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

厄尔尼诺/南方涛动(ENSO)主导着世界范围内的气候变化，但其对气候变化的总体敏感性尚不清楚。气候模型预测了未来ENSO驱动的海洋变率的明显不同变化，这在一定程度上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应对气候变化的了解。该项目将把观测数据与现有的模式集合和新的、有针对性的敏感性实验结合起来，以提供对ENSO气候变化反应的物理理解，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。研究成果将纳入一系列关于气候和海洋模拟的教学模块(“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本原理，更高级的模块将描述海洋模型的参数和动力学。气候数据实验室还将用于通过BREN/环境研究领导力计划培训未被充分代表的少数族裔本科生，提供数据科学技能并促进保留STEM职业。这项工作的目标是改善对未来ENSO预测的约束。该项目将探讨ENSO强迫变化与平均气候以及中、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和平均态之间的相互作用。将使用的主要工具将是史无前例的CMIP级合奏。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CMIP类模式中是一致的。一套理想化的纯海洋实验和热带不稳定波(TIW)活动的新诊断方法将允许分离单个过程对中尺度涡旋行为的影响，以及它们与平均气候的相互作用。此外，为阐明海洋对ENSO预测的物理控制而优化的第一组完全耦合扰动物理集合将被创建，并与现有耦合模型集合的行为进行对比。与新的、更详细的紧急约束诊断的拟议开发相结合，结果将是对气候变化可能如何影响21世纪ENSO的更强有力的见解。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

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.