Collaborative Research: Project PALEOVAR -- Past Climate Variability: Understanding Mechanisms and Interactions with the Mean State

该奖项将使研究人员能够采用协调和多学科的方法来提高对过去5万年气候变率和气候平均状态之间相互作用的理解。具体而言，研究人员将汇编全球现有数据阵列，获取关注西美洲和东太平洋气候变率的高分辨率记录，将这些数据放在一个共同的时间尺度上量化年龄不确定性，使用传统和新开发的时间序列分析工具量化该地区气候变化和变率的性质，并整合数值模型和数据。具体而言，研究团队将研究以下科学问题：1)气候系统的平均状态如何影响气候变率？2)气候变率对长期平均气候状态的反馈是什么？3)变率是否作为气候系统的一个阈值而变化？4)陆地和海洋系统对平均气候和气候变率变化的敏感性和响应是什么？该研究策略允许评估气候模式模拟气候变率变化的能力，并根据对未来气候变率预测的直接影响，为未来的实验设计提供指导。过程建模将有助于解决与气候科学、陆地和海洋生态系统以及水资源管理有关的无数问题。该项目将通过支持几名研究生和博士后学者，直接支持下一代古气候科学家，强调数据采集、数据分析和建模方面的交叉培训，并确保科学成果通过互动网站和积极的公众宣传向更广泛的公众传播。这项研究包括美国国家科学基金会（NSF）和美国地质调查局（USGS）之间的跨部门合作，通过美国地质调查局研究人员与学术同事的积极参与。美国地质勘探局对人员和计算资源的承诺将与美国国家科学基金会对学术研究人员及其机构的承诺相结合，以一种具有成本效益的伙伴关系来帮助该项目实现其科学目标。

This award will enable researchers to pursue a coordinated and multidisciplinary approach to improving the understanding of the interactions between climate variability and climatic mean state over the past 50,000 years. Specifically, the researchers will compile a global array of existing data, acquire high-resolution records that focus on climate variability across the western Americas and eastern Pacific Ocean, place these data on a common timescale to quantify age uncertainties, use traditional and newly developed time series analysis tools to quantify the nature of climate change and variability in the region, and integrate numerical models and data. Specifically, the research team will pursue the following science questions: 1) How does the mean state of the climate system influence climate variability? 2) What is the feedback of climate variability on the long-term mean climate state? 3) Does variability change as a threshold in the climate system is approached? and 4) What is the sensitivity and response of terrestrial and marine systems to changes in mean climate and climate variability?The research strategy allows for assessing the ability of climate models to simulate changes in climatic variability and providing guidance for future experimental designs in terms of direct implications on predictions of future climate variability. Process modeling will help address a myriad of questions relevant to climate science, terrestrial and marine ecosystems, and water resources management. The project will directly support the next generation of paleoclimate scientists by supporting several graduate students and post-doctoral scholars, emphasizing cross-training in data acquisition, data analysis, and modeling, and ensuring that science results are disseminated to the broader public through an interactive website and active public outreach.This study includes a strong element of interagency cooperation between the National Science Foundation (NSF) and the U.S. Geological Survey (USGS) thorough the active involvement of USGS researchers with academic colleagues. The USGS commitment of personnel and computing resources will be leveraged with the NSF commitment to the academic researchers and their institutions in a cost-effective partnership to help the project achieve its science goals.