Collaborative Research: Project PALEOVAR -- Past Climate Variability: Understanding Mechanisms and Interactions with the Mean State
Collaborative Research: Project PALEOVAR -- Past Climate Variability: Understanding Mechanisms and Interactions with the Mean State
批准号:
0602459
负责人:
Richard Edwards
金额:
$15.03万
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2006
资助国家:
美国
项目状态:
已结题
起止时间:
2006-06-15 至 2011-05-31
中文摘要
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英文摘要
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.
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Integrated in silico prediction of protein interaction motifs using interactome networks and high-resolution 3-dimensional structures
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依托单位:
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