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，北极加速变暖和海冰前所未有的损失引发了一系列研究和公众对高纬度地区这些变化如何影响低纬度天气的兴趣。关于我们是否已经目睹了重大影响，存在很大分歧。这些辩论的焦点是“谁造成了谁”的问题，因为高纬度地区的变化与其他纬度地区包括中纬度地区的变化发生在同一时期。如何从观测数据和模式输出数据中推断气候变化的因果关系是气候科学界迫切需要解决的问题之一。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方法，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北极温度与中纬度天气之间的因果关系，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如何变化。资助的研究将促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未来几十年天气/气候变化预测的改善。此外，该项目还将包括开发一个在线“网关”，为大气科学家提供数据分析技术的可访问解释，并附有以大气科学为动机的例子：大气科学家数据分析工具网关。最近气候数据的爆炸性增长和地球系统模型的日益复杂，要求大气科学家现在比以往任何时候都要具备必要的技能，以做出新颖而有力的发现。计划进行社区联合努力，以创建、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、研究生讲习班、统计和网关开发顾问，以及纳入七所大学目前和计划的课程。DATAS网关不仅将成为地球仪科学家的资源，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。将制定一项可持续发展计划，将DATAS网关过渡到社区驱动的努力，以确保它超过5年的视野，这个职业生涯补助金。该项目作为一个整体将通过支持六名女教师（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

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

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

Identifying Opportunities for Skillful Weather Prediction with Interpretable Neural Networks

利用可解释的神经网络识别熟练天气预报的机会

• 发表时间: 2020
• 期刊: NeurIPS AI4EARTH 2020
• 作者: Barnes, Elizabeth A.

Strengthened Causal Connections Between the MJO and the North Atlantic With Climate Warming

• DOI: 10.1029/2020gl091168
• 发表时间: 2020-10
• 期刊: Geophysical Research Letters
• 影响因子: 5.2
• 作者: S. Samarasinghe;Charlotte Connolly;E. Barnes;I. Ebert‐Uphoff;Lantao Sun

Assessing Decadal Predictability in an Earth‐System Model Using Explainable Neural Networks

• DOI: 10.1029/2021gl093842
• 发表时间: 2021-06
• 期刊: Geophysical Research Letters
• 影响因子: 5.2
• 作者: B. Toms;E. Barnes;J. Hurrell

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
• 期刊: Journal of Climate
• 影响因子: 4.9
• 作者: M. McGraw;E. Barnes