Collaborative Research: El Nino/Southern Oscillation (ENSO) Predictability--Initial Condition Signal versus Uncoupled Atmospheric Noise

合作研究:厄尔尼诺/南方涛动 (ENSO) 可预测性 - 初始条件信号与非耦合大气噪声

基本信息

  • 批准号:
    2241538
  • 负责人:
  • 金额:
    $ 70.85万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2023
  • 资助国家:
    美国
  • 起止时间:
    2023-06-01 至 2027-05-31
  • 项目状态:
    未结题

项目摘要

The equatorial Pacific has an outsized influence on weather and climate as it is home to the El Nino/Southern Oscillation (ENSO) phenomenon, featuring an alternation between warm equatorial sea surface temperatures (SSTs) during El Nino events and cold SSTs during La Nina events. These SST changes affect the global atmospheric circulation and thus induce long-range impacts including changes in the severity of winters in Canada, the distribution of rainfall in the Asian monsoon, and Atlantic hurricane activity. These worldwide impacts have motivated intensive efforts to develop ENSO prediction systems, which show some promise but so far have had mixed results.Here the PIs hypothesize that the mixed success of ENSO predictions is intrinsic to ENSO, meaning that some ENSO events are in fact more predictable than others. In that case a "forecast of the forecast skill", meaning a method to determine in advance the likely accuracy of an ENSO prediction, would have great practical value. The Principal Investigators (PIs) are particularly concerned with the skill of ENSO predictions made before the onset of the event, which are skillful to the extent that ENSO events develop from some form of preconditioning such as the buildup of heat in the subsurface equatorial ocean. Model simulations conducted previously by the PIs suggest that preconditioning is not a necessary condition for ENSO events, which can initiate rapidly starting from neutral conditions. Such events, arising purely from the chaotic growth of very small initial perturbations of the atmosphere-ocean system, would be inherently unpredictable. But the PIs argue that some forms of preconditioning can render the system less susceptible to noise-level perturbations and instead drive the evolution of an El Nino or La Nina event in a deterministic manner, allowing skillful predictions several months ahead of the onset.The PIs test their hypothesis through numerical simulations performed with the Community Earth System Model (CESM). The work takes advantage of procedures they have developed for strictly controlling the state of the equatorial Pacific in CESM simulations, so that various forms of preconditioning can be imposed or excluded. Additional work uses the PI's Interactive Ensemble (IE) technique (see for example AGS-1558837) to consider the role of random weather fluctuations unrelated to ENSO in limiting the predictability of ENSO events.The work is of societal as well as scientific interest given the global impacts of ENSO events, and results of this research have direct bearing on attempts to improve ENSO forecasts. The software developed for the project is made available to the research community, along with relevant datasets, to facilitate adoption of methods and results by the research and operational communities. In addition, the PIs participate in summer internship programs targeting high school and college students through Miami-Dade College and the American Indian Higher Education Consortium.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.
赤道太平洋对天气和气候有着巨大的影响,因为它是厄尔尼诺/南方涛动(ENSO)现象的发源地,其特征是厄尔尼诺事件期间温暖的赤道海面温度(SST)和拉尼娜事件期间寒冷的SST之间的交替。 这些SST变化影响全球大气环流,从而引起长期影响,包括加拿大冬季严酷程度的变化,亚洲季风的降雨分布和大西洋飓风活动。 这些全球性的影响促使人们加紧努力开发ENSO预测系统,这些系统显示出一定的前景,但迄今为止的结果好坏参半。在这里,PI假设ENSO预测的好坏参半是ENSO的内在原因,这意味着某些ENSO事件实际上比其他事件更容易预测。 在这种情况下,“预测技能的预测”,即预先确定厄尔尼诺/南方涛动预测可能准确性的方法,将具有很大的实用价值。 主要研究人员特别关注在事件发生之前所作的ENSO预测的技巧,这些预测的技巧达到了ENSO事件是从某种形式的预处理(如赤道次表层海洋热量的积累)发展而来的程度。 PI先前进行的模式模拟表明,预处理不是ENSO事件的必要条件,ENSO事件可以从中性条件迅速启动。 这种事件纯粹是由大气-海洋系统非常小的初始扰动的混乱增长引起的,从本质上讲是不可预测的。 但PI认为,某些形式的预处理可以使系统不太容易受到噪声水平扰动的影响,而是以确定性的方式驱动厄尔尼诺或拉尼娜事件的演变,允许提前几个月进行巧妙的预测。PI通过社区地球系统模型(CESM)进行的数值模拟来验证他们的假设。 这项工作利用了他们开发的程序,用于在CESM模拟中严格控制赤道太平洋的状态,以便可以施加或排除各种形式的预处理。 其他工作使用PI的交互式Ensemination(IE)技术(例如见AGS-1558837)考虑与ENSO无关的随机天气波动在限制ENSO事件可预测性方面的作用。考虑到ENSO事件的全球影响,这项工作具有社会和科学意义,这项研究的结果对改进ENSO预测的努力有直接影响。为该项目开发的软件连同相关数据集沿着提供给研究界,以便利研究界和业务界采用各种方法和成果。 此外,PI还通过迈阿密戴德学院和美国印第安人高等教育联盟参与针对高中生和大学生的暑期实习计划。该奖项反映了NSF的法定使命,并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,被认为值得支持。

