CAREER: Narrowing the Spread: Process Understanding for Reduced Uncertainty in Future El Nino/Southern Oscillation Projections

职业：缩小传播范围：减少未来厄尔尼诺/南方涛动预测不确定性的过程理解

• 批准号: 2142953
• 负责人: Samantha Stevenson
• 金额: $ 87.94万
• 依托单位: University of California-Santa Barbara
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-07-01 至 2027-06-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2142953&HistoricalAwards=false
• 关键词: CAREER; Narrowing; Spread; Process; Understanding

The El Nino/Southern Oscillation (ENSO) dominates worldwide climate variability, yet its overall sensitivity to climate change remains unknown. Climate models project distinctly different changes to future ENSO-driven oceanic variability, which are related in part to differences in simulated tropical Pacific mean climate changes. This project will improve understanding of ENSO response to climate change. The project will synthesize observational data with existing model ensembles and novel, targeted sensitivity experiments to provide both physical understanding of the ENSO climate change response and improved observational constraints on future ENSO projections. The project will train undergraduate and PhD students and postdoctoral researchers. Research results will be incorporated into a series of instructional modules on climate and ocean modeling (the “Climate DataLab”). Introductory modules will familiarize environmental science professionals with climate model fundamentals, and more advanced modules will describe ocean model parameterizations and dynamics. Climate DataLab will also be used to train underrepresented minority undergraduates through the Bren/Environmental Studies Leadership Program, providing data science skills and facilitating retention in STEM careers.The objective of this work is to improve constraints on future ENSO projections. The project will address how forced changes in ENSO are related to mean climate and mesoscale and submesoscale ocean dynamics. It will also examine how the mesoscale influences the interactions between ENSO and the mean state. The primary tool to be used will be an unprecedented array of CMIP-class ensembles. The project will also investigate whether the relationships between ENSO and mean and mesoscale dynamics are consistent across CMIP-class models. A suite of idealized ocean-only experiments and novel diagnostics for Tropical Instability Wave (TIW) activity will allow isolation of the influences of individual processes on mesoscale eddy behavior, and their interactions with mean climate. Additionally, the first set of fully coupled perturbed physics ensembles optimized for elucidating ocean physical controls on ENSO projections will be created and contrasted with the behavior of existing coupled model ensembles. When combined with the proposed development of new, more detailed emergent constraint diagnostics, the result will be more robust insights into how climate change may affect 21st century ENSO.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.

厄尔尼诺/南方涛动（ENSO）主导着全球气候变率，但其对气候变化的总体敏感性尚不清楚。气候模式对未来enso驱动的海洋变率的预测有明显不同的变化，这部分与模拟的热带太平洋平均气候变化的差异有关。该项目将提高对ENSO对气候变化响应的理解。该项目将把观测数据与现有的模式集合和新颖的、有针对性的灵敏度实验相结合，以提供对ENSO气候变化响应的物理理解，并改善对未来ENSO预测的观测约束。该项目将培养本科生、博士生和博士后研究人员。研究成果将被纳入气候和海洋模型的一系列教学模块（“气候数据实验室”）。入门模块将使环境科学专业人员熟悉气候模型的基础知识，更高级的模块将描述海洋模型的参数化和动力学。气候数据实验室还将通过布伦/环境研究领导力项目培训代表性不足的少数族裔本科生，提供数据科学技能，并促进STEM职业的保留。这项工作的目的是改善对未来ENSO预测的限制。该项目将探讨ENSO强迫变化与平均气候、中尺度和亚中尺度海洋动力学之间的关系。它还将研究中尺度如何影响ENSO和平均状态之间的相互作用。使用的主要工具将是前所未有的cip级集成阵列。该项目还将调查ENSO与平均和中尺度动力学之间的关系是否在cip级模式中是一致的。一套理想化的海洋实验和热带不稳定波（TIW）活动的新诊断方法将使单个过程对中尺度涡旋行为的影响及其与平均气候的相互作用得以分离。此外，将创建第一组完全耦合的微扰物理组合，并与现有耦合模式组合的行为进行对比，该组合优化了对ENSO预推算的海洋物理控制。当与新提出的更详细的紧急约束诊断相结合时，结果将更有力地了解气候变化如何影响21世纪的ENSO。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识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

Contributions of Climate Change and ENSO Variability to Future Precipitation Extremes Over California

气候变化和 ENSO 变化对加利福尼亚州未来极端降水的影响

• DOI: 10.1029/2023gl103322
• 发表时间: 2023
• 期刊: Geophysical Research Letters
• 影响因子: 5.2
• 作者: Huang, Xingying;Stevenson, Samantha
• 通讯作者: Stevenson, Samantha