Collaborative Research: The Relationship between El Niño-Southern Oscillation (ENSO) Diversity and Tropical Cyclones in a Hierarchy of Models

合作研究：模型层次结构中厄尔尼诺-南方涛动 (ENSO) 多样性与热带气旋之间的关系

• 批准号: 2043282
• 负责人: Christina Karamperidou
• 金额: $ 22.95万
• 依托单位: University of Hawaii
• 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: 2021-03-15 至 2025-02-28
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2043282&HistoricalAwards=false
• 关键词: Collaborative; Research; Relationship; between; El

Hurricanes are the most devastating natural disasters facing many coastal communities in the US and around the world. Since these storms, also called tropical cyclones (TCs), develop in warm air over warm sea surface temperatures (SSTs), it is natural to ask wether they will pose a greater threat as the world warms. Basic thermodynamics implies that the strongest hurricanes in a cooler climate are weaker than their counterparts in warmer climates, and this strengthening with warming has now been detected in the observed record. But the strengthening of the strongest storms may be just one of a number of changes in TC activity that result from warming. One question here is how TC activity will be influenced by the pattern of ocean surface warming, as observations and simulations both show an uneven pattern of tropical ocean warming accompanying greenhouse gas increases. Some clues to how the regional distribution of SST increases is likely to affect TC activity can be found in El Nino events(also called El Nino/Southern Oscillation events, or ENSOs), in which the equatorial Pacific warms between the west coast of South America and the dateline. Prior work by the Principal Investigators (PIs) and others shows that the influence of El Nino events on TCs is different depending on whether the El Nino-induced warming is greatest in the central or eastern equatorial Pacific. In particular they found that all El Nino events can suppress TCs in the Atlantic, but the central Pacific "flavor" of El Nino is substantially more effective at Atlantic TC suppression. The El Nino-TC connection can thus serve to guide expectations as to how the regional pattern of future SST warming might affect TC activity. It may also have direct implications if future warming affects either the frequency and intensity of El Nino events or the relative occurrence of the central and eastern Pacific flavors.Work performed under this award examines the El Nino-TC relationship and its implications for climate change using a combination of climate model simulations, machine learning techniques, and hybrid dynamical-statistical models. One goal of the project is to develop "emergent constraints" that connect the El Nino-TC relationship found in climate models to the relationship found in the observed record. If models show a strong connection between the El Nino-TC relationship in present-day climate and future TC change, then future TC change projections from models which correctly simulate the present-day El Nino-TC relationship are more credible. The physical mechanisms through which El Nino events influence TC activity are also explored.The work has societal value given the risks posed by TCs for coastal communities and the value of guidance as to how that risk might change in the future. The project also builds a research network spanning three institutions from the eastern seabord to Hawaii. In addition to its scientific value the network helps to overcome the geographical isolation of the University of Hawaii, a minority-serving institution. The project also supports a graduate student in Columbia University's Bridge to the PhD program, which helps college graduates from underrepresented groups with the transition to graduate school. Finally, the PIs are developing an online class titled "Machine learning applications across weather and climate" which will take advantage of tools and results from the project.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.

飓风是美国和世界各地许多沿海社区面临的最具破坏性的自然灾害。 由于这些风暴（也称为热带气旋（TC））在温暖的海面温度（SSTS）中发育，因此自然而然地问，随着世界的温暖，它们会构成更大的威胁。基本的热力学意味着在凉爽的气候中，最强烈的飓风比在温暖的气候中弱的飓风较弱，并且在观察到的记录中已经发现了这种随着变暖的增强。 但是，最大风暴的加强可能只是变暖导致的TC活动的许多变化之一。 这里的一个问题是TC活动将如何受到海面变暖模式的影响，因为观察结果和模拟都显示出伴随温室气体增加的热带海洋变暖模式。在El Nino事件（也称为El Nino/Southern振荡事件或ENSOS）中，SST增加的区域分布如何影响TC活动的一些线索，其中赤道太平洋在南美西海岸之间温暖和数据线。 首席研究人员（PIS）和其他人的先前工作表明，El Nino事件对TCS的影响不同，具体取决于El Nino诱导的变暖在中部还是东部赤道太平洋中是最大的。 特别是他们发现，所有厄尔尼诺现象都可以抑制大西洋中的TC，但是El Nino的中太平洋“风味”在大西洋TC抑制方面更为有效。因此，El Nino-TC连接可以指导人们对未来SST变暖的区域模式如何影响TC活动的期望。 如果未来的变暖影响El Nino事件的频率和强度或中部和东部太平洋风味的相对出现，则可能会产生直接的影响。根据该奖项进行的工作检查El Nino-TC的关系及其对使用气候变化的影响气候模型模拟，机器学习技术和混合动力学统计模型的组合。 该项目的一个目标是开发“紧急约束”，将气候模型中的El Nino-TC关系与观察到的记录中的关系联系起来。 如果模型在当今的气候和未来的TC变化中显示了El Nino-TC关系之间的牢固联系，则未来的TC变更预测来自模型，这些模型正确模拟了当今的El Nino-TC关系，更可信。还探讨了El Nino事件影响TC活动的物理机制。鉴于TCS对沿海社区带来的风险以及指导价值以及该风险在未来可能如何变化的指导价值，这项工作具有社会价值。 该项目还建立了一个研究网络，该研究网络跨越了从东部海湾到夏威夷的三个机构。 除了其科学价值外，网络有助于克服少数派服务机构夏威夷大学的地理隔离。 该项目还支持哥伦比亚大学的博士学位桥梁课程的研究生，该课程可帮助来自代表性不足的团体的大学毕业生过渡到研究生院。 最后，PI正在开发一个名为“天气和气候之间的机器学习应用程序”的在线课程，该奖项将利用该项目的工具和结果。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子进行评估来支持的。优点和更广泛的影响审查标准。