Future intensity of precipitation extremes over eastern Canada using very high-resolution modelling

使用超高分辨率模型计算加拿大东部未来极端降水强度

• 批准号: RGPIN-2020-05631
• 负责人: DiLuca, Alejandro
• 金额: $ 2.19万
• 依托单位: Université du Québec à Montréal
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=765313
• 关键词: Future; intensity; precipitation; extremes; over

Precipitation extremes are among the most damaging and costly weather phenomena to impact eastern Canada. During the cold season, snowfall events can produce massive disruptions in ground and air transportation. In summer and shoulder seasons, rainfall extremes can lead to flooding causing extensive economic and environmental damage. Precipitation extremes are expected to change in the future due to various processes often competing with each other. On the one hand, precipitation extremes are expected to increase due to the increase in atmospheric moisture content in response to the warming of the atmosphere. On the other hand, large-scale circulation changes associated with responses to changes in temperature distributions (i.e., baroclinicity and stability) are expected to lead to less extratropical storms and decreases in precipitation extremes. In addition, there are large uncertainties about the role to be played by some fine-scale processes and feedbacks including the extra latent heat being released and microphysical effects due to changes in hydrometeors. Assessing future changes in extreme precipitation thus requires considering several complex processes at spatial and temporal scales that current climate models, either global or standard regional models, are unable to reproduce due to their coarse resolution and somewhat simplistic parameterization of some processes. The overarching aim of my Discovery research is to determine the causes of future changes in the intensity of extreme precipitation events over eastern Canada. The proposed research program is structured according to two primary questions that combine advanced modelling with state-of-the-art observations: 1. How well do the newly developed convection-permitting models represents observed precipitation extremes? 2. What are the projected changes in the intensity of extreme precipitation and how these changes depend on the amount of moisture (thermodynamics) and the type of precipitation (microphysics)? This research will make use of a very high-resolution climate model that explicitly simulates convective processes (convection permitting) and includes a sophisticated representation of cloud and precipitation microphysical processes. To limit the required computational resources, the model is run over a limited area using the dynamical downscaling technique, and for a limited number of events where heavy precipitation has been previously identified. Simulations of future climate will use a hierarchy of future environments where different changes are introduced in a stepwise manner to help isolate key sources of future changes. That is, for the first time, the evolution of damaging storms will be explored at kilometre-scale resolutions using boundary forcings that emulate present and plausible future conditions. Outcomes will support the development of adaptation strategies to mitigate the future impact of extreme precipitation on runoff, freshwater resources and flooding.

极端降水是影响加拿大东部最具破坏性和代价最高的天气现象之一。在寒冷的季节，降雪事件可能会造成地面和空中运输的大规模中断。在夏季和平季，极端降雨量可能导致洪水，造成广泛的经济和环境损失。由于各种过程经常相互竞争，预计未来极端降水量将发生变化。一方面，由于大气变暖导致大气含水量增加，预计极端降水将增加。另一方面，与温度分布变化相关的大尺度环流变化（即，斜压性和稳定性）预计将导致热带风暴减少，极端降水减少。此外，一些小尺度过程和反馈，包括释放的额外潜热和水凝物变化引起的微物理效应所起的作用，存在很大的不确定性。因此，评估极端降水的未来变化需要考虑空间和时间尺度上的几个复杂过程，而目前的气候模式，无论是全球模式还是标准的区域模式，由于分辨率较低，对某些过程的参数化过于简单，无法再现这些过程。 我的发现研究的首要目标是确定加拿大东部极端降水事件强度未来变化的原因。拟议的研究计划是根据两个主要问题，结合联合收割机先进的建模与国家的最先进的观察：1。新开发的允许对流模式在多大程度上代表了观测到的极端降水？2.极端降水强度的预计变化是什么，这些变化如何取决于水分（热力学）和降水类型（微物理学）？这项研究将利用一个非常高分辨率的气候模式，明确模拟对流过程（对流允许），包括云和降水微物理过程的复杂表示。为了限制所需的计算资源，该模型运行在有限的区域使用动态降尺度技术，并为有限数量的事件，强降水已被确定。未来气候的模拟将使用未来环境的层次结构，其中以逐步的方式引入不同的变化，以帮助隔离未来变化的关键来源。也就是说，第一次，破坏性风暴的演变将探索在100%的分辨率使用边界强迫，模拟目前和未来的合理条件。成果将支持制定适应战略，以减轻极端降水对径流、淡水资源和洪水的未来影响。