Collaborative Research: El Nino/Southern Oscillation (ENSO) Predictability--Initial Condition Signal versus Uncoupled Atmospheric Noise

合作研究：厄尔尼诺/南方涛动 (ENSO) 可预测性 - 初始条件信号与非耦合大气噪声

• 批准号: 2241538
• 负责人: Benjamin Kirtman
• 金额: $ 70.85万
• 依托单位: University of Miami
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-06-01 至 2027-05-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2241538&HistoricalAwards=false
• 关键词: Collaborative; Research; El; Nino; Southern

The equatorial Pacific has an outsized influence on weather and climate as it is home to the El Nino/Southern Oscillation (ENSO) phenomenon, featuring an alternation between warm equatorial sea surface temperatures (SSTs) during El Nino events and cold SSTs during La Nina events. These SST changes affect the global atmospheric circulation and thus induce long-range impacts including changes in the severity of winters in Canada, the distribution of rainfall in the Asian monsoon, and Atlantic hurricane activity. These worldwide impacts have motivated intensive efforts to develop ENSO prediction systems, which show some promise but so far have had mixed results.Here the PIs hypothesize that the mixed success of ENSO predictions is intrinsic to ENSO, meaning that some ENSO events are in fact more predictable than others. In that case a "forecast of the forecast skill", meaning a method to determine in advance the likely accuracy of an ENSO prediction, would have great practical value. The Principal Investigators (PIs) are particularly concerned with the skill of ENSO predictions made before the onset of the event, which are skillful to the extent that ENSO events develop from some form of preconditioning such as the buildup of heat in the subsurface equatorial ocean. Model simulations conducted previously by the PIs suggest that preconditioning is not a necessary condition for ENSO events, which can initiate rapidly starting from neutral conditions. Such events, arising purely from the chaotic growth of very small initial perturbations of the atmosphere-ocean system, would be inherently unpredictable. But the PIs argue that some forms of preconditioning can render the system less susceptible to noise-level perturbations and instead drive the evolution of an El Nino or La Nina event in a deterministic manner, allowing skillful predictions several months ahead of the onset.The PIs test their hypothesis through numerical simulations performed with the Community Earth System Model (CESM). The work takes advantage of procedures they have developed for strictly controlling the state of the equatorial Pacific in CESM simulations, so that various forms of preconditioning can be imposed or excluded. Additional work uses the PI's Interactive Ensemble (IE) technique (see for example AGS-1558837) to consider the role of random weather fluctuations unrelated to ENSO in limiting the predictability of ENSO events.The work is of societal as well as scientific interest given the global impacts of ENSO events, and results of this research have direct bearing on attempts to improve ENSO forecasts. The software developed for the project is made available to the research community, along with relevant datasets, to facilitate adoption of methods and results by the research and operational communities. In addition, the PIs participate in summer internship programs targeting high school and college students through Miami-Dade College and the American Indian Higher Education Consortium.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.

赤道太平洋对天气和气候有着巨大的影响，因为它是厄尔尼诺/南方涛动（ENSO）现象的发源地，其特点是厄尔尼诺事件期间赤道海面温度（SST）温暖，拉尼娜事件期间寒冷海表温度交替。 。 这些海温变化影响全球大气环流，从而引发长期影响，包括加拿大冬季严酷程度的变化、亚洲季风降雨分布以及大西洋飓风活动。 这些全球影响促使人们大力努力开发 ENSO 预测系统，该系统显示出一些希望，但迄今为止结果好坏参半。在此，PI 假设 ENSO 预测的成功与否是 ENSO 所固有的，这意味着某些 ENSO 事件实际上更多比其他人更能预测。 在这种情况下，“预测技能的预测”，即提前确定 ENSO 预测的可能准确性的方法，将具有很大的实用价值。 首席研究员 (PI) 特别关注 ENSO 事件发生前预测的技巧，因为 ENSO 事件是由某种形式的预处理（例如赤道海洋地下热量积聚）发展而来的。 PI 之前进行的模型模拟表明，预处理并不是 ENSO 事件的必要条件，ENSO 事件可以从中性条件快速启动。 此类事件纯粹是由于大气-海洋系统最初非常小的扰动的混乱增长而引起的，本质上是不可预测的。 但 PI 认为，某些形式的预处理可以使系统不易受到噪声水平扰动的影响，而是以确定性方式推动厄尔尼诺或拉尼娜事件的演变，从而可以在事件发生前几个月进行熟练的预测。通过使用社区地球系统模型 (CESM) 进行的数值模拟来检验他们的假设。 这项工作利用了他们为严格控制CESM模拟中赤道太平洋状态而开发的程序，以便可以施加或排除各种形式的预处理。 其他工作使用 PI 的交互式集成 (IE) 技术（例如参见 AGS-1558837）来考虑与 ENSO 无关的随机天气波动在限制 ENSO 事件可预测性方面的作用。鉴于ENSO 事件的全球影响以及这项研究的结果对改进 ENSO 预报的尝试有直接影响。为该项目开发的软件以及相关数据集可供研究界使用，以促进研究和运营界采用方法和结果。 此外，PI 还通过迈阿密戴德学院和美洲印第安人高等教育联盟参加针对高中生和大学生的暑期实习计划。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能力进行评估，认为值得支持。更广泛的影响审查标准。