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: 2241539
• 负责人: Sarah Larson
• 金额: $ 48.06万
• 依托单位: North Carolina State University
• 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=2241539&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具有巨大的影响，因为它是El Nino/Southern振荡（ENSO）现象的所在地，在El Nino事件期间，在La Nina事件期间，在El Nino事件中具有温暖的赤道海面温度（SSTS）之间的交替。 这些SST的变化会影响全球大气环流，从而引起远程影响，包括加拿大冬季严重程度的变化，亚洲季风的降雨分布以及大西洋飓风活动。 这些全世界的影响促进了强烈的努力来开发ENSO预测系统，这些系统表现出了一些希望，但到目前为止的结果不同。PIS假设ENSO预测的混合成功对ENSO是固有的，这意味着某些ENSO事件实际上比其他事件更可预测。 在这种情况下，“预测技能的预测”是指事先确定ENSO预测可能准确性的方法，将具有巨大的实际价值。 主要研究人员（PIS）特别关注事件开始前的ENSO预测技巧，在ENSO事件从某种形式的预处理中（例如在地下赤道海洋中的热量堆积）中，这是熟练的。 PIS之前进行的模型模拟表明，预处理不是ENSO事件的必要条件，ENSO事件可以从中性条件开始迅速启动。 这些事件纯粹是由于大气 - 海洋系统的初始扰动非常小的混乱生长而产生的，这本质上是不可预测的。 但是PI认为，某些形式的预处理可以使系统不太容易受到噪声级的扰动的影响，而是以确定性的方式推动El Nino或La Nina事件的演变，从而使PIS在发病之前几个月进行熟练的预测。PIS通过与社区泥土系统模型（CESM）进行的数字模拟测试其假设（CESM）。 这项工作利用了他们开发的程序，用于严格控制CESM模拟中赤道太平洋的状态，因此可以强加或排除各种形式的预处理。 其他工作使用PI的互动集合（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事件的可预测性方面的作用。鉴于社会兴趣以及科学的兴趣，鉴于该研究的全球影响以及这项研究的全球影响以及这项研究的结果可以直接改善ENSO eNSSO的影响。为该项目开发的软件可供研究社区以及相关数据集提供，以促进研究和运营社区的方法和结果。 此外，PIS通过迈阿密戴德学院和美洲印第安高等教育财团参加了针对高中和大学生的暑期实习计划。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评估来获得支持的，并具有更广泛的影响。