CAREER: Causal Connections Between the Arctic and Mid-latitudes

职业：北极与中纬度地区之间的因果关系

• 批准号: 1749261
• 负责人: Elizabeth Barnes
• 金额: $ 86万
• 依托单位: Colorado State University
• 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: 2018-08-01 至 2024-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1749261&HistoricalAwards=false
• 关键词: CAREER; Causal; Connections; Between; Arctic

The accelerated warming of the Arctic and unprecedented loss of sea ice in recent years have spurred a flurry of research and public interest on how these changes at high latitudes may impact weather at lower latitudes. There is much disagreement on whether we have already witnessed substantial impacts. The focal point of these debates is the question "who-is-causing-who", as changes in high latitudes take place at the same era as those in other latitudes, including mid-latitudes. The question how to infer the causality from data (observations and model outputs) is one of the most outstanding issues that the climate science community needs to resolve urgently. Here, the PI plans to apply causal discovery techniques, a unique type of statistical and data analysis, to the question of causal connections between the Arctic and mid-latitude circulation. These tools will provide insight into the causal pathways connecting Arctic temperatures to mid-latitude weather, quantify the ability of state-of-the-art climate models to simulate these pathways, and assess how these pathways may change in the coming decades. The funded research will advance our understanding of the two-way links between the Arctic and mid-latitude weather, which in turn, can lead to improvements in short-term weather forecasts as well as improvements in predictions of weather/climate variability in the coming decades. In addition, this project will include the development of an online "gateway" of accessible explanations of data analysis techniques with accompanying atmospheric-science-motivated examples for atmospheric scientists: the Data Analysis Tools for Atmospheric Scientists (DATAS) Gateway. The recent explosion of climate data and increasing complexity of earth-system models requires that now, more than ever, atmospheric scientists be equipped with the necessary skills to make novel and robust discoveries. A joint community effort is planned for creating, testing, and disseminating the DATAS Gateway material. These community coordinated research/education activities include peer contributions and review, graduate student workshops, statistical and gateway-developer consultants, and integration into current and planned curricula across seven universities. The DATAS Gateway will not only be a resource for scientists across the globe, but will also allow for the sharing of ideas and tools, spur scientific breakthroughs and support five undergraduate researchers. A sustainability plan will be developed to transition the DATAS Gateway to a community-driven effort to ensure that it outlives the 5-year horizon of this CAREER grant. The project as a whole will additionally support a graduate student and individuals under-represented in STEM by supporting the efforts of six female faculty (the PI and five collaborators).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.

近年来，北极加速变暖和前所未有的海冰消失引发了一系列研究和公众兴趣，探讨高纬度地区的这些变化如何影响低纬度地区的天气。对于我们是否已经目睹了重大影响，存在很大分歧。这些争论的焦点是“谁造成谁”的问题，因为高纬度地区的变化与包括中纬度地区在内的其他纬度地区的变化发生在同一时代。如何从数据（观测和模型输出）推断因果关系是气候科学界迫切需要解决的最突出问题之一。在这里，PI 计划应用因果发现技术（一种独特的统计和数据分析类型）来解决北极和中纬度环流之间的因果关系问题。这些工具将深入了解连接北极温度与中纬度天气的因果路径，量化最先进的气候模型模拟这些路径的能力，并评估这些路径在未来几十年可能发生的变化。资助的研究将增进我们对北极和中纬度天气之间双向联系的理解，这反过来又可以改善短期天气预报以及对未来天气/气候变化的预测。几十年。此外，该项目还将包括开发一个在线“网关”，为大气科学家提供易于理解的数据分析技术解释以及大气科学驱动的示例：大气科学家数据分析工具（DATAS）网关。最近气候数据的爆炸性增长和地球系统模型的日益复杂性要求大气科学家比以往任何时候都更需要具备必要的技能来做出新颖而有力的发现。社区计划共同努力创建、测试和传播 DATAS 网关材料。这些社区协调的研究/教育活动包括同行贡献和审查、研究生研讨会、统计和网关开发顾问，以及融入七所大学当前和计划的课程。 DATAS Gateway 不仅将成为全球科学家的资源，还将允许共享想法和工具、促进科学突破并支持五名本科生研究人员。我们将制定一项可持续发展计划，将 DATAS Gateway 转变为社区驱动的工作，以确保其寿命超过本次职业补助金的 5 年期限。该项目作为一个整体，还将通过支持六名女教员（PI 和五名合作者）的努力，额外支持一名研究生和 STEM 领域代表性不足的个人。该奖项反映了 NSF 的法定使命，并通过使用以下方法进行评估，认为值得支持：基金会的智力价值和更广泛的影响审查标准。

项目成果

Viewing Forced Climate Patterns Through an AI Lens

通过人工智能镜头观察强迫气候模式

• DOI: 10.1029/2019gl084944
• 发表时间: 2019-11-27
• 期刊: Geophysical Research Letters
• 影响因子: 5.2
• 作者: E. Barnes;J. Hurrell;I. Ebert‐Uphoff;C. Anderson;David Anderson
• 通讯作者: David Anderson

New Insights on Subseasonal Arctic–Midlatitude Causal Connections from a Regularized Regression Model

• DOI: 10.1175/jcli-d-19-0142.1
• 发表时间: 2019-12-09
• 期刊: Journal of Climate
• 影响因子: 4.9
• 作者: M. McGraw;E. Barnes
• 通讯作者: E. Barnes

Incorporating Uncertainty Into a Regression Neural Network Enables Identification of Decadal State‐Dependent Predictability in CESM2

将不确定性纳入回归神经网络可识别 CESM2 中的十年状态 - 相关可预测性

• DOI: 10.1029/2022gl098635
• 发表时间: 2022-08-11
• 期刊: Geophysical Research Letters
• 影响因子: 5.2
• 作者: Emily M. Gordon;E. Barnes
• 通讯作者: E. Barnes

Using Neural Networks to Learn the Jet Stream Forced Response from Natural Variability

• DOI: 10.1175/aies-d-22-0094.1
• 发表时间: 2023-01-02
• 期刊: Artificial Intelligence for the Earth Systems
• 作者: Charlotte Connolly;E. Barnes;P. Hassanzadeh;M. Pritchard
• 通讯作者: M. Pritchard

Drivers of uncertainty in future projections of Madden–Julian Oscillation teleconnections

《麦登朱利安振荡》遥相关未来预测的不确定性驱动因素

• DOI: 10.5194/wcd-2-653-2021
• 发表时间: 2021-07-23
• 期刊: Weather and Climate Dynamics
• 作者: A. Jenney;D. R;all;all;E. Barnes
• 通讯作者: E. Barnes