| DOI: | 10.2172/1149586
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| 报告号: | DOE-PSU--64641
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| 报告题名: | Framework for Probabilistic Projections of Energy-Relevant Streamflow Indicators under Climate Change Scenarios for the U.S. |
| 作者: | Wagener, Thorsten1; Mann, Michael2; Crane, Robert2
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| 出版年: | 2014
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| 发表日期: | 2014-04-29
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| 总页数: | 17
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| 国家: | 美国
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| 语种: | 英语
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| 英文摘要: | This project focuses on uncertainty in streamflow forecasting under climate change conditions. The objective is to develop easy to use methodologies that can be applied across a range of river basins to estimate changes in water availability for realistic projections of climate change. There are three major components to the project: Empirical downscaling of regional climate change projections from a range of Global Climate Models; Developing a methodology to use present day information on the climate controls on the parameterizations in streamflow models to adjust the parameterizations under future climate conditions (a trading-space-for-time approach); and Demonstrating a bottom-up approach to establishing streamflow vulnerabilities to climate change. The results reinforce the need for downscaling of climate data for regional applications, and further demonstrates the challenges of using raw GCM data to make local projections. In addition, it reinforces the need to make projections across a range of global climate models. The project demonstrates the potential for improving streamflow forecasts by using model parameters that are adjusted for future climate conditions, but suggests that even with improved streamflow models and reduced climate uncertainty through the use of downscaled data, there is still large uncertainty is the streamflow projections. The most useful output from the project is the bottom-up vulnerability driven approach to examining possible climate and land use change impacts on streamflow. Here, we demonstrate an inexpensive and easy to apply methodology that uses Classification and Regression Trees (CART) to define the climate and environmental parameters space that can produce vulnerabilities in the system, and then feeds in the downscaled projections to determine the probability top transitioning to a vulnerable sate. Vulnerabilities, in this case, are defined by the end user. |
| URL: | http://www.osti.gov/scitech/servlets/purl/1149586
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| Citation statistics: |
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| 资源类型: | 研究报告
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| 标识符: | http://119.78.100.158/handle/2HF3EXSE/41542
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| Appears in Collections: | 过去全球变化的重建
影响、适应和脆弱性
科学计划与规划
气候变化与战略
全球变化的国际研究计划
气候减缓与适应
气候变化事实与影响
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| 1149586.pdf（1340KB） | 研究报告 | -- | 开放获取 | | View
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作者单位: | 1. Univ. of Bristol (United Kingdom)
2. Pennsylvania State Univ., State College, PA (United States)
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| Recommended Citation: | |
Wagener, Thorsten,Mann, Michael,Crane, Robert. Framework for Probabilistic Projections of Energy-Relevant Streamflow Indicators under Climate Change Scenarios for the U.S.. 2014-01-01.
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