Detection and Attribution of Anthropogenic Changes in Climate Extremes and Variability

气候模型被广泛用于预测与温室气体排放增加和其他人为气候影响相关的未来气候变化。气候变化的检测和归属提供了对气候模型现实地模拟与自然和人为影响有关的过去气候变化的能力的严格评估。探测方法还提供了一种手段，用于根据观察到的变化估计未来变化的概率分布，并估计温室气体强迫对极端事件风险变化的贡献。科学目标和学术价值：这项研究的目的是检测描述极端情况的气候统计数据中的大规模变化并将其归因于这些变化。这项工作的第一个主旨是将指纹检测和归属方法应用于炎热昼夜的变化，以及预计全球范围内强降水的增加，特别是在几天的时间里。结果将被用来估计热浪和罕见极端气温的人为变化风险。工作的第二个主旨是探索极端气候和变异性的变化，这些变化已被确定为可能对生态系统和社会产生重要影响。例如，热浪、假泉水或由于生长季降雨量减少或降雨量和温度综合变化而导致的干旱。这项工作现在是可行的，因为最近在观测数据集和气候模型模拟的质量和数量方面都有了改进。政府间气候变化专门委员会第四次评估报告的模拟最近提供了一大套最新的气候模型模拟。这些可以提供对气候变化信号的估计以及这些信号中的模型不确定性。此外，正在收集覆盖越来越多的全球陆地面积的每日温度和极端降雨量指数。此外，长站数据正在变得可用，这些数据允许测试从气候模型估计的内部气候变异性。更广泛的影响：极端气候对社会、农业和生态系统有很大影响，气候变化的许多影响可能与极端气候的变化直接相关。因此，了解20世纪极端气候的变化，并评估气候模式模拟这种变化的能力，对社会具有重要意义。探测极端气候中的人为变化对于了解当前气候中正在出现的风险，以及现实地预测进一步的变化及其不确定性至关重要。这项活动也对教学和教育产生了影响。预算包括资助一名研究生，从而培训一名学生在气候研究、与之相关的社会影响以及应用最新统计技术等重要问题上的培训。

Climate models are widely used to predict future climate changes associated with increasing greenhouse gas emissions and other anthropogenic influences on climate. Detection and attribution of climate change provides a rigorous evaluation of the ability of climate models to realistically simulate past climate change associated with natural and anthropogenic influences. Detection methods also provide a means for estimating the probability distribution of future changes based on observed changes, and to estimate the contribution from greenhouse gas forcing to changes in the risk of extreme events. Scientific Objectives and Intellectual Merit: The research aims at detecting and attributing large-scale changes in the statistics of climate that describe extremes. The first thrust of the work is to apply fingerprint detection and attribution approaches to changes in hot days and nights, and projected global-scale increases in heavy precipitation, particularly over several days. Results will be used to estimate anthropogenic changes in the risk of heat waves and rare temperature extremes. A second thrust of work is to explore changes in climate extremes and variability that have been determined as potentially important for impacts on ecosystems and society. Examples are heat waves, false springs, or droughts resulting from decreases in growing season rainfall or combined rainfall and temperature changes. The work is now feasible because of recent improvements in the quality and quantity of observational data sets and climate model simulations. A large set of the latest climate model simulations has recently become available from simulations performed for the 4th IPCC assessment report. These can provide estimates of climate change signals and model uncertainties in these signals. Furthermore, indices of daily temperature and rainfall extremes are being collected that cover an increasing area of the global land mass. Also, long station data are becoming available that allow to test internal climate variability estimates from climate models. Broader Impacts: Climatic extremes have large impacts on society, agriculture, and ecosystems, and many impacts of climate change may be directly related to changes in climate extremes. Therefore, it is of great importance to society to understand the variations in climate extremes encountered over the 20th century, and to evaluate the ability of climate models to simulate such changes. Detection of anthropogenic changes in climatic extremes is essential for understanding emerging risks in the current climate, and realistically predicting further changes and their uncertainties. The activity also has impacts on teaching and education. The budget contains funding for a graduate student, and thus for training a student in important problems of climate research, societal impacts associated with it, and applying up-to-date statistical techniques.