Collaborative Research: Targeted resampling of deep polar ice cores using information theory

合作研究:利用信息论对极地深部冰芯进行有针对性的重采样

基本信息

  • 批准号:
    1807478
  • 负责人:
  • 金额:
    $ 9.89万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2018
  • 资助国家:
    美国
  • 起止时间:
    2018-08-15 至 2021-07-31
  • 项目状态:
    已结题

项目摘要

Ice cores contain detailed accounts of Earth's climate history. The collection of an ice core can be logistically challenging, and extraction of data from the core can be time-consuming as well as susceptible to both human and machine error. Furthermore, locked in measurements from ice cores is information that scientists have not yet found ways to recover. This project will apply techniques from information theory to ice-core data to unlock that information. The primary goal is to demonstrate that information theory can (a) identify regions of a specific ice-core record that are in need of further analysis and (b) provide some specific guidance for that analysis. A secondary goal is to demonstrate that information theory has practical and scientific utility for studies of past climate. This project aims to use information theory in two distinct ways: first, to identify regions of a core where information appears to be damaged or missing, perhaps due to human and/or machine error. In the segment of the West Antarctic Ice Sheet Divide core that is 5000-8000 years old, for instance, information-theoretic methods reveal significant levels of noise, probably due to a laboratory instrument, and something that was not visible in the raw data. This is a particularly important segment of the record, as it contains valuable clues about climatic shifts and the onset of the Holocene. Targeted re-sampling of this segment of the core and reanalysis with newer laboratory apparatus could resolve the data issues. The second way in which information theory can potentially aid in ice-core analysis is by extracting climate signals from the data--such as the accumulation rate at the core site over the period of its formation. This quantity usually requires significant time and effort to produce, but information theory could help to streamline that process.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
冰芯包含了地球气候历史的详细记录。 收集冰芯在逻辑上可能具有挑战性,从冰芯中提取数据可能非常耗时,并且容易受到人为和机器错误的影响。 此外,科学家们还没有找到恢复冰芯测量结果的方法。该项目将把信息论的技术应用于冰芯数据,以解开这些信息。主要目标是证明信息理论可以(a)识别需要进一步分析的特定冰芯记录区域,以及(B)为该分析提供一些具体指导。第二个目标是证明信息理论对过去气候的研究具有实际和科学的效用。该项目旨在以两种不同的方式使用信息理论:第一,识别可能由于人为和/或机器错误而导致信息损坏或丢失的核心区域。例如,在5000-8000年前的西南极冰盖分水岭核心部分,信息论方法揭示了显着的噪音水平,可能是由于实验室仪器,以及原始数据中不可见的东西。这是一个特别重要的记录部分,因为它包含了关于气候变化和全新世开始的宝贵线索。有针对性地对这部分岩心进行重新取样,并使用较新的实验室仪器进行重新分析,可以解决数据问题。信息论可以潜在地帮助冰芯分析的第二种方式是从数据中提取气候信号,例如在冰芯形成期间在冰芯位置的积累率。 这个数量通常需要大量的时间和精力来生产,但信息理论可以帮助简化这一过程。这个奖项反映了NSF的法定使命,并已被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。

项目成果

期刊论文数量(4)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
An information-theoretic approach to extracting climate signals from deep polar ice cores
从极地深处冰芯提取气候信号的信息论方法
Information Theory in Earth and Space Science
地球与空间科学中的信息论
  • DOI:
  • 发表时间:
    2018
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Garland, Joshua;Bradley, Elizabeth
  • 通讯作者:
    Bradley, Elizabeth
Detection of local mixing in time-series data using permutation entropy
使用排列熵检测时间序列数据中的局部混合
  • DOI:
    10.1103/physreve.103.022217
  • 发表时间:
    2021
  • 期刊:
  • 影响因子:
    2.4
  • 作者:
    Neuder, Michael;Bradley, Elizabeth;Dlugokencky, Edward;White, James W.;Garland, Joshua
  • 通讯作者:
    Garland, Joshua
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Joshua Garland其他文献

Greetings from a Triparental Planet
来自三亲星球的问候
  • DOI:
  • 发表时间:
    2020
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Gizem Bacaksizlar;Stefani A. Crabtree;Joshua Garland;N. Grefenstette;Albert B. Kao;D. Kinney;Artemy Kolchinsky;T. Marghetis;M. Price;M. Riolo;Hajime Shimao;Ashley I. Teufel;Tamara van der Does;V. Yang
  • 通讯作者:
    V. Yang
Changes in group size during resource shifts reveal drivers of sociality across the tree of life
资源转移期间群体规模的变化揭示了整个生命树的社会性驱动因素
  • DOI:
  • 发表时间:
    2020
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Albert B. Kao;Amanda K. Hund;F. Santos;Jean;Deepak Bhat;Joshua Garland;Rebekah A. Oomen;H. McCreery
  • 通讯作者:
    H. McCreery
Hate Speech and Counter Speech Detection: Context Does Matter
仇恨言论和反言论检测:上下文很重要
  • DOI:
  • 发表时间:
    2021
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Joshua Garland;Keyan Ghazi;Laurent Hébert;M. Galesic;Dirk Hovy;Taylor Berg;Ashish Vaswani;Nicola F Johnson;R. Leahy;Johnson Restrepo;Klaus Krippendorff. 2011;Yinhan Liu;Myle Ott;Naman Goyal;Jingfei Du;Mandar Joshi;Danqi Chen;Omer Levy;Mike Lewis;Binny Mathew;Anurag Illendula;Punyajoy Saha;Soumya Sarkar;Pawan Goyal;Animesh Mukher;Hardik Tharad;Subham;Prajwal Rajgaria;Singhania;Suman Kalyan;Maity;Animesh Mukherjee;Thou;Seid Muhie Yimam;Stefano Menini;Alessio Palmero;Aprosio Sara;Chikashi Nobata;Joel R. Tetreault;Achint Thomas;Alexandra Olteanu;Carlos Castillo;Jeremy Boy;John Pavlopoulos;Jeffrey Sorensen;Lucas Dixon;Jason Phang;Phil Yeres;Jesse Swanson;Haokun Liu;John Pougué;Valentina Semenova;Alexandre;Rachel Matton;Aerin Han;Renaud Kim;Lambiotte;Rob Procter;Helena Webb;Pete Burnap;William Hous;Adam Edwards;Matthew L. Williams;William Yang;A. Dataset
  • 通讯作者:
    A. Dataset
A new method for choosing parameters in delay reconstruction-based forecast strategies
基于延迟重构的预测策略中参数选择的新方法
  • DOI:
  • 发表时间:
    2015
  • 期刊:
  • 影响因子:
    2.4
  • 作者:
    Joshua Garland;R. James;Elizabeth Bradley
  • 通讯作者:
    Elizabeth Bradley
Countering hate on social media: Large scale classification of hate and counter speech
反击社交媒体上的仇恨:仇恨和反言论的大规模分类
  • DOI:
  • 发表时间:
    2020
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Joshua Garland;K. Zahedi;Jean;Laurent Hébert;M. Galesic
  • 通讯作者:
    M. Galesic

Joshua Garland的其他文献

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