Modeling of Short-Duration Precipitation and Temperature Processes for Climate-Related Impact Assessment Studies in Urban Areas

城市地区气候相关影响评估研究的短期降水和温度过程建模

• 批准号: 6833-2012
• 负责人: Nguyen, VanThanhVan
• 金额: $ 1.53万
• 依托单位: McGill University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2015
• 资助国家: 加拿大
• 起止时间: 2015-01-01 至 2016-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=568492
• 关键词: Modeling; Short; Duration; Precipitation; Temperature

The overall objective of the present study is to develop innovative methods for modeling the two fundamental hydrologic processes (precipitation and temperature) over a wide range of scales in order to provide an accurate description of these processes within the framework of climate change. More specifically, statistical downscaling models for simulating short-duration precipitation and temperature time series will be developed to respect the observed temporal variability of these variables at a given site in a region as well as their spatial dependence over the entire region. The use of a hybrid approach based on a combination of scale-invariance methods and multivariate statistical and multidimensional stochastic techniques is useful in this case because the proposed models should be able to account for important statistical properties (average, variability, trend, and extreme) of the underlying processes over different temporal and spatial scales. In addition, the parameters of these models could be conditioned on suitable climate variables so that sensitivity analyses could be performed to study, for instance, how the frequency of extreme precipitations and temperatures would change as the model parameters change according to some variation in climate patterns. The proposed research deals exclusively with issues that have been received considerable attention due substantial investment involved. For instance, recent estimates of water's measurable contribution to the Canadian economy range from $7.5 to $23 billion annually. However, climate variability can stress Canada's water systems and even lead to water shortages. It is hence expected that results of this research will enhance our collective understanding of climate variations and their hydrological effects, will provide improved tools and methods for more effective water management in the context of a changing climate, and ultimately will help policy-makers in developing appropriate adaptive strategies and robust mitigating policies.

本研究的总体目标是开发在大范围尺度上模拟两个基本水文过程（降水和温度）的创新方法，以便在气候变化的框架内对这些过程提供准确的描述。更具体地说，将开发用于模拟短持续时间降水和温度时间序列的统计降尺度模式，以尊重在一个区域的给定地点观测到的这些变量的时间变率以及它们在整个区域的空间依赖性。在这种情况下，基于尺度不变性方法与多元统计和多维随机技术相结合的混合方法的使用是有用的，因为所提出的模型应该能够解释不同时空尺度上潜在过程的重要统计特性（平均、变异、趋势和极端）。此外，这些模式的参数可以以适当的气候变量为条件，以便进行敏感性分析，以研究极端降水和温度的频率如何随着模式参数根据气候模式的某些变化而变化。拟议的研究只涉及由于涉及大量投资而受到相当重视的问题。例如，最近估计水对加拿大经济的可衡量贡献每年在75亿至230亿美元之间。然而，气候变化会给加拿大的水系统带来压力，甚至导致水资源短缺。因此，预计本研究的结果将增强我们对气候变化及其水文影响的集体理解，将为气候变化背景下更有效的水管理提供改进的工具和方法，并最终将帮助决策者制定适当的适应战略和强有力的缓解政策。