Monitoring and Modelling Lake Ice in Canada

加拿大湖冰监测和建模

• 批准号: RGPIN-2015-05316
• 负责人: Brown, Laura
• 金额: $ 1.97万
• 依托单位: University of Toronto
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2018
• 资助国家: 加拿大
• 起止时间: 2018-01-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=646370
• 关键词: Monitoring; Modelling; Lake; Ice; Canada

Canada's lakes are a dominant part of the landscape and experience ice cover in most regions of the country. Lake ice is sensitive to climate variability and changes occurring in lake ice regimes in recent years have been primarily noted through modelling and satellite data since the ground based observation network in Canada essentially ceased to exist by the late 1990s. Satellite imagery can be very useful for monitoring the timing of ice-on/off, however, it currently has limited use for determining ice thickness. Lake ice models present a suitable option for examining ice duration and thickness processes as well as climate influenced changes to the ice cover of lakes. Complicating both modelling and monitoring efforts are the spatial aspects of lakes. Ice cover may not form or decay uniformly across a lake surface, or across lakes in close proximity. This is due to the ice formation and decay being affected by the lake size and shape, as well as the overlying snow cover, which can result in spatially varying ice thickness.***The overall objective of this proposal is to investigate the effects of lake size and shape on ice duration and thickness across the temperate, subarctic and High Arctic climate regions and address these effects in the Canadian Lake Ice Model. The chosen lakes are near Haliburton ON, Churchill MB, and Cambridge Bay NU and were selected based on their accessibility and potential for long term monitoring. Automated weather stations will be set up in each region to provide local climate conditions for model input, ice thickness sensors will be installed to monitor ice growth and decay, snow and ice thickness will be measured manually throughout the winter (ON site), and a network of outdoor digital cameras will be installed. Multiple cameras will provide the ability to monitor ice conditions on different sections of the lakes where the shape influences on the snow and ice may differ. Larger lakes will also be monitored using available satellite data. The collected data will be used to improve the effects of snow cover on modelled ice thickness, as well as to develop a technique to address the effect of lake size on the ice-off dates within the lake ice model. ***This research will contribute new knowledge on spatial patterns of lake ice at a smaller scale than satellites can capture. It will also lead to improvements in the lake ice model with respect to the morphometry of lakes and how climatic regions affect the growth/decay of lake ice. This research is of interest to researchers in hydrology and climatology, as well as biology and limnology with respect to under ice habitat and changing ice conditions on the lake ecosystem. Finally, improving the ability to accurately model ice thickness can contribute to improved predictions in areas such as recreation and transportation (e.g. ice roads), especially in the context of future climate scenarios.********

加拿大的湖泊是景观的主要部分，在该国大部分地区都有冰盖。湖冰对气候变化很敏感，近年来湖冰状况发生的变化主要是通过建模和卫星数据注意到的，因为加拿大的地面观测网络到1990年代末基本上已不复存在。卫星图像对于监测冰的出现/消失的时间非常有用，但是，目前它在确定冰的厚度方面的用途有限。湖冰模型为研究冰的持续时间和厚度过程以及气候影响下的湖泊冰盖变化提供了一个合适的选择。使建模和监测工作复杂化的是湖泊的空间方面。冰盖的形成或衰减可能不会均匀地分布在湖面上，也不会均匀地分布在附近的湖泊上。这是由于冰的形成和衰减受到湖泊大小和形状的影响，以及覆盖的积雪，这可能导致空间上不同的冰厚度。本提案的总体目标是调查湖泊大小和形状对温带、亚北极和高北极气候区域冰持续时间和厚度的影响，并在加拿大湖冰模型中解决这些影响。所选湖泊靠近哈利伯顿ON、丘吉尔MB和剑桥湾NU，并根据其可达性和长期监测潜力进行选择。 将在每个地区建立自动气象站，为模型输入提供当地气候条件，将安装冰厚度传感器以监测冰的生长和衰减，整个冬季将人工测量雪和冰的厚度（现场），并将安装户外数码相机网络。 多个摄像机将提供监测湖泊不同部分冰况的能力，这些部分的形状对冰雪的影响可能不同。还将利用现有的卫星数据对较大的湖泊进行监测。 收集的数据将用于改善积雪对模拟冰厚度的影响，以及开发一种技术，以解决湖泊大小对湖冰模型内的封冰日期的影响。* 这项研究将有助于在比卫星可以捕获的更小的尺度上了解湖冰的空间模式。它还将导致湖冰模型在湖泊形态学方面的改进，以及气候区域如何影响湖冰的生长/衰减。 这项研究是感兴趣的水文学和气候学，以及生物学和湖沼学的研究人员在冰下栖息地和不断变化的冰条件对湖泊生态系统。最后，提高准确模拟冰厚的能力有助于改善娱乐和交通（例如冰路）等领域的预测，特别是在未来气候情景的背景下。