Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.2172/1228364 |
报告编号 | BU0006914 |
来源ID | OSTI ID: 1228364 |
Detection of Historical and Future Precipitation Variations and Extremes Over the Continental United States | |
Anderson, Bruce T. | |
2015-12-11 | |
出版年 | 2015 |
页数 | 7 |
语种 | 英语 |
国家 | 美国 |
领域 | 地球科学 |
英文摘要 | Problem: The overall goal of this proposal is to detect observed seasonal-mean precipitation variations and extreme event occurrences over the United States. Detection, e.g. the process of demonstrating that an observed change in climate is unusual, first requires some means of estimating the range of internal variability absent any external drivers. Ideally, the internal variability would be derived from the observations themselves, however generally the observed variability is a confluence of both internal variability and variability in response to external drivers. Further, numerical climate modelsâthe standard tool for detection studiesâhave their own estimates of intrinsic variability, which may differ substantially from that found in the observed system as well as other model systems. These problems are further compounded for weather and climate extremes, which as singular events are particularly ill-suited for detection studies because of their infrequent occurrence, limited spatial range, and underestimation within global and even regional numerical models. Rationale: As a basis for this research we will show how stochastic daily-precipitation modelsâmodels in which the simulated interannual-to-multidecadal precipitation variance is purely the result of the random evolution of daily precipitation events within a given time periodâcan be used to address many of these issues simultaneously. Through the novel application of these well-established models, we can first estimate the changes/trends in various means and extremes that can occur even with fixed daily-precipitation characteristics, e.g. that can occur simply as a result of the stochastic evolution of daily weather events within a given climate. Detection of a change in the observed climateâeither naturally or anthropogenically forcedâcan then be defined as any change relative to this stochastic variability, e.g. as changes/trends in the means and extremes that could only have occurred through a change in the underlying climate. As such, this method is capable of detecting âhot spotâ regionsâas well as âflare upsâ within the hot spot regionsâthat have experienced interannual to multi-decadal scale variations and trends in seasonal-mean precipitation and extreme events. Further by applying the same methods to numerical climate models we can discern the fidelity of the current-generation climate models in representing detectability within the observed climate system. In this way, we can objectively determine the utility of these model systems for performing detection studies of historical and future climate change. |
英文关键词 | Precipitation Climate Change Stochastic modeling Trend detection Detection and attribution |
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来源平台 | US Department of Energy (DOE) |
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文献类型 | 科技报告 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/6858 |
专题 | 地球科学 |
推荐引用方式 GB/T 7714 | Anderson, Bruce T.. Detection of Historical and Future Precipitation Variations and Extremes Over the Continental United States,2015. |
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