Dynamically downscalled projections of climate change for the Canadian landscape and cryosphere

加拿大地貌和冰冻圈气候变化的动态预测

• 批准号: 570511-2021
• 负责人: Peltier, Richard
• 金额: $ 4.61万
• 依托单位: University of Toronto
• 依托单位国家: 加拿大
• 项目类别: Alliance Grants
• 财政年份: 2021
• 资助国家: 加拿大
• 起止时间: 2021-01-01 至 2022-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=723229
• 关键词: Dynamically; downscalled; projections; climate; change

Most of Canada is either seasonally or permanently covered by snow and in Northern regions, permafrost is a defining characteristic of the landscape. However, current knowledge regarding fundamental propertiesof snow and permafrost, such as how much water is stored in the snowpack and the depth of the active layer of permafrost, is rather poor. At the same time, significant changes are expected in both, snow coverand permafrost, due to global climate change, and it is critical for Canada to understand and quantify the expected changes. Unfortunately, at this point, the ability of global and regional climate models to faithfully simulate snow and in particular permafrost is extremely limited and projections in this area are not considered reliable. This is in part due to the fact that small errors in temperature can cause very large errors in snow and permafrost extent. Direct measurement and satellite observation are important tools in characterizing snow and permafrost in remote regions, but they have limited coverage. Physical computer modeling (simulation) can augment observations in a physically consistent way, and, moreover, can be used to make projections based on scenarios (which is essentially what climate projections are as well). In this project we intent to further develop our ability to simulate and predict snow and permafrost processes by combining a state-of-the-art regional climate model with a new land-surface model, which is capable of simulating such processes. This modeling framework will then be combined with the best available data from Environment and Climate Change Canada and Natural Resources Canada to simulate the historical evolution of snow and permafrost across Canada and to generate quantitative projections of changes in these variables, based on the latest set of global climate projections (CMIP6), which have just been released and upon which the current IPCC assessment report (AR6) is based. This approach is expected to yield reliable estimates of historical snow and permafrost extent in remote regions and the best projections of changes in these processes, that are currently possible.

加拿大的大部分地区要么是季节性的，要么是永久性的积雪覆盖，在北部地区，永久冻土是景观的一个决定性特征。然而，目前关于雪和永久冻土层的基本特性，如积雪中储存了多少水和永久冻土层活跃层的深度，所知甚少。与此同时，由于全球气候变化，预计积雪和永久冻土都将发生重大变化，对加拿大来说，了解和量化预期变化至关重要。不幸的是，在这一点上，全球和区域气候模式忠实地模拟雪，特别是永久冻土的能力极其有限，该地区的预测被认为是不可靠的。这部分是由于温度的小误差可能导致雪和永久冻土范围的大误差。直接测量和卫星观测是表征偏远地区积雪和永久冻土的重要工具，但它们的覆盖范围有限。物理计算机建模（模拟）可以以物理上一致的方式增加观测，而且，可以用来根据情景进行预测（这基本上也是气候预测的内容）。在这个项目中，我们打算通过将最先进的区域气候模型与能够模拟这些过程的新的陆地表面模型相结合，进一步发展我们模拟和预测积雪和永久冻土过程的能力。然后，该建模框架将与加拿大环境与气候变化部和加拿大自然资源部提供的最佳数据相结合，以模拟加拿大各地积雪和永久冻土的历史演变，并根据刚刚发布的最新一套全球气候预测（CMIP6）对这些变量的变化进行定量预测，目前的IPCC评估报告（AR6）就是基于这些预测。这种方法有望对偏远地区的历史积雪和永久冻土范围作出可靠的估计，并对这些过程的变化作出目前可能的最佳预测。