Empirically Determined Climate Predictability Using Nonlinear Time Series Models

使用非线性时间序列模型根据经验确定气候可预测性

• 批准号: 9417528
• 负责人: Ian McKeague
• 金额: $ 9.88万
• 依托单位: Florida State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1995
• 资助国家: 美国
• 起止时间: 1995-04-01 至 1997-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9417528&HistoricalAwards=false
• 关键词: Empirically; Determined; Climate; Predictability; Using

Abstract ATM-9417528 McKeague, Ian W. Florida State University Title: Empirically Determined Climate Predictability Using Nonlinear Time Series Models This grant is to apply various modern methods of nonlinear time series analysis to look at the problem of climate predictability. Observed and GCM simulated time series will be examined using the tools of nonlinear dynamical systems theory to construct nonlinear statistical models. This will enable the PIs to assess the predictability of climate.

摘要ATM-9417528 McKeague，Ian W. 佛罗里达州立大学 用经验确定的气候可预报性 非线性时间序列模型 该基金将应用各种现代非线性时间序列分析方法来研究气候可预测性问题。 观测和GCM模拟的时间序列将使用非线性动力系统理论的工具来构建非线性统计模型。 这将使PI能够评估气候的可预测性。