A Statistics Program at the National Center for Atmospheric Research

国家大气研究中心的统计项目

• 批准号: 0355474
• 负责人: Douglas Nychka
• 金额: $ 123万
• 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: 2004
• 资助国家: 美国
• 起止时间: 2004-07-01 至 2008-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0355474&HistoricalAwards=false
• 关键词: Statistics; Program; National; Center; Atmospheric

ABSTRACTPI: Douglas Nychkaproposal: 0355474The Geophysical Statistics Project (GSP) at the National Center forAtmospheric Research (NCAR) provides a unique opportunity to addressimportant research problems at the interface between the geosciences andstatistics. The statistical research includes contributions to theanalysis of nonstationary spatial and spatio-temporal data, the design andanalysis of computer experiments, filtering, the statistics of extremes,data mining, and statistical computing. These methods are adapted to largedata sets and publicly available software is available to implement newmethods for spatial data and extremes. The intellectual contributions toapplications in the geosciences is equally broad and includes theintroduction of stochastic modeling for sub-grid scale processes,estimating the climatology for extreme events, the construction ofspatially coherent weather generators, and statistical improvements tomethods of data assimilation.A grand scientific challenge for this century is to understand the complexinterrelationships among the atmosphere, ocean, land processes, biosphereand human activities that define the Earth System. Coupled with thiseffort is the need to predict changes to our environment and to translatesuch changes into more immediate economic and societal impacts. There isa corresponding challenge for statistical science to tackle the large andcomplex data sets that are now the norm in many areas of science andengineering and to leverage the rich structure and prior knowledgeafforded by traditional numerical models. Through the training of youngresearchers, a vigorous visitor program and participation within severalof the NCAR strategic initiatives, this work reaches a wide communityof statisticians and researchers in the geosciences. In this context, somespecific problems are the design and analysis of large computerexperiments that simulate the Earth's climate, extrapolating historicalmeteorological data sets to locations where they are not observed,improving the algorithms used to make numerical weather predictions, andidentifying models that include random processes to represent complicatedgeophysical phenomenon. One common element throughout this research isquantifying the uncertainty in a derived method or result. Uncertaintyestimates are often difficult to obtain without a statistical treatmentbut are particularly important when the analysis is subsequently used fordecision making or to assess risks.

国家大气研究中心(NCAR)的地球物理统计项目(GSP)为解决地学和统计学之间的重要研究问题提供了一个独特的机会。统计学研究包括对非平稳空间和时空数据的分析、计算机实验的设计和分析、过滤、极值统计、数据挖掘和统计计算。这些方法适用于大数据集，公开可用的软件可用于实施空间数据和极端情况的新方法。对地球科学应用的智力贡献同样广泛，包括引入亚格子尺度过程的随机模型，估计极端事件的气候学，构建空间连贯的天气发生器，以及对数据同化方法的统计改进。本世纪的一个重大科学挑战是理解定义地球系统的大气、海洋、陆地过程、生物圈和人类活动之间的复杂相互关系。与此相伴随的是，需要预测我们环境的变化，并将这种变化转化为更直接的经济和社会影响。统计科学面临着一个相应的挑战，即如何处理目前在许多科学和工程领域成为标准的庞大而复杂的数据集，以及如何利用传统数值模型所提供的丰富结构和先验知识。通过对年轻研究人员的培训，积极的访客计划，以及参与NCAR的几项战略倡议，这项工作接触到了广泛的统计人员和地学研究人员社区。在这种情况下，一些具体的问题是设计和分析模拟地球气候的大型计算机实验，将历史气象数据集外推到没有观测到的位置，改进用于进行数值天气预报的算法，以及确定包括随机过程的模型以表示复杂的地球物理现象。这项研究的一个共同要素是量化衍生方法或结果中的不确定度。不确定的估计往往很难在不进行统计处理的情况下获得，但当分析随后用于决策或评估风险时，这种估计尤其重要。