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.

El Nino/Southern振荡（ENSO）占主导地位，但其对气候变化的总体敏感性仍然未知。气候模型对未来ENSO驱动的海洋变异性的变化明显不同，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对气候变化的反应的理解。该项目将与现有模型集合和新颖的，有针对性的灵敏度实验合成观察数据，以提供对ENSO气候变化响应的物理理解，并改善对未来ENSO项目的观察性约束。该项目将培训本科生和博士生以及博士后研究人员。研究结果将纳入有关气候和海洋建模的一系列教学模块（“气候数据”）。入门模块将使环境科学专业人员具有气候模型基础知识，而更高级的模块将描述海洋模型参数和动态。气候数据也将用于通过Bren/Environmental Isword领导力计划培训代表性不足的少数群体本科生，提供数据科学技能并支持STEM职业的保留。这项工作的目的是改善对未来ENSO项目的约束。该项目将解决ENSO中强迫变化与平均气候和中尺度和子尺度海洋动力学有关的方式。它还将研究中尺度如何影响ENSO与平均状态之间的相互作用。要使用的主要工具将是CMIP级合奏的前所未有的阵列。该项目还将研究ENSO与Mean和Messocale Dynamics之间的关系是否在CMIP级模型之间是否保持一致。一组仅理想的海洋实验和热带不稳定性波（TIW）活性的新型诊断，将允许分离单个过程对中尺度涡流行为的影响及其与平均气候的相互作用。此外，将创建并与现有耦合模型集合的现有耦合模型集合的行为形成鲜明对比的第一组完全耦合的扰动物理集合，以阐明ENSO投影的海洋物理控制。当结合提议的新，更详细的紧急限制诊断的开发时，结果将对气候变化如何影响21世纪ENSO有更强有力的见解。该奖项反映了NSF的法定任务，并被认为是通过基金会的知识分子优点和更广泛影响的评估来评估的珍贵的支​​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