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.

本研究的总体目的是开发创新的方法，以在广泛的尺度上建模两个基本水文过程（降水和温度），以便在气候变化框架内准确描述这些过程。更具体地说，将开发用于模拟短期降水和温度时间序列的统计缩减模型，以尊重在一个区域中给定位点上观察到的这些变量的时间变化，以及它们对整个区域的空间依赖性。在这种情况下，基于比例不变方法以及多元统计和多维随机技术的组合使用混合方法的使用是有用的，因为在不同的时间和空间尺度上，所提出的模型应该能够说明重要的统计属性（平均，可变性，趋势和极端）。此外，这些模型的参数可以在适当的气候变量上进行调节，以便可以进行灵敏度分析以研究，例如，随着模型参数根据气候模式的某些变化而变化，极端沉淀和温度的频率将如何变化。拟议的研究专门涉及由于涉及大量投资而受到大量关注的问题。例如，最近对加拿大经济的可衡量贡献的估计每年从7.5至230亿加元不等。但是，气候变异性会压力加拿大的水系统，甚至导致水短缺。因此，预计这项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，将在气候变化的情况下为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性策略并强大的缓解政策。