Mathematical Sciences:Collaboration Between Statistical and Atmospheric Sciences on Modeling the Climate System

数学科学:统计与大气科学在气候系统建模方面的合作

• 批准号: 9312686
• 负责人: Richard Katz
• 金额: $ 360万
• 依托单位: University Corporation For Atmospheric Res
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1993
• 资助国家: 美国
• 起止时间: 1993-07-15 至 1999-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9312686&HistoricalAwards=false
• 关键词: Mathematical; Sciences; Collaboration; Between; Statistical

9312686 Katz The modeling and analysis of the climate system is a complex problem that challenges the statistical, mathematical, and geophysical sciences. Increased collaboration among these sciences would result in more efficient analyses and more accurate interpretation of data from the climate system and its models, and in a more reliable assessment of accompanying uncertainties. It is proposed that a team of statistical scientist be assembled at the National Center for Atmospheric Research (NCAR) to help foster such a collaboration. NCAR, basefunded by the National Sciences Foundation, is a focal point for basic research on the atmosphere and has strong links to universities throughout North America. With the addition of more statistical and mathematical expertise, it could serve as well as a focal point for promoting collaboration among geophysical, statistical, and other mathematical sciences. The general objective is to develop and utilize new techniques of data analysis that arise from the collective understanding of physical scientists, mathematicians, and statisticians. The climate system has a very large number of degrees of freedom and exhibits some chaotic behavior. Consequently, the specific focus of the collaborative research would be on the development of inferential methods appropriate for high-resolution analysis of the climate system. Such analyses are appropriate both because realistic models of the climate system require the treatment of smaller scale phenomena, and because assessments of societal impact of climate require information on regional or smaller scales. Besides the immediate benefits to the scientific fields directly involved, improved understanding of the climate system would result in potential benefits to society that would be accrued indefinitely into the future. For instance, it could lead to improved weather and climate forecasts over a wide range of time scales from hours to seasons in advance, as well as to more realistic scenarios of future changes in climate. Such improvements would be of substantial value to decision makers and policy analysts.

小行星9312686 气候系统的建模和分析是一个复杂的问题，挑战统计，数学和地球物理科学。 加强这些科学之间的合作将导致对来自气候系统及其模型的数据进行更有效的分析和更准确的解释，并对伴随的不确定性进行更可靠的评估。 建议在国家大气研究中心（NCAR）组建一个统计科学家小组，以帮助促进这种合作。NCAR由美国国家科学基金会资助，是大气基础研究的焦点，与北美各地的大学有着密切的联系。 随着更多的统计和数学专业知识的增加，它可以作为促进地球物理，统计和其他数学科学之间合作的协调中心。 总体目标是开发和利用新的数据分析技术，这些技术来自物理科学家，数学家和统计学家的集体理解。 气候系统具有非常大的自由度，并表现出一些混沌行为。 因此，合作研究的具体重点将是开发适合气候系统高分辨率分析的推理方法。 这种分析是适当的，因为气候系统的现实模型需要处理较小尺度的现象，而且评估气候的社会影响需要区域或较小尺度的信息。 除了对直接涉及的科学领域的直接利益外，对气候系统的更好理解将给社会带来潜在的利益，这些利益将在未来无限期地积累下去。 例如，它可以改进从数小时到季节的各种时间尺度上的天气和气候预报，以及对未来气候变化的更现实的设想。 这种改进将对决策者和政策分析人员具有重大价值。