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: 1066348
• 负责人: David Reusch
• 金额: $ 3.14万
• 依托单位: New Mexico Institute of Mining and Technology
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-10-01 至 2011-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1066348&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这项奖项通过研究观察和预测模型数据集的研究来支持使用非线性技术来提高对南极气候的理解的三年努力；从冰核数据中改善和扩展过去南极气候的重建；并重建了观察记录中缺少的数据，并有可能进入乐器前时代。拟议活动的智力优点源于改善对南极的过去，现在和未来气候的理解，这是全球气候系统中的关键组成部分。 自组织地图（SOMS）是一种新兴的，有力的非线性工具，将用于将自由大气重新分析数据分类为原型模式（SOM状态）。然后，将训练前进的人工神经网络（FF-ANN），以预测涵盖乐器时代的冰核数据的首选SOM状态。受过训练的FF-ANN将将SOM状态的重建扩展到冰核数据的全长，从而导致气候的长期重建。通过使用FF-ANN和自由大圈重新分析数据填补观察性记录中的数据空白，将改善表面条件的历史。 这些记录也可以使用上述大气循环的基于冰核的重建来扩展到乐器前时代。 该项目的更广泛影响与地球和矿产科学博物馆的活动有关（地球科学大楼合作），这将通过开发为博物馆固定和旅行的Geowall显示器开发互动式图形可视化/演示文稿，从而为更广泛的受众带来项目结果/工具。该学院的一个或多个大学生将参与该项目，并可以选择在全国会议/研讨会上介绍项目结果。 这项工作还将为“早期职业”调查员的持续发展做出贡献，包括有机会继续建立（并完善）相关和有用的技能，以实现教学，外展，协作等。