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创新方法，在广泛的尺度上模拟两个基本的水文过程（降水和温度），以便在气候变化的框架内提供这些过程的准确描述。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降尺度模型，以考虑到在一个区域某一地点观测到的这些变量的时间变异性及其在整个区域的空间依赖性。在这种情况下，基于尺度不变方法和多元统计和多维随机技术的组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在不同的时间和空间尺度上解释基本过程的重要统计特性（平均值，变异性，趋势和极端）。此外，这些模式的参数可以适当的气候变量为条件，以便进行敏感性分析，研究例如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。拟议的研究专门处理的问题，已受到相当大的关注，由于大量的投资参与。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供水系统带来压力，甚至导致水资源短缺。因此，预计这项研究的结果将提高我们对气候变化及其水文影响的集体理解，将提供更好的工具和方法，在不断变化的气候背景下进行更有效的水资源管理，并最终帮助决策者制定适当的适应战略和强有力的缓解政策。