CAREER: Quantifying the Dynamics and Spatiotemporal Variability of Blocking Events Using Linear Response Functions and the Buckingham-Pi Theorem

职业:使用线性响应函数和 Buckingham-Pi 定理量化阻塞事件的动力学和时空变化

基本信息

  • 批准号:
    2046309
  • 负责人:
  • 金额:
    $ 73.5万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2021
  • 资助国家:
    美国
  • 起止时间:
    2021-04-15 至 2026-03-31
  • 项目状态:
    未结题

项目摘要

An atmospheric blocking event describes the occurrence of a large-scale, quasi-stationary, high-pressure system that persists between 5 days to a few weeks in the extratropics. Its appearance diverts the jet stream flow (altering nearby weather) and can contribute to extreme events like heat waves and droughts. Predicting blocking events is difficult. Our understanding of blocking events is poor, and complete theory for blocking still does not exist. The outcome of this project will advance our knowledge of blocking, which will enhance our capabilities to better forecast midlatitude weather extremes and project the response of blocking to climate change. In addition to training doctoral students, the project will develop (1) a Research Experiences for Teachers (RET) program with workshops focused on developing innovative teaching materials on climate science, and (2) a course to educate college students from non-geoscience quantitative majors about climate science.Specifically, this proposal seeks to understand blocking dynamics and their spatiotemporal variability as well as their response to climate change. The research objectives are to: (1) assess the role of positive eddy-blocking feedback mechanism in blocking persistence, (2) evaluate the impact of large-scale circulation on blocking characteristics, (3) examine the impact of climate change to blocking, and (4) investigate the roles of latent heating in the previous objectives. The research approach includes an innovative use of the linear response function theory, Buckingham-pi scale analysis, and wavelet analysis in a hierarchy of models, from dry/moist two-layer quasi-geostrophic to dry/moist idealized general circulation models (GCMs) to large-ensemble simulations from fully coupled GCMs. The RET program will provide 7 research positions for high-school science teachers, who will develop introductory lessons on climate change. These lessons will be shared with 100s of science teachers through workshops and other venues and will be taught to 10000s of Houston public school students, many from the underrepresented groups. The developed class will result in novel materials for introducing climate science/research to a broad group of STEM students, strengthening efforts aimed at training a skilled future workforce in climate science.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.
大气阻塞事件描述了在温带外地区持续5天到几周的大范围、准静止的高压系统的发生。它的出现改变了急流的流向(改变了附近的天气),并可能导致热浪和干旱等极端事件。预测阻塞事件是困难的。我们对阻塞事件的理解很差,关于阻塞的完整理论仍然不存在。该项目的成果将提高我们对阻塞的认识,这将增强我们更好地预报中纬度极端天气和预测阻塞对气候变化的反应的能力。除了培养博士生,该项目还将开发(1)教师研究经验(RET)计划,以开发气候科学创新教材为重点;(2)为非地球科学量化专业的大学生提供气候科学方面的教育课程。具体地说,该计划旨在了解阻塞动力学及其时空变异性以及他们对气候变化的反应。研究的目的是:(1)评估正涡旋阻塞反馈机制在阻塞持续中的作用;(2)评估大尺度环流对阻塞特征的影响;(3)考察气候变化对阻塞的影响;(4)考察潜热在先前目标中的作用。从干湿两层准地转模式到干湿两层准地转模式到干湿理想大气环流模式,再到全耦合大气环流模式的大集合模拟,本研究方法创新地运用了线性响应函数理论、白金汉-皮尺度分析和小波分析。RET计划将为高中科学教师提供7个研究职位,他们将开发关于气候变化的入门课程。这些课程将通过研讨会和其他场所与100多名科学教师分享,并将教授给1000多名休斯顿公立学校的学生,其中许多来自代表性不足的群体。开发的课程将产生新的材料,将气候科学/研究介绍给更广泛的STEM学生,加强旨在培训气候科学未来熟练劳动力的努力。该奖项反映了NSF的法定使命,并通过使用基金会的智力优势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

期刊论文数量(2)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
The Intrinsic 150‐Day Periodicity of the Southern Hemisphere Extratropical Large‐Scale Atmospheric Circulation
  • DOI:
    10.1029/2022av000833
  • 发表时间:
    2023-05
  • 期刊:
  • 影响因子:
    8.4
  • 作者:
    Sandro W. Lubis;P. Hassanzadeh
  • 通讯作者:
    Sandro W. Lubis;P. Hassanzadeh
The Summertime Pacific‐North American Weather Regimes and Their Predictability
  • DOI:
    10.1029/2022gl099401
  • 发表时间:
    2022-08
  • 期刊:
  • 影响因子:
    5.2
  • 作者:
    Ebrahim Nabizadeh;Sandro W. Lubis;P. Hassanzadeh
  • 通讯作者:
    Ebrahim Nabizadeh;Sandro W. Lubis;P. Hassanzadeh
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Pedram Hassanzadeh其他文献

Stable ema posteriori/em LES of 2D turbulence using convolutional neural networks: Backscattering analysis and generalization to higher emRe/em via transfer learning
  • DOI:
    10.1016/j.jcp.2022.111090
  • 发表时间:
    2022-06-01
  • 期刊:
  • 影响因子:
    3.800
  • 作者:
    Yifei Guan;Ashesh Chattopadhyay;Adam Subel;Pedram Hassanzadeh
  • 通讯作者:
    Pedram Hassanzadeh
Machine learning for the physics of climate
用于气候物理学的机器学习
  • DOI:
    10.1038/s42254-024-00776-3
  • 发表时间:
    2024-11-11
  • 期刊:
  • 影响因子:
    39.500
  • 作者:
    Annalisa Bracco;Julien Brajard;Henk A. Dijkstra;Pedram Hassanzadeh;Christian Lessig;Claire Monteleoni
  • 通讯作者:
    Claire Monteleoni

Pedram Hassanzadeh的其他文献

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{{ truncateString('Pedram Hassanzadeh', 18)}}的其他基金

Collaborative Research: Framework: Improving the Understanding and Representation of Atmospheric Gravity Waves using High-Resolution Observations and Machine Learning
合作研究:框架:利用高分辨率观测和机器学习提高对大气重力波的理解和表示
  • 批准号:
    2005123
  • 财政年份:
    2020
  • 资助金额:
    $ 73.5万
  • 项目类别:
    Standard Grant
Collaborative Research: Revisiting the Low-Frequency Variability of the Extratropical Circulation Using Non-Empirical Orthogonal Function (EOF) Modes and Linear Response Functions
合作研究:使用非经验正交函数 (EOF) 模式和线性响应函数重新审视温带环流的低频变化
  • 批准号:
    1921413
  • 财政年份:
    2019
  • 资助金额:
    $ 73.5万
  • 项目类别:
    Standard Grant

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