing of permafrost caused by global warming could release tens of Pg of carbon in the form of CO2 and CH4 to the atmosphere. This could constitute a major positive feedback in a warming climate. Furthermore, permafrost thawing has a significant impact on Northern communities and on the development of the Arctic. Quantifying the rate of permafrost evolution and mitigating its effect is therefore an issue of scientific, societal and economic interest.Today, accurate predictions of permafrost thawing are not possible because processes that determine the permafrost thermal regime are insufficiently understood. In particular, land surface models (LSMs) neglect or oversimplify many key processes, such as snow and top soil physical properties. This is especially the case for the thermal conductivity of the snow, top soil and vegetation layers, and how these variables depend on the type of vegetation. Since snow acts as an insulating layer that limits permafrost winter cooling, effect of the snowpack on the surface energy budget must be quantified accurately. We propose to set up snow instrumental stations in the subarctic and Arctic to monitor continuously snow and top soil physical properties, in particular their thermal conductivity. We will use novel systems that we have tested in the Alps for that purpose. We will also study the radiative budget of the snow surface, focussing on light scattering, by measuring the specific surface area of surface snow.We have selected sites ranging from the boreal forest to high arctic tundra. The data obtained will serve to produce novel parameterizations in a coupled snow-soil model, which will be coupled to LSMs to predict the thermal evolution of permafrost under warming scenarios. Collaborations with experts in polar vegetation and permafrost, in particular those involved in the NSERC-funded ADAPT project have been established. Collaborations with modelling groups (Meteo France and the Canadian Centre for Climate Modelling) have been initiated and we will also act as a link between both these groups.