项目成果

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Benjamin Kirtman其他文献

Special issue: ENSO diversity
  • DOI:
    10.1007/s00382-019-04723-2
  • 发表时间:
    2019-04-02
  • 期刊:
  • 影响因子:
    3.700
  • 作者:
    Benjamin Kirtman
  • 通讯作者:
    Benjamin Kirtman

Benjamin Kirtman的其他文献

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{{ truncateString('Benjamin Kirtman', 18)}}的其他基金

Collaborative Research: The Atlantic Meridional Overturning Circulation and Internal Climate Variability
合作研究:大西洋经向翻转环流和内部气候变率
  • 批准号:
    1558837
  • 财政年份:
    2016
  • 资助金额:
    $ 70.85万
  • 项目类别:
    Standard Grant
Collaborative Research: Extratropical Triggering of El Nino/Southern Oscillation (ENSO) Events Through the Trade-Wind Charging Mechanism
合作研究:通过信风充电机制触发厄尔尼诺/南方涛动(ENSO)事件的温带事件
  • 批准号:
    1547137
  • 财政年份:
    2016
  • 资助金额:
    $ 70.85万
  • 项目类别:
    Standard Grant
Revisiting Coupled Instability Theory and the Initiation of ENSO (El Nino/Southern Oscillation)
重新审视耦合不稳定理论和 ENSO(厄尔尼诺/南方涛动)的引发
  • 批准号:
    1450811
  • 财政年份:
    2015
  • 资助金额:
    $ 70.85万
  • 项目类别:
    Standard Grant
Collaborative Research: "EaSM-3": The Role of Ocean Eddies in Decadal Prediction
合作研究:“EaSM-3”:海洋涡流在年代际预测中的作用
  • 批准号:
    1419569
  • 财政年份:
    2014
  • 资助金额:
    $ 70.85万
  • 项目类别:
    Standard Grant
Collaborative Research: Understanding Atlantic Decadal-to-Multidecadal Variability and Predictability
合作研究:了解大西洋十年间到多十年间的变异性和可预测性
  • 批准号:
    1137911
  • 财政年份:
    2011
  • 资助金额:
    $ 70.85万
  • 项目类别:
    Standard Grant
Collaborative Research: Consensus on Climate Predication by Adaptive Synchronization of Models
合作研究:通过模型自适应同步进行气候预测共识
  • 批准号:
    0838235
  • 财政年份:
    2009
  • 资助金额:
    $ 70.85万
  • 项目类别:
    Standard Grant
PRAC Collaborative Research: Testing Hypotheses about Climate Prediction at Unprecedented Resolutions on the NSF Blue Waters System
PRAC 合作研究:在 NSF Blue Waters 系统上以前所未有的分辨率测试有关气候预测的假设
  • 批准号:
    0832604
  • 财政年份:
    2009
  • 资助金额:
    $ 70.85万
  • 项目类别:
    Standard Grant
Collaborative Research: PetaApps: New Coupling Strategies and Capabilities for Petascale Climate Modeling
合作研究:PetaApps:千万亿次气候建模的新耦合策略和功能
  • 批准号:
    0749165
  • 财政年份:
    2008
  • 资助金额:
    $ 70.85万
  • 项目类别:
    Standard Grant
Collaborative Research: Westerly Wind Burst Modulation by the Sea-Surface Temperature (SST): from Understanding to El Nino-Southern Oscillation (ENSO) Prediction
合作研究:海面温度(SST)对西风爆发的调节:从理解到厄尔尼诺-南方涛动(ENSO)预测
  • 批准号:
    0754341
  • 财政年份:
    2008
  • 资助金额:
    $ 70.85万
  • 项目类别:
    Continuing Grant
Interactive Ensembles: A New Strategy for Coupled Ocean-Atmosphere Predictability Research
交互式集成:海洋-大气耦合可预测性研究的新策略
  • 批准号:
    0122859
  • 财政年份:
    2001
  • 资助金额:
    $ 70.85万
  • 项目类别:
    Continuing Grant

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合作研究:RAPID:一场完美风暴:2023/24厄尔尼诺干旱和森林退化的双重影响是否会导致亚马逊东部地区出现局部临界点?
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  • 批准号:
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