Observations, Reanalyses and Ice Cores: A Synthesis of West Antarctic Climate

观测、再分析和冰芯：西南极气候综合

• 批准号: 0636618
• 负责人: David Reusch
• 金额: --
• 依托单位: Pennsylvania State Univ University Park
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-07-01 至 2010-10-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0636618&HistoricalAwards=false
• 关键词: Observations; Reanalyses; Ice; Cores; Synthesis

Reusch/0636618This award supports a three-year effort to use nonlinear techniques to improve understanding of Antarctic climate through studies of observational and forecast model data sets; improve and extend reconstructions of past Antarctic climate from ice-core data; and reconstruct data missing from the observational records, potentially into the pre-instrumental era. The intellectual merit of the proposed activity arises from the opportunity to improve understanding of the past, present and future climate of the Antarctic, a key component in the global climate system. Self-organizing maps (SOMs), an emerging, powerful nonlinear tool, will be used to classify free-atmosphere reanalysis data into archetypal patterns (SOM states). Feed-forward artificial neural networks (FF-ANNs) will then be trained to predict the preferred SOM states from ice-core data covering the instrumental era. The trained FF-ANNs will extend the reconstructions of SOM states to the full length of the ice core data, leading to long-term reconstruction of climate. Histories of surface conditions will be improved by filling data gaps in observational records using FF-ANNs and free-atmosphere reanalysis data. These records may also be extended into the pre-instrumental era using the above ice-core based reconstructions of the atmospheric circulation. The broader impacts of the project relate to activities with the Earth and Mineral Sciences Museum (co-located in the Geosciences building) which will bring project results/tools to a wider audience through development of interactive graphical visualizations/presentations for the Museum's fixed and traveling GeoWall displays. One or more undergraduates from the College will be involved in the project with an option to also present project results at a national meeting/workshop. The work will also contribute to the continuing development of an "early career" investigator, including the opportunity to continue building (and refining) relevant and useful skills in teaching, outreach, collaboration, etc.

Reusch/0636618该奖项支持一项为期三年的努力，通过对观测和预测模型数据集的研究，利用非线性技术提高对南极气候的理解;改进和扩展根据冰芯数据重建过去南极气候的工作;重建观测记录中缺失的数据，可能进入仪器前时代。拟议活动的知识价值来自于有机会增进对南极过去、现在和未来气候的了解，南极是全球气候系统的一个关键组成部分。 自组织映射（SOM），一个新兴的，强大的非线性工具，将被用来分类自由大气再分析数据到原型模式（SOM状态）。前馈人工神经网络（FF-ANN），然后将被训练来预测的首选SOM状态从冰芯数据覆盖的仪器时代。训练好的FF-ANN将把SOM状态的重建扩展到冰芯数据的全长，从而实现长期的气候重建。通过使用FF-ANN和自由大气再分析数据填补观测记录中的数据空白，将改善地表条件的历史。 使用上述基于冰芯的大气环流重建，这些记录也可以扩展到仪器出现之前的时代。 该项目更广泛的影响涉及与地球和矿物科学博物馆（共同设在地球科学大楼）的活动，通过为博物馆的固定和移动GeoWall显示器开发交互式图形可视化/演示，将项目成果/工具带给更广泛的受众。学院的一名或多名本科生将参与该项目，并可选择在国家会议/研讨会上展示项目成果。 这项工作还将有助于继续培养“早期职业”调查员，包括有机会继续培养（和完善）教学、外联、协作等方面的相关和有用技能。