Collaborative Research: Dynamics of Seasonal Forecast Uncertainty: Cross-Basin Ocean-Atmosphere Interactions

合作研究：季节预报不确定性的动态：跨流域海洋-大气相互作用

• 批准号: 2105641
• 负责人: Yuko Okumura
• 金额: $ 29.91万
• 依托单位: University of Texas at Austin
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-07-15 至 2024-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2105641&HistoricalAwards=false
• 关键词: Collaborative; Research; Dynamics; Seasonal; Forecast

Every few years the Pacific ocean warms dramatically in a narrow strip along the equator extending roughly from the South American coast to the dateline. This warming is called an El Nino event, and El Ninos and their cold La Nina opposites are referred to collectively as El Nino/Southern Oscillation (ENSO) events. While ENSO events are broadly similar there are important differences, in particular they differ in whether the sea surface temperature (SST) change is greatest in the eastern or central Pacific. They also differ in their magnitude, and El Nino events are often stronger than La Nina events. The consequences of ENSO are felt worldwide, from changes in the Indian monsoon to the severity of winters in Canada, and these impacts vary according to the pattern and magnitude of the event. The dynamical mechanisms that cause diversity in behavior among ENSO events and their global impacts are thus an important practical problem as well as a topic of scientific interest.This project examines the idea that much of the diversity of ENSO events occurs because of interactions between the developing ENSO event and a variety of less prominent climate variability modes occurring over the global oceans. For example the Pacific meridional mode (PMM) is a variability pattern in which fluctuations of the Aleutian Low over the North Pacific generate warm SSTs (or cold, in the opposite phase) which propagate slowly toward the equatorial Pacific through air-sea interactions. The overlap between the domains of the PMM and ENSO makes the PMM a likely suspect in diversifying ENSO events. Likewise, the episodic warming of the Indian Ocean in the Indian Ocean Dipole (IOD) mode affects the trade winds in the western Pacific, with potential consequences for ENSO given the central role of trade wind fluctuations in ENSO evolution.To examine the effect of secondary modes on ENSO diversity the Principal Investigators (PIs) of this award take advantage of the ensemble method used to predict ENSO events. Ensemble prediction means using a climate model to predict ENSO based on observed initial conditions (the state of the atmosphere and ocean at a given time) but performing several forecast simulations instead of one, and starting each forecast simulation with slightly different initial conditions. The resulting Perturbed Initial Condition Ensemble (PICE) gives a best estimate of the evolution of ENSO and also estimates the uncertainty in the prediction. The idea of this project is that the individual forecast simulations in a PICE contain different secondary modes, and the interactions between secondary modes and ENSO can be assessed by examining differences in ENSO evolution among the simulations. An advantage of this method is that a large database of PICE simulations has been created by the Earth System Prediction (ESP) Working Group of the Communtiy Earth System Model (CESM). The PICE dataset provides a much larger sample size than the observational record, thus statistically robust results can be obtained.The work is of societal importance given its direct connection to ENSO prediction. In addition to its examination of ENSO evolution in prediction simulations the research uses the PICE simulations to understand how differences among ENSO events lead to differences in the impacts of ENSO in populous parts of the world. The project also supports two graduate students and provides internship opportunities for undergraduates.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.

每隔几年，太平洋就会沿着赤道以一条狭窄的狭长地带急剧变暖，大致从南美海岸延伸到日期变更线。这种变暖被称为厄尔尼诺事件，厄尔尼诺和它们寒冷的拉尼娜相反被统称为厄尔尼诺/南方涛动(ENSO)事件。虽然ENSO事件大致相似，但也有重要的差异，特别是在东太平洋或中太平洋海表面温度(SST)变化最大的问题上。它们的震级也不同，厄尔尼诺事件往往比拉尼娜事件更强烈。从印度季风的变化到加拿大冬季的严酷程度，全世界都能感受到ENSO的影响，这些影响因事件的模式和规模而异。因此，引起ENSO事件行为多样性及其全球影响的动力机制是一个重要的实际问题和科学兴趣的主题。本项目研究了ENSO事件的大部分多样性是由于发展中的ENSO事件与发生在全球海洋上的各种不太显著的气候变率模式之间的相互作用而产生的。例如，太平洋子午线模式(PMM)是一种变率模式，在这种模式中，北太平洋阿留申低压的波动产生暖的海温(或相反的冷的海温)，这些海温通过海气相互作用向赤道太平洋缓慢传播。PMM和ENSO之间的区域重叠使PMM可能成为ENSO事件多样化的嫌疑人。同样，印度洋偶极子(IOD)模式中印度洋的周期性变暖影响了西太平洋的信风，鉴于信风波动在ENSO演变中的中心作用，可能会对ENSO产生影响。为了研究次要模式对ENSO多样性的影响，该奖项的首席调查员利用了用于预测ENSO事件的集合方法。集合预测是指使用气候模式根据观测到的初始条件(给定时间的大气和海洋状态)预测ENSO，但执行多个预测模拟而不是一个，并以略有不同的初始条件开始每次预测模拟。由此产生的扰动初始条件集合(PICE)给出了对ENSO演变的最佳估计，并估计了预测中的不确定性。这个项目的思想是，在一个pICE中的各个预报模拟包含不同的次要模，并且可以通过检查不同模拟之间的ENSO演变的差异来评估次要模与ENSO之间的相互作用。这种方法的一个优点是，社区地球系统模型(CESM)的地球系统预测(ESP)工作组已经创建了一个大型的PICE模拟数据库。PICE数据集提供的样本量比观测记录大得多，因此可以获得统计上可靠的结果。鉴于其与ENSO预测的直接联系，这项工作具有重要的社会意义。除了在预测模拟中检验ENSO的演变，这项研究还使用PICE模拟来理解ENSO事件之间的差异如何导致ENSO在世界人口稠密地区的影响不同。该项目还支持两名研究生，并为本科生提供实习机会。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。